{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": { "id": "HJQ4TI0_Qowr" }, "source": [ "## Setup Notebook, Install\n" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "r8wG_tIaOV0Q", "outputId": "6ea4ba04-3578-41e7-f9b5-4a44ca654452" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "fatal: destination path 'bark' already exists and is not an empty directory.\n", "/home/jon/mamba_projects/bark_postfixes/bark/bark\n", "\u001b[31mERROR: Could not open requirements file: [Errno 2] No such file or directory: 'requirements-pip.txt'\u001b[0m\u001b[31m\n", "\u001b[0mRequirement already satisfied: encodec in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (0.1.1)\n", "Requirement already satisfied: rich-argparse in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (1.1.0)\n", "Requirement already satisfied: torch in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from encodec) (2.0.0)\n", "Requirement already satisfied: numpy in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from encodec) (1.24.3)\n", "Requirement already satisfied: einops in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from encodec) (0.6.1)\n", "Requirement already satisfied: torchaudio in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from encodec) (2.0.0)\n", "Requirement already satisfied: rich>=11.0.0 in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from rich-argparse) (12.5.1)\n", "Requirement already satisfied: pygments<3.0.0,>=2.6.0 in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from rich>=11.0.0->rich-argparse) (2.11.2)\n", "Requirement already satisfied: commonmark<0.10.0,>=0.9.0 in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from rich>=11.0.0->rich-argparse) (0.9.1)\n", "Requirement already satisfied: filelock in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from torch->encodec) (3.9.0)\n", "Requirement already satisfied: typing-extensions in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from torch->encodec) (4.5.0)\n", "Requirement already satisfied: sympy in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from torch->encodec) (1.11.1)\n", "Requirement already satisfied: networkx in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from torch->encodec) (2.8.4)\n", "Requirement already satisfied: jinja2 in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from torch->encodec) (3.1.2)\n", "Requirement already satisfied: MarkupSafe>=2.0 in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages (from jinja2->torch->encodec) (2.1.1)\n", "Requirement already satisfied: mpmath>=0.19 in /home/jon/mambaforge/envs/bark-infinity-oneclick/lib/python3.10/site-packages/mpmath-1.2.1-py3.10.egg (from sympy->torch->encodec) (1.2.1)\n", "^C\n", "\u001b[31mERROR: Operation cancelled by user\u001b[0m\u001b[31m\n", "\u001b[0m" ] } ], "source": [ "!git clone https://github.com/JonathanFly/bark.git\n", "%cd bark\n", "!pip install -r requirements-pip.txt\n", "!pip install encodec rich-argparse\n", "!pip install librosa pydub" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "id": "FHlxNCt3QwIr" }, "source": [ "## Run Once Per Notebook Restart (if files still exist)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "jKTvqvVkOwXM" }, "outputs": [], "source": [ "import os\n", "import time\n", "from bark_infinity import config\n", "import numpy as np\n", "\n", "logger = config.logger\n", "logger.setLevel(\"WARNING\")\n", "\n", "from bark_infinity import generation\n", "from bark_infinity import api\n", "\n", "import rich\n", "from rich import print\n", "from rich import pretty\n", "from rich.pretty import pprint\n", "from rich import inspect\n", "\n", "from pydub import AudioSegment\n", "import ipywidgets as widgets\n", "from IPython.display import display, Audio\n", "from io import BytesIO\n", "\n", "# None of this code, just fiddlign with Colab stuff\n", "# Just to save Colab with outputs and float32 wavs are GIGANTO\n", "# actually this doesn't work, the iPython widget converts it back to float32? or I messed up\n", "\n", "def display_audio_int16_but(audio_arr_segments, file_name, sample_rate=generation.SAMPLE_RATE, width='200px'):\n", " file_name_label = widgets.Label(value=f\"Playing: {file_name}\")\n", " file_name_label.layout.width = width\n", " audio_data_int16 = audio_arr_segments\n", " if isinstance(audio_data_int16, list):\n", " audio_data_int16 = np.concatenate(audio_data_int16) \n", "\n", " #audio_data_int16 = np.int16(audio_data_int16 * np.iinfo(np.int16).max)\n", "\n", "\n", " audio_widget = Audio(audio_data_int16, rate=sample_rate)\n", " display(file_name_label, audio_widget)\n", " \n", "\n", "def on_button_click(button):\n", " audio_data, sample_rate = librosa.load(button.wav_path, sr=None)\n", " file_name = os.path.basename(button.wav_path)\n", " display_audio_int16_but(audio_data,file_name, sample_rate)\n", "\n", "\n", "def display_wav_files(directory):\n", " subdirs, wav_files = [], []\n", " \n", " for item in os.listdir(directory):\n", " item_path = os.path.join(directory, item)\n", " \n", " if os.path.isfile(item_path) and item_path.endswith('.wav'):\n", " wav_files.append(item_path)\n", " elif os.path.isdir(item_path):\n", " subdirs.append(item_path)\n", "\n", " wav_files.sort(key=lambda x: os.path.basename(x))\n", "\n", " for wav_file in wav_files:\n", "\n", " filename = os.path.basename(wav_file)\n", " print(f\" {filename}\")\n", " button = widgets.Button(description=f\"Play {filename}\")\n", " button.wav_path = wav_file \n", " button.on_click(on_button_click)\n", " display(button)\n", "\n", " for subdir in sorted(subdirs):\n", " print(f\"<{subdir}>\")\n", " display_wav_files(subdir)\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\n", "\n", "def call_with_non_none_params(func, **kwargs):\n", " non_none_params = {key: value for key, value in kwargs.items() if value is not None}\n", " return func(**non_none_params)\n", "\n", "global save_semantic_tokens\n", "def generate_audio_barki(\n", " text: str,\n", " **kwargs,\n", "):\n", " \"\"\"Generate audio array from input text.\n", "\n", " Args:\n", " text: text to be turned into audio\n", " history_prompt: history choice for audio cloning\n", " text_temp: generation temperature (1.0 more diverse, 0.0 more conservative)\n", " waveform_temp: generation temperature (1.0 more diverse, 0.0 more conservative)\n", " silent: disable progress bar\n", " output_full: return full generation to be used as a history prompt\n", "\n", "\n", " Returns:\n", " numpy audio array at sample frequency 24khz\n", " \"\"\"\n", " #logger.debug(locals())\n", " #print(\"before load all defaults\")\n", " kwargs = config.load_all_defaults(**kwargs)\n", "\n", " #logger.debug(locals())\n", " #print(\"after load all defaults\")\n", " history_prompt = kwargs.get(\"history_prompt\", None)\n", " text_temp = kwargs.get(\"text_temp\", None)\n", " waveform_temp = kwargs.get(\"waveform_temp\", None)\n", " silent = kwargs.get(\"silent\", None)\n", " output_full = kwargs.get(\"output_full\", None)\n", "\n", " global gradio_try_to_cancel\n", " global done_cancelling\n", "\n", " seed = kwargs.get(\"seed\",None)\n", " if seed is not None:\n", " generation.set_seed(seed)\n", "\n", " ## TODO seperate stage seeds\n", "\n", " ## Semantic Options\n", " semantic_temp = text_temp\n", " if kwargs.get(\"semantic_temp\", None):\n", " semantic_temp = kwargs.get(\"semantic_temp\")\n", "\n", " semantic_seed = kwargs.get(\"semantic_seed\",None)\n", " if semantic_seed is not None:\n", " generation.set_seed(semantic_seed)\n", "\n", "\n", " if api.gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", " semantic_tokens = call_with_non_none_params(\n", " api.generate_text_semantic,\n", " text=text,\n", " history_prompt=history_prompt,\n", " temp=semantic_temp,\n", " top_k=kwargs.get(\"semantic_top_k\", None),\n", " top_p=kwargs.get(\"semantic_top_p\", None),\n", " silent=silent,\n", " min_eos_p = kwargs.get(\"semantic_min_eos_p\", None),\n", " max_gen_duration_s = kwargs.get(\"semantic_max_gen_duration_s\", None),\n", " allow_early_stop = kwargs.get(\"semantic_allow_early_stop\", True),\n", " use_kv_caching=kwargs.get(\"semantic_use_kv_caching\", True),\n", " )\n", " \n", " inspect(semantic_tokens)\n", " if api.gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", "\n", " ## Coarse Options\n", " coarse_temp = waveform_temp\n", " if kwargs.get(\"coarse_temp\", None):\n", " coarse_temp = kwargs.get(\"coarse_temp\")\n", "\n", " coarse_seed = kwargs.get(\"coarse_seed\",None)\n", " if coarse_seed is not None:\n", " generation.set_seed(coarse_seed)\n", " \n", " \n", " if api.gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", " \n", " coarse_tokens = call_with_non_none_params(\n", " generation.generate_coarse,\n", " x_semantic=semantic_tokens,\n", " history_prompt=history_prompt,\n", " temp=coarse_temp,\n", " top_k=kwargs.get(\"coarse_top_k\", None),\n", " top_p=kwargs.get(\"coarse_top_p\", None),\n", " silent=silent,\n", " max_coarse_history=kwargs.get(\"coarse_max_coarse_history\", None),\n", " sliding_window_len=kwargs.get(\"coarse_sliding_window_len\", None),\n", " use_kv_caching=kwargs.get(\"coarse_kv_caching\", True),\n", " )\n", "\n", " fine_temp = kwargs.get(\"fine_temp\", 0.5)\n", "\n", " fine_seed = kwargs.get(\"fine_seed\",None)\n", " if fine_seed is not None:\n", " generation.set_seed(fine_seed)\n", "\n", " if api.gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", " fine_tokens = call_with_non_none_params(\n", " api.generate_fine,\n", " x_coarse_gen=coarse_tokens,\n", " history_prompt=history_prompt,\n", " temp=fine_temp,\n", " silent=silent,\n", " )\n", "\n", " # do we ever care about setting this seed? Probably not? You can always just decode it again\n", "\n", " if api.gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", " audio_arr = api.codec_decode(fine_tokens)\n", " full_generation = {\n", " \"semantic_prompt\": semantic_tokens,\n", " \"coarse_prompt\": coarse_tokens,\n", " \"fine_prompt\": fine_tokens,\n", " }\n", "\n", " if api.gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", " \n", " hoarder_mode = kwargs.get(\"hoarder_mode\", None)\n", " total_segments = kwargs.get(\"total_segments\", 1)\n", " if hoarder_mode and (total_segments > 1):\n", " kwargs[\"text\"] = text\n", " api.write_one_segment(audio_arr, full_generation, **kwargs)\n", "\n", " if output_full:\n", " return full_generation, audio_arr\n", " \n", " return audio_arr\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/home/jon/mamba_projects/bark_postfixes/bark\n" ] } ], "source": [ "!pwd" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
set_seed Enabling deterministic algorithms                                                        generation.py:929\n",
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set_seed Set seed to 37                                                                           generation.py:944\n",
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generate_audio_barki {'text': 'With me, brave the tumultuous seas, claim treasures untold, and send foes api.py:392\n",
              "to their watery \\ndoom', 'kwargs': {'text_prompt': 'With me, brave the tumultuous seas, claim treasures            \n",
              "untold, and send foes to their watery \\ndoom', 'list_speakers': None, 'dry_run': False,                            \n",
              "'text_splits_only': False, 'history_prompt': None, 'prompt_file': None,                                            \n",
              "'split_input_into_separate_prompts_by': None, 'split_input_into_separate_prompts_by_value': None,                  \n",
              "'always_save_speaker': True, 'output_iterations': 1, 'output_filename': None, 'output_dir':                        \n",
              "'pieced_debug/', 'hoarder_mode': True, 'extra_stats': False, 'text_use_gpu': True, 'text_use_small':               \n",
              "False, 'coarse_use_gpu': True, 'coarse_use_small': False, 'fine_use_gpu': True, 'fine_use_small': False,           \n",
              "'codec_use_gpu': True, 'force_reload': False, 'GLOBAL_ENABLE_MPS': None, 'USE_SMALL_MODELS': None,                 \n",
              "'OFFLOAD_CPU': None, 'text_temp': 0.7, 'waveform_temp': 0.7, 'confused_travolta_mode': None, 'silent':             \n",
              "False, 'seed': None, 'stable_mode_interval': 1, 'single_starting_seed': None,                                      \n",
              "'split_character_goal_length': 145, 'split_character_max_length': 190, 'split_character_jitter': 0,                \n",
              "'add_silence_between_segments': 0.0, 'split_each_text_prompt_by': None,                                            \n",
              "'split_each_text_prompt_by_value': None, 'extra_confused_travolta_mode': None,                                     \n",
              "'semantic_history_starting_weight': 1.0, 'semantic_history_future_weight': 1.0,                                    \n",
              "'semantic_prev_segment_weight': 0.5, 'coarse_history_starting_weight': 1.0,                                        \n",
              "'coarse_history_future_weight': 0.5, 'coarse_prev_segment_weight': 0.5, 'fine_history_starting_weight':            \n",
              "1.0, 'fine_history_future_weight': 0.0, 'fine_prev_segment_weight': 0.0,                                           \n",
              "'custom_audio_processing_function': None, 'use_smaller_models': False, 'semantic_temp': 0.7,                       \n",
              "'semantic_top_k': None, 'semantic_top_p': None, 'semantic_min_eos_p': 0.2,                                         \n",
              "'semantic_max_gen_duration_s': None, 'semantic_allow_early_stop': True, 'semantic_use_kv_caching': True,           \n",
              "'semantic_seed': None, 'semantic_history_oversize_limit': None, 'coarse_temp': 0.7, 'coarse_top_k':                \n",
              "None, 'coarse_top_p': None, 'coarse_max_coarse_history': 630, 'coarse_sliding_window_len': 60,                     \n",
              "'coarse_kv_caching': True, 'coarse_seed': None, 'coarse_history_time_alignment_hack': -2, 'fine_temp':             \n",
              "0.5, 'fine_seed': None, 'render_npz_samples': False, 'loglevel': 'WARNING', 'output_full': True}}                  \n",
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generate_audio_barki {'text': 'With me, brave the tumultuous seas, claim treasures untold, and send foes api.py:396\n",
              "to their watery \\ndoom', 'kwargs': {'text_prompt': 'With me, brave the tumultuous seas, claim treasures            \n",
              "untold, and send foes to their watery \\ndoom', 'list_speakers': None, 'dry_run': False,                            \n",
              "'text_splits_only': False, 'history_prompt': None, 'prompt_file': None,                                            \n",
              "'split_input_into_separate_prompts_by': None, 'split_input_into_separate_prompts_by_value': None,                  \n",
              "'always_save_speaker': True, 'output_iterations': 1, 'output_filename': None, 'output_dir':                        \n",
              "'pieced_debug/', 'hoarder_mode': True, 'extra_stats': False, 'text_use_gpu': True, 'text_use_small':               \n",
              "False, 'coarse_use_gpu': True, 'coarse_use_small': False, 'fine_use_gpu': True, 'fine_use_small': False,           \n",
              "'codec_use_gpu': True, 'force_reload': False, 'GLOBAL_ENABLE_MPS': None, 'USE_SMALL_MODELS': None,                 \n",
              "'OFFLOAD_CPU': None, 'text_temp': 0.7, 'waveform_temp': 0.7, 'confused_travolta_mode': None, 'silent':             \n",
              "False, 'seed': None, 'stable_mode_interval': 1, 'single_starting_seed': None,                                      \n",
              "'split_character_goal_length': 145, 'split_character_max_length': 190, 'split_character_jitter': 0,                \n",
              "'add_silence_between_segments': 0.0, 'split_each_text_prompt_by': None,                                            \n",
              "'split_each_text_prompt_by_value': None, 'extra_confused_travolta_mode': None,                                     \n",
              "'semantic_history_starting_weight': 1.0, 'semantic_history_future_weight': 1.0,                                    \n",
              "'semantic_prev_segment_weight': 0.5, 'coarse_history_starting_weight': 1.0,                                        \n",
              "'coarse_history_future_weight': 0.5, 'coarse_prev_segment_weight': 0.5, 'fine_history_starting_weight':            \n",
              "1.0, 'fine_history_future_weight': 0.0, 'fine_prev_segment_weight': 0.0,                                           \n",
              "'custom_audio_processing_function': None, 'use_smaller_models': False, 'semantic_temp': 0.7,                       \n",
              "'semantic_top_k': None, 'semantic_top_p': None, 'semantic_min_eos_p': 0.2,                                         \n",
              "'semantic_max_gen_duration_s': None, 'semantic_allow_early_stop': True, 'semantic_use_kv_caching': True,           \n",
              "'semantic_seed': None, 'semantic_history_oversize_limit': None, 'coarse_temp': 0.7, 'coarse_top_k':                \n",
              "None, 'coarse_top_p': None, 'coarse_max_coarse_history': 630, 'coarse_sliding_window_len': 60,                     \n",
              "'coarse_kv_caching': True, 'coarse_seed': None, 'coarse_history_time_alignment_hack': -2, 'fine_temp':             \n",
              "0.5, 'fine_seed': None, 'render_npz_samples': False, 'loglevel': 'WARNING', 'output_full': True}}                  \n",
              "
\n" ], "text/plain": [ "generate_audio_barki \u001b[1m{\u001b[0m\u001b[32m'text'\u001b[0m: \u001b[32m'With me, brave the tumultuous seas, claim treasures untold, and send foes\u001b[0m \u001b]8;id=629846;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py\u001b\\\u001b[2mapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=834181;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py#396\u001b\\\u001b[2m396\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[32mto their watery \\ndoom'\u001b[0m, \u001b[32m'kwargs'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'text_prompt'\u001b[0m: \u001b[32m'With me, brave the tumultuous seas, claim treasures \u001b[0m \u001b[2m \u001b[0m\n", "\u001b[32muntold, and send foes to their watery \\ndoom'\u001b[0m, \u001b[32m'list_speakers'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'dry_run'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'text_splits_only'\u001b[0m: \u001b[3;91mFalse\u001b[0m, 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generate_text_semantic {'text': 'With me, brave the tumultuous seas, claim treasures untold, and  generation.py:302\n",
              "send foes to their watery \\ndoom', 'history_prompt': None, 'temp': 0.7, 'top_k': None, 'top_p':                    \n",
              "None, 'silent': False, 'min_eos_p': 0.2, 'max_gen_duration_s': None, 'allow_early_stop': True,                     \n",
              "'use_kv_caching': True}                                                                                            \n",
              "
\n" ], "text/plain": [ "generate_text_semantic \u001b[1m{\u001b[0m\u001b[32m'text'\u001b[0m: \u001b[32m'With me, brave the tumultuous seas, claim treasures untold, and \u001b[0m \u001b]8;id=465439;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py\u001b\\\u001b[2mgeneration.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=151412;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py#302\u001b\\\u001b[2m302\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[32msend foes to their watery \\ndoom'\u001b[0m, \u001b[32m'history_prompt'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'top_k'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'top_p'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[3;35mNone\u001b[0m, \u001b[32m'silent'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'min_eos_p'\u001b[0m: \u001b[1;36m0.2\u001b[0m, \u001b[32m'max_gen_duration_s'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'allow_early_stop'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'use_kv_caching'\u001b[0m: \u001b[3;92mTrue\u001b[0m\u001b[1m}\u001b[0m \u001b[2m \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 100/100 [00:04<00:00, 24.31it/s]\n" ] }, { "data": { "text/html": [ "
generate_coarse {'x_semantic': array([ 131,   10,   10,  266,  459,  206,  206,  206,  206,  206, generation.py:460\n",
              "206,                                                                                                               \n",
              "         65,  206,   65,  344,   65,  344,  147,  147,  147,  147, 1271,                                           \n",
              "       1489, 7907, 5274, 8871,  579,  107,  107, 5727, 1620,   41,   41,                                           \n",
              "         41, 5119, 6557, 6557, 3963, 3963, 3767, 3767,   26,   26,   26,                                           \n",
              "         26,   26,   26,  894,  736,  894,  736, 1688,  252,  252,  252,                                           \n",
              "       6038, 6038, 6038, 6038,   96, 6038,   10, 2138, 9260,   10, 2138,                                           \n",
              "       8610, 1532, 3401,  441, 1419, 4860, 6323, 4868, 2244, 2244, 3841,                                           \n",
              "       3841, 9351, 4237,  166, 3247,  245,  483, 8671, 7095, 7784,  833,                                           \n",
              "         10,    5,    5, 7740, 9158, 3593, 1732,   41,   41, 3135, 5250,                                           \n",
              "       8114, 8114, 3400, 1794,  419,   59,   59,  107,  349, 9191, 2312,                                           \n",
              "       2312, 3664, 3164, 1796, 3917,  880, 7086,   59,   28,   28,   28,                                           \n",
              "         28,   28, 1133, 3195, 6155, 3182, 3182, 8522, 3767,   26,   26,                                           \n",
              "         44, 3753, 3753, 5986,  327,   59,   28, 6172,  589,   10,   27,                                           \n",
              "        399,  399, 6289, 3969, 6185, 6185, 2703, 1544,   41,  489,  210,                                           \n",
              "        210,  282,  401,  401, 2739, 2773, 1463, 3840, 3890, 1450,  620,                                           \n",
              "         92,   92,  190, 2280, 4394, 6022, 1517, 5191,   92,   92,   28,                                           \n",
              "        148, 7473, 3700, 3700, 1948, 8711,  171,   40,   59,    5,    5,                                           \n",
              "        265, 9367, 9367, 2745, 2745, 2745, 6696, 2779, 2779,  326,  326,                                           \n",
              "        326,  326, 2756,  100, 1823,  522, 1333, 1333,  898,  376,  492,                                           \n",
              "         59,   28,   28,   28, 1998, 8218, 3198, 1858,   29, 6965,  321,                                           \n",
              "         41,   40,  181,  181,   59,   10,   41, 9596,  323, 8498, 1001,                                           \n",
              "       4816, 4816, 4207, 2622, 2622, 1647, 1647,   92,   59,   31,   31,                                           \n",
              "        196,  100,    5, 5853, 5563, 5819,   41,   17, 9968, 5839, 3177,                                           \n",
              "       1493, 1536,  393,  429,   41,   41,   41, 5505,  774,  774, 6247,                                           \n",
              "       6247, 9804, 9804,  677,   17,   17, 9105, 8099,  389, 7677, 7069,                                           \n",
              "       2853, 2853, 5640, 5640, 2970,   50,   41,   10,    5, 8136, 4448,                                           \n",
              "       3449, 9329, 7589, 7589, 4236, 4236,  842,  407,  407, 7781,  578,                                           \n",
              "        508, 1385, 2536, 1602,  825,  138,   10,   10,  266,  266,  206,                                           \n",
              "        206,  206,  206,  206,  107,  276,  206, 1444,   91,  206, 4695,                                           \n",
              "        206,  206,  206, 2314,  206,  206,  206,  206,   65,   65,   65,                                           \n",
              "         65,   65,   65,   65,   65,  147,  147]), 'history_prompt': None, 'temp': 0.7, 'top_k':                   \n",
              "None, 'top_p': None, 'silent': False, 'max_coarse_history': 630, 'sliding_window_len': 60,                         \n",
              "'use_kv_caching': True}                                                                                            \n",
              "
\n" ], "text/plain": [ "generate_coarse \u001b[1m{\u001b[0m\u001b[32m'x_semantic'\u001b[0m: \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m \u001b[1;36m131\u001b[0m, \u001b[1;36m10\u001b[0m, \u001b[1;36m10\u001b[0m, \u001b[1;36m266\u001b[0m, \u001b[1;36m459\u001b[0m, \u001b[1;36m206\u001b[0m, \u001b[1;36m206\u001b[0m, \u001b[1;36m206\u001b[0m, \u001b[1;36m206\u001b[0m, \u001b[1;36m206\u001b[0m, \u001b]8;id=433174;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py\u001b\\\u001b[2mgeneration.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=78803;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py#460\u001b\\\u001b[2m460\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[1;36m206\u001b[0m, \u001b[2m \u001b[0m\n", " \u001b[1;36m65\u001b[0m, \u001b[1;36m206\u001b[0m, \u001b[1;36m65\u001b[0m, \u001b[1;36m344\u001b[0m, \u001b[1;36m65\u001b[0m, \u001b[1;36m344\u001b[0m, \u001b[1;36m147\u001b[0m, \u001b[1;36m147\u001b[0m, 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\u001b[1;36m65\u001b[0m, \u001b[1;36m65\u001b[0m, \u001b[1;36m65\u001b[0m, \u001b[1;36m65\u001b[0m, \u001b[1;36m65\u001b[0m, \u001b[1;36m147\u001b[0m, \u001b[1;36m147\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m, \u001b[32m'history_prompt'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'top_k'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[3;35mNone\u001b[0m, \u001b[32m'top_p'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'silent'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'max_coarse_history'\u001b[0m: \u001b[1;36m630\u001b[0m, \u001b[32m'sliding_window_len'\u001b[0m: \u001b[1;36m60\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'use_kv_caching'\u001b[0m: \u001b[3;92mTrue\u001b[0m\u001b[1m}\u001b[0m \u001b[2m \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 17/17 [00:11<00:00, 1.48it/s]\n" ] }, { "data": { "text/html": [ "
generate_fine {'x_coarse_gen': array([[ 855,  855, 1019, ...,  408,  408,  408],                  generation.py:626\n",
              "       [ 424,  937,  913, ...,  518,  424,  518]]), 'history_prompt': None, 'temp': 0.5,                           \n",
              "'silent': False}                                                                                                   \n",
              "
\n" ], "text/plain": [ "generate_fine \u001b[1m{\u001b[0m\u001b[32m'x_coarse_gen'\u001b[0m: \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1m[\u001b[0m \u001b[1;36m855\u001b[0m, \u001b[1;36m855\u001b[0m, \u001b[1;36m1019\u001b[0m, \u001b[33m...\u001b[0m, \u001b[1;36m408\u001b[0m, \u001b[1;36m408\u001b[0m, \u001b[1;36m408\u001b[0m\u001b[1m]\u001b[0m, \u001b]8;id=739196;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py\u001b\\\u001b[2mgeneration.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=453353;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py#626\u001b\\\u001b[2m626\u001b[0m\u001b]8;;\u001b\\\n", " \u001b[1m[\u001b[0m \u001b[1;36m424\u001b[0m, \u001b[1;36m937\u001b[0m, \u001b[1;36m913\u001b[0m, \u001b[33m...\u001b[0m, \u001b[1;36m518\u001b[0m, \u001b[1;36m424\u001b[0m, \u001b[1;36m518\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m, \u001b[32m'history_prompt'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'temp'\u001b[0m: \u001b[1;36m0.5\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'silent'\u001b[0m: \u001b[3;91mFalse\u001b[0m\u001b[1m}\u001b[0m \u001b[2m \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 1/1 [00:04<00:00, 4.22s/it]\n" ] } ], "source": [ "text = \"\"\"With me, brave the tumultuous seas, claim treasures untold, and send foes to their watery \n", "doom\"\"\"\n", "logger.setLevel(\"DEBUG\")\n", "kwargs[\"semantic_min_eos_p\"] = 0.2 \n", "kwargs[\"text_prompt\"] = text\n", "generation.set_seed(37)\n", "kwargs['output_full'] = True\n", "kwargs['output_dir'] = \"bark_test\"\n", "kwargs[\"history_prompt\"] = None\n", "#kwargs['history_prompt'] = 'custom_speakers/en_fiery.npz'\n", "barkifull, audio_arr_segments_barki = api.generate_audio_barki(text, **kwargs)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
337\n",
              "
\n" ], "text/plain": [ "\u001b[1;36m337\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(len(api.our_semantic_tokens))\n", "import copy\n", "\n", "tokens = copy.deepcopy(api.our_semantic_tokens)\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
╭────────────────────────────── <class 'numpy.ndarray'> ───────────────────────────────╮\n",
              " ndarray(shape, dtype=float, buffer=None, offset=0,                                   \n",
              "         strides=None, order=None)                                                    \n",
              "                                                                                      \n",
              " ╭──────────────────────────────────────────────────────────────────────────────────╮ \n",
              "  array([ 131,   10,   10,  266,  266,  266,  206,  206,  206,  206,  206,          \n",
              "  │   │    65,  206,   65,  344,   65,  344,  147,  147,  147,  147, 1271,          \n",
              "  1489, 7907, 5274, 8871,  579,  107,  107, 5727, 1620,   41,   41,          \n",
              "  │   │    41, 5119, 6557, 6557, 3963, 3963, 3767, 3767,   26,   26,   26,          \n",
              "  │   │    26,   26,   26,  894,  736,  894,   10,  230,  230,  230,   10,          \n",
              "  │   │   206, 6032,  206, 6032,  147,  206,  206,  206,  206,   10,  206,          \n",
              "  │   │   206, 3252, 2966,  147,  147, 1278,  147,  147,  147,  147,  147,          \n",
              "  │   │   991,  991,  402,   10,   41,  245, 8969, 4860, 6323, 4099, 4868,          \n",
              "  2244, 2244,  250, 9768, 1307, 4388, 9351, 7895,  178,  166, 1620,          \n",
              "  1573, 6274, 7095, 7784,  210,   50,   10,    5, 2837, 3368, 3415,          \n",
              "  │   │    41,   41,   41, 3135, 2065, 3240, 4579, 9792, 3400,  210,   10,          \n",
              "  │   │   232,  401,  401, 9502, 2402, 2312, 2312, 3664, 1859, 5422, 1796,          \n",
              "  3917,  880,   59,   59,   28,   28,   28,   28,   28,   28,   28,          \n",
              "  1133, 3195, 6155, 6155, 3182, 8522, 8522, 3767, 3767,   44,   44,          \n",
              "  4775,   44,   44, 9839, 8142, 3753, 5986, 1540,   59,   59,   28,          \n",
              "  │   │   107,  589,  589,   10,   10,   27,  399,  287, 1460,  927, 9763,          \n",
              "  4600, 6185, 6185, 7304, 3301, 4149, 5293, 5293, 5293,  911, 1544,          \n",
              "  │   │    41,   41,  489,  850,  547,  210,   10,    5,  265,  401, 2739,          \n",
              "  2773, 2848, 3840, 3890, 3890, 1450, 9403, 4146, 4146,  190,  190,          \n",
              "  2280, 4394, 6022, 6022, 1517,  153,   71,   92,   92,  107, 1835,          \n",
              "  3454, 3454, 3700, 1948, 1948,  444, 1315,  171,  171,  171,  489,          \n",
              "  │   │   489,  489,  210,   10,    5,    5, 9367, 9367, 8498, 2745, 2745,          \n",
              "  6696, 2779, 2779, 2779, 2779, 9454, 9454, 9454, 9454, 8417, 7006,          \n",
              "  6672, 8270, 6018, 6018, 6139, 6139,  227, 6047,  441, 5647,   10,          \n",
              "  │   │    10, 1096, 1096,   10,   10,  266,  206,  206,  206,  206,  206,          \n",
              "  │   │   206,   10,  206,  206,  206,  206,   65,   65,  344,  147,  147,          \n",
              "  │   │    57,   41,   57,  604, 5851, 8604, 5673, 4119,  171,   41,  171,          \n",
              "  │   │   489,   59,   28,   28,   28,   28,   28,   10,   28, 6801, 9235,          \n",
              "  3198, 1858,   29, 3793, 1315,  171,  171,  171,  171,  171,  489,          \n",
              "  │   │   181,  181,   28,   28,   10,  337, 8963, 6412, 6412, 1001, 1001,          \n",
              "  4816, 5301, 6303, 5301, 1667, 8525, 8525, 7365, 7365, 1647, 1647,          \n",
              "  │   │    92,   59,   31,   31,   67,   10,    5, 8911, 5853, 5563, 5563,          \n",
              "  │   │   521,   41,  483, 9968, 5839, 3177, 1493, 1536,  393,  429,  429,          \n",
              "  │   │    41,   38, 4967,  774,  774, 6247, 6247, 6247, 9804,  620,  118,          \n",
              "  │   │    10,   27,  455, 9192, 8099, 8099,  389,  389, 9944, 7069, 2853,          \n",
              "  2853, 5640,   26,  122,   50,  210,   41,   10,   41, 8136, 4448,          \n",
              "  9329, 9329, 4236, 4236, 4236, 4236, 9104, 9104,  407,  407,  407,          \n",
              "  │   │   407, 6258, 6258, 8685, 6258, 1385, 5340, 1980, 6047, 1980, 4838,          \n",
              "  │   │    10, 1811,  278, 1811,  278, 3587,  278,  848,  174,   10, 8555])         \n",
              " ╰──────────────────────────────────────────────────────────────────────────────────╯ \n",
              "                                                                                      \n",
              "     base = array([[ 22661,  20959,  10165,  77651,  20660,  20153,  23103,  62630,   \n",
              "                     21039,  23547,  73904,  10165,  37493,  21665,  98715,  20155,   \n",
              "                     20167,  58578,  20210,  10165,  20159,  55615,  10222,  57173,   \n",
              "                     20162,  20503,  22334,  20205,  20197,  20740, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                    129595, 129595, 129595, 129595, 129595, 129595, 129595, 129595,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                     10000,  10000,  10000,  10000,  10000,  10000,  10000,  10000,   \n",
              "                    129599,    131,     10,     10,    266,    266,    266,    206,   \n",
              "                       206,    206,    206,    206,     65,    206,     65,    344,   \n",
              "                        65,    344,    147,    147,    147,    147,   1271,   1489,   \n",
              "                      7907,   5274,   8871,    579,    107,    107,   5727,   1620,   \n",
              "                        41,     41,     41,   5119,   6557,   6557,   3963,   3963,   \n",
              "                      3767,   3767,     26,     26,     26,     26,     26,     26,   \n",
              "                       894,    736,    894,     10,    230,    230,    230,     10,   \n",
              "                       206,   6032,    206,   6032,    147,    206,    206,    206,   \n",
              "                       206,     10,    206,    206,   3252,   2966,    147,    147,   \n",
              "                      1278,    147,    147,    147,    147,    147,    991,    991,   \n",
              "                       402,     10,     41,    245,   8969,   4860,   6323,   4099,   \n",
              "                      4868,   2244,   2244,    250,   9768,   1307,   4388,   9351,   \n",
              "                      7895,    178,    166,   1620,   1573,   6274,   7095,   7784,   \n",
              "                       210,     50,     10,      5,   2837,   3368,   3415,     41,   \n",
              "                        41,     41,   3135,   2065,   3240,   4579,   9792,   3400,   \n",
              "                       210,     10,    232,    401,    401,   9502,   2402,   2312,   \n",
              "                      2312,   3664,   1859,   5422,   1796,   3917,    880,     59,   \n",
              "                        59,     28,     28,     28,     28,     28,     28,     28,   \n",
              "                      1133,   3195,   6155,   6155,   3182,   8522,   8522,   3767,   \n",
              "                      3767,     44,     44,   4775,     44,     44,   9839,   8142,   \n",
              "                      3753,   5986,   1540,     59,     59,     28,    107,    589,   \n",
              "                       589,     10,     10,     27,    399,    287,   1460,    927,   \n",
              "                      9763,   4600,   6185,   6185,   7304,   3301,   4149,   5293,   \n",
              "                      5293,   5293,    911,   1544,     41,     41,    489,    850,   \n",
              "                       547,    210,     10,      5,    265,    401,   2739,   2773,   \n",
              "                      2848,   3840,   3890,   3890,   1450,   9403,   4146,   4146,   \n",
              "                       190,    190,   2280,   4394,   6022,   6022,   1517,    153,   \n",
              "                        71,     92,     92,    107,   1835,   3454,   3454,   3700,   \n",
              "                      1948,   1948,    444,   1315,    171,    171,    171,    489,   \n",
              "                       489,    489,    210,     10,      5,      5,   9367,   9367,   \n",
              "                      8498,   2745,   2745,   6696,   2779,   2779,   2779,   2779,   \n",
              "                      9454,   9454,   9454,   9454,   8417,   7006,   6672,   8270,   \n",
              "                      6018,   6018,   6139,   6139,    227,   6047,    441,   5647,   \n",
              "                        10,     10,   1096,   1096,     10,     10,    266,    206,   \n",
              "                       206,    206,    206,    206,    206,     10,    206,    206,   \n",
              "                       206,    206,     65,     65,    344,    147,    147,     57,   \n",
              "                        41,     57,    604,   5851,   8604,   5673,   4119,    171,   \n",
              "                        41,    171,    489,     59,     28,     28,     28,     28,   \n",
              "                        28,     10,     28,   6801,   9235,   3198,   1858,     29,   \n",
              "                      3793,   1315,    171,    171,    171,    171,    171,    489,   \n",
              "                       181,    181,     28,     28,     10,    337,   8963,   6412,   \n",
              "                      6412,   1001,   1001,   4816,   5301,   6303,   5301,   1667,   \n",
              "                      8525,   8525,   7365,   7365,   1647,   1647,     92,     59,   \n",
              "                        31,     31,     67,     10,      5,   8911,   5853,   5563,   \n",
              "                      5563,    521,     41,    483,   9968,   5839,   3177,   1493,   \n",
              "                      1536,    393,    429,    429,     41,     38,   4967,    774,   \n",
              "                       774,   6247,   6247,   6247,   9804,    620,    118,     10,   \n",
              "                        27,    455,   9192,   8099,   8099,    389,    389,   9944,   \n",
              "                      7069,   2853,   2853,   5640,     26,    122,     50,    210,   \n",
              "                        41,     10,     41,   8136,   4448,   9329,   9329,   4236,   \n",
              "                      4236,   4236,   4236,   9104,   9104,    407,    407,    407,   \n",
              "                       407,   6258,   6258,   8685,   6258,   1385,   5340,   1980,   \n",
              "                      6047,   1980,   4838,     10,   1811,    278,   1811,    278,   \n",
              "                      3587,    278,    848,    174,     10,   8555]])                 \n",
              "   ctypes = <numpy.core._internal._ctypes object at 0x7f63a46c7340>                   \n",
              "     data = <memory at 0x7f62b7223ac0>                                                \n",
              "    dtype = dtype('int64')                                                            \n",
              "    flags =   C_CONTIGUOUS : True                                                     \n",
              "              F_CONTIGUOUS : True                                                     \n",
              "              OWNDATA : False                                                         \n",
              "              WRITEABLE : True                                                        \n",
              "              ALIGNED : True                                                          \n",
              "              WRITEBACKIFCOPY : False                                                 \n",
              "                                                                                      \n",
              "     flat = <numpy.flatiter object at 0x7a33500>                                      \n",
              "     imag = array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  \n",
              "                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])                                  \n",
              " itemsize = 8                                                                         \n",
              "   nbytes = 3432                                                                      \n",
              "     ndim = 1                                                                         \n",
              "     real = array([ 131,   10,   10,  266,  266,  266,  206,  206,  206,  206,  206,  \n",
              "                     65,  206,   65,  344,   65,  344,  147,  147,  147,  147, 1271,  \n",
              "                   1489, 7907, 5274, 8871,  579,  107,  107, 5727, 1620,   41,   41,  \n",
              "                     41, 5119, 6557, 6557, 3963, 3963, 3767, 3767,   26,   26,   26,  \n",
              "                     26,   26,   26,  894,  736,  894,   10,  230,  230,  230,   10,  \n",
              "                    206, 6032,  206, 6032,  147,  206,  206,  206,  206,   10,  206,  \n",
              "                    206, 3252, 2966,  147,  147, 1278,  147,  147,  147,  147,  147,  \n",
              "                    991,  991,  402,   10,   41,  245, 8969, 4860, 6323, 4099, 4868,  \n",
              "                   2244, 2244,  250, 9768, 1307, 4388, 9351, 7895,  178,  166, 1620,  \n",
              "                   1573, 6274, 7095, 7784,  210,   50,   10,    5, 2837, 3368, 3415,  \n",
              "                     41,   41,   41, 3135, 2065, 3240, 4579, 9792, 3400,  210,   10,  \n",
              "                    232,  401,  401, 9502, 2402, 2312, 2312, 3664, 1859, 5422, 1796,  \n",
              "                   3917,  880,   59,   59,   28,   28,   28,   28,   28,   28,   28,  \n",
              "                   1133, 3195, 6155, 6155, 3182, 8522, 8522, 3767, 3767,   44,   44,  \n",
              "                   4775,   44,   44, 9839, 8142, 3753, 5986, 1540,   59,   59,   28,  \n",
              "                    107,  589,  589,   10,   10,   27,  399,  287, 1460,  927, 9763,  \n",
              "                   4600, 6185, 6185, 7304, 3301, 4149, 5293, 5293, 5293,  911, 1544,  \n",
              "                     41,   41,  489,  850,  547,  210,   10,    5,  265,  401, 2739,  \n",
              "                   2773, 2848, 3840, 3890, 3890, 1450, 9403, 4146, 4146,  190,  190,  \n",
              "                   2280, 4394, 6022, 6022, 1517,  153,   71,   92,   92,  107, 1835,  \n",
              "                   3454, 3454, 3700, 1948, 1948,  444, 1315,  171,  171,  171,  489,  \n",
              "                    489,  489,  210,   10,    5,    5, 9367, 9367, 8498, 2745, 2745,  \n",
              "                   6696, 2779, 2779, 2779, 2779, 9454, 9454, 9454, 9454, 8417, 7006,  \n",
              "                   6672, 8270, 6018, 6018, 6139, 6139,  227, 6047,  441, 5647,   10,  \n",
              "                     10, 1096, 1096,   10,   10,  266,  206,  206,  206,  206,  206,  \n",
              "                    206,   10,  206,  206,  206,  206,   65,   65,  344,  147,  147,  \n",
              "                     57,   41,   57,  604, 5851, 8604, 5673, 4119,  171,   41,  171,  \n",
              "                    489,   59,   28,   28,   28,   28,   28,   10,   28, 6801, 9235,  \n",
              "                   3198, 1858,   29, 3793, 1315,  171,  171,  171,  171,  171,  489,  \n",
              "                    181,  181,   28,   28,   10,  337, 8963, 6412, 6412, 1001, 1001,  \n",
              "                   4816, 5301, 6303, 5301, 1667, 8525, 8525, 7365, 7365, 1647, 1647,  \n",
              "                     92,   59,   31,   31,   67,   10,    5, 8911, 5853, 5563, 5563,  \n",
              "                    521,   41,  483, 9968, 5839, 3177, 1493, 1536,  393,  429,  429,  \n",
              "                     41,   38, 4967,  774,  774, 6247, 6247, 6247, 9804,  620,  118,  \n",
              "                     10,   27,  455, 9192, 8099, 8099,  389,  389, 9944, 7069, 2853,  \n",
              "                   2853, 5640,   26,  122,   50,  210,   41,   10,   41, 8136, 4448,  \n",
              "                   9329, 9329, 4236, 4236, 4236, 4236, 9104, 9104,  407,  407,  407,  \n",
              "                    407, 6258, 6258, 8685, 6258, 1385, 5340, 1980, 6047, 1980, 4838,  \n",
              "                     10, 1811,  278, 1811,  278, 3587,  278,  848,  174,   10, 8555]) \n",
              "    shape = (429,)                                                                    \n",
              "     size = 429                                                                       \n",
              "  strides = (8,)                                                                      \n",
              "        T = array([ 131,   10,   10,  266,  266,  266,  206,  206,  206,  206,  206,  \n",
              "                     65,  206,   65,  344,   65,  344,  147,  147,  147,  147, 1271,  \n",
              "                   1489, 7907, 5274, 8871,  579,  107,  107, 5727, 1620,   41,   41,  \n",
              "                     41, 5119, 6557, 6557, 3963, 3963, 3767, 3767,   26,   26,   26,  \n",
              "                     26,   26,   26,  894,  736,  894,   10,  230,  230,  230,   10,  \n",
              "                    206, 6032,  206, 6032,  147,  206,  206,  206,  206,   10,  206,  \n",
              "                    206, 3252, 2966,  147,  147, 1278,  147,  147,  147,  147,  147,  \n",
              "                    991,  991,  402,   10,   41,  245, 8969, 4860, 6323, 4099, 4868,  \n",
              "                   2244, 2244,  250, 9768, 1307, 4388, 9351, 7895,  178,  166, 1620,  \n",
              "                   1573, 6274, 7095, 7784,  210,   50,   10,    5, 2837, 3368, 3415,  \n",
              "                     41,   41,   41, 3135, 2065, 3240, 4579, 9792, 3400,  210,   10,  \n",
              "                    232,  401,  401, 9502, 2402, 2312, 2312, 3664, 1859, 5422, 1796,  \n",
              "                   3917,  880,   59,   59,   28,   28,   28,   28,   28,   28,   28,  \n",
              "                   1133, 3195, 6155, 6155, 3182, 8522, 8522, 3767, 3767,   44,   44,  \n",
              "                   4775,   44,   44, 9839, 8142, 3753, 5986, 1540,   59,   59,   28,  \n",
              "                    107,  589,  589,   10,   10,   27,  399,  287, 1460,  927, 9763,  \n",
              "                   4600, 6185, 6185, 7304, 3301, 4149, 5293, 5293, 5293,  911, 1544,  \n",
              "                     41,   41,  489,  850,  547,  210,   10,    5,  265,  401, 2739,  \n",
              "                   2773, 2848, 3840, 3890, 3890, 1450, 9403, 4146, 4146,  190,  190,  \n",
              "                   2280, 4394, 6022, 6022, 1517,  153,   71,   92,   92,  107, 1835,  \n",
              "                   3454, 3454, 3700, 1948, 1948,  444, 1315,  171,  171,  171,  489,  \n",
              "                    489,  489,  210,   10,    5,    5, 9367, 9367, 8498, 2745, 2745,  \n",
              "                   6696, 2779, 2779, 2779, 2779, 9454, 9454, 9454, 9454, 8417, 7006,  \n",
              "                   6672, 8270, 6018, 6018, 6139, 6139,  227, 6047,  441, 5647,   10,  \n",
              "                     10, 1096, 1096,   10,   10,  266,  206,  206,  206,  206,  206,  \n",
              "                    206,   10,  206,  206,  206,  206,   65,   65,  344,  147,  147,  \n",
              "                     57,   41,   57,  604, 5851, 8604, 5673, 4119,  171,   41,  171,  \n",
              "                    489,   59,   28,   28,   28,   28,   28,   10,   28, 6801, 9235,  \n",
              "                   3198, 1858,   29, 3793, 1315,  171,  171,  171,  171,  171,  489,  \n",
              "                    181,  181,   28,   28,   10,  337, 8963, 6412, 6412, 1001, 1001,  \n",
              "                   4816, 5301, 6303, 5301, 1667, 8525, 8525, 7365, 7365, 1647, 1647,  \n",
              "                     92,   59,   31,   31,   67,   10,    5, 8911, 5853, 5563, 5563,  \n",
              "                    521,   41,  483, 9968, 5839, 3177, 1493, 1536,  393,  429,  429,  \n",
              "                     41,   38, 4967,  774,  774, 6247, 6247, 6247, 9804,  620,  118,  \n",
              "                     10,   27,  455, 9192, 8099, 8099,  389,  389, 9944, 7069, 2853,  \n",
              "                   2853, 5640,   26,  122,   50,  210,   41,   10,   41, 8136, 4448,  \n",
              "                   9329, 9329, 4236, 4236, 4236, 4236, 9104, 9104,  407,  407,  407,  \n",
              "                    407, 6258, 6258, 8685, 6258, 1385, 5340, 1980, 6047, 1980, 4838,  \n",
              "                     10, 1811,  278, 1811,  278, 3587,  278,  848,  174,   10, 8555]) \n",
              "╰──────────────────────────────────────────────────────────────────────────────────────╯\n",
              "
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semantic_prompt 429\n",
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\n" ], "text/plain": [ "fine_prompt \u001b[1;36m8\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for x in barkifull.keys():\n", " print(x, len(barkifull[x]))\n", "\n", "api.save_as_prompt(\"custom_prompts/seed37_bark_piece.npz\", barkifull)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "logger.setLevel(\"DEBUG\")\n", "generation.set_seed(37)\n", "#kwargs['history_prompt'] = 'custom_speakers/en_fiery.npz'\n", "\n", "text = \"\"\"With me, brave the tumultuous seas, claim treasures untold, and send foes to their watery \n", "doom\"\"\"\n", "#kwargs['history_prompt'] = 'custom_speakers/en_fiery.npz'\n", "\n", "\n", "fullgen, gen_audio_orig_segs = api.generate_audio(text, output_full=True)" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Audio(audio_arr_segments_barki, rate=24000)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "id": "OTRtNy1xT1sI" }, "source": [ "## Generate\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "id": "LKLe_gYkQ59l" }, "source": [ "### Choose Bark Models" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 354, "referenced_widgets": [ "027e4d85d7ec446ea17933b1fd4e676c", "32224d540c5244869462288f645951b1", "819711a97a6e4fe2b6633eae173b6575", "377b633bc3994b52bd0956243d09047a", "013a3a01de444015993f29262e764d31", "7b2d2049047b459c8e2262c40d0cfa45", "576df395690b4c0b99830552e2b31cd5", "d5c81d66785d4db3b57fbb92fcab58a8", "8169f42d4d8e4b73bb8d8219aa2e5470", "00a62ed0e2a7466487681968208fa3bb", "ced6cb4550d7488286be0b3638c24c84", "ce598375216545fb9f872b5885675ad6", "321a14b744234326bb8054b8054cbe2a", "9a705060d08f41b4ab63838cc18a0b26", "e49e13dba43747fe8eef104ae9dc29bb", "f5ca8b4b942f43f589aa8a32195129a5", "1bfd3dcb8838423292eac4f14fb91826", "e552b786de384492b19c100cd80eade6", "7b37d306a0d54a24ae2c2c608874ee3e", "62d32b94270c41f49616c042ef3fd247", "99537f40148e4a4693045a9c21f27922", "89b9dceaedc4486891f691662599a129", "0b01544340a146b0bd4a98c9e070afbe", "a78700fee93643aab26605c995accb20", "445436b5d19e4f579044ffcf054059ec", "52cc22a98c8a41248e970c236de3c54a", "c55c40e634874df9964171bd0e4dc8f1", "838e8cacd05f4b67b08dd8c9d47121f6", "a32e5dc742534acd840867b718b7de26", "6e04bc6dba3a48b98dcab93ca4f2d663", "8f6013de1c1e4b97b739ca9ccd6e6aa9", "ec2a76e0610c4ad98d65accdc4a76c00", "424eaff7db5f4a6f93b63f6f3689e925", "5bd22e64eae04001ac45ea6d7c0e7e87", "a497d371f1e544b9b78a5218264d1ff9", "fe12056cfa4e4f99b4d2f50f678e5ed1", "53b1192d99ed41c8a77977329884fec6", "6b014648489141fd961ef5f22ddf5fd7", "6b0ccecb9e134820a1fe274d30f59537", "8d6be754d6f44266875d523cc36a3440", "833a52e4023541568e8617ad3e55342e", "73fb07bc20f94d2f80cb52405489d541", "f8dfd5fc27974becbc62a34c26a47e59", "f05dbf93cf484f4fa2130048ea0bb3ef", "0196e347c9994627bbcc132d86b8422b", "f2bf510f5e67418f8bde74c11636e2a8", "1cf1934e32b74ff3a070b3c6ea1d8dc3", "3eaf9a0e62ed494e892905a1b29c68ad", "ebfb1dd8e70745b29ed93efa1d44fcad", "8d35ce696ee143fd95295652d6cd2977", "349f0786f9df43328291527f593435d8", "897fde99f5d248dcbe917779b5cc2526", "218c5f11039f43bb8496a6e21efcee91", "36247efa11dc494c8efc0afafaee5e7b", "bd8681508bcb4d7799036010537633ff", "dba563834f79488ab1516806c5df19b5", "5c088c4eeffa446c9bbc93ce2ece68da", "57e700ef080e41b68d3e0a42e4d6ca2d", "08f4442e9955495e8b9bb254cfca0635", "82395e07a76441d4a21f4f52d7c2d45c", "b5188eeb32ed40fc97da82c009515816", "5336744cf34c40bc83582a75abe5b366", "2f4e1836c7234e21a9dad9c6f0217a40", "d6e2321c74d84f8ebcdc6d4418f7afb3", "cd216b4627aa416cbf99ae82efe26a0f", "404e00dbe5d3426eb438034275151c2c" ] }, "id": "QLa2jPOUjSyd", "outputId": "50727264-7675-4ac5-b539-735f31fb4a11" }, "outputs": [], "source": [ "generation.OFFLOAD_CPU = True # On your home system set to True probably, but Colab GPU should have plenty of memory for all three models\n", "generation.preload_models() # Optional, will lazy load if not preloaded. First time run in New Colab has to download models" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "text = \"\"\"\n", "Hark! I, the phantom visage of Edward Teach, rise from the \n", "abyss, forever bound to the briny depths. With me, brave the tumultuous seas, claim treasures untold,\n", "and send foes to their watery doom.\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import os\n", "import time\n", "from bark_infinity import config\n", "import numpy as np\n", "\n", "logger = config.logger\n", "logger.setLevel(\"WARNING\")\n", "\n", "from bark_infinity import generation\n", "from bark_infinity import api\n", "\n", "import rich\n", "from rich import print\n", "from rich import pretty\n", "from rich.pretty import pprint\n", "from rich import inspect\n", "\n", "\n", "from pydub import AudioSegment\n", "import ipywidgets as widgets\n", "from IPython.display import display, Audio\n", "from io import BytesIO\n", "from tqdm import tqdm\n", "\n", "\n", "# For split set split_character_goal_length and split_character_max_length\n", "kwargs = {}\n", "\n", "kwargs = config.load_all_defaults()\n", "#kwargs['text_prompt'] = text\n", "kwargs['hoarder_mode'] = True\n", "kwargs[\"output_dir\"] = 'bark_samples'\n", "kwargs[\"history_prompt\"] = None\n", "# kwargs[\"single_starting_seed\"] = None # \n", "# If you set seed you might want manually call generation.set_seed(-1) after to disable deterministic generation settings \n", "# I'm not cleaning up after this paramater at the moment and I'm not sure on other side effects\n", "kwargs[\"stable_mode_interval\"] = 1 # 0 for continous, 2,3,4 for mixed\n", "kwargs[\"split_character_goal_length\"] = 145\n", "kwargs[\"split_character_max_length\"] = 190\n", "# kwargs[\"output_iterations\"] = 1\n", "kwargs[\"add_silence_between_segments\"] = 0.0 # See: https://github.com/suno-ai/bark/blob/main/notebooks/long_form_generation.ipynb but not great for songs or stable_mode_interval 0\n", "kwargs[\"semantic_min_eos_p\"] = 0.2 # 0.20 is default, lower means more likely to stotp\n", "\n", "\n", "# not sure on overall effect so far from these, but for example:\n", "kwargs[\"semantic_top_k\"] = None \n", "kwargs[\"semantic_top_p\"] = None\n", "kwargs[\"coarse_top_k\"] = None\n", "kwargs[\"coarse_top_p\"] = None\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\n", "\n", "from rich import prompt, print,inspect\n", "pprint(kwargs)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 54, "metadata": {}, "outputs": [], "source": [ "kwargs['history_prompt'] = \"custom_speakers/hark_woman.npz\"\n", "text = \"\"\"With me, brave the tumultuous seas, claim treasures untold, and send foes to their watery \n", "doom\"\"\"\n", "kwargs['text_prompt'] = text\n", "kwargs['single_starting_seed'] = None\n", "generation.set_seed(37)\n", "logger.setLevel(\"DEBUG\")" ] }, { "cell_type": "code", "execution_count": 55, "metadata": {}, "outputs": [], "source": [ "api.gradio_try_to_cancel = False" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
set_seed Enabling deterministic algorithms                                                        generation.py:929\n",
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set_seed Set seed to 37                                                                           generation.py:944\n",
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generate_audio_long {'kwargs': {'text_prompt': 'With me, brave the tumultuous seas, claim treasures      api.py:507\n",
              "untold, and send foes to their watery \\ndoom', 'list_speakers': None, 'dry_run': False,                            \n",
              "'text_splits_only': False, 'history_prompt': 'custom_speakers/hark_woman.npz', 'prompt_file': None,                \n",
              "'split_input_into_separate_prompts_by': None, 'split_input_into_separate_prompts_by_value': None,                  \n",
              "'always_save_speaker': True, 'output_iterations': 1, 'output_filename': None, 'output_dir': 'long',                \n",
              "'hoarder_mode': True, 'extra_stats': False, 'text_use_gpu': True, 'text_use_small': False,                         \n",
              "'coarse_use_gpu': True, 'coarse_use_small': False, 'fine_use_gpu': True, 'fine_use_small': False,                  \n",
              "'codec_use_gpu': True, 'force_reload': False, 'GLOBAL_ENABLE_MPS': None, 'USE_SMALL_MODELS': None,                 \n",
              "'OFFLOAD_CPU': None, 'text_temp': 0.7, 'waveform_temp': 0.7, 'confused_travolta_mode': None, 'silent':             \n",
              "False, 'seed': None, 'stable_mode_interval': 1, 'single_starting_seed': None,                                      \n",
              "'split_character_goal_length': 145, 'split_character_max_length': 190, 'split_character_jitter': 0,                \n",
              "'add_silence_between_segments': 0.0, 'split_each_text_prompt_by': None,                                            \n",
              "'split_each_text_prompt_by_value': None, 'extra_confused_travolta_mode': None,                                     \n",
              "'semantic_history_starting_weight': 1.0, 'semantic_history_future_weight': 1.0,                                    \n",
              "'semantic_prev_segment_weight': 0.5, 'coarse_history_starting_weight': 1.0,                                        \n",
              "'coarse_history_future_weight': 0.5, 'coarse_prev_segment_weight': 0.5, 'fine_history_starting_weight':            \n",
              "1.0, 'fine_history_future_weight': 0.0, 'fine_prev_segment_weight': 0.0,                                           \n",
              "'custom_audio_processing_function': None, 'use_smaller_models': False, 'semantic_temp': 0.7,                       \n",
              "'semantic_top_k': None, 'semantic_top_p': None, 'semantic_min_eos_p': 2, 'semantic_max_gen_duration_s':            \n",
              "None, 'semantic_allow_early_stop': True, 'semantic_use_kv_caching': True, 'semantic_seed': None,                   \n",
              "'semantic_history_oversize_limit': None, 'coarse_temp': 0.7, 'coarse_top_k': None, 'coarse_top_p': None,           \n",
              "'coarse_max_coarse_history': 630, 'coarse_sliding_window_len': 60, 'coarse_kv_caching': True,                      \n",
              "'coarse_seed': None, 'coarse_history_time_alignment_hack': -2, 'fine_temp': 0.5, 'fine_seed': None,                \n",
              "'render_npz_samples': False, 'loglevel': 'WARNING'}}                                                               \n",
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    () Segment Breakdown                                                                                           \n",
              "┏━━━┳━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
              "┃ #  Words  Time Est  Splitting long text aiming for 145 chars max 190                                         ┃\n",
              "┡━━━╇━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
              "│ 1  16     6.40 s   │ With me, brave the tumultuous seas, claim treasures untold, and send foes to their       │\n",
              "│           94 chars │ watery doom                                                                              │\n",
              "└───┴───────┴──────────┴──────────────────────────────────────────────────────────────────────────────────────────┘\n",
              "
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write_seg_npz   .npz saved to long/With_me_brave_t-SPK-hark_woman_3.wav_initial_prompt.npz               api.py:316\n",
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            "segment_text: With me, brave the tumultuous seas, claim treasures untold, and send foes to their watery doom\n"
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--Segment 1/1: est. 6.40s ( of 1 iterations)\n",
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generate_audio_barki {'text': 'With me, brave the tumultuous seas, claim treasures untold, and send foes api.py:362\n",
              "to their watery doom', 'kwargs': {'text_prompt': 'With me, brave the tumultuous seas, claim treasures              \n",
              "untold, and send foes to their watery doom', 'list_speakers': None, 'dry_run': False,                              \n",
              "'text_splits_only': False, 'history_prompt': {'semantic_prompt': array([ 131,   10,   27,  282,  395,              \n",
              "7686,  131,  131,  266, 1373,  459,                                                                                \n",
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              "        206,  206,  206,  206,  206,  206,  206,  206,  206,  206,  206,                                           \n",
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              "        602, 5064,  302, 1075, 1556, 1556, 1556, 1556, 6122, 2673, 6437,                                           \n",
              "       6437, 6437, 6437, 6105, 4382, 7378, 1471, 1471, 1471, 9935, 9935,                                           \n",
              "       5771, 5771, 5771,  178,   27,   10,   27,   27, 3971, 3971, 1233,                                           \n",
              "       1206,  206,  230,  230,  230, 1613, 1613, 1613, 1613, 1613, 1613,                                           \n",
              "       2009, 2009, 2009, 1380, 6206, 6206,  147, 5064,  302,  302, 7644,                                           \n",
              "       9877, 5214, 3427, 3427, 3427, 3427,  133, 8308,  133, 8308,  133,                                           \n",
              "       2665, 2665, 7532, 2665, 7532, 4155,  990,  163,  990,  990,  990,                                           \n",
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              "         59,   28,   59,   10,   41, 3620, 5743, 4884, 7433, 7433, 7858,                                           \n",
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              "         41, 1732,   41,   41,   41, 9532, 6903, 6903, 6903,   92,   28,                                           \n",
              "         59, 3529, 5027, 5027, 6714, 6714, 6714,  826,  826,  178,   99,                                           \n",
              "         27,   27,  532, 8419, 3745, 3745,  117,   41,  402, 6666, 1025,                                           \n",
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              "       8399, 5508, 6059,  452, 1079,  210,  441,   10,    5,  282, 3538,                                           \n",
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              "       2068,  232,   10,  532,  532,  532,  107,  142, 6802, 5211,  266,                                           \n",
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              "        206,  397, 5128,  397,  215,  107, 2315,  548, 1362, 6340,  441,                                           \n",
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              "       8512, 3427, 5651, 8308, 8308, 8308, 8308, 2665, 2665, 2665, 7038,                                           \n",
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              "         41, 1461, 7101, 4640, 2655, 4800, 6358,  808,  808,   41,   41,                                           \n",
              "         10,   41, 5991, 1831, 1831, 1831,  621,  621, 5865, 2453,  529,                                           \n",
              "         59,   59,   28,   28,   28,   28,   28,   28,   28,   28,  107,                                           \n",
              "        107,  385, 2465,  230,  131,  230, 2443,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206, 3252,  206,  193,  206,                                           \n",
              "        206,  517,  147,  822,  206,  206,  206, 1278, 2305,  302, 5064,                                           \n",
              "       1075,  181,  107,  181, 2595, 4051, 7439, 7698, 7698,  389, 7194,                                           \n",
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              "        402,   41, 6821, 3973, 5265, 1282,   41,   41,   10,   27,  429,                                           \n",
              "       6945, 8234, 5838, 5451, 3139, 8512, 5611, 8092, 8092, 8695, 8688,                                           \n",
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              "         50,   10,    5,  652, 8921, 8921, 9245, 8141, 8141, 6997, 6997,                                           \n",
              "          3,    3,   27,   27,  232,   10,  403,  403, 9563, 9563,  481,                                           \n",
              "        481,  481,   28,  107,   28,   28,   28,  107,  385, 9355, 2672,                                           \n",
              "        131,  206,  266, 1373, 1572,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206,  206, 3252, 3252,  206,                                           \n",
              "        206,  206, 7567, 3252, 2966, 1278,  206, 1278, 1278, 1278, 2009,                                           \n",
              "       2009, 8735, 8735,  147, 5128,   57,   57, 9817, 9817]), 'coarse_prompt': array([[738, 738, 738,             \n",
              "..., 479, 850, 865],                                                                                               \n",
              "       [363, 363, 913, ..., 430, 132, 648]]), 'fine_prompt': array([[ 738,  738,  738, ...,  479,  850,            \n",
              "865],                                                                                                              \n",
              "       [ 363,  363,  913, ...,  430,  132,  648],                                                                  \n",
              "       [1000,   36,  786, ...,  127,   62,  910],                                                                  \n",
              "       ...,                                                                                                        \n",
              "       [1011,  939,  939, ...,  521,  760,  632],                                                                  \n",
              "       [ 562,  782,  748, ...,  413,  709,  528],                                                                  \n",
              "       [ 948,  518,  975, ...,  285,  214,   42]], dtype=int32)}, 'prompt_file': None,                             \n",
              "'split_input_into_separate_prompts_by': None, 'split_input_into_separate_prompts_by_value': None,                  \n",
              "'always_save_speaker': True, 'output_iterations': 1, 'output_filename': None, 'output_dir': 'long',                \n",
              "'hoarder_mode': True, 'extra_stats': False, 'text_use_gpu': True, 'text_use_small': False,                         \n",
              "'coarse_use_gpu': True, 'coarse_use_small': False, 'fine_use_gpu': True, 'fine_use_small': False,                  \n",
              "'codec_use_gpu': True, 'force_reload': False, 'GLOBAL_ENABLE_MPS': None, 'USE_SMALL_MODELS': None,                 \n",
              "'OFFLOAD_CPU': None, 'text_temp': 0.7, 'waveform_temp': 0.7, 'confused_travolta_mode': None, 'silent':             \n",
              "False, 'seed': None, 'stable_mode_interval': 1, 'single_starting_seed': None,                                      \n",
              "'split_character_goal_length': 145, 'split_character_max_length': 190, 'split_character_jitter': 0,                \n",
              "'add_silence_between_segments': 0.0, 'split_each_text_prompt_by': None,                                            \n",
              "'split_each_text_prompt_by_value': None, 'extra_confused_travolta_mode': None,                                     \n",
              "'semantic_history_starting_weight': 1.0, 'semantic_history_future_weight': 1.0,                                    \n",
              "'semantic_prev_segment_weight': 0.5, 'coarse_history_starting_weight': 1.0,                                        \n",
              "'coarse_history_future_weight': 0.5, 'coarse_prev_segment_weight': 0.5, 'fine_history_starting_weight':            \n",
              "1.0, 'fine_history_future_weight': 0.0, 'fine_prev_segment_weight': 0.0,                                           \n",
              "'custom_audio_processing_function': None, 'use_smaller_models': False, 'semantic_temp': 0.7,                       \n",
              "'semantic_top_k': None, 'semantic_top_p': None, 'semantic_min_eos_p': 2, 'semantic_max_gen_duration_s':            \n",
              "None, 'semantic_allow_early_stop': True, 'semantic_use_kv_caching': True, 'semantic_seed': None,                   \n",
              "'semantic_history_oversize_limit': None, 'coarse_temp': 0.7, 'coarse_top_k': None, 'coarse_top_p': None,           \n",
              "'coarse_max_coarse_history': 630, 'coarse_sliding_window_len': 60, 'coarse_kv_caching': True,                      \n",
              "'coarse_seed': None, 'coarse_history_time_alignment_hack': -2, 'fine_temp': 0.5, 'fine_seed': None,                \n",
              "'render_npz_samples': False, 'loglevel': 'WARNING', 'history_prompt_string':                                       \n",
              "'custom_speakers/hark_woman.npz', 'segment_number': 1, 'output_full': True, 'total_segments': 1}}                  \n",
              "
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\u001b[33m...\u001b[0m, \u001b[1;36m285\u001b[0m, \u001b[1;36m214\u001b[0m, \u001b[1;36m42\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m, \u001b[33mdtype\u001b[0m=\u001b[35mint32\u001b[0m\u001b[1m)\u001b[0m\u001b[1m}\u001b[0m, \u001b[32m'prompt_file'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'split_input_into_separate_prompts_by'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'split_input_into_separate_prompts_by_value'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'always_save_speaker'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'output_iterations'\u001b[0m: \u001b[1;36m1\u001b[0m, \u001b[32m'output_filename'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'output_dir'\u001b[0m: \u001b[32m'long'\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'hoarder_mode'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'extra_stats'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'text_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'text_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'coarse_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'coarse_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'fine_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'fine_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'codec_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'force_reload'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'GLOBAL_ENABLE_MPS'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'USE_SMALL_MODELS'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'OFFLOAD_CPU'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'text_temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'waveform_temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'confused_travolta_mode'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'silent'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[3;91mFalse\u001b[0m, \u001b[32m'seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'stable_mode_interval'\u001b[0m: \u001b[1;36m1\u001b[0m, \u001b[32m'single_starting_seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'split_character_goal_length'\u001b[0m: \u001b[1;36m145\u001b[0m, \u001b[32m'split_character_max_length'\u001b[0m: \u001b[1;36m190\u001b[0m, \u001b[32m'split_character_jitter'\u001b[0m: \u001b[1;36m0\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'add_silence_between_segments'\u001b[0m: \u001b[1;36m0.0\u001b[0m, \u001b[32m'split_each_text_prompt_by'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'split_each_text_prompt_by_value'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'extra_confused_travolta_mode'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'semantic_history_starting_weight'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[32m'semantic_history_future_weight'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[2m 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generate_audio_barki {'text': 'With me, brave the tumultuous seas, claim treasures untold, and send foes api.py:366\n",
              "to their watery doom', 'kwargs': {'text_prompt': 'With me, brave the tumultuous seas, claim treasures              \n",
              "untold, and send foes to their watery doom', 'list_speakers': None, 'dry_run': False,                              \n",
              "'text_splits_only': False, 'history_prompt': {'semantic_prompt': array([ 131,   10,   27,  282,  395,              \n",
              "7686,  131,  131,  266, 1373,  459,                                                                                \n",
              "        206,  206,  206,  206,  206,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206, 5196,   91, 7567,  206, 3252,  822, 7782, 7782,                                           \n",
              "        602, 5064,  302, 1075, 1556, 1556, 1556, 1556, 6122, 2673, 6437,                                           \n",
              "       6437, 6437, 6437, 6105, 4382, 7378, 1471, 1471, 1471, 9935, 9935,                                           \n",
              "       5771, 5771, 5771,  178,   27,   10,   27,   27, 3971, 3971, 1233,                                           \n",
              "       1206,  206,  230,  230,  230, 1613, 1613, 1613, 1613, 1613, 1613,                                           \n",
              "       2009, 2009, 2009, 1380, 6206, 6206,  147, 5064,  302,  302, 7644,                                           \n",
              "       9877, 5214, 3427, 3427, 3427, 3427,  133, 8308,  133, 8308,  133,                                           \n",
              "       2665, 2665, 7532, 2665, 7532, 4155,  990,  163,  990,  990,  990,                                           \n",
              "       9682, 9682, 2292, 2292, 8844, 1573,  402,  483, 7910, 5265, 8119,                                           \n",
              "         59,   28,   59,   10,   41, 3620, 5743, 4884, 7433, 7433, 7858,                                           \n",
              "       5566,  321,   99,  100,    5, 9717, 2036, 2267, 2267,   41,   41,                                           \n",
              "         41, 1732,   41,   41,   41, 9532, 6903, 6903, 6903,   92,   28,                                           \n",
              "         59, 3529, 5027, 5027, 6714, 6714, 6714,  826,  826,  178,   99,                                           \n",
              "         27,   27,  532, 8419, 3745, 3745,  117,   41,  402, 6666, 1025,                                           \n",
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              "       4737, 6664, 8726, 8522, 3767, 3767,  233,  233,   44, 8142, 8290,                                           \n",
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              "        206,  397, 5128,  397,  215,  107, 2315,  548, 1362, 6340,  441,                                           \n",
              "       2305,  147, 5128,  302, 4929,  429,   41,   41, 7168, 5451, 9742,                                           \n",
              "       8512, 3427, 5651, 8308, 8308, 8308, 8308, 2665, 2665, 2665, 7038,                                           \n",
              "       2323, 4155, 4155, 5012, 5012, 5012, 5012, 5986, 2585,   59,   28,                                           \n",
              "        107, 4063, 9608,  417, 9725, 9725, 6445, 2428,   41,   41,  130,                                           \n",
              "         41, 1461, 7101, 4640, 2655, 4800, 6358,  808,  808,   41,   41,                                           \n",
              "         10,   41, 5991, 1831, 1831, 1831,  621,  621, 5865, 2453,  529,                                           \n",
              "         59,   59,   28,   28,   28,   28,   28,   28,   28,   28,  107,                                           \n",
              "        107,  385, 2465,  230,  131,  230, 2443,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206, 3252,  206,  193,  206,                                           \n",
              "        206,  517,  147,  822,  206,  206,  206, 1278, 2305,  302, 5064,                                           \n",
              "       1075,  181,  107,  181, 2595, 4051, 7439, 7698, 7698,  389, 7194,                                           \n",
              "       1463, 3840, 3890,  969,    3,   41, 1468, 6772, 3281, 1009, 1536,                                           \n",
              "        393,   41,   10,   27, 9057, 5665, 4704, 4704, 5764, 5764, 7111,                                           \n",
              "       8557, 8557, 8557, 7252, 7252, 2582,  704, 3038,  407, 3038, 3038,                                           \n",
              "       3734,  657,    4,    4,  255,  255,  255,   99,  583,  395,  395,                                           \n",
              "       4565, 4565, 3889, 1037,  131,    5,    5, 2837, 5853, 5563, 5819,                                           \n",
              "        402,   41, 6821, 3973, 5265, 1282,   41,   41,   10,   27,  429,                                           \n",
              "       6945, 8234, 5838, 5451, 3139, 8512, 5611, 8092, 8092, 8695, 8688,                                           \n",
              "       3694, 6069,  288,   41, 4331, 4418, 7265, 7265, 1262,   26,  122,                                           \n",
              "         50,   10,    5,  652, 8921, 8921, 9245, 8141, 8141, 6997, 6997,                                           \n",
              "          3,    3,   27,   27,  232,   10,  403,  403, 9563, 9563,  481,                                           \n",
              "        481,  481,   28,  107,   28,   28,   28,  107,  385, 9355, 2672,                                           \n",
              "        131,  206,  266, 1373, 1572,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206,  206, 3252, 3252,  206,                                           \n",
              "        206,  206, 7567, 3252, 2966, 1278,  206, 1278, 1278, 1278, 2009,                                           \n",
              "       2009, 8735, 8735,  147, 5128,   57,   57, 9817, 9817]), 'coarse_prompt': array([[738, 738, 738,             \n",
              "..., 479, 850, 865],                                                                                               \n",
              "       [363, 363, 913, ..., 430, 132, 648]]), 'fine_prompt': array([[ 738,  738,  738, ...,  479,  850,            \n",
              "865],                                                                                                              \n",
              "       [ 363,  363,  913, ...,  430,  132,  648],                                                                  \n",
              "       [1000,   36,  786, ...,  127,   62,  910],                                                                  \n",
              "       ...,                                                                                                        \n",
              "       [1011,  939,  939, ...,  521,  760,  632],                                                                  \n",
              "       [ 562,  782,  748, ...,  413,  709,  528],                                                                  \n",
              "       [ 948,  518,  975, ...,  285,  214,   42]], dtype=int32)}, 'prompt_file': None,                             \n",
              "'split_input_into_separate_prompts_by': None, 'split_input_into_separate_prompts_by_value': None,                  \n",
              "'always_save_speaker': True, 'output_iterations': 1, 'output_filename': None, 'output_dir': 'long',                \n",
              "'hoarder_mode': True, 'extra_stats': False, 'text_use_gpu': True, 'text_use_small': False,                         \n",
              "'coarse_use_gpu': True, 'coarse_use_small': False, 'fine_use_gpu': True, 'fine_use_small': False,                  \n",
              "'codec_use_gpu': True, 'force_reload': False, 'GLOBAL_ENABLE_MPS': None, 'USE_SMALL_MODELS': None,                 \n",
              "'OFFLOAD_CPU': None, 'text_temp': 0.7, 'waveform_temp': 0.7, 'confused_travolta_mode': None, 'silent':             \n",
              "False, 'seed': None, 'stable_mode_interval': 1, 'single_starting_seed': None,                                      \n",
              "'split_character_goal_length': 145, 'split_character_max_length': 190, 'split_character_jitter': 0,                \n",
              "'add_silence_between_segments': 0.0, 'split_each_text_prompt_by': None,                                            \n",
              "'split_each_text_prompt_by_value': None, 'extra_confused_travolta_mode': None,                                     \n",
              "'semantic_history_starting_weight': 1.0, 'semantic_history_future_weight': 1.0,                                    \n",
              "'semantic_prev_segment_weight': 0.5, 'coarse_history_starting_weight': 1.0,                                        \n",
              "'coarse_history_future_weight': 0.5, 'coarse_prev_segment_weight': 0.5, 'fine_history_starting_weight':            \n",
              "1.0, 'fine_history_future_weight': 0.0, 'fine_prev_segment_weight': 0.0,                                           \n",
              "'custom_audio_processing_function': None, 'use_smaller_models': False, 'semantic_temp': 0.7,                       \n",
              "'semantic_top_k': None, 'semantic_top_p': None, 'semantic_min_eos_p': 2, 'semantic_max_gen_duration_s':            \n",
              "None, 'semantic_allow_early_stop': True, 'semantic_use_kv_caching': True, 'semantic_seed': None,                   \n",
              "'semantic_history_oversize_limit': None, 'coarse_temp': 0.7, 'coarse_top_k': None, 'coarse_top_p': None,           \n",
              "'coarse_max_coarse_history': 630, 'coarse_sliding_window_len': 60, 'coarse_kv_caching': True,                      \n",
              "'coarse_seed': None, 'coarse_history_time_alignment_hack': -2, 'fine_temp': 0.5, 'fine_seed': None,                \n",
              "'render_npz_samples': False, 'loglevel': 'WARNING', 'history_prompt_string':                                       \n",
              "'custom_speakers/hark_woman.npz', 'segment_number': 1, 'output_full': True, 'total_segments': 1}}                  \n",
              "
\n" ], "text/plain": [ "generate_audio_barki \u001b[1m{\u001b[0m\u001b[32m'text'\u001b[0m: \u001b[32m'With me, brave the tumultuous seas, claim treasures untold, and send foes\u001b[0m \u001b]8;id=151412;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py\u001b\\\u001b[2mapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=839049;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py#366\u001b\\\u001b[2m366\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[32mto their watery doom'\u001b[0m, \u001b[32m'kwargs'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'text_prompt'\u001b[0m: \u001b[32m'With me, brave the tumultuous seas, claim treasures \u001b[0m \u001b[2m \u001b[0m\n", "\u001b[32muntold, and send foes to their watery doom'\u001b[0m, \u001b[32m'list_speakers'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'dry_run'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'text_splits_only'\u001b[0m: \u001b[3;91mFalse\u001b[0m, 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\u001b[33m...\u001b[0m, \u001b[1;36m285\u001b[0m, \u001b[1;36m214\u001b[0m, \u001b[1;36m42\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m, \u001b[33mdtype\u001b[0m=\u001b[35mint32\u001b[0m\u001b[1m)\u001b[0m\u001b[1m}\u001b[0m, \u001b[32m'prompt_file'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'split_input_into_separate_prompts_by'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'split_input_into_separate_prompts_by_value'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'always_save_speaker'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'output_iterations'\u001b[0m: \u001b[1;36m1\u001b[0m, \u001b[32m'output_filename'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'output_dir'\u001b[0m: \u001b[32m'long'\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'hoarder_mode'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'extra_stats'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'text_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'text_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'coarse_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'coarse_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'fine_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'fine_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'codec_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'force_reload'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'GLOBAL_ENABLE_MPS'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'USE_SMALL_MODELS'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'OFFLOAD_CPU'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'text_temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'waveform_temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'confused_travolta_mode'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'silent'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[3;91mFalse\u001b[0m, \u001b[32m'seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'stable_mode_interval'\u001b[0m: \u001b[1;36m1\u001b[0m, \u001b[32m'single_starting_seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'split_character_goal_length'\u001b[0m: \u001b[1;36m145\u001b[0m, \u001b[32m'split_character_max_length'\u001b[0m: \u001b[1;36m190\u001b[0m, \u001b[32m'split_character_jitter'\u001b[0m: \u001b[1;36m0\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'add_silence_between_segments'\u001b[0m: \u001b[1;36m0.0\u001b[0m, \u001b[32m'split_each_text_prompt_by'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'split_each_text_prompt_by_value'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'extra_confused_travolta_mode'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'semantic_history_starting_weight'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[32m'semantic_history_future_weight'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[2m 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generate_text_semantic {'text': 'With me, brave the tumultuous seas, claim treasures untold, and  generation.py:302\n",
              "send foes to their watery doom', 'history_prompt': {'semantic_prompt': array([ 131,   10,   27,                    \n",
              "282,  395, 7686,  131,  131,  266, 1373,  459,                                                                     \n",
              "        206,  206,  206,  206,  206,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206, 5196,   91, 7567,  206, 3252,  822, 7782, 7782,                                           \n",
              "        602, 5064,  302, 1075, 1556, 1556, 1556, 1556, 6122, 2673, 6437,                                           \n",
              "       6437, 6437, 6437, 6105, 4382, 7378, 1471, 1471, 1471, 9935, 9935,                                           \n",
              "       5771, 5771, 5771,  178,   27,   10,   27,   27, 3971, 3971, 1233,                                           \n",
              "       1206,  206,  230,  230,  230, 1613, 1613, 1613, 1613, 1613, 1613,                                           \n",
              "       2009, 2009, 2009, 1380, 6206, 6206,  147, 5064,  302,  302, 7644,                                           \n",
              "       9877, 5214, 3427, 3427, 3427, 3427,  133, 8308,  133, 8308,  133,                                           \n",
              "       2665, 2665, 7532, 2665, 7532, 4155,  990,  163,  990,  990,  990,                                           \n",
              "       9682, 9682, 2292, 2292, 8844, 1573,  402,  483, 7910, 5265, 8119,                                           \n",
              "         59,   28,   59,   10,   41, 3620, 5743, 4884, 7433, 7433, 7858,                                           \n",
              "       5566,  321,   99,  100,    5, 9717, 2036, 2267, 2267,   41,   41,                                           \n",
              "         41, 1732,   41,   41,   41, 9532, 6903, 6903, 6903,   92,   28,                                           \n",
              "         59, 3529, 5027, 5027, 6714, 6714, 6714,  826,  826,  178,   99,                                           \n",
              "         27,   27,  532, 8419, 3745, 3745,  117,   41,  402, 6666, 1025,                                           \n",
              "       4566, 6119, 6119, 4187,   17,  452, 1119,  429,  879, 9215, 9215,                                           \n",
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              "       2305,  147, 5128,  302, 4929,  429,   41,   41, 7168, 5451, 9742,                                           \n",
              "       8512, 3427, 5651, 8308, 8308, 8308, 8308, 2665, 2665, 2665, 7038,                                           \n",
              "       2323, 4155, 4155, 5012, 5012, 5012, 5012, 5986, 2585,   59,   28,                                           \n",
              "        107, 4063, 9608,  417, 9725, 9725, 6445, 2428,   41,   41,  130,                                           \n",
              "         41, 1461, 7101, 4640, 2655, 4800, 6358,  808,  808,   41,   41,                                           \n",
              "         10,   41, 5991, 1831, 1831, 1831,  621,  621, 5865, 2453,  529,                                           \n",
              "         59,   59,   28,   28,   28,   28,   28,   28,   28,   28,  107,                                           \n",
              "        107,  385, 2465,  230,  131,  230, 2443,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206, 3252,  206,  193,  206,                                           \n",
              "        206,  517,  147,  822,  206,  206,  206, 1278, 2305,  302, 5064,                                           \n",
              "       1075,  181,  107,  181, 2595, 4051, 7439, 7698, 7698,  389, 7194,                                           \n",
              "       1463, 3840, 3890,  969,    3,   41, 1468, 6772, 3281, 1009, 1536,                                           \n",
              "        393,   41,   10,   27, 9057, 5665, 4704, 4704, 5764, 5764, 7111,                                           \n",
              "       8557, 8557, 8557, 7252, 7252, 2582,  704, 3038,  407, 3038, 3038,                                           \n",
              "       3734,  657,    4,    4,  255,  255,  255,   99,  583,  395,  395,                                           \n",
              "       4565, 4565, 3889, 1037,  131,    5,    5, 2837, 5853, 5563, 5819,                                           \n",
              "        402,   41, 6821, 3973, 5265, 1282,   41,   41,   10,   27,  429,                                           \n",
              "       6945, 8234, 5838, 5451, 3139, 8512, 5611, 8092, 8092, 8695, 8688,                                           \n",
              "       3694, 6069,  288,   41, 4331, 4418, 7265, 7265, 1262,   26,  122,                                           \n",
              "         50,   10,    5,  652, 8921, 8921, 9245, 8141, 8141, 6997, 6997,                                           \n",
              "          3,    3,   27,   27,  232,   10,  403,  403, 9563, 9563,  481,                                           \n",
              "        481,  481,   28,  107,   28,   28,   28,  107,  385, 9355, 2672,                                           \n",
              "        131,  206,  266, 1373, 1572,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206,  206, 3252, 3252,  206,                                           \n",
              "        206,  206, 7567, 3252, 2966, 1278,  206, 1278, 1278, 1278, 2009,                                           \n",
              "       2009, 8735, 8735,  147, 5128,   57,   57, 9817, 9817]), 'coarse_prompt': array([[738, 738,                  \n",
              "738, ..., 479, 850, 865],                                                                                          \n",
              "       [363, 363, 913, ..., 430, 132, 648]]), 'fine_prompt': array([[ 738,  738,  738, ...,  479,                  \n",
              "850,  865],                                                                                                        \n",
              "       [ 363,  363,  913, ...,  430,  132,  648],                                                                  \n",
              "       [1000,   36,  786, ...,  127,   62,  910],                                                                  \n",
              "       ...,                                                                                                        \n",
              "       [1011,  939,  939, ...,  521,  760,  632],                                                                  \n",
              "       [ 562,  782,  748, ...,  413,  709,  528],                                                                  \n",
              "       [ 948,  518,  975, ...,  285,  214,   42]], dtype=int32)}, 'temp': 0.7, 'top_k': None,                      \n",
              "'top_p': None, 'silent': False, 'min_eos_p': 2, 'max_gen_duration_s': None, 'allow_early_stop':                    \n",
              "True, 'use_kv_caching': True}                                                                                      \n",
              "
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\u001b[1;36m1278\u001b[0m, \u001b[1;36m2009\u001b[0m, \u001b[2m \u001b[0m\n", " \u001b[1;36m2009\u001b[0m, \u001b[1;36m8735\u001b[0m, \u001b[1;36m8735\u001b[0m, \u001b[1;36m147\u001b[0m, \u001b[1;36m5128\u001b[0m, \u001b[1;36m57\u001b[0m, \u001b[1;36m57\u001b[0m, \u001b[1;36m9817\u001b[0m, \u001b[1;36m9817\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m, \u001b[32m'coarse_prompt'\u001b[0m: \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m738\u001b[0m, \u001b[1;36m738\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[1;36m738\u001b[0m, \u001b[33m...\u001b[0m, \u001b[1;36m479\u001b[0m, \u001b[1;36m850\u001b[0m, \u001b[1;36m865\u001b[0m\u001b[1m]\u001b[0m, \u001b[2m \u001b[0m\n", " \u001b[1m[\u001b[0m\u001b[1;36m363\u001b[0m, \u001b[1;36m363\u001b[0m, \u001b[1;36m913\u001b[0m, \u001b[33m...\u001b[0m, \u001b[1;36m430\u001b[0m, \u001b[1;36m132\u001b[0m, \u001b[1;36m648\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m, 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\u001b[32m'min_eos_p'\u001b[0m: \u001b[1;36m2\u001b[0m, \u001b[32m'max_gen_duration_s'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'allow_early_stop'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[3;92mTrue\u001b[0m, \u001b[32m'use_kv_caching'\u001b[0m: \u001b[3;92mTrue\u001b[0m\u001b[1m}\u001b[0m \u001b[2m \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 100/100 [00:05<00:00, 17.65it/s]\n" ] }, { "data": { "text/html": [ "
generate_coarse {'x_semantic': array([3589,   17,  298, 9182, 6948, 6948,   92,   28,  148,  234, generation.py:460\n",
              "3825,                                                                                                              \n",
              "       5947,  171,   41,  171,  181,   59,   28,   28, 7313,   41, 1298,                                           \n",
              "       8407, 9054, 9054, 1896, 1896, 7433, 4869, 7858, 5566,  812,   23,                                           \n",
              "        171,  492,  492,   28,   28,  107, 8218, 1879, 1879, 2359, 8141,                                           \n",
              "       8141, 6997, 6997, 6997, 2199,  620,   59,   59,   28,   28,   28,                                           \n",
              "         28,   28,   28,  107,  385, 2954, 9381, 6319,  230,   10, 8849,                                           \n",
              "       7010, 7010,  441,  441, 5128,   41,   43,  448, 8747, 8747, 9224,                                           \n",
              "       9224, 6819, 6819, 2313,   41,   27,  474, 2928, 8060, 7443,   50,                                           \n",
              "         10,   27, 5248, 9005, 3675, 3675, 5932, 5932, 9768, 9768, 9945,                                           \n",
              "         26,   26,   26,  288,  262,  131,   10,   27,  282,  385,  385,                                           \n",
              "       1863, 2465, 2465,  230,  206,  230,  230,  230,  206,  206, 3317,                                           \n",
              "        206, 3317, 3317,  206,  206,  206,  206, 4653, 5196,  206,  206,                                           \n",
              "        206,  206, 5196,  206,  206,   65,  822,  822,  206, 1278, 1278,                                           \n",
              "        147,  147, 8395, 8395,  383, 5064,   10,    5,  651, 1169, 3504,                                           \n",
              "       3504,   41,   41,   40,   41,   10,   41,  399, 1460, 5694, 4808,                                           \n",
              "       4808, 9875, 9875, 9020, 9020, 4797,  575,  575,  685,  121,  292,                                           \n",
              "       2344, 3696,  686, 5640,  122,   41,   10,    5,  399, 6021, 8586,                                           \n",
              "       7934, 7934, 3305, 3305, 9765, 6564, 1239,  326, 2723, 7543, 8544,                                           \n",
              "       8399, 5508,   71,  100,    5, 6881, 5853, 5563, 5819,   41,  483,                                           \n",
              "       8671, 3948, 6699,   59,   59,   59,   41,  142,  830, 7429,  215,                                           \n",
              "        215,   77, 5067, 9090, 7484, 2120,   41,   17, 1793, 5303, 1335,                                           \n",
              "       7518,    3,   41,   10,   41, 7078, 5143, 5143, 8293, 8293, 8293,                                           \n",
              "       8293, 8919, 8919, 8919, 8919, 8919, 2286, 2286, 2286, 1093, 1093,                                           \n",
              "       1093,  894,  825,   97,   97,  230,  147,  206,  206,  230,  206,                                           \n",
              "        206, 1743, 6032, 3317,  206,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206, 3252,  206,  206,  206,                                           \n",
              "       3252,  206,  206,  822, 1278,  822, 1278, 5772, 2305,  302, 5064,                                           \n",
              "       5064,  402, 1506, 7907, 6320, 2016,  579,   27,   27, 5727,   41,                                           \n",
              "         41,   41,   41, 1535, 6557, 6557, 6557, 3963, 3963, 3963, 3963,                                           \n",
              "       6321, 7298, 7298,   44, 1262,   26,   26,   26,   26,  894,  894,                                           \n",
              "        736,  736, 1233,  230,  131,  230,  230,  206,  230,  206, 1743,                                           \n",
              "       6032, 3317,  206, 3317,  206, 4653,  206, 4653,  206,  193,  206,                                           \n",
              "        206,  517,  517,  822,  206,  206, 1278, 1278, 2305,  147,  302,                                           \n",
              "       5064,  991,  991,  211,  211,   10,   27,  399, 1419, 6945, 4860,                                           \n",
              "       6323, 4099, 4099, 2244, 2244,  250, 9768, 1307, 4388, 9351, 2452,                                           \n",
              "          3,  166, 8745, 8745,  402,  483, 5194, 7095, 1449,   50,   10,                                           \n",
              "          5,    5, 2837, 9158, 3368, 3415,   41,   41,   41, 8265, 5250,                                           \n",
              "       8114, 8114, 4427, 1794,  118,  100,   27,  401,  349,  310, 2312,                                           \n",
              "       2312, 3664,  648, 5422, 3917, 8984, 8984,  207,   59,   28,   28,                                           \n",
              "         28,   28,   28,   28,   28,   28]), 'history_prompt': {'semantic_prompt': array([ 131,                    \n",
              "10,   27,  282,  395, 7686,  131,  131,  266, 1373,  459,                                                          \n",
              "        206,  206,  206,  206,  206,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206, 5196,   91, 7567,  206, 3252,  822, 7782, 7782,                                           \n",
              "        602, 5064,  302, 1075, 1556, 1556, 1556, 1556, 6122, 2673, 6437,                                           \n",
              "       6437, 6437, 6437, 6105, 4382, 7378, 1471, 1471, 1471, 9935, 9935,                                           \n",
              "       5771, 5771, 5771,  178,   27,   10,   27,   27, 3971, 3971, 1233,                                           \n",
              "       1206,  206,  230,  230,  230, 1613, 1613, 1613, 1613, 1613, 1613,                                           \n",
              "       2009, 2009, 2009, 1380, 6206, 6206,  147, 5064,  302,  302, 7644,                                           \n",
              "       9877, 5214, 3427, 3427, 3427, 3427,  133, 8308,  133, 8308,  133,                                           \n",
              "       2665, 2665, 7532, 2665, 7532, 4155,  990,  163,  990,  990,  990,                                           \n",
              "       9682, 9682, 2292, 2292, 8844, 1573,  402,  483, 7910, 5265, 8119,                                           \n",
              "         59,   28,   59,   10,   41, 3620, 5743, 4884, 7433, 7433, 7858,                                           \n",
              "       5566,  321,   99,  100,    5, 9717, 2036, 2267, 2267,   41,   41,                                           \n",
              "         41, 1732,   41,   41,   41, 9532, 6903, 6903, 6903,   92,   28,                                           \n",
              "         59, 3529, 5027, 5027, 6714, 6714, 6714,  826,  826,  178,   99,                                           \n",
              "         27,   27,  532, 8419, 3745, 3745,  117,   41,  402, 6666, 1025,                                           \n",
              "       4566, 6119, 6119, 4187,   17,  452, 1119,  429,  879, 9215, 9215,                                           \n",
              "       8399, 5508, 6059,  452, 1079,  210,  441,   10,    5,  282, 3538,                                           \n",
              "       4737, 6664, 8726, 8522, 3767, 3767,  233,  233,   44, 8142, 8290,                                           \n",
              "       2068,  232,   10,  532,  532,  532,  107,  142, 6802, 5211,  266,                                           \n",
              "        206,  266, 1730, 1730, 2037,  206, 5738,  206,  206,  206,  206,                                           \n",
              "        206,  397, 5128,  397,  215,  107, 2315,  548, 1362, 6340,  441,                                           \n",
              "       2305,  147, 5128,  302, 4929,  429,   41,   41, 7168, 5451, 9742,                                           \n",
              "       8512, 3427, 5651, 8308, 8308, 8308, 8308, 2665, 2665, 2665, 7038,                                           \n",
              "       2323, 4155, 4155, 5012, 5012, 5012, 5012, 5986, 2585,   59,   28,                                           \n",
              "        107, 4063, 9608,  417, 9725, 9725, 6445, 2428,   41,   41,  130,                                           \n",
              "         41, 1461, 7101, 4640, 2655, 4800, 6358,  808,  808,   41,   41,                                           \n",
              "         10,   41, 5991, 1831, 1831, 1831,  621,  621, 5865, 2453,  529,                                           \n",
              "         59,   59,   28,   28,   28,   28,   28,   28,   28,   28,  107,                                           \n",
              "        107,  385, 2465,  230,  131,  230, 2443,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206, 3252,  206,  193,  206,                                           \n",
              "        206,  517,  147,  822,  206,  206,  206, 1278, 2305,  302, 5064,                                           \n",
              "       1075,  181,  107,  181, 2595, 4051, 7439, 7698, 7698,  389, 7194,                                           \n",
              "       1463, 3840, 3890,  969,    3,   41, 1468, 6772, 3281, 1009, 1536,                                           \n",
              "        393,   41,   10,   27, 9057, 5665, 4704, 4704, 5764, 5764, 7111,                                           \n",
              "       8557, 8557, 8557, 7252, 7252, 2582,  704, 3038,  407, 3038, 3038,                                           \n",
              "       3734,  657,    4,    4,  255,  255,  255,   99,  583,  395,  395,                                           \n",
              "       4565, 4565, 3889, 1037,  131,    5,    5, 2837, 5853, 5563, 5819,                                           \n",
              "        402,   41, 6821, 3973, 5265, 1282,   41,   41,   10,   27,  429,                                           \n",
              "       6945, 8234, 5838, 5451, 3139, 8512, 5611, 8092, 8092, 8695, 8688,                                           \n",
              "       3694, 6069,  288,   41, 4331, 4418, 7265, 7265, 1262,   26,  122,                                           \n",
              "         50,   10,    5,  652, 8921, 8921, 9245, 8141, 8141, 6997, 6997,                                           \n",
              "          3,    3,   27,   27,  232,   10,  403,  403, 9563, 9563,  481,                                           \n",
              "        481,  481,   28,  107,   28,   28,   28,  107,  385, 9355, 2672,                                           \n",
              "        131,  206,  266, 1373, 1572,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206,  206, 3252, 3252,  206,                                           \n",
              "        206,  206, 7567, 3252, 2966, 1278,  206, 1278, 1278, 1278, 2009,                                           \n",
              "       2009, 8735, 8735,  147, 5128,   57,   57, 9817, 9817]), 'coarse_prompt': array([[738, 738,                  \n",
              "738, ..., 479, 850, 865],                                                                                          \n",
              "       [363, 363, 913, ..., 430, 132, 648]]), 'fine_prompt': array([[ 738,  738,  738, ...,  479,                  \n",
              "850,  865],                                                                                                        \n",
              "       [ 363,  363,  913, ...,  430,  132,  648],                                                                  \n",
              "       [1000,   36,  786, ...,  127,   62,  910],                                                                  \n",
              "       ...,                                                                                                        \n",
              "       [1011,  939,  939, ...,  521,  760,  632],                                                                  \n",
              "       [ 562,  782,  748, ...,  413,  709,  528],                                                                  \n",
              "       [ 948,  518,  975, ...,  285,  214,   42]], dtype=int32)}, 'temp': 0.7, 'top_k': None,                      \n",
              "'top_p': None, 'silent': False, 'max_coarse_history': 630, 'sliding_window_len': 60,                               \n",
              "'use_kv_caching': True}                                                                                            \n",
              "
\n" ], "text/plain": [ "generate_coarse \u001b[1m{\u001b[0m\u001b[32m'x_semantic'\u001b[0m: \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m3589\u001b[0m, \u001b[1;36m17\u001b[0m, \u001b[1;36m298\u001b[0m, \u001b[1;36m9182\u001b[0m, \u001b[1;36m6948\u001b[0m, \u001b[1;36m6948\u001b[0m, \u001b[1;36m92\u001b[0m, \u001b[1;36m28\u001b[0m, \u001b[1;36m148\u001b[0m, \u001b[1;36m234\u001b[0m, \u001b]8;id=679719;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py\u001b\\\u001b[2mgeneration.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=739196;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py#460\u001b\\\u001b[2m460\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[1;36m3825\u001b[0m, \u001b[2m \u001b[0m\n", " \u001b[1;36m5947\u001b[0m, \u001b[1;36m171\u001b[0m, \u001b[1;36m41\u001b[0m, \u001b[1;36m171\u001b[0m, \u001b[1;36m181\u001b[0m, \u001b[1;36m59\u001b[0m, \u001b[1;36m28\u001b[0m, 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generate_fine {'x_coarse_gen': array([[958, 967, 432, ..., 160, 160, 160],                        generation.py:626\n",
              "       [394, 510, 129, ..., 993, 646, 993]]), 'history_prompt': {'semantic_prompt': array([ 131,                   \n",
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              "         41, 1461, 7101, 4640, 2655, 4800, 6358,  808,  808,   41,   41,                                           \n",
              "         10,   41, 5991, 1831, 1831, 1831,  621,  621, 5865, 2453,  529,                                           \n",
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              "        393,   41,   10,   27, 9057, 5665, 4704, 4704, 5764, 5764, 7111,                                           \n",
              "       8557, 8557, 8557, 7252, 7252, 2582,  704, 3038,  407, 3038, 3038,                                           \n",
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              "        131,  206,  266, 1373, 1572,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,  206,  206,  206, 3252, 3252,  206,                                           \n",
              "        206,  206, 7567, 3252, 2966, 1278,  206, 1278, 1278, 1278, 2009,                                           \n",
              "       2009, 8735, 8735,  147, 5128,   57,   57, 9817, 9817]), 'coarse_prompt': array([[738, 738,                  \n",
              "738, ..., 479, 850, 865],                                                                                          \n",
              "       [363, 363, 913, ..., 430, 132, 648]]), 'fine_prompt': array([[ 738,  738,  738, ...,  479,                  \n",
              "850,  865],                                                                                                        \n",
              "       [ 363,  363,  913, ...,  430,  132,  648],                                                                  \n",
              "       [1000,   36,  786, ...,  127,   62,  910],                                                                  \n",
              "       ...,                                                                                                        \n",
              "       [1011,  939,  939, ...,  521,  760,  632],                                                                  \n",
              "       [ 562,  782,  748, ...,  413,  709,  528],                                                                  \n",
              "       [ 948,  518,  975, ...,  285,  214,   42]], dtype=int32)}, 'temp': 0.5, 'silent': False}                    \n",
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        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Saved to long/With_me_brave_t-SPK-hark_woman_3.wav\n"
          ]
        }
      ],
      "source": [
        "kwargs['output_dir'] = \"long\"\n",
        "generation.set_seed(37)\n",
        "full_generation_segments, audio_arr_segments, final_filename_will_be = api.generate_audio_long(**kwargs)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "\n",
              "                \n",
              "              "
            ],
            "text/plain": [
              ""
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Audio(audio_arr_segments, rate=generation.SAMPLE_RATE) "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "
╭──────────────────────────────────────────── <class 'list'> ─────────────────────────────────────────────╮\n",
              " Built-in mutable sequence.                                                                              \n",
              "                                                                                                         \n",
              " ╭─────────────────────────────────────────────────────────────────────────────────────────────────────╮ \n",
              "  [                                                                                                    \n",
              "  {                                                                                                \n",
              "  │   │   'semantic_prompt': array([3589,   17,  298, 9182, 6948, 6948,   92,   28,  148,  234, 3825,  \n",
              "  5947,  171,   41,  171,  181,   59,   28,   28, 7313,   41, 1298,                             \n",
              "  8407, 9054, 9054, 1896, 1896, 7433, 4869, 7858, 5566,  812,   23,                             \n",
              "  │   │   171,  492,  492,   28,   28,  107, 8218, 1879, 1879, 2359, 8141,                             \n",
              "  8141, 6997, 6997, 6997, 2199,  620,   59,   59,   28,   28,   28,                             \n",
              "  │   │    28,   28,   28,  107,  385, 2954, 9381, 6319,  230,   10, 8849,                             \n",
              "  7010, 7010,  441,  441, 5128,   41,   43,  448, 8747, 8747, 9224,                             \n",
              "  9224, 6819, 6819, 2313,   41,   27,  474, 2928, 8060, 7443,   50,                             \n",
              "  │   │    10,   27, 5248, 9005, 3675, 3675, 5932, 5932, 9768, 9768, 9945,                             \n",
              "  │   │    26,   26,   26,  288,  262,  131,   10,   27,  282,  385,  385,                             \n",
              "  1863, 2465, 2465,  230,  206,  230,  230,  230,  206,  206, 3317,                             \n",
              "  │   │   206, 3317, 3317,  206,  206,  206,  206, 4653, 5196,  206,  206,                             \n",
              "  │   │   206,  206, 5196,  206,  206,   65,  822,  822,  206, 1278, 1278,                             \n",
              "  │   │   147,  147, 8395, 8395,  383, 5064,   10,    5,  651, 1169, 3504,                             \n",
              "  3504,   41,   41,   40,   41,   10,   41,  399, 1460, 5694, 4808,                             \n",
              "  4808, 9875, 9875, 9020, 9020, 4797,  575,  575,  685,  121,  292,                             \n",
              "  2344, 3696,  686, 5640,  122,   41,   10,    5,  399, 6021, 8586,                             \n",
              "  7934, 7934, 3305, 3305, 9765, 6564, 1239,  326, 2723, 7543, 8544,                             \n",
              "  8399, 5508,   71,  100,    5, 6881, 5853, 5563, 5819,   41,  483,                             \n",
              "  8671, 3948, 6699,   59,   59,   59,   41,  142,  830, 7429,  215,                             \n",
              "  │   │   215,   77, 5067, 9090, 7484, 2120,   41,   17, 1793, 5303, 1335,                             \n",
              "  7518,    3,   41,   10,   41, 7078, 5143, 5143, 8293, 8293, 8293,                             \n",
              "  8293, 8919, 8919, 8919, 8919, 8919, 2286, 2286, 2286, 1093, 1093,                             \n",
              "  1093,  894,  825,   97,   97,  230,  147,  206,  206,  230,  206,                             \n",
              "  │   │   206, 1743, 6032, 3317,  206,  206,  206,  206,  206,  206,  206,                             \n",
              "  │   │   206,  206,  206,  206,  206,  206,  206, 3252,  206,  206,  206,                             \n",
              "  3252,  206,  206,  822, 1278,  822, 1278, 5772, 2305,  302, 5064,                             \n",
              "  5064,  402, 1506, 7907, 6320, 2016,  579,   27,   27, 5727, 3265,                             \n",
              "  │   │    41,   41,   41,   41, 5119, 6557, 6557, 3963, 3963, 3963, 3963,                             \n",
              "  3767,   26,   26,   26,   26,   26,   26,   26,   26,  894,  894,                             \n",
              "  │   │   138,  138,  206,  230,  230,  230,  230,  206,  193,  206,  193,                             \n",
              "  │   │   193,  206,  206,  193,  193, 4488, 4488,  193, 2009,  193, 2403,                             \n",
              "  │   │   206, 2009,  147, 1613, 8735, 8395,  147, 8395,  147, 8610,  147,                             \n",
              "  5128,   41,   43, 1419, 6945, 4860, 6323, 6323, 4099, 2244, 2244,                             \n",
              "  4718, 9768, 9768, 1307, 1307, 1307, 1307,   44, 8142, 8142,  761,                             \n",
              "  │   │   761, 7979,    3,  166,  166, 8745,  402,  245,  483, 8671, 7095,                             \n",
              "  1449,   50,   10,    5,    5, 2837, 3368, 3368, 1802,   41,   41,                             \n",
              "  │   │    41, 3135, 5250, 8114, 8114, 3400, 1794,  210,   12,    5,  401,                             \n",
              "  │   │   401, 9502, 2312, 2312, 3916, 1859, 3164, 1796, 8984, 8984, 3850,                             \n",
              "  │   │    59,   28,   28,   28,   28,   28]),                                                         \n",
              "  │   │   'coarse_prompt': array([[958, 967, 432, ..., 160, 160, 160],                                 \n",
              "  [394, 510, 129, ..., 646, 646, 993]]),                                                        \n",
              "  │   │   'fine_prompt': array([[ 958,  967,  432, ...,  160,  160,  160],                             \n",
              "  [ 394,  510,  129, ...,  646,  646,  993],                                                    \n",
              "  [  62,  532,  925, ...,  601,  601,  936],                                                    \n",
              "  ...,                                                                                          \n",
              "  [ 866,  451,  350, ...,  435,  949,   96],                                                    \n",
              "  [ 928,  711, 1013, ...,  853,  772,  772],                                                    \n",
              "  [ 617,  413,  468, ...,  916,  475, 1018]], dtype=int32)                                      \n",
              "  }                                                                                                \n",
              "  ]                                                                                                    \n",
              " ╰─────────────────────────────────────────────────────────────────────────────────────────────────────╯ \n",
              "                                                                                                         \n",
              " 36 attribute(s) not shown. Run inspect(inspect) for options.                                            \n",
              "╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
              "
\n" ], "text/plain": [ "\u001b[34m╭─\u001b[0m\u001b[34m─────────────────────────────────────────── \u001b[0m\u001b[1;34m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[32m'list'\u001b[0m\u001b[1;34m>\u001b[0m\u001b[34m ────────────────────────────────────────────\u001b[0m\u001b[34m─╮\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[36mBuilt-in mutable sequence.\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m╭─────────────────────────────────────────────────────────────────────────────────────────────────────╮\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m[\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m{\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[32m'semantic_prompt'\u001b[0m: 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"\u001b[34m╰─────────────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "inspect(full_generation_segments)" ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
set_seed Enabling deterministic algorithms                                                        generation.py:929\n",
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set_seed Set seed to 37                                                                           generation.py:944\n",
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generate_audio_barki {'text': 'With me, brave the tumultuous seas, claim treasures untold, and send foes api.py:362\n",
              "to their watery \\ndoom', 'kwargs': {'text_prompt': 'With me, brave the tumultuous seas, claim treasures            \n",
              "untold, and send foes to their watery \\ndoom', 'list_speakers': None, 'dry_run': False,                            \n",
              "'text_splits_only': False, 'history_prompt': None, 'prompt_file': None,                                            \n",
              "'split_input_into_separate_prompts_by': None, 'split_input_into_separate_prompts_by_value': None,                  \n",
              "'always_save_speaker': True, 'output_iterations': 1, 'output_filename': None, 'output_dir': 'seed37',              \n",
              "'hoarder_mode': True, 'extra_stats': False, 'text_use_gpu': True, 'text_use_small': False,                         \n",
              "'coarse_use_gpu': True, 'coarse_use_small': False, 'fine_use_gpu': True, 'fine_use_small': False,                  \n",
              "'codec_use_gpu': True, 'force_reload': False, 'GLOBAL_ENABLE_MPS': None, 'USE_SMALL_MODELS': None,                 \n",
              "'OFFLOAD_CPU': None, 'text_temp': 0.7, 'waveform_temp': 0.7, 'confused_travolta_mode': None, 'silent':             \n",
              "False, 'seed': None, 'stable_mode_interval': 1, 'single_starting_seed': None,                                      \n",
              "'split_character_goal_length': 145, 'split_character_max_length': 190, 'split_character_jitter': 0,                \n",
              "'add_silence_between_segments': 0.0, 'split_each_text_prompt_by': None,                                            \n",
              "'split_each_text_prompt_by_value': None, 'extra_confused_travolta_mode': None,                                     \n",
              "'semantic_history_starting_weight': 1.0, 'semantic_history_future_weight': 1.0,                                    \n",
              "'semantic_prev_segment_weight': 0.5, 'coarse_history_starting_weight': 1.0,                                        \n",
              "'coarse_history_future_weight': 0.5, 'coarse_prev_segment_weight': 0.5, 'fine_history_starting_weight':            \n",
              "1.0, 'fine_history_future_weight': 0.0, 'fine_prev_segment_weight': 0.0,                                           \n",
              "'custom_audio_processing_function': None, 'use_smaller_models': False, 'semantic_temp': 0.7,                       \n",
              "'semantic_top_k': None, 'semantic_top_p': None, 'semantic_min_eos_p': 0.2,                                         \n",
              "'semantic_max_gen_duration_s': None, 'semantic_allow_early_stop': True, 'semantic_use_kv_caching': True,           \n",
              "'semantic_seed': None, 'semantic_history_oversize_limit': None, 'coarse_temp': 0.7, 'coarse_top_k':                \n",
              "None, 'coarse_top_p': None, 'coarse_max_coarse_history': 630, 'coarse_sliding_window_len': 60,                     \n",
              "'coarse_kv_caching': True, 'coarse_seed': None, 'coarse_history_time_alignment_hack': -2, 'fine_temp':             \n",
              "0.5, 'fine_seed': None, 'render_npz_samples': False, 'loglevel': 'WARNING', 'output_full': True}}                  \n",
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\n" ], "text/plain": [ "generate_audio_barki \u001b[1m{\u001b[0m\u001b[32m'text'\u001b[0m: \u001b[32m'With me, brave the tumultuous seas, claim treasures untold, and send foes\u001b[0m \u001b]8;id=540035;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py\u001b\\\u001b[2mapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=37163;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py#362\u001b\\\u001b[2m362\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[32mto their watery \\ndoom'\u001b[0m, \u001b[32m'kwargs'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'text_prompt'\u001b[0m: \u001b[32m'With me, brave the tumultuous seas, claim treasures \u001b[0m \u001b[2m \u001b[0m\n", "\u001b[32muntold, and send foes to their watery \\ndoom'\u001b[0m, \u001b[32m'list_speakers'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'dry_run'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'text_splits_only'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'history_prompt'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'prompt_file'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'split_input_into_separate_prompts_by'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'split_input_into_separate_prompts_by_value'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'always_save_speaker'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'output_iterations'\u001b[0m: \u001b[1;36m1\u001b[0m, \u001b[32m'output_filename'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'output_dir'\u001b[0m: \u001b[32m'seed37'\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'hoarder_mode'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'extra_stats'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'text_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'text_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'coarse_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'coarse_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'fine_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'fine_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'codec_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'force_reload'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'GLOBAL_ENABLE_MPS'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'USE_SMALL_MODELS'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'OFFLOAD_CPU'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'text_temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'waveform_temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'confused_travolta_mode'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'silent'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[3;91mFalse\u001b[0m, \u001b[32m'seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'stable_mode_interval'\u001b[0m: \u001b[1;36m1\u001b[0m, \u001b[32m'single_starting_seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'split_character_goal_length'\u001b[0m: \u001b[1;36m145\u001b[0m, \u001b[32m'split_character_max_length'\u001b[0m: \u001b[1;36m190\u001b[0m, \u001b[32m'split_character_jitter'\u001b[0m: \u001b[1;36m0\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'add_silence_between_segments'\u001b[0m: \u001b[1;36m0.0\u001b[0m, \u001b[32m'split_each_text_prompt_by'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'split_each_text_prompt_by_value'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'extra_confused_travolta_mode'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'semantic_history_starting_weight'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[32m'semantic_history_future_weight'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'semantic_prev_segment_weight'\u001b[0m: \u001b[1;36m0.5\u001b[0m, 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"\u001b[32m'semantic_max_gen_duration_s'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'semantic_allow_early_stop'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'semantic_use_kv_caching'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'semantic_seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'semantic_history_oversize_limit'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'coarse_temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'coarse_top_k'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[3;35mNone\u001b[0m, \u001b[32m'coarse_top_p'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'coarse_max_coarse_history'\u001b[0m: \u001b[1;36m630\u001b[0m, \u001b[32m'coarse_sliding_window_len'\u001b[0m: \u001b[1;36m60\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'coarse_kv_caching'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'coarse_seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'coarse_history_time_alignment_hack'\u001b[0m: \u001b[1;36m-2\u001b[0m, 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generate_audio_barki {'text': 'With me, brave the tumultuous seas, claim treasures untold, and send foes api.py:366\n",
              "to their watery \\ndoom', 'kwargs': {'text_prompt': 'With me, brave the tumultuous seas, claim treasures            \n",
              "untold, and send foes to their watery \\ndoom', 'list_speakers': None, 'dry_run': False,                            \n",
              "'text_splits_only': False, 'history_prompt': None, 'prompt_file': None,                                            \n",
              "'split_input_into_separate_prompts_by': None, 'split_input_into_separate_prompts_by_value': None,                  \n",
              "'always_save_speaker': True, 'output_iterations': 1, 'output_filename': None, 'output_dir': 'seed37',              \n",
              "'hoarder_mode': True, 'extra_stats': False, 'text_use_gpu': True, 'text_use_small': False,                         \n",
              "'coarse_use_gpu': True, 'coarse_use_small': False, 'fine_use_gpu': True, 'fine_use_small': False,                  \n",
              "'codec_use_gpu': True, 'force_reload': False, 'GLOBAL_ENABLE_MPS': None, 'USE_SMALL_MODELS': None,                 \n",
              "'OFFLOAD_CPU': None, 'text_temp': 0.7, 'waveform_temp': 0.7, 'confused_travolta_mode': None, 'silent':             \n",
              "False, 'seed': None, 'stable_mode_interval': 1, 'single_starting_seed': None,                                      \n",
              "'split_character_goal_length': 145, 'split_character_max_length': 190, 'split_character_jitter': 0,                \n",
              "'add_silence_between_segments': 0.0, 'split_each_text_prompt_by': None,                                            \n",
              "'split_each_text_prompt_by_value': None, 'extra_confused_travolta_mode': None,                                     \n",
              "'semantic_history_starting_weight': 1.0, 'semantic_history_future_weight': 1.0,                                    \n",
              "'semantic_prev_segment_weight': 0.5, 'coarse_history_starting_weight': 1.0,                                        \n",
              "'coarse_history_future_weight': 0.5, 'coarse_prev_segment_weight': 0.5, 'fine_history_starting_weight':            \n",
              "1.0, 'fine_history_future_weight': 0.0, 'fine_prev_segment_weight': 0.0,                                           \n",
              "'custom_audio_processing_function': None, 'use_smaller_models': False, 'semantic_temp': 0.7,                       \n",
              "'semantic_top_k': None, 'semantic_top_p': None, 'semantic_min_eos_p': 0.2,                                         \n",
              "'semantic_max_gen_duration_s': None, 'semantic_allow_early_stop': True, 'semantic_use_kv_caching': True,           \n",
              "'semantic_seed': None, 'semantic_history_oversize_limit': None, 'coarse_temp': 0.7, 'coarse_top_k':                \n",
              "None, 'coarse_top_p': None, 'coarse_max_coarse_history': 630, 'coarse_sliding_window_len': 60,                     \n",
              "'coarse_kv_caching': True, 'coarse_seed': None, 'coarse_history_time_alignment_hack': -2, 'fine_temp':             \n",
              "0.5, 'fine_seed': None, 'render_npz_samples': False, 'loglevel': 'WARNING', 'output_full': True}}                  \n",
              "
\n" ], "text/plain": [ "generate_audio_barki \u001b[1m{\u001b[0m\u001b[32m'text'\u001b[0m: \u001b[32m'With me, brave the tumultuous seas, claim treasures untold, and send foes\u001b[0m \u001b]8;id=827442;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py\u001b\\\u001b[2mapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=113095;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py#366\u001b\\\u001b[2m366\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[32mto their watery \\ndoom'\u001b[0m, \u001b[32m'kwargs'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'text_prompt'\u001b[0m: \u001b[32m'With me, brave the tumultuous seas, claim treasures \u001b[0m \u001b[2m \u001b[0m\n", "\u001b[32muntold, and send foes to their watery \\ndoom'\u001b[0m, \u001b[32m'list_speakers'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'dry_run'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'text_splits_only'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'history_prompt'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'prompt_file'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'split_input_into_separate_prompts_by'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'split_input_into_separate_prompts_by_value'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'always_save_speaker'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'output_iterations'\u001b[0m: \u001b[1;36m1\u001b[0m, \u001b[32m'output_filename'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'output_dir'\u001b[0m: \u001b[32m'seed37'\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'hoarder_mode'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'extra_stats'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'text_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'text_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'coarse_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'coarse_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'fine_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'fine_use_small'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'codec_use_gpu'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'force_reload'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'GLOBAL_ENABLE_MPS'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'USE_SMALL_MODELS'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'OFFLOAD_CPU'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'text_temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'waveform_temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'confused_travolta_mode'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'silent'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[3;91mFalse\u001b[0m, \u001b[32m'seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'stable_mode_interval'\u001b[0m: \u001b[1;36m1\u001b[0m, 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"\u001b[32m'semantic_max_gen_duration_s'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'semantic_allow_early_stop'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'semantic_use_kv_caching'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'semantic_seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'semantic_history_oversize_limit'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'coarse_temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'coarse_top_k'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[3;35mNone\u001b[0m, \u001b[32m'coarse_top_p'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'coarse_max_coarse_history'\u001b[0m: \u001b[1;36m630\u001b[0m, \u001b[32m'coarse_sliding_window_len'\u001b[0m: \u001b[1;36m60\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'coarse_kv_caching'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[32m'coarse_seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'coarse_history_time_alignment_hack'\u001b[0m: \u001b[1;36m-2\u001b[0m, \u001b[32m'fine_temp'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[1;36m0.5\u001b[0m, \u001b[32m'fine_seed'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'render_npz_samples'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'loglevel'\u001b[0m: \u001b[32m'WARNING'\u001b[0m, \u001b[32m'output_full'\u001b[0m: \u001b[3;92mTrue\u001b[0m\u001b[1m}\u001b[0m\u001b[1m}\u001b[0m \u001b[2m \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "after load all defaults\n" ] }, { "data": { "text/html": [ "
generate_text_semantic {'text': 'With me, brave the tumultuous seas, claim treasures untold, and  generation.py:302\n",
              "send foes to their watery \\ndoom', 'history_prompt': None, 'temp': 0.7, 'top_k': None, 'top_p':                    \n",
              "None, 'silent': False, 'min_eos_p': 0.2, 'max_gen_duration_s': None, 'allow_early_stop': True,                     \n",
              "'use_kv_caching': True}                                                                                            \n",
              "
\n" ], "text/plain": [ "generate_text_semantic \u001b[1m{\u001b[0m\u001b[32m'text'\u001b[0m: \u001b[32m'With me, brave the tumultuous seas, claim treasures untold, and \u001b[0m \u001b]8;id=295619;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py\u001b\\\u001b[2mgeneration.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=970216;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py#302\u001b\\\u001b[2m302\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[32msend foes to their watery \\ndoom'\u001b[0m, \u001b[32m'history_prompt'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'temp'\u001b[0m: \u001b[1;36m0.7\u001b[0m, \u001b[32m'top_k'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'top_p'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[3;35mNone\u001b[0m, \u001b[32m'silent'\u001b[0m: \u001b[3;91mFalse\u001b[0m, \u001b[32m'min_eos_p'\u001b[0m: \u001b[1;36m0.2\u001b[0m, \u001b[32m'max_gen_duration_s'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'allow_early_stop'\u001b[0m: \u001b[3;92mTrue\u001b[0m, \u001b[2m \u001b[0m\n", "\u001b[32m'use_kv_caching'\u001b[0m: \u001b[3;92mTrue\u001b[0m\u001b[1m}\u001b[0m \u001b[2m \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 100/100 [00:05<00:00, 17.48it/s]\n" ] }, { "data": { "text/html": [ "
generate_coarse {'x_semantic': array([ 131,   10,   10,  266,  266,  266,  206,  206,  206,  206, generation.py:460\n",
              "206,                                                                                                               \n",
              "         65,  206,   65,  344,   65,  344,  147,  147,  147,  147, 1271,                                           \n",
              "       1489, 7907, 5274, 8871,  579,  107,  107, 5727, 1620,   41,   41,                                           \n",
              "         41, 5119, 6557, 6557, 3963, 3963, 3767, 3767,   26,   26,   26,                                           \n",
              "         26,   26,   26,  894,  736,  894,   10,  230,  230,  230,   10,                                           \n",
              "        206, 6032,  206, 6032,  147,  206,  206,  206,  206,   10,  206,                                           \n",
              "        206, 3252, 2966,  147,  147, 1278,  147,  147,  147,  147,  147,                                           \n",
              "        991,  991,  402,   10,   41,  245, 8969, 4860, 6323, 4099, 4868,                                           \n",
              "       2244, 2244,  250, 9768, 1307, 4388, 9351, 7895,  178,  166, 1620,                                           \n",
              "       1573, 6274, 7095, 7784,  210,   50,   10,    5, 2837, 3368, 3415,                                           \n",
              "         41,   41,   41, 3135, 2065, 3240, 4579, 9792, 3400,  210,   10,                                           \n",
              "        232,  401,  401, 9502, 2402, 2312, 2312, 3664, 1859, 5422, 1796,                                           \n",
              "       3917,  880,   59,   59,   28,   28,   28,   28,   28,   28,   28,                                           \n",
              "       1133, 3195, 6155, 6155, 3182, 8522, 8522, 3767, 3767,   44,   44,                                           \n",
              "       4775,   44,   44, 9839, 8142, 3753, 5986, 1540,   59,   59,   28,                                           \n",
              "        107,  589,  589,   10,   10,   27,  399,  287, 1460,  927, 9763,                                           \n",
              "       4600, 6185, 6185, 7304, 3301, 4149, 5293, 5293, 5293,  911, 1544,                                           \n",
              "         41,   41,  489,  850,  547,  210,   10,    5,  265,  401, 2739,                                           \n",
              "       2773, 2848, 3840, 3890, 3890, 1450, 9403, 4146, 4146,  190,  190,                                           \n",
              "       2280, 4394, 6022, 6022, 1517,  153,   71,   92,   92,  107, 1835,                                           \n",
              "       3454, 3454, 3700, 1948, 1948,  444, 1315,  171,  171,  171,  489,                                           \n",
              "        489,  489,  210,   10,    5,    5, 9367, 9367, 8498, 2745, 2745,                                           \n",
              "       6696, 2779, 2779, 2779, 2779, 9454, 9454, 9454, 9454, 8417, 7006,                                           \n",
              "       6672, 8270, 6018, 6018, 6139, 6139,  227, 6047,  441, 5647,   10,                                           \n",
              "         10, 1096, 1096,   10,   10,  266,  206,  206,  206,  206,  206,                                           \n",
              "        206,   10,  206,  206,  206,  206,   65,   65,  344,  147,  147,                                           \n",
              "         57,   41,   57,  604, 5851, 8604, 5673, 4119,  171,   41,  171,                                           \n",
              "        489,   59,   28,   28,   28,   28,   28,   10,   28, 6801, 9235,                                           \n",
              "       3198, 1858,   29, 3793, 1315,  171,  171,  171,  171,  171,  489,                                           \n",
              "        181,  181,   28,   28,   10,  337, 8963, 6412, 6412, 1001, 1001,                                           \n",
              "       4816, 5301, 6303, 5301, 1667, 8525, 8525, 7365, 7365, 1647, 1647,                                           \n",
              "         92,   59,   31,   31,   67,   10,    5, 8911, 5853, 5563, 5563,                                           \n",
              "        521,   41,  483, 9968, 5839, 3177, 1493, 1536,  393,  429,  429,                                           \n",
              "         41,   38, 4967,  774,  774, 6247, 6247, 6247, 9804,  620,  118,                                           \n",
              "         10,   27,  455, 9192, 8099, 8099,  389,  389, 9944, 7069, 2853,                                           \n",
              "       2853, 5640,   26,  122,   50,  210,   41,   10,   41, 8136, 4448,                                           \n",
              "       9329, 9329, 4236, 4236, 4236, 4236, 9104, 9104,  407,  407,  407,                                           \n",
              "        407, 6258, 6258, 8685, 6258, 1385, 5340, 1980, 6047, 1980, 4838,                                           \n",
              "         10, 1811,  278, 1811,  278, 3587,  278,  848,  174,   10, 8555]), 'history_prompt':                       \n",
              "None, 'temp': 0.7, 'top_k': None, 'top_p': None, 'silent': False, 'max_coarse_history': 630,                       \n",
              "'sliding_window_len': 60, 'use_kv_caching': True}                                                                  \n",
              "
\n" ], "text/plain": [ "generate_coarse \u001b[1m{\u001b[0m\u001b[32m'x_semantic'\u001b[0m: \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m \u001b[1;36m131\u001b[0m, \u001b[1;36m10\u001b[0m, \u001b[1;36m10\u001b[0m, \u001b[1;36m266\u001b[0m, \u001b[1;36m266\u001b[0m, \u001b[1;36m266\u001b[0m, \u001b[1;36m206\u001b[0m, \u001b[1;36m206\u001b[0m, \u001b[1;36m206\u001b[0m, \u001b[1;36m206\u001b[0m, \u001b]8;id=151412;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py\u001b\\\u001b[2mgeneration.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=839049;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py#460\u001b\\\u001b[2m460\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[1;36m206\u001b[0m, \u001b[2m \u001b[0m\n", " \u001b[1;36m65\u001b[0m, \u001b[1;36m206\u001b[0m, \u001b[1;36m65\u001b[0m, \u001b[1;36m344\u001b[0m, \u001b[1;36m65\u001b[0m, \u001b[1;36m344\u001b[0m, \u001b[1;36m147\u001b[0m, \u001b[1;36m147\u001b[0m, 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generate_fine {'x_coarse_gen': array([[876, 738, 855, ..., 408, 408, 738],                        generation.py:626\n",
              "       [700, 841, 544, ..., 424, 424, 544]]), 'history_prompt': None, 'temp': 0.5, 'silent':                       \n",
              "False}                                                                                                             \n",
              "
\n" ], "text/plain": [ "generate_fine \u001b[1m{\u001b[0m\u001b[32m'x_coarse_gen'\u001b[0m: \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m876\u001b[0m, \u001b[1;36m738\u001b[0m, \u001b[1;36m855\u001b[0m, \u001b[33m...\u001b[0m, \u001b[1;36m408\u001b[0m, \u001b[1;36m408\u001b[0m, \u001b[1;36m738\u001b[0m\u001b[1m]\u001b[0m, \u001b]8;id=433174;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py\u001b\\\u001b[2mgeneration.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=78803;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py#626\u001b\\\u001b[2m626\u001b[0m\u001b]8;;\u001b\\\n", " \u001b[1m[\u001b[0m\u001b[1;36m700\u001b[0m, \u001b[1;36m841\u001b[0m, \u001b[1;36m544\u001b[0m, \u001b[33m...\u001b[0m, \u001b[1;36m424\u001b[0m, \u001b[1;36m424\u001b[0m, \u001b[1;36m544\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m, \u001b[32m'history_prompt'\u001b[0m: \u001b[3;35mNone\u001b[0m, \u001b[32m'temp'\u001b[0m: \u001b[1;36m0.5\u001b[0m, \u001b[32m'silent'\u001b[0m: \u001b[2m \u001b[0m\n", "\u001b[3;91mFalse\u001b[0m\u001b[1m}\u001b[0m \u001b[2m \u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "100%|██████████| 1/1 [00:04<00:00, 4.00s/it]\n" ] } ], "source": [ "text = \"\"\"With me, brave the tumultuous seas, claim treasures untold, and send foes to their watery \n", "doom\"\"\"\n", "kwargs[\"semantic_min_eos_p\"] = 0.2 \n", "kwargs[\"text_prompt\"] = text\n", "generation.set_seed(37)\n", "kwargs['output_full'] = True\n", "kwargs['output_dir'] = \"seed37\"\n", "kwargs[\"history_prompt\"] = None\n", "#kwargs['history_prompt'] = 'custom_speakers/en_fiery.npz'\n", "barkifull, audio_arr_segments_barki = api.generate_audio_barki(text, **kwargs)" ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
semantic_prompt 429\n",
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coarse_prompt 2\n",
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fine_prompt 8\n",
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\n" ], "text/plain": [ "fine_prompt \u001b[1;36m8\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#inspect(barkifull)\n", "\n", "for x in barkifull.keys():\n", " print(f\"{x} {len(barkifull[x])}\")\n", "\n", "api.save_as_prompt(\"custom_speakers/seed37_barki.npz\",barkifull)" ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Audio(audio_arr_segments_barki, rate=generation.SAMPLE_RATE)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\n", "def generate_audio_barki(\n", " text: str,\n", " **kwargs,\n", "):\n", " \"\"\"Generate audio array from input text.\n", "\n", " Args:\n", " text: text to be turned into audio\n", " history_prompt: history choice for audio cloning\n", " text_temp: generation temperature (1.0 more diverse, 0.0 more conservative)\n", " waveform_temp: generation temperature (1.0 more diverse, 0.0 more conservative)\n", " silent: disable progress bar\n", " output_full: return full generation to be used as a history prompt\n", "\n", "\n", " Returns:\n", " numpy audio array at sample frequency 24khz\n", " \"\"\"\n", " logger.debug(locals())\n", " print(\"before load all defaults\")\n", " kwargs = load_all_defaults(**kwargs)\n", "\n", " logger.debug(locals())\n", " print(\"after load all defaults\")\n", " history_prompt = kwargs.get(\"history_prompt\", None)\n", " text_temp = kwargs.get(\"text_temp\", None)\n", " waveform_temp = kwargs.get(\"waveform_temp\", None)\n", " silent = kwargs.get(\"silent\", None)\n", " output_full = kwargs.get(\"output_full\", None)\n", "\n", " global gradio_try_to_cancel\n", " global done_cancelling\n", "\n", " seed = kwargs.get(\"seed\",None)\n", " if seed is not None:\n", " generation.set_seed(seed)\n", "\n", " ## TODO seperate stage seeds\n", "\n", " ## Semantic Options\n", " semantic_temp = text_temp\n", " if kwargs.get(\"semantic_temp\", None):\n", " semantic_temp = kwargs.get(\"semantic_temp\")\n", "\n", " semantic_seed = kwargs.get(\"semantic_seed\",None)\n", " if semantic_seed is not None:\n", " generation.set_seed(semantic_seed)\n", "\n", "\n", " if gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", " semantic_tokens = call_with_non_none_params(\n", " generate_text_semantic,\n", " text=text,\n", " history_prompt=history_prompt,\n", " temp=semantic_temp,\n", " top_k=kwargs.get(\"semantic_top_k\", None),\n", " top_p=kwargs.get(\"semantic_top_p\", None),\n", " silent=silent,\n", " min_eos_p = kwargs.get(\"semantic_min_eos_p\", None),\n", " max_gen_duration_s = kwargs.get(\"semantic_max_gen_duration_s\", None),\n", " allow_early_stop = kwargs.get(\"semantic_allow_early_stop\", True),\n", " use_kv_caching=kwargs.get(\"semantic_use_kv_caching\", True),\n", " )\n", " \n", " if gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", "\n", " ## Coarse Options\n", " coarse_temp = waveform_temp\n", " if kwargs.get(\"coarse_temp\", None):\n", " coarse_temp = kwargs.get(\"coarse_temp\")\n", "\n", " coarse_seed = kwargs.get(\"coarse_seed\",None)\n", " if coarse_seed is not None:\n", " generation.set_seed(coarse_seed)\n", " \n", " \n", " if gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", " \n", " coarse_tokens = call_with_non_none_params(\n", " generate_coarse,\n", " x_semantic=semantic_tokens,\n", " history_prompt=history_prompt,\n", " temp=coarse_temp,\n", " top_k=kwargs.get(\"coarse_top_k\", None),\n", " top_p=kwargs.get(\"coarse_top_p\", None),\n", " silent=silent,\n", " max_coarse_history=kwargs.get(\"coarse_max_coarse_history\", None),\n", " sliding_window_len=kwargs.get(\"coarse_sliding_window_len\", None),\n", " use_kv_caching=kwargs.get(\"coarse_kv_caching\", True),\n", " )\n", "\n", " fine_temp = kwargs.get(\"fine_temp\", 0.5)\n", "\n", " fine_seed = kwargs.get(\"fine_seed\",None)\n", " if fine_seed is not None:\n", " generation.set_seed(fine_seed)\n", "\n", " if gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", " fine_tokens = call_with_non_none_params(\n", " generate_fine,\n", " x_coarse_gen=coarse_tokens,\n", " history_prompt=history_prompt,\n", " temp=fine_temp,\n", " silent=silent,\n", " )\n", "\n", " # do we ever care about setting this seed? Probably not? You can always just decode it again\n", "\n", " if gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", " audio_arr = codec_decode(fine_tokens)\n", " full_generation = {\n", " \"semantic_prompt\": semantic_tokens,\n", " \"coarse_prompt\": coarse_tokens,\n", " \"fine_prompt\": fine_tokens,\n", " }\n", "\n", " if gradio_try_to_cancel:\n", " done_cancelling = True\n", " return None, None\n", " \n", " hoarder_mode = kwargs.get(\"hoarder_mode\", None)\n", " total_segments = kwargs.get(\"total_segments\", 1)\n", " if hoarder_mode and (total_segments > 1):\n", " kwargs[\"text\"] = text\n", " write_one_segment(audio_arr, full_generation, **kwargs)\n", "\n", " if output_full:\n", " return full_generation, audio_arr\n", " \n", " return audio_arr" ] }, { "cell_type": "code", "execution_count": 60, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
set_seed Enabling deterministic algorithms                                                        generation.py:929\n",
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set_seed Set seed to 37                                                                           generation.py:944\n",
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\n" ], "text/plain": [ "set_seed Set seed to \u001b[1;36m37\u001b[0m \u001b]8;id=647827;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py\u001b\\\u001b[2mgeneration.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=697756;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py#944\u001b\\\u001b[2m944\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
generate_text_semantic {'text': 'With me, brave the tumultuous seas, claim treasures untold, and  generation.py:302\n",
              "send foes to their watery \\ndoom', 'history_prompt': None, 'temp': 0.7, 'top_k': None, 'top_p':                    \n",
              "None, 'silent': False, 'min_eos_p': 0.2, 'max_gen_duration_s': None, 'allow_early_stop': True,                     \n",
              "'use_kv_caching': True}                                                                                            \n",
              "
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generate_coarse {'x_semantic': array([ 131,   10,   10,  266,  266,  266,  206,  206,  206,  206, generation.py:460\n",
              "206,                                                                                                               \n",
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              "       2244, 2244,  250, 9768, 1307, 4388, 9351, 7895,  178,  166, 1620,                                           \n",
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              "       8522, 6089,  215,  215, 4116, 8541, 8541, 3767, 4139,   44, 9839,                                           \n",
              "       9839, 9339, 5986, 5986,  137,  107,   28,   28,  107,  667, 2672,                                           \n",
              "         10,   10,  266, 1147,  206,  107,  206,  206,  206,  206,  147,                                           \n",
              "       2127, 2156,  147, 5008,   27,   27,  399,  399, 3188, 6289, 3969,                                           \n",
              "       6185, 6185, 6185, 4475, 4149, 2425, 2425, 4145,  717,  633,   41,                                           \n",
              "        171,  489,  210,  100,    5,  401, 2361, 2739, 2773, 2848, 3840,                                           \n",
              "       3890, 1450, 1450,   92,   59,  190, 9578, 2280, 6022, 6022,  153,                                           \n",
              "       5191,   92,   59,   28,  148, 3454, 3700, 3700, 1948,  444, 5693,                                           \n",
              "        171,  171,  489,  489,  210,   10,    5,  265, 9367, 9367, 2745,                                           \n",
              "       2745, 6696, 2745, 6696, 6696, 2779, 2779, 9454, 9454, 8417, 8417,                                           \n",
              "       5500, 8270, 7183,   10, 6139,  227, 1980, 6047,  441, 5647,   10,                                           \n",
              "         10, 1096, 1096,   10,  206,  206,  206,  206,  206,  206,  206,                                           \n",
              "        206,   65,  206,  344,   65,  344,  147,  147, 3888,   57,  567,                                           \n",
              "       1973,  898,  171,  122,   59,   28,   28,   10,   28, 1133, 9235,                                           \n",
              "       3198, 1858,   29, 3793, 1315,  171,  171,  171,  171,  181,   59,                                           \n",
              "         28,   10,   41, 1966,  323, 6412, 1001, 1001, 4816, 5301, 6303,                                           \n",
              "       6303, 1667, 1667, 1667, 7365, 7365, 1647, 1647,   92,   59,   59,                                           \n",
              "         31,   31,   10,    5, 5853, 5563, 5563,  521,   41,  483, 9968,                                           \n",
              "       5839, 5839, 3177, 1493,  393,  429,   41,   41, 1904, 3277,  774,                                           \n",
              "       6247, 6247, 6247, 9804, 9804, 3216,   17,  128, 8099, 8099, 2790,                                           \n",
              "       9944, 7069, 2853, 2853, 7604, 5640, 2230,  685,   50,   10,   10,                                           \n",
              "        652, 4448, 4448, 9329, 9329, 4236, 4236, 4236, 4236, 4236,  407,                                           \n",
              "        407,  407, 7781, 4324, 2536]), 'history_prompt': None, 'temp': 0.7, 'top_k': None,                         \n",
              "'top_p': None, 'silent': False, 'max_coarse_history': 630, 'sliding_window_len': 60,                               \n",
              "'use_kv_caching': True}                                                                                            \n",
              "
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generate_fine {'x_coarse_gen': array([[1019, 1019, 1019, ...,  432,  432,  724],                  generation.py:626\n",
              "       [ 829,  841,  928, ...,  894,  894,  765]]), 'history_prompt': None, 'temp': 0.5,                           \n",
              "'silent': True}                                                                                                    \n",
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k: semantic_prompt\n",
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k: coarse_prompt\n",
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k: fine_prompt\n",
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              "
\n" ], "text/plain": [ "len: \u001b[1;36m8\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for k in fullgen:\n", " print(f\"k: {k}\")\n", " print(f\"len: {len(fullgen[k])}\")" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Rendering samples for speakers in: custom_speakers\n", " Rendering audio for custom_speakers/hark_woman.npz to custom_speakers/hark_woman_1.wav\n" ] }, { "data": { "text/html": [ "
write_seg_wav   .wav saved to custom_speakers/hark_woman_1.wav                                           api.py:325\n",
              "
\n" ], "text/plain": [ "write_seg_wav .wav saved to custom_speakers/hark_woman_1.wav \u001b]8;id=552246;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py\u001b\\\u001b[2mapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=649487;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py#325\u001b\\\u001b[2m325\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " Rendering audio for custom_speakers/hark1.npz to custom_speakers/hark1_1.wav\n" ] }, { "data": { "text/html": [ "
write_seg_wav   .wav saved to custom_speakers/hark1_1.wav                                                api.py:325\n",
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\n" ], "text/plain": [ "write_seg_wav .wav saved to custom_speakers/hark1_1.wav \u001b]8;id=9210;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py\u001b\\\u001b[2mapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=7946;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py#325\u001b\\\u001b[2m325\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ " Rendering audio for custom_speakers/en_fiery.npz to custom_speakers/en_fiery_1.wav\n" ] }, { "data": { "text/html": [ "
write_seg_wav   .wav saved to custom_speakers/en_fiery_1.wav                                             api.py:325\n",
              "
\n" ], "text/plain": [ "write_seg_wav .wav saved to custom_speakers/en_fiery_1.wav \u001b]8;id=71943;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py\u001b\\\u001b[2mapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=741508;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py#325\u001b\\\u001b[2m325\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "api.render_npz_samples(\"custom_speakers\", start_from=\"semantic\")" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Audio(gen_audio_orig_segs, rate=generation.SAMPLE_RATE)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\n", "\n", "def generate_audio(\n", " text: str,\n", " history_prompt: Optional[Union[Dict, str]] = None,\n", " text_temp: float = 0.7,\n", " waveform_temp: float = 0.7,\n", " silent: bool = False,\n", " output_full: bool = False,\n", "):\n", " \"\"\"Generate audio array from input text.\n", "\n", " Args:\n", " text: text to be turned into audio\n", " history_prompt: history choice for audio cloning\n", " text_temp: generation temperature (1.0 more diverse, 0.0 more conservative)\n", " waveform_temp: generation temperature (1.0 more diverse, 0.0 more conservative)\n", " silent: disable progress bar\n", " output_full: return full generation to be used as a history prompt\n", "\n", " Returns:\n", " numpy audio array at sample frequency 24khz\n", " \"\"\"\n", " semantic_tokens = text_to_semantic(\n", " text,\n", " history_prompt=history_prompt,\n", " temp=text_temp,\n", " silent=silent,\n", " )\n", " out = semantic_to_waveform(\n", " semantic_tokens,\n", " history_prompt=history_prompt,\n", " temp=waveform_temp,\n", " silent=silent,\n", " output_full=output_full,\n", " )\n", " if output_full:\n", " full_generation, audio_arr = out\n", " return full_generation, audio_arr\n", " else:\n", " audio_arr = out\n", " return audio_arr\n", "\n", "## ADDED BELOW" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Audio(audio_arr_segments_barki, rate=generation.SAMPLE_RATE)" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [], "source": [ "kwargs['history_prompt'] = 'custom_speakers/hark_woman.npz'" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(kwargs)" ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Rendering samples for speakers in: custom_speakers\n" ] }, { "data": { "text/html": [ "
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              "False, 'max_coarse_history': 630, 'sliding_window_len': 60, 'use_kv_caching': False}                               \n",
              "
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generate_fine {'x_coarse_gen': array([[475, 475, 475, ..., 572, 566, 910],                        generation.py:626\n",
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              "True}                                                                                                              \n",
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              "59,                                                                                                                \n",
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              "         28,   28,   28,   28,   28, 1998, 9235, 1879, 3727, 1236, 1236,                                           \n",
              "       2793, 7713, 7713, 7236, 7236,   15,   15,   15,  232,  118,   10,                                           \n",
              "         27,  200,  137,   59,   28,   28,   28,   28,  107,  107,  107,                                           \n",
              "        107,  385,  385,  577,  126,  126,  126, 2640, 2640, 2640,  230,                                           \n",
              "        206,  230,  230,  230,  528, 2691,  446,  446,  206,  446, 4764,                                           \n",
              "        446,  446, 4764, 4764,  446,  446,  446,  446, 4764, 4764,  134,                                           \n",
              "        446,  134, 4764,  446,  134, 4764, 3302, 4764,  446, 2009, 3302,                                           \n",
              "       2009,  528, 2009, 2009, 3350, 8735,  147, 2305,  147, 5128,  302,                                           \n",
              "       1271, 1489, 7907, 5274, 2016,  181,  107,  481, 5727, 6655, 1732,                                           \n",
              "         41,   41,   41,   41, 6557, 6557, 6557, 8591, 8591, 8591, 6321,                                           \n",
              "       6321, 6321,   44,   44,   26,   26,   26,   26,   26,   26,  894,                                           \n",
              "        736,  736,  736, 1300, 1300, 1593, 8665, 8665, 8844, 5064,  985,                                           \n",
              "       5051,   41,   27,   43, 6945, 6945, 8234, 6323, 6323, 4099, 4099,                                           \n",
              "       4868, 2244, 2244, 9768, 9768, 9768, 9768, 1307, 1307, 1307,   44,                                           \n",
              "       1163,   44, 8142, 8142,  761, 4248,  117,  166,  166, 8745, 1573,                                           \n",
              "         41,  483, 8671, 7095, 1449,   50,   10,    5,    5, 2837, 3368,                                           \n",
              "       3368, 4151,   41,   41, 8265, 5250, 2745, 8114, 4427,  326, 1794,                                           \n",
              "        118,  100,  401,  401,  349,  310, 2312, 2312, 3664, 2208, 5422,                                           \n",
              "       1796, 8984, 7086,   59,   28,   28,   28,   28,   28,   28,   28,                                           \n",
              "         28,  107, 1696, 3195, 6155, 3182, 3182, 8522, 8522, 3767, 3767,                                           \n",
              "         44, 7298,   44,   44,   26, 8142,   26, 3753, 3212, 5986,  327,                                           \n",
              "         92,   59,   28,   28,   28,   28,  107,  667,  138,   10,  206,                                           \n",
              "        266,  206,  276,  276,  206,  206,  276,  107,  276,  206,  206,                                           \n",
              "        206,  206,  206,  206,  206,   91,  206,  206,  206,  206,  206,                                           \n",
              "        206,   65,  517,  344,  344,  344, 1278, 1278, 3057,  383, 5064,                                           \n",
              "         27,   27,  282,  287,  399,  927, 3969, 4600, 6185, 6185, 2703,                                           \n",
              "       5293, 5293,  911, 5083,   41,   41,  489,  547,   99,  282,  401,                                           \n",
              "        401, 1939, 2739, 2773, 1463, 1463, 3840, 3890, 1450,   92,   59,                                           \n",
              "        190, 2280, 4394, 6022, 6022,  153,  153, 5191,   71,   92,   59,                                           \n",
              "         28,  315, 7473, 3454, 3700, 1948, 1948, 4249,  171,  171,  171,                                           \n",
              "        171,  255,   41,    5,  265,  265, 1149, 9367, 9367, 2745, 2745,                                           \n",
              "       2745, 6696, 2779, 2779, 2779, 2779, 2508, 2508, 2508, 1667, 1667,                                           \n",
              "       2286, 1191,  326,  326, 1093, 2282,  178,   27,   27,  583,  583,                                           \n",
              "       1863,   97, 2365, 2365,  157,   96,  157,  157, 2365, 2365,  157,                                           \n",
              "       3017, 6806,  604,   10,  604, 3249, 5673, 5475,  321,  171,  171,                                           \n",
              "        489,   59,   28,   28,   28,   28,   28, 1998, 9235, 3198, 1858,                                           \n",
              "         29,   29, 6965,  657,   41,  171,  255,  255,  547, 3145,  181,                                           \n",
              "         59,   28,   28, 5128,   41,  337,  323, 3704, 5384, 4816, 4816,                                           \n",
              "       4816, 6303, 6303, 1667, 1667, 1667, 1667, 1667, 7365, 1647, 1021,                                           \n",
              "         92,   59,   28,   28,  107, 5331,   67,    5, 5294, 5853, 5563,                                           \n",
              "       5819,  402,   41, 2686, 9968, 5839, 3177, 1493, 1536,  393,  429,                                           \n",
              "        198,   10,   38, 4967,  774]), 'history_prompt': None, 'temp': 0.7, 'top_k': None,                         \n",
              "'top_p': None, 'silent': False, 'max_coarse_history': 630, 'sliding_window_len': 60,                               \n",
              "'use_kv_caching': False}                                                                                           \n",
              "
\n" ], "text/plain": [ "generate_coarse \u001b[1m{\u001b[0m\u001b[32m'x_semantic'\u001b[0m: \u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m7160\u001b[0m, \u001b[1;36m298\u001b[0m, \u001b[1;36m429\u001b[0m, \u001b[1;36m41\u001b[0m, \u001b[1;36m1058\u001b[0m, \u001b[1;36m5564\u001b[0m, \u001b[1;36m5564\u001b[0m, \u001b[1;36m6627\u001b[0m, \u001b[1;36m92\u001b[0m, \u001b[1;36m28\u001b[0m, \u001b]8;id=383947;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py\u001b\\\u001b[2mgeneration.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=670240;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/generation.py#460\u001b\\\u001b[2m460\u001b[0m\u001b]8;;\u001b\\\n", "\u001b[1;36m59\u001b[0m, \u001b[2m \u001b[0m\n", " \u001b[1;36m9296\u001b[0m, \u001b[1;36m4093\u001b[0m, \u001b[1;36m1335\u001b[0m, \u001b[1;36m7518\u001b[0m, \u001b[1;36m117\u001b[0m, \u001b[1;36m41\u001b[0m, \u001b[1;36m41\u001b[0m, 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generate_fine {'x_coarse_gen': array([[1019,  879,  491, ...,  983,  683,  865],                  generation.py:626\n",
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              "'silent': True}                                                                                                    \n",
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write_seg_wav   .wav saved to custom_speakers/hark3_1.wav                                                api.py:325\n",
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generate_coarse {'x_semantic': array([ 147, 6242,  302, 1106,  401, 2739, 9511, 9924, 9924, 9924, generation.py:460\n",
              "2092,                                                                                                              \n",
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              "'sliding_window_len': 60, 'use_kv_caching': False}                                                                 \n",
              "
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generate_fine {'x_coarse_gen': array([[408, 408, 408, ..., 408, 408,  62],                        generation.py:626\n",
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              "True}                                                                                                              \n",
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write_seg_wav   .wav saved to custom_speakers/en_fiery_1.wav                                             api.py:325\n",
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\n" ], "text/plain": [ "write_seg_wav .wav saved to custom_speakers/en_fiery_1.wav \u001b]8;id=763391;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py\u001b\\\u001b[2mapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=14160;file:///home/jon/mamba_projects/bark_postfixes/bark/bark_infinity/api.py#325\u001b\\\u001b[2m325\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "api.render_npz_samples(\"custom_speakers\", start_from=\"semantic_prompt\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Audio(audio_arr_segments_barki, rate=generation.SAMPLE_RATE) " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "generation.preload_models()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "text = \"\"\"\n", "Hark! I, the phantom visage of Edward Teach, rise from the \n", "abyss, forever bound to the briny depths. With me, brave the tumultuous seas, claim treasures untold,\n", "and send foes to their watery doom.\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "history_prompt = np.load(\"pirates/base/pirate.npz\")\n", "from rich import inspect" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "for key in history_prompt.keys():\n", " length = len(history_prompt[key])\n", " print(f\"key: {key}, length: {length}\")\n", " inspect(history_prompt[key], title=f\"{key} ({length})\")\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "new_semantic = np.hstack([x_semantic_history, x_semantic]).astype(np.int32)\n", "\n", "semantic_prompt = history_prompt[\"semantic_prompt\"]\n", "midpoint = len(semantic_prompt) // 2\n", "new_semantic_first_half = semantic_prompt[:midpoint].astype(np.int32)\n", "\n", "\n", "Instead I would like new_semantic to be half the size of x_semantic_history, just the last half of the space." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ " if length > 0:\n", " for sub_key in history_prompt[key].keys():\n", " print(f\" {sub_key}={history_prompt[key][sub_key]}\")\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\n", "gen_minor_variants = 20\n", "import random\n", "\n", "npz_file = \"pirate.npz\"\n", "npz_directory = \"pirates/base\"\n", "npz_filepath = \"pirates/base/pirate.npz\"\n", "\n", "semantic_prompt = history_prompt[\"semantic_prompt\"]\n", "original_semantic_prompt = semantic_prompt.copy()\n", "starting_point = 128\n", "ending_point = len(semantic_prompt) - starting_point\n", "\n", "\n", "\n", "points = np.linspace(starting_point, ending_point, gen_minor_variants)\n", " \n", "for starting_point in points:\n", " starting_point = int(starting_point)\n", " print(starting_point)\n", "\n", " new_semantic_from_beginning = original_semantic_prompt[:starting_point].astype(np.int32)\n", " new_semantic_from_ending = original_semantic_prompt[starting_point:].astype(np.int32)\n", "\n", " for semantic_prompt in [new_semantic_from_beginning, new_semantic_from_ending]:\n", " \n", " print(f\"len(semantic_prompt): {len(semantic_prompt)}\")\n", " print(f\"starting_point: {starting_point}, ending_poinst: {ending_point}\") \n", "\n", " temp_coarse = random.uniform(0.5, 0.9)\n", " top_k_coarse = None if random.random() < 1/3 else random.randint(50, 100)\n", " top_p_coarse = None if random.random() < 1/3 else random.uniform(0.8, 0.95)\n", "\n", " max_coarse_history_options = [630, random.randint(500, 630), random.randint(60, 500)]\n", " max_coarse_history = random.choice(max_coarse_history_options)\n", "\n", " coarse_tokens = generation.generate_coarse(semantic_prompt, temp=temp_coarse, top_k=top_k_coarse, top_p=top_p_coarse, max_coarse_history=max_coarse_history)\n", "\n", " temp_fine = random.uniform(0.3, 0.7)\n", " fine_tokens = generation.generate_fine(coarse_tokens, temp=temp_fine)\n", "\n", " history_prompt_render_variant = {\"semantic_prompt\": semantic_prompt, \"coarse_prompt\": coarse_tokens, \"fine_prompt\": fine_tokens}\n", "\n", " try:\n", " audio_arr = generation.codec_decode(fine_tokens)\n", " base_output_filename = os.path.splitext(npz_file)[0] + f\"_var_{i}.wav\"\n", " output_filepath = os.path.join(npz_directory, base_output_filename)\n", " output_filepath = api.generate_unique_filepath(output_filepath)\n", " print(f\" Rendering minor variant voice audio for {npz_filepath} to {output_filepath}\")\n", " api.write_seg_wav(output_filepath, audio_arr)\n", "\n", " api.write_seg_npz(output_filepath, history_prompt_render_variant)\n", " except:\n", " print(f\" \")" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "id": "yPr_MuqFXZ5r" }, "source": [ "### Set Text and Other Generation Options" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "nTzF9iamO1Tm" }, "outputs": [], "source": [ "text = \"\"\"\n", "Hey, have you heard about this new text-to-audio model called \"Bark\"? \n", "It's like rain on your wedding day. It's a free ride when you've already paid. It's the good advice that you just didn't take.\n", "And who would've thought? It figures.\n", "\n", "Well, life has a funny way of sneaking up on you. When you think everything's okay and everything's going right. \n", "And life has a funny way of helping you out. When you think everything's gone wrong. \n", "And everything blows up in your face.\n", "\n", "It's a traffic jam when you're already late. A \"No smoking\" sign on your cigarette break.\n", "It's like ten thousand spoons when all you need is a knife. It's meeting the man of my dreams.\n", "And then meeting his beautiful wife.\n", "\n", "And isn't it ironic? Don't you think? A little too ironic.\n", "And yeah, I really do think.\n", "\"\"\"\n", "\n", "# FOr split set split_character_goal_length and split_character_max_length\n", "kwargs = {}\n", "\n", "kwargs = config.load_all_defaults()\n", "kwargs['text_prompt'] = text\n", "kwargs['hoarder_mode'] = True\n", "kwargs[\"output_dir\"] = 'bark_samples'\n", "kwargs[\"history_prompt\"] = None\n", "# kwargs[\"single_starting_seed\"] = None # \n", "# If you set seed you might want manually call generation.set_seed(-1) after to disable deterministic generation settings \n", "# I'm not cleaning up after this paramater at the moment and I'm not sure on other side effects\n", "kwargs[\"stable_mode_interval\"] = 1 # 0 for continous, 2,3,4 for mixed\n", "kwargs[\"split_character_goal_length\"] = 90\n", "kwargs[\"split_character_max_length\"] = 130\n", "# kwargs[\"output_iterations\"] = 1\n", "kwargs[\"add_silence_between_segments\"] = .025 # See: https://github.com/suno-ai/bark/blob/main/notebooks/long_form_generation.ipynb but not great for songs or stable_mode_interval 0\n", "kwargs[\"semantic_min_eos_p\"] = 0.05 # 0.20 is default, lower means more likely to stotp\n", "\n", "\n", "# not sure on overall effect so far from these, but for example:\n", "kwargs[\"semantic_top_k\"] = 50\n", "kwargs[\"semantic_top_p\"] = 0.95" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "id": "uuqkchecXnbm" }, "source": [ "### First Attempt" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "id": "6ANm93mHZIa6" }, "source": [ "#### Before we run, let's double check out settings" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 582 }, "id": "6SPmYLSoQBBp", "outputId": "d896cba0-fc95-4343-ff59-57d822a71467" }, "outputs": [], "source": [ "kwargs[\"dry_run\"] = True # Check how the text is being split, don't actually run the model. \n", "full_generation_segments, audio_arr_segments, final_filename_will_be = api.generate_audio_long(**kwargs)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 582 }, "id": "IEFQgcemX7Ih", "outputId": "49e553d8-2b3d-43e4-9c8a-62cea105bb86" }, "outputs": [], "source": [ "# that's the output we expect to see, we didn't generate audio yet\n", "# these text segments look a little small small so let's try this instead\n", "kwargs[\"split_character_goal_length\"] = 110\n", "kwargs[\"split_character_max_length\"] = 175\n", "\n", "full_generation_segments, audio_arr_segments, final_filename_will_be = api.generate_audio_long(**kwargs)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "id": "iPwaLVKCZNaN" }, "source": [ "#### Run Bark" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 908 }, "id": "gnvv0zEZY7vP", "outputId": "5a501a72-a2d0-4a66-8ab9-ab876cf6a10f" }, "outputs": [], "source": [ "# These segement sizes look better so now so set dry_run to False to run for real\n", "# Because we set hoarder_mode we can see the wav files for each segment in the Colab File Manager\n", "\n", "kwargs[\"dry_run\"] = False\n", "full_generation_segments, audio_arr_segments, final_filename_will_be = api.generate_audio_long(**kwargs)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "Qqyw-Uk1axiC" }, "outputs": [], "source": [ "print(f\" final wav at {final_filename_will_be} \")\n", "# (we see many wav because we set hoarder_mode, but one file will be the final product\n", "# set hoarder_mode=False if you just want the file wav and aren't in explore mode\n", "\n", "# or play here \n", "Audio(np.concatenate(audio_arr_segments), rate=generation.SAMPLE_RATE) \n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 497, "referenced_widgets": [ "8ea29b7225d541f080777684c195f999", "a98dc53d118d496981706e6b51165c62", "6caacddbe9c342a7b385dee13264b934", "2abd2834c2e64c0fb4ca048e3e022949", "c85a04777707427fb4feaa1a490bbf59", "917113d8bf08419eaae8225762200a3b", "71bbd6f43cf144f7ab36bed80b4a68d6", "5d10427092ce494092dd22dde8b329f6", "a3f6f1b2f7e84dd5a49a5581c0769a62", "6b6084bdd35e4d178057706993d60140", "7f4e5dff04df4aaeb093c8f0c82df3b3", "9019d02759574f9e959c85ec2730ca59", "db9a72ac819040338d9af5d9814820a0", "25d7021cabf5433298269e42666f9a85", "c812f5dc984444ad9dba077f0e64ef1c", "da58ffbea7604844aa6c54815887445f", "4221c0af5d7f4eed884d4647db6a4d7e", "16c5ddc2cd62477e80085a7f969ea4e0", "6d939e0401824fa0a02a00e1358504ad", "a32ffcd3be074dc7be0a6e2d65b0c4bb", "fe89cce3a1eb4ef59210501f8e853cf2" ] }, "id": "yqORA8ajXMrk", "outputId": "1c9960b5-da6c-458a-9af2-d8a814db0b99" }, "outputs": [], "source": [ "# because we set hoarder mode we also saved each segement as its own seperate sample with wav\n", "\n", "!find \"bark_samples/\" -name \"*.npz\"\n", "\n", "display_wav_files(\"bark_samples/\")" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "id": "psbR-0mxW4Dn" }, "source": [ "### Second Attempt. Can we do better?" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "WQvyiM2sW5xC" }, "outputs": [], "source": [ "# we used stable_mode_interval = 1, so the history_prompt does not evolve between segments\n", "# even still the voices that are saved for each segment are one-generation different than the original history prompt\n", "# this means they are a *little* bit different, and we may prefer one of them over the original\n", "# for example maybe segment 2 was a little more clear, or had a particular emotion, we could use that segment's version as the speaker\n", "# in the particular run I'm doing now, that segment ended with a little bit an interesting accent. I'm curious if I can bring that out more.\n", "\n", "# (should probably rename the file to something sensible though)\n", "\n", "kwargs[\"history_prompt\"] = \"/content/bark/bark_samples/Hey_have_you_heard_a-SPK-random.wav/002_Its_the_good_advice_-SPK-random.wav.npz\"" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "btp4V86BfAT1", "outputId": "0dc09a5e-baca-450f-c7e9-63302a974bea" }, "outputs": [], "source": [ "kwargs[\"text_prompt\"] = f\"I'm speaker number two. I'm the best speaker. Also I'm a free spirit. Let me evolve my voice with every step. Here's my version.\"\n", "kwargs[\"text_prompt\"] += text\n", "kwargs[\"stable_mode_interval\"] = 0 \n", "kwargs[\"output_dir\"] = \"speaker_2_test\"\n", "kwargs[\"add_silence_between_segments\"] = 0.0 # No silence, fully merge clips\n", "\n", "kwargs[\"semantic_min_eos_p\"] = 0.20 # Back to default, let Bark umm and ahh a bit\n", "full_generation_segments, audio_arr_segments, final_filename_will_be = api.generate_audio_long(**kwargs)\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "9fthW9oGw-5g" }, "outputs": [], "source": [ "print(f\" final wave at {final_filename_will_be}\")\n", "Audio(np.concatenate(audio_arr_segments), rate=generation.SAMPLE_RATE) " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 419, "referenced_widgets": [ "84a7d2a44cff4af0a7ac51201a451c2c", "6ea50794f0df4129a5ccc7c736a177c8", "500a8ffd11ba44e781ba9bd30cf01798", "34f31ddd3abf4912ad4b4d1b6db17c0a", "0bcae29b25c24fb7b2304394c5e4b5ff", "c4665df69acf4675ac6aa728ece70631", "f11e33866bae4f97afd7d8be04f69d08", "ba676a7a9b4540f08199903d9d83fea8", "d95d5fec436040698a5b4236f3d5d81f", "bfb0c1f37e4541aa938041ceb9bfacc2", "8aec7773934a4651a88ba343c1a6f6a6", "e1a97cc9969c482ebe5ce0c9d1967989", "18e25b6d233f4fbeb9fc9ed8e8d0c609", "20a060f910274c75a04af4493000a478", "d1798f0507c444248c68286d27c26458", "8fb28922d6a24e97b5ebe582cc981b07", "ee01a0665af84f35a3a9e779e140ef67", "b595442996e94d9b87b1fd657ebc512a", "8fd2ab5f1b704ac2bbc88a95ff60614a", "000ef644370a46adb4bc9918ce248dc2", "a3550d6eb97a45809978825e4b8b36a0", "82165a42741a4baf8ffc795687a249de", "471b04ef64584089b8526b7a2805f94f", "e61f0582de914f0ca216966185139808" ] }, "id": "Rlv4CQrfthY8", "outputId": "a759d618-ab34-4e72-f28b-fad64205550a" }, "outputs": [], "source": [ "# this clip probably got really weird after a full segments, fully feedbacking into itself. So kwargs[\"stable_mode_interval\"] = 3 might be a good compromise\n", "\n", "display_wav_files(\"speaker_2_test\")" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "id": "z64RIV6Kc2_K" }, "source": [ "### Finding Our Voice" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "Q_2NNCiso3vV" }, "outputs": [], "source": [ "# That final clip is an improvement, the random voice we got isn't bad but it's not quite doing our beautiful prose justice\n", "# we could use an existing history_prompt, but let's try to summon a perfect speaker from the model\n", "# we do that by generating many speakers randomly\n", "# we could use our first segment text, in my experience there is a better method\n", "# try to image: what type of text would be the context in voice I want to hear is likely to appear?\n", "# then let's generate 20 sample clips from that\n", "\n", "# TODO" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "\n", "text=\"\"\"\n", "How many fucken morons can wave his arms and keep people in tempo? \n", "I was there to push people beyond what's expected of them. \n", "I believe that is an absolute necessity. \n", "Otherwise we're depriving the world of the next Louis Armstrong, \n", "or the next Charlie Parker. \n", "Have I told you that story about how Charlie Parker became Charlie Parker?\n", "Parker's a young kid, pretty good on the Sax, \n", "gets up to play at a cutting session, \n", "and well, he fucks it up. \n", "And Jones nearly decapitates him for it, throws a cymbal at his head. \n", "And Charlie's laughed off stage. Cries himself to sleep that night. \n", "But the next morning, what does he do? He practices. \n", "And he practices and he practices and he practices. \n", "With one goal in mind - never to be laughed at again. \n", "And a year later he goes back to the Reno, \n", "and he steps up on that stage \n", "and he plays the best motherfucken solo the world has ever heard. \n", "So imagine if Jones had just said, \n", "\"Well that's okay, Charlie, that was alright. Good job.” \n", "And Charlie thinks to himself, “Well, shit I did do a pretty good job.” \n", "End of story. That to me is an absolute tragedy. \n", "But that's just what the world wants now. \n", "No wonder Jazz is dying.\n", "\n", "[He takes a sip of his drink.]\n", "I tell you man, every Starbucks “Jazz” album, just proves my point really \n", "- there are no two words more harmful in the English language than “Good job”.\n", "\n", "The truth is Andrew I… never really had a Charlie Parker. \n", "But I tried. I actually fucking tried. \n", "And that's more than most people ever do, \n", "and I will never apologise for how I tried.\n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import re\n", "def apply_rule_to_prompt(regex, replacement, flags, text):\n", "\n", " \n", " re_flags = 0\n", " if 'MULTILINE' in flags:\n", " re_flags |= re.MULTILINE\n", " return re.sub(regex, replacement, text, flags=re_flags)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "regex = \"[\\.?,]\"\n", "replacement = \" \"\n", "flags = \"MULTILINE\"\n", "\n", "print(apply_rule_to_prompt(regex, replacement, flags, text))" ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "id": "Q0v6zLxmcr5W" }, "outputs": [ { "data": { "text/plain": [ "'\\ndef split_by_sentences(text: str, n: int, language=\"en\") -> List[str]:\\n seg = pysbd.Segmenter(language=language, clean=False)\\n sentences = seg.segment(text)\\n return [\\' \\'.join(sentences[i:i + n]) for i in range(0, len(sentences), n)]\\n'" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from typing import List\n", "import re\n", "import random \n", "from typing import Dict, Optional, Union\n", "import logging\n", "\n", "import rich\n", "from rich import print\n", "from rich import pretty\n", "from rich.pretty import pprint\n", "from rich import inspect\n", "\n", "\n", "\n", "logger = logging.getLogger(__name__)\n", "\n", "def split_text(text: str, split_type: Optional[str] = None, split_type_quantity = 1, split_type_string: Optional[str] = None, split_type_value_type: Optional[str] = None) -> List[str]:\n", " if text == '':\n", " return [text]\n", "\n", " # the old syntax still works if you don't use this parameter, ie\n", " # split_type line, split_type_value 4, splits into groups of 4 lines\n", " if split_type_value_type == '':\n", " split_type_value_type = split_type\n", "\n", " \"\"\"\n", " if split_type == 'phrase':\n", " # print(f\"Loading spacy to split by phrase.\")\n", " nlp = spacy.load('en_core_web_sm')\n", "\n", " chunks = split_by_phrase(text, nlp)\n", " # print(chunks)\n", " return chunks\n", " \"\"\"\n", " if split_type == 'string' or split_type == 'regex':\n", "\n", " if split_type_string is None:\n", " logger.warning(\n", " f\"Splitting by {split_type} requires a string to split by. Returning original text.\")\n", " return [text]\n", "\n", " split_type_to_function = {\n", " 'word': split_by_words,\n", " 'line': split_by_lines,\n", " 'sentence': split_by_sentence,\n", " 'string': split_by_string,\n", " 'char' : split_by_char,\n", " #'random': split_by_random,\n", " # 'rhyme': split_by_rhymes,\n", " # 'pos': split_by_part_of_speech,\n", " 'regex': split_by_regex,\n", " }\n", "\n", "\n", "\n", " if split_type in split_type_to_function:\n", " # split into groups of 1 by the desired type\n", " # this is so terrible even I'm embarassed, destroy all this code later, but I guess it does something useful atm\n", " segmented_text = split_type_to_function[split_type](text, split_type = split_type, split_type_quantity=1, split_type_string=split_type_string, split_type_value_type=split_type_value_type)\n", " final_segmented_text = []\n", " current_segment = ''\n", " split_type_quantity_found = 0\n", "\n", " if split_type_value_type is None:\n", " split_type_value_type = split_type\n", " \n", " for seg in segmented_text: # for each line, for example, we can now split by 'words' or whatever, as a counter for when to break the group\n", " current_segment += seg\n", "\n", " #print(split_type_to_function[split_type](current_segment, split_type=split_type_value_type, split_type_quantity=1, split_type_string=split_type_string))\n", " split_type_quantity_found = len(split_type_to_function[split_type_value_type](current_segment, split_type=split_type_value_type, split_type_quantity=1, split_type_string=split_type_string))\n", " #print(f\"I see {split_type_quantity_found} {split_type_value_type} in {current_segment}\")\n", " if split_type_quantity_found >= split_type_quantity:\n", " final_segmented_text.append(current_segment)\n", " split_type_quantity_found = 0\n", " current_segment = ''\n", " \n", " return final_segmented_text\n", "\n", " logger.warning(\n", " f\"Splitting by {split_type} not a supported option. Returning original text.\")\n", " return [text]\n", "\n", "def split_by_string(text: str, split_type: Optional[str] = None, split_type_quantity: Optional[int] = 1, split_type_string: Optional[str] = None, split_type_value_type: Optional[str] = None) -> List[str]:\n", " if split_type_string is not None:\n", " split_pattern = f\"({split_type_string})\"\n", " split_list = re.split(split_pattern, text)\n", " result = [split_list[0]]\n", " for i in range(1, len(split_list), 2):\n", " result.append(split_list[i] + split_list[i+1])\n", " return result\n", " else:\n", " return text.split()\n", "\n", "def split_by_regex(text: str, split_type: Optional[str] = None, split_type_quantity: Optional[int] = 1, split_type_string: Optional[str] = None, split_type_value_type: Optional[str] = None) -> List[str]:\n", " chunks = []\n", " start = 0\n", " if split_type_string is not None:\n", " for match in re.finditer(split_type_string, text):\n", " end = match.start()\n", " chunks.append(text[start:end].strip())\n", " start = end\n", "\n", " chunks.append(text[start:].strip())\n", " return chunks\n", " else:\n", " return text.split()\n", "\n", "def split_by_char(text: str, split_type: Optional[str] = None, split_type_quantity = 1, split_type_string: Optional[str] = None, split_type_value_type: Optional[str] = None) -> List[str]:\n", " return list(text)\n", "\n", "def split_by_words(text: str, split_type: Optional[str] = None, split_type_quantity = 1, split_type_string: Optional[str] = None, split_type_value_type: Optional[str] = None) -> List[str]:\n", " \n", " return [word + ' ' for word in text.split() if text.strip()]\n", " #return [' '.join(words[i:i + split_type_quantity]) for i in range(0, len(words), split_type_quantity)]\n", "\n", "\n", "def split_by_lines(text: str, split_type: Optional[str] = None, split_type_quantity = 1, split_type_string: Optional[str] = None, split_type_value_type: Optional[str] = None) -> List[str]:\n", " lines = [line + '\\n' for line in text.split('\\n') if line.strip()]\n", " return lines\n", " #return ['\\n'.join(lines[i:i + split_type_quantity]) for i in range(0, len(lines), split_type_quantity)]\n", "\n", "def split_by_sentence(text: str, split_type: Optional[str] = None, split_type_quantity = 1, split_type_string: Optional[str] = None, split_type_value_type: Optional[str] = None) -> List[str]:\n", " import nltk \n", " text = text.replace(\"\\n\", \" \").strip()\n", " sentences = nltk.sent_tokenize(text)\n", " return [sentence + ' ' for sentence in sentences]\n", " #return [' '.join(sentences[i:i + split_type_quantity]) for i in range(0, len(sentences), split_type_quantity)]\n", "\n", "\n", "\"\"\"\n", "def split_by_sentences(text: str, n: int, language=\"en\") -> List[str]:\n", " seg = pysbd.Segmenter(language=language, clean=False)\n", " sentences = seg.segment(text)\n", " return [' '.join(sentences[i:i + n]) for i in range(0, len(sentences), n)]\n", "\"\"\"\n" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [], "source": [ "text = \"\"\"\n", "How many fucken morons can wave his arms and keep people in tempo? \n", "I was there to push people beyond what's expected of them. \n", "I believe that is an absolute necessity. \n", "Otherwise we're depriving the world of the next Louis Armstrong, \n", "or the next Charlie Parker. \n", "Have I told you that story about how Charlie Parker became Charlie Parker?\n", "Parker's a young kid, pretty good on the Sax, \n", "gets up to play at a cutting session, \n", "and well, he fucks it up. \n", "And Jones nearly decapitates him for it, throws a cymbal at his head. \n", "\"\"\"" ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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\n" ], "text/plain": [ "\u001b[1m[\u001b[0m\n", " \u001b[32m'How many fucken morons can wave his arms and keep people in tempo? '\u001b[0m,\n", " \u001b[32m\"I was there to push people beyond what's expected of them. \"\u001b[0m,\n", " \u001b[32m'I believe that is an absolute necessity. '\u001b[0m,\n", " \u001b[32m\"Otherwise we're depriving the world of the next Louis Armstrong, or the next Charlie Parker. \"\u001b[0m,\n", " \u001b[32m'Have I told you that story about how Charlie Parker became Charlie Parker? '\u001b[0m,\n", " \u001b[32m\"Parker's a young kid, pretty good on the Sax, gets up to play at a cutting session, and well, he fucks it \u001b[0m\n", "\u001b[32mup. \"\u001b[0m,\n", " \u001b[32m'And Jones nearly decapitates him for it, throws a cymbal at his head. '\u001b[0m\n", "\u001b[1m]\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(split_by_sentence(text))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(list(text))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(split_by_words(text))" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['How many fucken morons can wave his arms and ke', 'ep pe', 'ople in te', 'mpo? \\nI was there to push pe', \"ople beyond what's e\", \"xpected of them. \\nI believe that is an absolute necessity. \\nOtherwise we're d\", \"epriving the world of the next Louis Armstrong, \\nor the next Charlie Parker. \\nHave I told you that story about how Charlie Parker became Charlie Parker?\\nParker's a young kid, pretty good on the Sax, \\ngets\", 'up to play at a cutting session, \\nand well, he fucks it', 'up. \\nAnd Jones nearly dec', 'apitates him for it, throws a cymbal at his head.']" ] }, "execution_count": 71, "metadata": {}, "output_type": "execute_result" } ], "source": [ "split_text(text, split_type=\"regex\", split_type_string=f\"[\\w]p\")" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
[]\n",
              "
\n" ], "text/plain": [ "\u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "pprint(split_text(text, split_type=\"sentence\", split_type_quantity=2, split_type_value_type=\"line\"))\n", "\n", "process_text_by\n", "# process by words/lines split into chunks of size X words/lines" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "text = \"\"\"\n", "It's like rain on your wedding day.\n", "It's a free ride when you've already paid.\n", "It's the good advice that you just didn't take.\n", "And who would've thought? It figures.\n", "It's like rain on your wedding day.\n", "It's a free ride when you've already paid.\n", "It's the good advice that you just didn't take.\n", "And who would've thought? It figures.\n", "\"\"\"\n", "\n", "result = split_text(text, split_type=\"line\", split_type_quantity=3)\n", "print(result)\n", "\n", "result = split_text(text, split_type=\"word\", split_type_quantity=4)\n", "print(result)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "result = split_text(text, split_type=\"string\", split_type_quantity=23, split_type_string = \"the\")\n", "print(result)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(split_by_string(\"The dog went to the dog store and ate\", split_type=\"string\", split_type_quantity=23, split_type_string=\"dog\"))\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "split_text(text, split_type=\"line\", split_type_quantity=3, split_type_value_type=\"word\")" ] } ], "metadata": { "accelerator": "GPU", "colab": { "collapsed_sections": [ "HJQ4TI0_Qowr", "FHlxNCt3QwIr", "uuqkchecXnbm" 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