Spaces:
Runtime error
Runtime error
adding app and requirements
Browse files- app.py +188 -0
- requirements.txt +8 -0
app.py
ADDED
@@ -0,0 +1,188 @@
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import gradio as gr
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from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
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from wgpu.utils.shadertoy import *
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from wgpu.gui.offscreen import WgpuCanvas as OffscreenCanvas, run as run_offscreen
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import wgpu
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import time
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import ctypes
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import datasets
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from PIL import Image
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import asyncio
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import numpy as np
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# reimplement the Shadertoy class with offscreen canvas!
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class ShadertoyCustom(Shadertoy):
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def __init__(self, shader_code, resolution=(800, 450), canvas_class=WgpuCanvas, run_fn=run):
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self._canvas_class = canvas_class
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self._fun_fn = run_fn
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super().__init__(shader_code, resolution)
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self._uniform_data = UniformArray(
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("mouse", "f", 4),
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("resolution", "f", 3),
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("time", "f", 1),
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("time_delta", "f", 1),
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("frame", "I", 1),
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)
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self._shader_code = shader_code
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self._uniform_data["resolution"] = resolution + (1,)
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self._prepare_render()
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self._bind_events()
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def _prepare_render(self):
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import wgpu.backends.rs # noqa
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self._canvas = self._canvas_class(title="Shadertoy", size=self.resolution, max_fps=60)
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adapter = wgpu.request_adapter(
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canvas=self._canvas, power_preference="high-performance"
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)
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self._device = adapter.request_device()
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self._present_context = self._canvas.get_context()
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# We use "bgra8unorm" not "bgra8unorm-srgb" here because we want to let the shader fully control the color-space.
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self._present_context.configure(
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device=self._device, format=wgpu.TextureFormat.bgra8unorm
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)
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shader_type = self.shader_type
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if shader_type == "glsl":
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vertex_shader_code = vertex_code_glsl
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frag_shader_code = (
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builtin_variables_glsl + self.shader_code + fragment_code_glsl
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)
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elif shader_type == "wgsl":
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vertex_shader_code = vertex_code_wgsl
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frag_shader_code = (
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builtin_variables_wgsl + self.shader_code + fragment_code_wgsl
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)
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vertex_shader_program = self._device.create_shader_module(
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label="triangle_vert", code=vertex_shader_code
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)
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frag_shader_program = self._device.create_shader_module(
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label="triangle_frag", code=frag_shader_code
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)
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self._uniform_buffer = self._device.create_buffer(
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size=self._uniform_data.nbytes,
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usage=wgpu.BufferUsage.UNIFORM | wgpu.BufferUsage.COPY_DST,
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)
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bind_group_layout = self._device.create_bind_group_layout(
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entries=binding_layout
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)
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self._bind_group = self._device.create_bind_group(
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layout=bind_group_layout,
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entries=[
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{
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"binding": 0,
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"resource": {
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"buffer": self._uniform_buffer,
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"offset": 0,
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"size": self._uniform_data.nbytes,
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},
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},
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],
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)
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self._render_pipeline = self._device.create_render_pipeline(
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layout=self._device.create_pipeline_layout(
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bind_group_layouts=[bind_group_layout]
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),
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vertex={
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"module": vertex_shader_program,
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"entry_point": "main",
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"buffers": [],
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},
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primitive={
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"topology": wgpu.PrimitiveTopology.triangle_list,
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"front_face": wgpu.FrontFace.ccw,
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"cull_mode": wgpu.CullMode.none,
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},
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depth_stencil=None,
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multisample=None,
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fragment={
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"module": frag_shader_program,
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"entry_point": "main",
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"targets": [
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{
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"format": wgpu.TextureFormat.bgra8unorm,
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"blend": {
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"color": (
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wgpu.BlendFactor.one,
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wgpu.BlendFactor.zero,
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wgpu.BlendOperation.add,
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),
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"alpha": (
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wgpu.BlendFactor.one,
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wgpu.BlendFactor.zero,
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wgpu.BlendOperation.add,
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),
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},
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},
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],
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},
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)
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def show(self, time: float = 0.0):
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self._canvas.request_draw(self._draw_frame)
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self._fun_fn()
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text = """
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# Welcome to the interactive shadercoding demo.
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## (WIP), you can try and explore the dataset a bit right now. (frames are rendered on the fly, not part of the dataset(yet))
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This gives you access to a filtered version of the [Shadertoys](https://huggingface.co/datasets/Vipitis/Shadertoys) dataset, only shaders that const of a single pass (and have at least one fuction with a return statement) are available.
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In the near future there will be some buttons and sliders to generate variations of the shadercode itself, and hence get some different images.
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If I find an efficient way, the shaders might run in real time and be interactive.
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"""
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passes_dataset = datasets.load_dataset("Vipitis/Shadertoys")
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single_passes = passes_dataset.filter(lambda x: not x["has_inputs"] and x["num_passes"] == 1 and x["code"].count("return") >= 1) #filter easier than having a custom loader script?
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all_single_passes = datasets.concatenate_datasets([single_passes["train"], single_passes["test"]])
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num_samples = len(all_single_passes)
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async def get_image(code, time= 0.0, resolution=(512, 420)):
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shader = ShadertoyCustom(code, resolution, OffscreenCanvas, run_offscreen) #pass offscreen canvas here.
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shader._uniform_data["time"] = time #set any time you want
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shader._canvas.request_draw(shader._draw_frame)
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# frame = shader._canvas.snapshot().data
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frame = np.asarray(shader._canvas.draw())
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img = Image.fromarray(frame)
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# remove transparent pixels
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img = img.convert('RGB')
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return img
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def grab_sample(sample_idx):
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sample_pass = all_single_passes[sample_idx]
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sample_code = sample_pass["code"]
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sample_source = sample_pass["source"]
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sample_title = sample_pass["title"]
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sample_auhtor = sample_pass["author"]
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return sample_code, sample_source #, sample_title, sample_auhtor
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def _make_pipeline(model_cp):
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tokenizer = AutoTokenizer.from_pretrained(model_cp, trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained(model_cp, trust_remote_code=True)
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return pipeline("text-generation", model=model, tokenizer=tokenizer, trust_remote_code=True)
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with gr.Blocks() as site:
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text_md = gr.Markdown(text)
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model_cp = gr.Textbox(value="Vipitis/santacoder-finetuned-Shadertoys", label="Model Checkpoint", interactive=True)
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sample_idx = gr.Slider(minimum=0, maximum=num_samples, value=5, label="pick sample from dataset", step=1.0)
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# run_button = gr.Button(label="generate code")
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render_button = gr.Button("render frame0",label="render frame")
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time_slider = gr.Slider(minimum=0, maximum=10, value=0, label="time (update on release)", step=0.02)
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#output = gr.Textbox(label="Output")
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rendered_frame = gr.Image(shape=(512, 420), label=f"rendered frame preview")
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info_md = gr.Markdown(value="code_source", label="source URL for this shader", interactive=False)
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sample_code = gr.Code(label="Sample Code", language=None, readonly=True, lines=20)
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sample_pass = gr.State(value=None)
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sample_idx.release(fn=grab_sample, inputs=[sample_idx], outputs=[sample_code, info_md])
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time_slider.release(fn=lambda code, time: asyncio.run(get_image(code, time)), inputs=[sample_code, time_slider], outputs=rendered_frame)
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render_button.click(fn=lambda code: asyncio.run(get_image(code)), inputs=[sample_code], outputs=rendered_frame)
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# run_button.click(fn=print, inputs=[model_cp, sample_idx], outputs=output)
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site.launch()
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requirements.txt
ADDED
@@ -0,0 +1,8 @@
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1 |
+
transformers
|
2 |
+
datasets
|
3 |
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jsonlines
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4 |
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wgpu
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5 |
+
torch
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6 |
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pillow
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7 |
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gradio
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8 |
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numpy
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