Spaces:
Running
Running
feat: log to backend
Browse files- dev/inference/samples.csv +102 -0
- dev/inference/wandb-backend.ipynb +353 -0
dev/inference/samples.csv
ADDED
@@ -0,0 +1,102 @@
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Caption,Theme
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a cat seats on top of an alligator,Animals
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a dog eating worthlessness,Animals
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a dog playing with a ball,Animals
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a rat holding a red lightsable in a white background,Animals
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A unicorn is passing by a rainbow in a field of flowers,Animals
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an elephant made of carrots,Animals
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an elephant on a unicycle during a circus,Animals
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photography of a penguin watching television,Animals
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rat wearing a crown,Animals
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"a background consisting of colors blue, green, and red.",Art
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a colorful stairway to heaven,Art
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a graphite sketch of a gothic cathedral,Art
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a portrait of a nightmare creature watching at you,Art
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a white room full of a black substance,Art
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epic sword fight,Art
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"happy, happiness",Art
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painting of an oniric forest glade surrounded by tall trees,Art
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real painting of an alien from Monet,Art
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robots taking control over humans,Art
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"sad, sadness",Art
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still life in the style of Kandinsky,Art
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still life in the style of Picasso,Art
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the representation of infinity,Art
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a cute avocado armchair singing karaoke on stage in front of a crowd of strawberry shaped lamps,Avocado
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an armchair in the shape of an avocado,Avocado
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an avocado armchair,Avocado
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an avocado armchair flying into space,Avocado
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an illustration of an avocado in a christmas sweater staring at its reflection in a mirror,Avocado
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illustration of an avocado armchair,Avocado
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illustration of an avocado armchair getting married to a pineapple,Avocado
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logo of an avocado armchair,Avocado
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watercolor of the Eiffel tower on the moon,Avocado
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a cute pikachu teapot,Culture
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a picture of a castle from minecraft,Culture
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an illustration of pikachu seating on a bench,Culture
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mario eating an avocado while walking his baby koala,Culture
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star wars concept art,Culture
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a cartoon of a superhero bear,Illustrations
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an illustration of a cute skeleton wearing a blue hoodie,Illustrations
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Cartoon of a carrot with big eyes,Illustrations
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illustration of a baby shark swimming around corals,Illustrations
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logo of a robot wearing glasses and reading a book,Illustrations
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a beautiful sunset at a beach with a shell on the shore,Landscape
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a farmhouse surrounded by beautiful flowers,Landscape
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a photo of a fantasy version of New York City,Landscape
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a picture of fantasy kingdoms,Landscape
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a volcano erupting in the middle of New York city,Landscape
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aerial view of the beach at night,Landscape
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aerial view of the beach during daytime,Landscape
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big wave destroying a city,Landscape
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"London in a far future, futuristic London",Landscape
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sunset over green mountains,Landscape
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the last sunrise on earth,Landscape
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underwater cathedral,Landscape
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white snow covered mountain under blue sky during daytime,Landscape
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a bottle of coca-cola on a table,Objects
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a cactus lifitng weights,Objects
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a living room with two white armchairs and a painting of the collosseum. The painting is mounted above a modern fireplace.,Objects
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a long line of alternating green and red blocks,Objects
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a long line of green blocks on a beach at subset,Objects
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a long line of peaches on a beach at sunset,Objects
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a peanut,Objects
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a photo of a camera from the future,Objects
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a restaurant menu,Objects
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a skeleton with the shape of a spider,Objects
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"looking into the sky, 10 airplanes are seen overhead",Objects
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sheves filled with books and archemy potion bottles,Objects
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the communist statue of liberty,Objects
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this is a detailed high-resolution scan of a human brain,Objects
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a collection of glasses is sitting on a table,OpenAI
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a cross-section view of a walnut,OpenAI
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a painting of a capybara sitting on a mountain during fall in surrealist style,OpenAI
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a pentagonal green clock,OpenAI
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a photo of san francisco golden gate bridge,OpenAI
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a pixel art illustration of an eagle sitting in a field in the afternoon,OpenAI
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a professional high-quality emoji of a lovestruck cup of boba,OpenAI
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a small red block sitting on a large green block,OpenAI
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a storefront that has the word 'openai' written on it,OpenAI
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a tatoo of a black broccoli,OpenAI
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a variety of clocks is sitting on a table,OpenAI
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"an emoji of a baby fox wearing a blue hat, blue gloves, red shirt, and red pants",OpenAI
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"an emoji of a baby penguin wearing a blue hat, blue gloves, red shirt, and green pants",OpenAI
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an extreme close-up view of a capybara sitting in a field,OpenAI
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an illustration of a baby cucumber with a mustache playing chess,OpenAI
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an illustration of a baby daikon radish in a tutu walking a dog,OpenAI
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an illustration of a baby hedgehog in a cape staring at its reflection in a mirror,OpenAI
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an illustration of a baby panda with headphones holding an umbrella in the rain,OpenAI
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an illustration of an avocado in a beanie riding a motorcycle,OpenAI
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urinals are lined up in a jungle,OpenAI
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a human face,People
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"a person is holding a phone and a waterbottle, running a marathon.",People
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a photograph of Ellen G. White,People
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Mohammed Ali and Mike Tyson in a hypothetical match,People
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Pele and Maradona in a hypothetical match,People
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Young woman riding her bike through the forest,People
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a clown wearing a spacesuit floating in space,Space
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a photo of the French flag on the planet Saturn,Space
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a picture of the eiffel tower on the moon,Space
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illustration of an astronaut in a space suit playing guitar,Space
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the moon is a skull,Space
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view of mars from space,Space
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dev/inference/wandb-backend.ipynb
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@@ -0,0 +1,353 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4ff2a984-b8b2-4a69-89cf-0d16da2393c8",
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"metadata": {},
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"outputs": [],
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"source": [
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"import csv\n",
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"import tempfile\n",
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"import wandb\n",
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"from dalle_mini.model import CustomFlaxBartForConditionalGeneration\n",
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"from vqgan_jax.modeling_flax_vqgan import VQModel\n",
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"from transformers import BartTokenizer, CLIPProcessor, FlaxCLIPModel\n",
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"from dalle_mini.text import TextNormalizer"
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]
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},
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{
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"cell_type": "code",
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21 |
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"execution_count": null,
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"id": "92f4557c-fd7f-4edc-81c2-de0b0a10c270",
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"metadata": {},
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"outputs": [],
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"source": [
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"wandb_runs = ['rjf3rycy']\n",
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"VQGAN_REPO, VQGAN_COMMIT_ID = 'dalle-mini/vqgan_imagenet_f16_16384', None\n",
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"normalize_text = True"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c6a878fa-4bf5-4978-abb5-e235841d765b",
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"metadata": {},
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"outputs": [],
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"source": [
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"vqgan = VQModel.from_pretrained(VQGAN_REPO, revision=VQGAN_COMMIT_ID)\n",
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"clip = FlaxCLIPModel.from_pretrained(\"openai/clip-vit-base-patch32\")\n",
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"processor = CLIPProcessor.from_pretrained(\"openai/clip-vit-base-patch32\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e57797ab-0b3a-4490-be58-03d8d1c23fe9",
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"metadata": {},
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"outputs": [],
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"source": [
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"with open('samples.csv', newline='', encoding='utf8') as f:\n",
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" reader = csv.reader(f)\n",
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" for row in reader:\n",
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" breakpoint()"
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]
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},
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{
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"cell_type": "code",
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58 |
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"execution_count": null,
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"id": "3ffb1d09-bd1c-4f57-9ae5-3eda6f7d3a08",
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"metadata": {},
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"outputs": [],
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"source": [
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"wandb_run = wandb_runs[0]\n",
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"api = wandb.Api()"
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]
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},
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{
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68 |
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"cell_type": "code",
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69 |
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"execution_count": null,
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70 |
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"id": "f3e02d9d-4ee1-49e7-a7bc-4d8b139e9614",
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"metadata": {},
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"outputs": [],
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"source": [
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"try:\n",
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" versions = api.artifact_versions(type_name='bart_model', name=f'dalle-mini/dalle-mini/model-{wandb_run}', per_page=10000)\n",
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"except:\n",
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" versions = []"
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]
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},
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{
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"cell_type": "code",
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82 |
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"execution_count": null,
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"id": "e8026e63-9e73-472c-9440-5e742c614901",
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"metadata": {},
|
85 |
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"outputs": [],
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"source": [
|
87 |
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"versions, len(versions)"
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88 |
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]
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},
|
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{
|
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"cell_type": "code",
|
92 |
+
"execution_count": null,
|
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"id": "29613a9d-de7e-44e3-94f1-650085039204",
|
94 |
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"metadata": {},
|
95 |
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"outputs": [],
|
96 |
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"source": [
|
97 |
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"versions = sorted(versions, key=lambda x: int(x.version[1:]))"
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98 |
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]
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},
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{
|
101 |
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"cell_type": "code",
|
102 |
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"execution_count": null,
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"id": "d77159df-1a16-4996-aafd-1df82c5a3509",
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"metadata": {},
|
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"outputs": [],
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"source": [
|
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"versions"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "cfd48de9-6022-444f-8b12-05cba8fad071",
|
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"metadata": {},
|
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"outputs": [],
|
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"source": [
|
117 |
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"artifact = versions[0]"
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]
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},
|
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{
|
121 |
+
"cell_type": "code",
|
122 |
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"execution_count": null,
|
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"id": "4db848c1-2bb5-432c-a732-1c6d0636e172",
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"metadata": {},
|
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"outputs": [],
|
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"source": [
|
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"version = int(artifact.version[1:])"
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]
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},
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{
|
131 |
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"cell_type": "code",
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132 |
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"execution_count": null,
|
133 |
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"id": "25fac577-146d-4e62-a3ea-f0baea79ef83",
|
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"metadata": {},
|
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"outputs": [],
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"source": [
|
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"version"
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]
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},
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{
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141 |
+
"cell_type": "code",
|
142 |
+
"execution_count": null,
|
143 |
+
"id": "f0d7ed17-7abb-4a31-ab3c-a12b9039a570",
|
144 |
+
"metadata": {},
|
145 |
+
"outputs": [],
|
146 |
+
"source": [
|
147 |
+
"# retrieve training run\n",
|
148 |
+
"training_run = api.run(f'dalle-mini/dalle-mini/{wandb_run}')\n",
|
149 |
+
"config = training_run.config"
|
150 |
+
]
|
151 |
+
},
|
152 |
+
{
|
153 |
+
"cell_type": "code",
|
154 |
+
"execution_count": null,
|
155 |
+
"id": "9b9393c6-0a3c-46a8-ba27-ba37982b0009",
|
156 |
+
"metadata": {},
|
157 |
+
"outputs": [],
|
158 |
+
"source": [
|
159 |
+
"# see summary metrics\n",
|
160 |
+
"training_run.summary"
|
161 |
+
]
|
162 |
+
},
|
163 |
+
{
|
164 |
+
"cell_type": "code",
|
165 |
+
"execution_count": null,
|
166 |
+
"id": "7e784a43-626d-4e8d-9e47-a23775b2f35f",
|
167 |
+
"metadata": {},
|
168 |
+
"outputs": [],
|
169 |
+
"source": [
|
170 |
+
"# retrieve inference run details\n",
|
171 |
+
"def get_last_version_inference(run_id):\n",
|
172 |
+
" try:\n",
|
173 |
+
" inference_run = api.run(f'dalle-mini/dalle-mini/inference-{run_id}')\n",
|
174 |
+
" return inference_run.summary.get('_step', None)\n",
|
175 |
+
" except:\n",
|
176 |
+
" return None"
|
177 |
+
]
|
178 |
+
},
|
179 |
+
{
|
180 |
+
"cell_type": "code",
|
181 |
+
"execution_count": null,
|
182 |
+
"id": "93b8d869-1658-4fa4-a401-2b91f8ac7a11",
|
183 |
+
"metadata": {},
|
184 |
+
"outputs": [],
|
185 |
+
"source": [
|
186 |
+
"last_version_inference = get_last_version_inference(wandb_run)"
|
187 |
+
]
|
188 |
+
},
|
189 |
+
{
|
190 |
+
"cell_type": "code",
|
191 |
+
"execution_count": null,
|
192 |
+
"id": "8324835e-fd94-408e-b106-138be308480b",
|
193 |
+
"metadata": {},
|
194 |
+
"outputs": [],
|
195 |
+
"source": [
|
196 |
+
"if last_version_inference is None:\n",
|
197 |
+
" assert version == 0\n",
|
198 |
+
"else:\n",
|
199 |
+
" assert version == last_version_inference + 1"
|
200 |
+
]
|
201 |
+
},
|
202 |
+
{
|
203 |
+
"cell_type": "code",
|
204 |
+
"execution_count": null,
|
205 |
+
"id": "8ce9d2d3-aea3-4d5e-834a-c5caf85dd117",
|
206 |
+
"metadata": {},
|
207 |
+
"outputs": [],
|
208 |
+
"source": [
|
209 |
+
"run = wandb.init(job_type='inference', config=config, id=f'inference-{wandb_run}', resume='allow')"
|
210 |
+
]
|
211 |
+
},
|
212 |
+
{
|
213 |
+
"cell_type": "code",
|
214 |
+
"execution_count": null,
|
215 |
+
"id": "ffe392c9-36d2-4aaa-a1b3-a827e348c1ef",
|
216 |
+
"metadata": {},
|
217 |
+
"outputs": [],
|
218 |
+
"source": [
|
219 |
+
"tmp_f.cleanup\n",
|
220 |
+
"tmp_f = tempfile.TemporaryDirectory()\n",
|
221 |
+
"tmp = tmp_f.name\n",
|
222 |
+
"#TODO: use context manager"
|
223 |
+
]
|
224 |
+
},
|
225 |
+
{
|
226 |
+
"cell_type": "code",
|
227 |
+
"execution_count": null,
|
228 |
+
"id": "562036ed-dc86-48af-90b1-9c18383b3552",
|
229 |
+
"metadata": {},
|
230 |
+
"outputs": [],
|
231 |
+
"source": [
|
232 |
+
"# remove tmp\n",
|
233 |
+
"tmp_f.cleanup()"
|
234 |
+
]
|
235 |
+
},
|
236 |
+
{
|
237 |
+
"cell_type": "code",
|
238 |
+
"execution_count": null,
|
239 |
+
"id": "299db1bb-fbe6-4d79-a48f-89893f8ed809",
|
240 |
+
"metadata": {},
|
241 |
+
"outputs": [],
|
242 |
+
"source": [
|
243 |
+
"artifact = run.use_artifact(artifact)"
|
244 |
+
]
|
245 |
+
},
|
246 |
+
{
|
247 |
+
"cell_type": "code",
|
248 |
+
"execution_count": null,
|
249 |
+
"id": "d71481bf-98aa-42cb-b7e2-545d13ae4309",
|
250 |
+
"metadata": {},
|
251 |
+
"outputs": [],
|
252 |
+
"source": [
|
253 |
+
"# only download required files\n",
|
254 |
+
"for f in ['config.json', 'flax_model.msgpack', 'merges.txt', 'special_tokens_map.json', 'tokenizer.json', 'tokenizer_config.json', 'vocab.json']:\n",
|
255 |
+
" artifact.get_path(f).download(tmp)"
|
256 |
+
]
|
257 |
+
},
|
258 |
+
{
|
259 |
+
"cell_type": "code",
|
260 |
+
"execution_count": null,
|
261 |
+
"id": "6f8ad8dd-da8f-40f9-b438-e43b779d637c",
|
262 |
+
"metadata": {},
|
263 |
+
"outputs": [],
|
264 |
+
"source": [
|
265 |
+
"# we verify all the files are present\n",
|
266 |
+
"from pathlib import Path\n",
|
267 |
+
"list(Path(tmp).glob('*'))"
|
268 |
+
]
|
269 |
+
},
|
270 |
+
{
|
271 |
+
"cell_type": "code",
|
272 |
+
"execution_count": null,
|
273 |
+
"id": "5b715c32-e757-4cb0-9912-ff90238b9f10",
|
274 |
+
"metadata": {},
|
275 |
+
"outputs": [],
|
276 |
+
"source": [
|
277 |
+
"tokenizer = BartTokenizer.from_pretrained(tmp)\n",
|
278 |
+
"model = CustomFlaxBartForConditionalGeneration.from_pretrained(tmp)"
|
279 |
+
]
|
280 |
+
},
|
281 |
+
{
|
282 |
+
"cell_type": "code",
|
283 |
+
"execution_count": null,
|
284 |
+
"id": "d1cc9993-1bfc-4ec6-a004-c056189c42ac",
|
285 |
+
"metadata": {},
|
286 |
+
"outputs": [],
|
287 |
+
"source": []
|
288 |
+
},
|
289 |
+
{
|
290 |
+
"cell_type": "code",
|
291 |
+
"execution_count": null,
|
292 |
+
"id": "43d2a99b-3501-4b30-b041-0fdeead12380",
|
293 |
+
"metadata": {},
|
294 |
+
"outputs": [],
|
295 |
+
"source": []
|
296 |
+
},
|
297 |
+
{
|
298 |
+
"cell_type": "code",
|
299 |
+
"execution_count": null,
|
300 |
+
"id": "06472541-75f1-44e5-841f-a4a26a0493e3",
|
301 |
+
"metadata": {},
|
302 |
+
"outputs": [],
|
303 |
+
"source": []
|
304 |
+
},
|
305 |
+
{
|
306 |
+
"cell_type": "code",
|
307 |
+
"execution_count": null,
|
308 |
+
"id": "7a24b903-777b-4e3d-817c-00ed613a7021",
|
309 |
+
"metadata": {},
|
310 |
+
"outputs": [],
|
311 |
+
"source": []
|
312 |
+
},
|
313 |
+
{
|
314 |
+
"cell_type": "code",
|
315 |
+
"execution_count": null,
|
316 |
+
"id": "e1c04761-1016-47e9-925c-3a9ec6fec95a",
|
317 |
+
"metadata": {},
|
318 |
+
"outputs": [],
|
319 |
+
"source": [
|
320 |
+
"wandb.finish()"
|
321 |
+
]
|
322 |
+
},
|
323 |
+
{
|
324 |
+
"cell_type": "code",
|
325 |
+
"execution_count": null,
|
326 |
+
"id": "b37c1714-d54b-479e-a9e8-740affc0de2c",
|
327 |
+
"metadata": {},
|
328 |
+
"outputs": [],
|
329 |
+
"source": []
|
330 |
+
}
|
331 |
+
],
|
332 |
+
"metadata": {
|
333 |
+
"kernelspec": {
|
334 |
+
"display_name": "Python 3 (ipykernel)",
|
335 |
+
"language": "python",
|
336 |
+
"name": "python3"
|
337 |
+
},
|
338 |
+
"language_info": {
|
339 |
+
"codemirror_mode": {
|
340 |
+
"name": "ipython",
|
341 |
+
"version": 3
|
342 |
+
},
|
343 |
+
"file_extension": ".py",
|
344 |
+
"mimetype": "text/x-python",
|
345 |
+
"name": "python",
|
346 |
+
"nbconvert_exporter": "python",
|
347 |
+
"pygments_lexer": "ipython3",
|
348 |
+
"version": "3.9.7"
|
349 |
+
}
|
350 |
+
},
|
351 |
+
"nbformat": 4,
|
352 |
+
"nbformat_minor": 5
|
353 |
+
}
|