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* WIP: Stable diffusion WebGPU port * Load whole model: split safetensor to avoid Chrome allocation limit * Gitignore .DS_Store, remove debug print * Clip tokenizer in JS * WIP: Compile model in parts (text model, diffusor, get_x_prev_and_pred_x0, decoder), and recreate forward logic in JS * e2e stable diffusion flow * Create initial random latent tensor in JS * SD working e2e * Log if some weights were not loaded properly * Remove latent_tensor.npy used for debugging * Cleanup, remove useless logs * Improve UI * Add progress bar * Remove .npy files used for debugging * Add clip tokenizer as external dependency * Remove alphas_cumprod.js and load it from safetensors * Refactor * Simplify a lot * Dedup base when limiting elementwise merge (webgpu) * Add return type to safe_load_metadata * Do not allow run when webgpu is not supported * Add progress bar, refactor, fix special names * Add option to chose from local vs huggingface weights * lowercase tinygrad :) * fp16 model dl, decompression client side * Cache f16 model in browser, better progress * Cache miss recovery --------- Co-authored-by: George Hotz <72895+geohot@users.noreply.github.com>
46 lines
657 B
Plaintext
46 lines
657 B
Plaintext
__pycache__
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.venv/
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.vscode
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.DS_Store
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notebooks
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.*.swp
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.*.swo
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*.pyc
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*.so
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*.txt
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build
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/dist
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*.egg-info
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/env
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a.out
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boxes.jpg
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pandecode.dump
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vertex.bin
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recognize*
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.idea
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disassemblers/applegpu
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disassemblers/cuda_ioctl_sniffer
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*.prof
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extra/datasets/cifar-10-python.tar.gz
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extra/datasets/librispeech/
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extra/datasets/imagenet/
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extra/datasets/kits19/
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extra/datasets/squad/
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extra/datasets/img_align_celeba*
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extra/datasets/open-images-v6-mlperf
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extra/datasets/kits/
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extra/datasets/COCO/
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extra/datasets/audio*
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venv
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examples/**/net.*[js,json]
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examples/**/*.safetensors
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node_modules
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package.json
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package-lock.json
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temp
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*.csv
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.coverage
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coverage.xml
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htmlcov
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outputs_yolov8
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