mirror of
https://github.com/immich-app/immich.git
synced 2025-07-09 03:04:16 -04:00
upload to hf
This commit is contained in:
mertalev
parent
c57c562166
commit
9958ac9ec9
@ -1,9 +1,10 @@
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from pathlib import Path
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import typer
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from exporters.constants import SOURCE_TO_METADATA, ModelSource
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from exporters.constants import DELETE_PATTERNS, SOURCE_TO_METADATA, ModelSource
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from exporters.onnx import export as onnx_export
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from exporters.rknn import export as rknn_export
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from tenacity import retry, stop_after_attempt
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from typing_extensions import Annotated
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app = typer.Typer(pretty_exceptions_show_locals=False)
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@ -45,7 +46,8 @@ def main(
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hf_organization: str = "immich-app",
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hf_auth_token: Annotated[str | None, typer.Option(envvar="HF_AUTH_TOKEN")] = None,
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):
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hf_model_name = model_name.replace("xlm-roberta-large", "XLM-Roberta-Large")
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hf_model_name = model_name.split("/")[-1]
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hf_model_name = hf_model_name.replace("xlm-roberta-large", "XLM-Roberta-Large")
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hf_model_name = hf_model_name.replace("xlm-roberta-base", "XLM-Roberta-Base")
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output_dir = output_dir / hf_model_name
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match model_source:
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@ -75,22 +77,21 @@ def main(
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from huggingface_hub import create_repo, upload_folder
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repo_id = f"{hf_organization}/{hf_model_name}"
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create_repo(repo_id, exist_ok=True, token=hf_auth_token)
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# glob to delete old UUID blobs when reuploading models
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uuid_char = "[a-fA-F0-9]"
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uuid_glob = (
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uuid_char * 8 + "-" + uuid_char * 4 + "-" + uuid_char * 4 + "-" + uuid_char * 4 + "-" + uuid_char * 12
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)
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@retry(stop=stop_after_attempt(3), wait=2)
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def upload_model():
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create_repo(repo_id, exist_ok=True, token=hf_auth_token)
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upload_folder(
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repo_id=repo_id,
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folder_path=output_dir,
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# remote repo files to be deleted before uploading
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# deletion is in the same commit as the upload, so it's atomic
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delete_patterns=[f"**/{uuid_glob}"],
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delete_patterns=DELETE_PATTERNS,
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token=hf_auth_token,
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)
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upload_model()
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if __name__ == "__main__":
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typer.run(main)
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@ -21,3 +21,34 @@ SOURCE_TO_METADATA = {
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"InsightFace", "https://github.com/deepinsight/insightface/tree/master", "facial recognition"
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),
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}
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RKNN_SOCS = ["rk3566", "rk3576", "rk3588"]
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# the builder hangs when using flash attention with these models
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RKNN_VISUAL_FLASH_ATTENTION_BLACKLIST = {
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"ViT-H-14-378-quickgelu__dfn5b",
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"ViT-L-16-SigLIP-384__webli",
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"ViT-L-16-SigLIP2-384__webli",
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"ViT-L-16-SigLIP2-512__webli",
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"ViT-SO400M-14-SigLIP-384__webli",
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"ViT-SO400M-14-SigLIP2-378__webli",
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"ViT-SO400M-16-SigLIP2-378__webli",
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"ViT-SO400M-16-SigLIP2-512__webli",
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}
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# glob to delete old UUID blobs when reuploading models
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_uuid_char = "[a-fA-F0-9]"
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_uuid_glob = _uuid_char * 8 + "-" + _uuid_char * 4 + "-" + _uuid_char * 4 + "-" + _uuid_char * 4 + "-" + _uuid_char * 12
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DELETE_PATTERNS = [
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"**/*onnx*",
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"**/Constant*",
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"**/*.weight",
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"**/*.bias",
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"**/*.proj",
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"**/*in_proj_bias",
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"**/*.npy",
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"**/*.latent",
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"**/*.pos_embed",
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f"**/{_uuid_glob}",
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]
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@ -38,7 +38,9 @@ def to_onnx(
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_export_text_encoder(model, textual_path, opset_version)
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else:
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print(f"Model {textual_path} already exists, skipping")
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visual_path, _ = openclip_to_onnx(_MCLIP_TO_OPENCLIP[model_name], output_dir_visual, no_cache=no_cache)
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visual_path, _ = openclip_to_onnx(
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_MCLIP_TO_OPENCLIP[model_name], opset_version, output_dir_visual, no_cache=no_cache
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)
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assert visual_path is not None, "Visual model export failed"
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return visual_path, textual_path
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@ -105,13 +105,14 @@ def _export_image_encoder(
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assert isinstance(output, torch.Tensor)
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return output
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model.forward = encode_image
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args = (torch.randn(1, 3, model_cfg.image_size, model_cfg.image_size),)
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traced = torch.jit.trace(encode_image, args) # type: ignore[no-untyped-call]
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", UserWarning)
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torch.onnx.export(
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traced,
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model,
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args,
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output_path.as_posix(),
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input_names=["image"],
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@ -133,13 +134,14 @@ def _export_text_encoder(
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assert isinstance(output, torch.Tensor)
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return output
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model.forward = encode_text
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args = (torch.ones(1, model_cfg.sequence_length, dtype=torch.int32),)
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traced = torch.jit.trace(encode_text, args) # type: ignore[no-untyped-call]
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", UserWarning)
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torch.onnx.export(
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traced,
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model,
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args,
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output_path.as_posix(),
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input_names=["text"],
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@ -1,6 +1,6 @@
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from pathlib import Path
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RKNN_SOCS = ["rk3566", "rk3576", "rk3588"]
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from .constants import RKNN_SOCS, RKNN_VISUAL_FLASH_ATTENTION_BLACKLIST
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def _export_platform(
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@ -22,11 +22,12 @@ def _export_platform(
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rknn = RKNN(verbose=False)
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# flash_attention = model_dir.name != "visual" or model_dir.parent.name not in RKNN_VISUAL_FLASH_ATTENTION_BLACKLIST
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rknn.config(
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target_platform=target_platform,
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dynamic_input=dynamic_input,
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disable_rules=["fuse_matmul_softmax_matmul_to_sdpa"] if not fuse_matmul_softmax_matmul_to_sdpa else [],
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enable_flash_attention=True,
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enable_flash_attention=False,
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model_pruning=True,
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)
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ret = rknn.load_onnx(model=input_path.as_posix())
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@ -49,13 +50,13 @@ def _export_platforms(model_dir: Path, dynamic_input=None, no_cache: bool = Fals
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fuse_matmul_softmax_matmul_to_sdpa = True
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for soc in RKNN_SOCS:
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try:
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_export_platform(model_dir, soc, dynamic_input, fuse_matmul_softmax_matmul_to_sdpa)
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_export_platform(model_dir, soc, dynamic_input, fuse_matmul_softmax_matmul_to_sdpa, no_cache=no_cache)
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except Exception as e:
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print(f"Failed to export model for {soc}: {e}")
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if "inputs or 'outputs' must be set" in str(e):
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print("Retrying without fuse_matmul_softmax_matmul_to_sdpa")
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fuse_matmul_softmax_matmul_to_sdpa = False
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_export_platform(model_dir, soc, dynamic_input, fuse_matmul_softmax_matmul_to_sdpa)
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_export_platform(model_dir, soc, dynamic_input, fuse_matmul_softmax_matmul_to_sdpa, no_cache=no_cache)
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def export(model_dir: Path, no_cache: bool = False):
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@ -1,71 +1,69 @@
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import subprocess
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models = [
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# "ViT-B-16-SigLIP__webli",
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# "ViT-B-16-SigLIP-256__webli",
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# "ViT-B-16-SigLIP-384__webli",
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# "ViT-B-16-SigLIP-512__webli",
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# "ViT-B-16-SigLIP-i18n-256__webli",
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# "ViT-B-16-plus-240__laion400m_e31",
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# "ViT-B-16-plus-240__laion400m_e32",
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# "ViT-B-16__laion400m_e31",
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# "ViT-B-16__laion400m_e32",
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# "ViT-B-16__openai",
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# "ViT-B-32__laion2b-s34b-b79k",
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# "ViT-B-32__laion2b_e16",
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# "ViT-B-32__laion400m_e31",
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# "ViT-B-32__laion400m_e32",
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# "ViT-B-32__openai",
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# "ViT-L-14-336__openai",
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# "ViT-B-16-SigLIP2__webli",
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# "ViT-B-32-SigLIP2-256__webli",
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# "ViT-B-32-SigLIP2-384__webli", # not available yet
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# "ViT-B-32-SigLIP2-512__webli", # not available yet
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# "ViT-L-16-SigLIP2-256__webli",
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# "ViT-L-16-SigLIP2-384__webli", # rknn seems to hang
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# "ViT-L-16-SigLIP2-512__webli",
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"ViT-SO400M-14-SigLIP2__webli",
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"M-CLIP/LABSE-Vit-L-14",
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"M-CLIP/XLM-Roberta-Large-Vit-B-16Plus",
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"M-CLIP/XLM-Roberta-Large-Vit-B-32",
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"M-CLIP/XLM-Roberta-Large-Vit-L-14",
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"RN101__openai",
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"RN101__yfcc15m",
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"RN50__cc12m",
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"RN50__openai",
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"RN50__yfcc15m",
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"RN50x16__openai",
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"RN50x4__openai",
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"RN50x64__openai",
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"ViT-B-16-SigLIP-256__webli",
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"ViT-B-16-SigLIP-384__webli",
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"ViT-B-16-SigLIP-512__webli",
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"ViT-B-16-SigLIP-i18n-256__webli",
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"ViT-B-16-SigLIP2__webli",
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"ViT-B-16-SigLIP__webli",
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"ViT-B-16-plus-240__laion400m_e31",
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"ViT-B-16-plus-240__laion400m_e32",
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"ViT-B-16__laion400m_e31",
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"ViT-B-16__laion400m_e32",
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"ViT-B-16__openai",
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"ViT-B-32-SigLIP2-256__webli",
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"ViT-B-32__laion2b-s34b-b79k",
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"ViT-B-32__laion2b_e16",
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"ViT-B-32__laion400m_e31",
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"ViT-B-32__laion400m_e32",
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"ViT-B-32__openai",
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"ViT-H-14-378-quickgelu__dfn5b",
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"ViT-H-14-quickgelu__dfn5b",
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"ViT-H-14__laion2b-s32b-b79k",
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"ViT-L-14-336__openai",
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"ViT-L-14-quickgelu__dfn2b",
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"ViT-L-14__laion2b-s32b-b82k",
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"ViT-L-14__laion400m_e31",
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"ViT-L-14__laion400m_e32",
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"ViT-L-14__openai",
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"ViT-L-16-SigLIP-256__webli",
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"ViT-L-16-SigLIP-384__webli",
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"ViT-L-16-SigLIP2-256__webli",
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"ViT-L-16-SigLIP2-384__webli",
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"ViT-L-16-SigLIP2-512__webli",
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"ViT-SO400M-14-SigLIP-384__webli",
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"ViT-SO400M-14-SigLIP2-378__webli",
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"ViT-SO400M-14-SigLIP2__webli",
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"ViT-SO400M-16-SigLIP2-256__webli",
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"ViT-SO400M-16-SigLIP2-384__webli",
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"ViT-SO400M-16-SigLIP2-512__webli",
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# "ViT-gopt-16-SigLIP2-256__webli",
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# "ViT-gopt-16-SigLIP2-384__webli",
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# "ViT-L-14-quickgelu__dfn2b",
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# "ViT-L-14__laion2b-s32b-b82k",
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# "ViT-L-14__laion400m_e31",
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# "ViT-L-14__laion400m_e32",
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# "ViT-L-14__openai",
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# "ViT-L-16-SigLIP-256__webli",
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# "ViT-L-16-SigLIP-384__webli",
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# "ViT-SO400M-14-SigLIP-384__webli",
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# "ViT-H-14__laion2b-s32b-b79k",
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# "ViT-H-14-quickgelu__dfn5b",
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# "ViT-H-14-378-quickgelu__dfn5b",
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# "RN101__openai",
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# "RN101__yfcc15m",
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# "RN50__cc12m",
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# "RN50__openai",
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# "RN50__yfcc15m",
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# "RN50x16__openai",
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# "RN50x4__openai",
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# "RN50x64__openai",
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# "nllb-clip-base-siglip__mrl",
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# "nllb-clip-base-siglip__v1",
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# "nllb-clip-large-siglip__mrl",
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# "nllb-clip-large-siglip__v1",
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# "xlm-roberta-base-ViT-B-32__laion5b_s13b_b90k",
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# "xlm-roberta-large-ViT-H-14__frozen_laion5b_s13b_b90k",
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# "M-CLIP/LABSE-Vit-L-14",
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# "M-CLIP/XLM-Roberta-Large-Vit-B-16Plus",
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# "M-CLIP/XLM-Roberta-Large-Vit-B-32",
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# "M-CLIP/XLM-Roberta-Large-Vit-L-14",
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"ViT-gopt-16-SigLIP2-256__webli",
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"ViT-gopt-16-SigLIP2-384__webli",
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"nllb-clip-base-siglip__mrl",
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"nllb-clip-base-siglip__v1",
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"nllb-clip-large-siglip__mrl",
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"nllb-clip-large-siglip__v1",
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"xlm-roberta-base-ViT-B-32__laion5b_s13b_b90k",
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"xlm-roberta-large-ViT-H-14__frozen_laion5b_s13b_b90k",
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]
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if __name__ == "__main__":
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for model in models:
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try:
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print(f"Exporting model {model}")
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subprocess.check_call(["python", "export.py", model, "openclip"])
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subprocess.check_call(["python", "export.py", model, "mclip" if "M-CLIP" in model else "openclip"])
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except Exception as e:
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print(f"Failed to export model {model}: {e}")
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@ -13,6 +13,7 @@ dependencies = [
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"typer>=0.15.2",
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"rknn-toolkit2>=2.3.0",
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"transformers>=4.49.0",
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"tenacity>=9.0.0",
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]
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[tool.uv]
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11
machine-learning/export/uv.lock
generated
11
machine-learning/export/uv.lock
generated
@ -231,6 +231,7 @@ dependencies = [
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{ name = "onnxruntime" },
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{ name = "open-clip-torch" },
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{ name = "rknn-toolkit2" },
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{ name = "tenacity" },
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{ name = "transformers" },
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{ name = "typer" },
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]
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@ -243,6 +244,7 @@ requires-dist = [
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{ name = "onnxruntime", specifier = ">=1.16.0" },
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{ name = "open-clip-torch", specifier = ">=2.31.0" },
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{ name = "rknn-toolkit2", specifier = ">=2.3.0" },
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{ name = "tenacity", specifier = ">=9.0.0" },
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{ name = "transformers", specifier = ">=4.49.0" },
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{ name = "typer", specifier = ">=0.15.2" },
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]
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@ -971,6 +973,15 @@ wheels = [
|
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{ url = "https://files.pythonhosted.org/packages/b2/fe/81695a1aa331a842b582453b605175f419fe8540355886031328089d840a/sympy-1.13.1-py3-none-any.whl", hash = "sha256:db36cdc64bf61b9b24578b6f7bab1ecdd2452cf008f34faa33776680c26d66f8", size = 6189177 },
|
||||
]
|
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[[package]]
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name = "tenacity"
|
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version = "9.0.0"
|
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source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/cd/94/91fccdb4b8110642462e653d5dcb27e7b674742ad68efd146367da7bdb10/tenacity-9.0.0.tar.gz", hash = "sha256:807f37ca97d62aa361264d497b0e31e92b8027044942bfa756160d908320d73b", size = 47421 }
|
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wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/b6/cb/b86984bed139586d01532a587464b5805f12e397594f19f931c4c2fbfa61/tenacity-9.0.0-py3-none-any.whl", hash = "sha256:93de0c98785b27fcf659856aa9f54bfbd399e29969b0621bc7f762bd441b4539", size = 28169 },
|
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]
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[[package]]
|
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name = "timm"
|
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version = "1.0.15"
|
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|
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