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kevchengcodeskevchengcodes
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bump coreai-core, coreai-torch, coreai-opt versions (#78)
1 parent 1303957 commit c2a0274

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Lines changed: 77 additions & 74 deletions

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‎models/clap/export.py‎

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# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "coreai-core==1.0.0b1",
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# "coreai-torch==0.4.0",
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# "coreai-core==1.0.0b2",
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# "coreai-torch==0.4.1",
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# "transformers==4.57.3",
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# ]
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#

‎models/clip/export.py‎

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# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "coreai-core==1.0.0b1",
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# "coreai-torch==0.4.0",
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# "coreai-core==1.0.0b2",
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# "coreai-torch==0.4.1",
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# "transformers==4.57.3",
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# ]
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#

‎models/depth-anything/export.py‎

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# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "coreai-core==1.0.0b1",
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# "coreai-torch==0.4.0",
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# "coreai-core==1.0.0b2",
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# "coreai-torch==0.4.1",
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# "depth-anything-3 @ git+https://github.com/ByteDance-Seed/Depth-Anything-3.git",
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# "scipy<1.15",
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# ]

‎models/edsr/export.py‎

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# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "coreai-core==1.0.0b1",
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# "coreai-torch==0.4.0",
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# "coreai-core==1.0.0b2",
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# "coreai-torch==0.4.1",
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# "torchsr",
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# ]
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#

‎models/efficient-sam/export.py‎

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# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "coreai-core==1.0.0b1",
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# "coreai-torch==0.4.0",
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# "coreai-core==1.0.0b2",
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# "coreai-torch==0.4.1",
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# "efficient-sam @ git+https://github.com/yformer/EfficientSAM.git",
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# "torch<=2.11.0"
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# ]
@@ -235,7 +235,7 @@ def main():
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parser.add_argument(
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"--num-pts",
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type=int,
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default=1,
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default=2,
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help=(
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"Number of points per query (P dim of batched_points). Use 1 for a single "
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"point prompt, or 2 with labels [2, 3] for a box prompt (top-left + "

‎models/pvt/export.py‎

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# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "coreai-core==1.0.0b1",
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# "coreai-torch==0.4.0",
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# "coreai-core==1.0.0b2",
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# "coreai-torch==0.4.1",
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# "timm",
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# ]
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#
@@ -27,9 +27,11 @@
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from coreai_torch import TorchConverter, get_decomp_table
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def reference_inputs(dynamic: bool = False) -> dict[str, torch.Tensor]:
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def reference_inputs(
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dynamic: bool = False, dtype: torch.dtype = torch.float32
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) -> dict[str, torch.Tensor]:
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B = 2 if dynamic else 1
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return {"x": torch.randn(B, 3, 224, 224)}
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return {"x": torch.randn(B, 3, 224, 224, dtype=dtype)}
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def dynamic_shapes() -> dict:
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model.to(dtype)
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print("[INFO] Model sourced. Running torch export with decompositions...")
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example_inputs = {k: v.to(dtype) for k, v in reference_inputs(dynamic).items()}
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example_inputs = example_inputs = reference_inputs(dynamic, dtype)
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ds = dynamic_shapes() if dynamic else None
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with torch.autocast(device_type="cpu", dtype=dtype):

‎models/roberta/export.py‎

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# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "coreai-core==1.0.0b1",
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# "coreai-torch==0.4.0",
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# "coreai-core==1.0.0b2",
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# "coreai-torch==0.4.1",
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# "transformers==4.57.3",
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# ]
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#

‎models/sam3/export.py‎

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# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "coreai-core==1.0.0b1",
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# "coreai-torch==0.4.0",
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# "coreai-core==1.0.0b2",
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# "coreai-torch==0.4.1",
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# "tokenizers<0.23.0rc",
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# "torchvision",
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# "transformers>=5.5.4,<5.10.1",

‎models/t5/export.py‎

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# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "coreai-core==1.0.0b1",
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# "coreai-torch==0.4.0",
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# "coreai-core==1.0.0b2",
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# "coreai-torch==0.4.1",
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# "transformers==4.57.3",
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# ]
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#

‎models/wav2vec2/export.py‎

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# /// script
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# requires-python = ">=3.11"
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# dependencies = [
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# "coreai-core==1.0.0b1",
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# "coreai-torch==0.4.0",
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# "coreai-core==1.0.0b2",
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# "coreai-torch==0.4.1",
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# "torchaudio",
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# ]
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#

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