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Add missing dtype parameter type annotations
Summary: Add missing dtype parameter type annotations Reviewed By: nikhilaravi Differential Revision: D28943370 fbshipit-source-id: 2a411d78895f3f3aa9ab0e4807c17a13e7f25caf
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@ -137,7 +137,9 @@ def compute_extrinsic_matrix(azimuth, elevation, distance):
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return RT
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return RT
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def read_binvox_coords(f, integer_division=True, dtype=torch.float32):
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def read_binvox_coords(
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f, integer_division: bool = True, dtype: torch.dtype = torch.float32
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):
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"""
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"""
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Copied from meshrcnn codebase:
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Copied from meshrcnn codebase:
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https://github.com/facebookresearch/meshrcnn/blob/master/shapenet/utils/binvox_torch.py#L5
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https://github.com/facebookresearch/meshrcnn/blob/master/shapenet/utils/binvox_torch.py#L5
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@ -462,7 +462,7 @@ def _read_ply_element_ascii(f, definition: _PlyElementType):
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return data
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return data
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def _read_raw_array(f, aim: str, length: int, dtype=np.uint8, dtype_size=1):
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def _read_raw_array(f, aim: str, length: int, dtype: type = np.uint8, dtype_size=1):
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"""
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"""
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Read [length] elements from a file.
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Read [length] elements from a file.
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@ -142,7 +142,7 @@ def sample_points_from_meshes(
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def _rand_barycentric_coords(
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def _rand_barycentric_coords(
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size1, size2, dtype, device
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size1, size2, dtype: torch.dtype, device: torch.device
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) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
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) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
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"""
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"""
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Helper function to generate random barycentric coordinates which are uniformly
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Helper function to generate random barycentric coordinates which are uniformly
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