58 lines
1.7 KiB
Python
58 lines
1.7 KiB
Python
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import torch
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import numpy as np
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def compare_tensors(
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a: torch.Tensor,
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b: torch.Tensor,
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tol: float = 1e-6,
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verbose: bool = False
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) -> int:
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"""
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Compare two PyTorch tensors and count the number of elements whose absolute difference
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exceeds the given tolerance.
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Args:
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a (torch.Tensor): The first tensor to compare.
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b (torch.Tensor): The second tensor to compare.
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tol (float, optional): The absolute tolerance threshold. Defaults to 1e-6.
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verbose (bool, optional): If True, print the indices and values of differing elements. Defaults to False.
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Returns:
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int: The number of elements where abs(a - b) > tol.
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Raises:
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ValueError: If the shapes of the input tensors do not match.
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"""
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# Check if tensor shapes are the same
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if a.shape != b.shape:
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raise ValueError(f"Shape mismatch: {a.shape} vs {b.shape}")
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# Create a boolean mask where differences exceed the tolerance
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diff_mask = (a - b).abs() > tol
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# Count the number of differing elements
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diff_count = int(diff_mask.sum().item())
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# If verbose, print details of differing elements
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if verbose and diff_count > 0:
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indices = torch.nonzero(diff_mask, as_tuple=False)
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for idx in indices:
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i, j = idx[0].item(), idx[1].item()
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print(
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f"diff at {i},{j}: "
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f"{a[i, j].item():.6f} - {b[i, j].item():.6f} = "
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f"{(a[i, j] - b[i, j]).item():.6f}"
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)
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return diff_count
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if __name__ == "__main__":
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# example:
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# a = torch.load("/path/to/a.pt")
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# b = torch.load("/path/to/b.pt")
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# diff_count = compare_tensors(a, b)
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# print(f"diff count: {diff_count}")
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pass
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