[fix] check for histogramdd when bins is int[] #100624
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| const int64_t bin_size = bin_ct.size(); | ||
| TORCH_CHECK( | ||
| N == bin_size, | ||
| "histogramdd: The size of bins must be equal to the innermost dimension of the input."); | ||
| for (const auto dim : c10::irange(N)) { | ||
| linspace_out(outer_bin_edges.first[dim], outer_bin_edges.second[dim], | ||
| bin_ct[dim] + 1, bin_edges_out[dim]); |
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We'd end up reading garbage value for bin_ct[dim] for dim > bin_size.
import torch
# invalid bins
bins = [1, 1, 1, 1, 1]
# Valid bins, all asserts pass.
# bins = [1, 1, 1, 1, 1, 1]
def fn(input):
return torch.histogramdd(input, bins)
x = torch.rand([5, 6], dtype=torch.float32)
# For invalid bins, consecutive call return incorrect output (with different shapes)
o1 = fn(x)
o2 = fn(x)
for o_, oo_ in zip(o1, o2):
# AssertionError: The values for attribute 'shape' do not match: torch.Size([1, 1, 1, 1, 1, 273]) != torch.Size([1, 1, 1, 1, 1, 33]).
torch.testing.assert_close(o_, oo_)
| # Not implemented on CUDA | ||
| DecorateInfo(unittest.expectedFailure, 'TestCommon', 'test_errors', device_type='cuda'), |
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Let's add it for the cuda path now that we're at it.
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This operator is not implemented for CUDA.
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That's a bug in the implementation of test_errors then I guess. That's fine.
It doesn't (tried grepping). Also, inductor falls back on the eager implementation. pytorch/torch/_inductor/lowering.py Lines 1556 to 1557 in aa081d8 |
| # Not implemented on CUDA | ||
| DecorateInfo(unittest.expectedFailure, 'TestCommon', 'test_errors', device_type='cuda'), |
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That's a bug in the implementation of test_errors then I guess. That's fine.
|
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Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Fixes pytorch#93274 Pull Request resolved: pytorch#100624 Approved by: https://github.com/lezcano
Fixes #93274