Mixing
Check if PyTorch tensors are equal within epsilon
How do I check if two PyTorch tensors are semantically equal?
Given floating point errors, I want to know if the the elements differ only by a small epsilon value.
pytorch
asked Nov 19 '18 at 12:44
Tom Hale
6,4413951
add a comment |
How do I check if two PyTorch tensors are semantically equal?
Given floating point errors, I want to know if the the elements differ only by a small epsilon value.
pytorch
asked Nov 19 '18 at 12:44
Tom Hale
6,4413951
add a comment |
How do I check if two PyTorch tensors are semantically equal?
Given floating point errors, I want to know if the the elements differ only by a small epsilon value.
pytorch
asked Nov 19 '18 at 12:44
Tom Hale
6,4413951
How do I check if two PyTorch tensors are semantically equal?
Given floating point errors, I want to know if the the elements differ only by a small epsilon value.
pytorch
pytorch
asked Nov 19 '18 at 12:44
Tom Hale
6,4413951
asked Nov 19 '18 at 12:44
Tom Hale
6,4413951
edited Nov 19 '18 at 13:11
asked Nov 19 '18 at 12:44
Tom Hale
6,4413951
asked Nov 19 '18 at 12:44
Tom Hale
6,4413951
asked Nov 19 '18 at 12:44
Tom Hale
6,4413951
6,4413951
add a comment |
add a comment |
1 Answer
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At the time of writing, this is a undocumented function in the latest stable release (0.4.1), but the documentation is in the master (unstable) branch.
torch.allclose() will return a boolean indicating whether all element-wise differences are equal allowing for a margin of error.
Additionally, there's the undocumented isclose():
>>> torch.isclose(torch.Tensor([1]), torch.Tensor([1.00000001]))
tensor([1], dtype=torch.uint8)
answered Nov 19 '18 at 12:44
Tom Hale
6,4413951
add a comment |
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1 Answer
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active
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votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
At the time of writing, this is a undocumented function in the latest stable release (0.4.1), but the documentation is in the master (unstable) branch.
torch.allclose() will return a boolean indicating whether all element-wise differences are equal allowing for a margin of error.
Additionally, there's the undocumented isclose():
>>> torch.isclose(torch.Tensor([1]), torch.Tensor([1.00000001]))
tensor([1], dtype=torch.uint8)
answered Nov 19 '18 at 12:44
Tom Hale
6,4413951
add a comment |
At the time of writing, this is a undocumented function in the latest stable release (0.4.1), but the documentation is in the master (unstable) branch.
torch.allclose() will return a boolean indicating whether all element-wise differences are equal allowing for a margin of error.
Additionally, there's the undocumented isclose():
>>> torch.isclose(torch.Tensor([1]), torch.Tensor([1.00000001]))
tensor([1], dtype=torch.uint8)
answered Nov 19 '18 at 12:44
Tom Hale
6,4413951
add a comment |
At the time of writing, this is a undocumented function in the latest stable release (0.4.1), but the documentation is in the master (unstable) branch.
torch.allclose() will return a boolean indicating whether all element-wise differences are equal allowing for a margin of error.
Additionally, there's the undocumented isclose():
>>> torch.isclose(torch.Tensor([1]), torch.Tensor([1.00000001]))
tensor([1], dtype=torch.uint8)
answered Nov 19 '18 at 12:44
Tom Hale
6,4413951
At the time of writing, this is a undocumented function in the latest stable release (0.4.1), but the documentation is in the master (unstable) branch.
torch.allclose() will return a boolean indicating whether all element-wise differences are equal allowing for a margin of error.
Additionally, there's the undocumented isclose():
>>> torch.isclose(torch.Tensor([1]), torch.Tensor([1.00000001]))
tensor([1], dtype=torch.uint8)
answered Nov 19 '18 at 12:44
Tom Hale
6,4413951
answered Nov 19 '18 at 12:44
Tom Hale
6,4413951
answered Nov 19 '18 at 12:44
Tom Hale
6,4413951
answered Nov 19 '18 at 12:44
Tom Hale
6,4413951
6,4413951
add a comment |
add a comment |
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