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enable type check common_distributed (#44821)

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Summary:
Enabled type checking in common_distributed by using tensors of ints

Pull Request resolved: https://github.com/pytorch/pytorch/pull/44821

Test Plan: Run python test/test_type_hints.py, errors are no longer ingnored by mypy.ini

Reviewed By: walterddr

Differential Revision: D23747466

Pulled By: alanadakotashine

fbshipit-source-id: 820fd502d7ff715728470fbef0be90ae7f128dd6
This commit is contained in:
alanashine 2020-09-16 19:16:43 -07:00 committed by Facebook GitHub Bot
parent e48201c5cf
commit ba6534ae2b
2 changed files with 2 additions and 5 deletions
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3
mypy.ini
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@ -65,9 +65,6 @@ ignore_errors = True
[mypy-torch.testing._internal.common_quantized.*]
ignore_errors = True
[mypy-torch.testing._internal.common_distributed.*]
ignore_errors = True
[mypy-torch.testing._internal.jit_utils.*]
ignore_errors = True

4
torch/testing/_internal/common_distributed.py
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@ -161,10 +161,10 @@ def simple_sparse_reduce_tests(rank, world_size, num_inputs=1):
# First sparse dimension is [0..rank].
# Subsequent dimensions are always 0, so we know there is
# a non-empty intersection between any two sparse tensors.
indices = [range(rank + 1)]
indices = torch.reshape(torch.arange(rank + 1), (1, rank + 1))
shape = [world_size] + [2 for _ in range(dense_dims)]
for _ in range(sparse_dims - 1):
indices.append([0] * (rank + 1))
indices = torch.cat((indices, torch.zeros(1, rank + 1)))
shape.append(world_size)
values = torch.ones([rank + 1] + [2 for _ in range(dense_dims)])
return torch.sparse_coo_tensor(indices, values, shape)