Make torch.randint have default dtype int64 #11040
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ssnl
requested review from
apaszke,
colesbury,
ezyang,
gchanan,
soumith and
zdevito
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|
@pytorchbot retest this please |
gchanan
approved these changes
Sep 7, 2018
test/test_torch.py
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| @@ -2853,6 +2853,25 @@ def test_arange_inference(self): | |||
| torch.tensor(1, dtype=torch.int16)).dtype) | |||
| torch.set_default_dtype(saved_dtype) | |||
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|
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| def test_randint_inference(self): | |||
| saved_dtype = torch.get_default_dtype() | |||
| torch.set_default_dtype(torch.float32) | |||
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| auto size = r.intlist(1); | ||
| auto generator = r.generator(2); | ||
| // NOTE: r.scalartype(X) gives the default dtype if r.isNone(X) | ||
| auto dtype = r.isNone(4) ? at::ScalarType::Long : r.scalartype(4); |
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| auto high = r.toInt64(0); | ||
| auto size = r.intlist(1); | ||
| // NOTE: r.scalartype(X) gives the default dtype if r.isNone(X) | ||
| auto dtype = r.isNone(3) ? at::ScalarType::Long : r.scalartype(3); |
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| auto high = r.toInt64(1); | ||
| auto size = r.intlist(2); | ||
| // NOTE: r.scalartype(X) gives the default dtype if r.isNone(X) | ||
| auto dtype = r.isNone(4) ? at::ScalarType::Long : r.scalartype(4); |
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PenghuiCheng
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Sep 11, 2018
Summary: cc gchanan apaszke Pull Request resolved: pytorch#11040 Differential Revision: D9565728 Pulled By: SsnL fbshipit-source-id: eb5be9609f30c88f52746fa7e13ad71e2856648e
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cc @gchanan @apaszke