triu/tril: complete dtype support for CPU/CUDA. #101414
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/101414
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit a5c05bf: This comment was automatically generated by Dr. CI and updates every 15 minutes. |
nikitaved
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module: cuda
ngimel
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May 15, 2023
ngimel
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May 15, 2023
| @@ -69,8 +69,12 @@ void triu_tril_cuda_template(const Tensor& result, const Tensor& self, int64_t k | |||
| int64_t N = self.numel(); | |||
| dim3 dim_block = cuda::getApplyBlock(); | |||
| dim3 dim_grid((N + dim_block.x - 1) / dim_block.x); | |||
| AT_DISPATCH_ALL_TYPES_AND_COMPLEX_AND3(kComplexHalf, at::ScalarType::Half, at::ScalarType::Bool, | |||
| self.scalar_type(), "triu_tril_cuda_template", [&]{ | |||
| AT_DISPATCH_ALL_TYPES_AND_COMPLEX_AND4( | |||
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btw given that this op only copies elements or sets them to 0, can you dispatch just based on the size of the type?
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jcaip
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May 23, 2023
As per title, we can support full dtype table for these ops. Pull Request resolved: #101414 Approved by: https://github.com/ngimel
This was referenced Mar 29, 2024
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As per title, we can support full dtype table for these ops.
Stack from ghstack (oldest at bottom):
cc @ngimel @jgong5 @mingfeima @XiaobingSuper @sanchitintel @ashokei @jingxu10