[PrimTorch] Reference for linalg.matrix_norm #81113
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As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. [ghstack-poisoned]
lezcano
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nikitaved and
soulitzer
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This was referenced Jul 8, 2022
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lezcano
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As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. ghstack-source-id: db85492 Pull Request resolved: #81113
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module: linear algebra
As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. [ghstack-poisoned]
lezcano
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Jul 9, 2022
As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. ghstack-source-id: 5898f73 Pull Request resolved: #81113
As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. [ghstack-poisoned]
lezcano
added a commit
that referenced
this pull request
Jul 9, 2022
As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. ghstack-source-id: 49e2ebd Pull Request resolved: #81113
As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. [ghstack-poisoned]
As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. [ghstack-poisoned]
As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. [ghstack-poisoned]
ngimel
approved these changes
Jul 20, 2022
| TORCH_CHECK(A.dim() >= 2, | ||
| "linalg.matrix_norm: input tensor must be a matrix or a batch of matrices"); | ||
| void _linalg_matrix_norm_checks(const Tensor& A, std::vector<int64_t>& dim, optional<ScalarType> opt_dtype, bool low_precision) { | ||
| // A |
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In this function I perform the checks for A, dim and dtype. This is just a comment indicating what are the preconditions in each input, but yeha, I agree that I could've been a bit more verbose :D
As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. [ghstack-poisoned]
As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. [ghstack-poisoned]
facebook-github-bot
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Jul 22, 2022
Summary: As per title. I corrected a thing or two from my previous implementation to make for better errors in some weird edge-cases and have a more clear understanding of when does this function support low_precision types and when it doesn't. We also use the optimisation for bfloat16 within `vector_norm` within this function. Pull Request resolved: #81113 Approved by: https://github.com/ngimel Test Plan: contbuild & OSS CI, see https://hud.pytorch.org/commit/pytorch/pytorch/c5330183ca453d4b0e9d3b4ad46a5adb128eb4b1 Reviewed By: jeanschmidt Differential Revision: D38067128 Pulled By: jeanschmidt fbshipit-source-id: 873d82bafbb33a3257871fc0da0d774b4e9ed8fd
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Stack from ghstack:
As per title. I corrected a thing or two from my previous implementation
to make for better errors in some weird edge-cases and have a more clear
understanding of when does this function support low_precision types and
when it doesn't.
We also use the optimisation for bfloat16 within
vector_normwithinthis function.
cc @jianyuh @nikitaved @pearu @mruberry @walterddr @IvanYashchuk @xwang233 @lezcano @ezyang @ngimel @peterbell10