{"action":"created","comment":{"url":"https://api.github.com/repos/pytorch/pytorch/pulls/comments/208399024","pull_request_review_id":144194717,"id":208399024,"node_id":"MDI0OlB1bGxSZXF1ZXN0UmV2aWV3Q29tbWVudDIwODM5OTAyNA==","diff_hunk":"@@ -0,0 +1,126 @@\n+#pragma once\n+\n+#include <cuda.h>\n+#include <limits.h>\n+#include <assert.h>\n+#include <typeinfo>\n+\n+// CUDANumerics.cuh contains mathematical functions that are either\n+// not in the std namespace or are specialized for compilation\n+// with CUDA NVCC or CUDA NVRTC. This header is derived from the\n+// legacy THCNumerics.cuh.\n+\n+namespace at{\n+\n+template <typename T>\n+struct numerics {\n+};\n+\n+template <typename scalar_t>\n+static inline __host__ __device__ scalar_t powi(scalar_t a, scalar_t b) {","path":"aten/src/ATen/cuda/CUDANumerics.cuh","position":20,"original_position":20,"commit_id":"b2b66c7c966debee5ffeefd76117a42526252ea6","original_commit_id":"b2b66c7c966debee5ffeefd76117a42526252ea6","user":{"login":"colesbury","id":655866,"node_id":"MDQ6VXNlcjY1NTg2Ng==","avatar_url":"https://avatars1.githubusercontent.com/u/655866?v=4","gravatar_id":"","url":"https://api.github.com/users/colesbury","html_url":"https://github.com/colesbury","followers_url":"https://api.github.com/users/colesbury/followers","following_url":"https://api.github.com/users/colesbury/following{/other_user}","gists_url":"https://api.github.com/users/colesbury/gists{/gist_id}","starred_url":"https://api.github.com/users/colesbury/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/colesbury/subscriptions","organizations_url":"https://api.github.com/users/colesbury/orgs","repos_url":"https://api.github.com/users/colesbury/repos","events_url":"https://api.github.com/users/colesbury/events{/privacy}","received_events_url":"https://api.github.com/users/colesbury/received_events","type":"User","site_admin":false},"body":"I'm not convinced that the usefulness of square and multiply merits putting it in a generic file like this. The std::pow overloads work with integers. If there's a kernel that requires square-and-multiply, we should move this there.","created_at":"2018-08-07T21:58:58Z","updated_at":"2018-08-07T21:59:01Z","html_url":"https://github.com/pytorch/pytorch/pull/10301#discussion_r208399024","pull_request_url":"https://api.github.com/repos/pytorch/pytorch/pulls/10301","author_association":"MEMBER","_links":{"self":{"href":"https://api.github.com/repos/pytorch/pytorch/pulls/comments/208399024"},"html":{"href":"https://github.com/pytorch/pytorch/pull/10301#discussion_r208399024"},"pull_request":{"href":"https://api.github.com/repos/pytorch/pytorch/pulls/10301"}}},"pull_request":{"url":"https://api.github.com/repos/pytorch/pytorch/pulls/10301","id":206722910,"node_id":"MDExOlB1bGxSZXF1ZXN0MjA2NzIyOTEw","html_url":"https://github.com/pytorch/pytorch/pull/10301","diff_url":"https://github.com/pytorch/pytorch/pull/10301.diff","patch_url":"https://github.com/pytorch/pytorch/pull/10301.patch","issue_url":"https://api.github.com/repos/pytorch/pytorch/issues/10301","number":10301,"state":"open","locked":false,"title":"Refactor THCNumerics and add common math functions for at::Half","user":{"login":"syed-ahmed","id":8906225,"node_id":"MDQ6VXNlcjg5MDYyMjU=","avatar_url":"https://avatars1.githubusercontent.com/u/8906225?v=4","gravatar_id":"","url":"https://api.github.com/users/syed-ahmed","html_url":"https://github.com/syed-ahmed","followers_url":"https://api.github.com/users/syed-ahmed/followers","following_url":"https://api.github.com/users/syed-ahmed/following{/other_user}","gists_url":"https://api.github.com/users/syed-ahmed/gists{/gist_id}","starred_url":"https://api.github.com/users/syed-ahmed/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/syed-ahmed/subscriptions","organizations_url":"https://api.github.com/users/syed-ahmed/orgs","repos_url":"https://api.github.com/users/syed-ahmed/repos","events_url":"https://api.github.com/users/syed-ahmed/events{/privacy}","received_events_url":"https://api.github.com/users/syed-ahmed/received_events","type":"User","site_admin":false},"body":"**Summary**: This PR is a followup of @mruberry's https://github.com/pytorch/pytorch/pull/9318/. It tries to achieve the following:\r\n- Specializing std common math functions for `at::Half` type.\r\n- Create `CUDANumerics.cuh` to contain necessary parts from `THCNumerics.cuh`.\r\n- Update `THCNumerics.cuh` with new usage and comments to  demonstrate the best practice for developers and hence, making way for its deprecation.\r\n- Remove legacy/redundant code path.\r\n- Remove unused CUDA HALF macros (see separate PR https://github.com/pytorch/pytorch/pull/10147)\r\n\r\n**Comments**: `CUDANumerics.cuh` contains mathematical functions that are either not in the std namespace or are specialized for compilation with CUDA NVCC or CUDA NVRTC. This header is derived from the legacy `THCNumerics.cuh`. Following are some rationale behind why some functions were kept while others were removed:\r\n- All arithmetic can now be done in ATen using binary cuda kernel  or CUDA tensor pointwise apply (check https://github.com/pytorch/pytorch/pull/8919 and `CUDAApplyUtils`). `at::Half` comparisons rely on implicit conversion to float.\r\n- Functions that are c/c++ standard compliant, have been specialized for user defined types, for instance, the std namespace has been opened up for `at::Half`, that defines math function definitions for `at::Half`. Check `Half-inl.h`\r\n- Some standard compliant functions are specialized here for performance reasons. For instance, `powi` is used for `pow` calculation on integral types. Moreover, `abs`, `isinf`, `isnan` are specialized to save one API call vs when used with std. Although this is subject to change, depending on if we really care about saving one API call.\r\n- Numeric limits such as `max/min` is removed since they call standard defines. Moreover, numeric limits for\r\n`at::Half` is present in `Half-inl.h`. I understood that HIP has some issue with `std::numeric_limits` and this the related github issue I found: https://github.com/ROCm-Developer-Tools/HIP/issues/374. @AlexVlx mentions that the issue can be avoided by launching `std::numeric_limits` in `__device__`. Since, we are launching lambdas with device contexts, I don't see an issue why `std::numeric_limits` won't compile on HIP if launched with device context within a kernel, unless I am not aware of the real reason why max/min was there in THCNumerics in the first place. (Haven't ever tried a build with HIP).\r\n\r\nHere are some reference PRs that was handy in refactoring TH into ATen:\r\n- https://github.com/pytorch/pytorch/pull/6786\r\n- https://github.com/pytorch/pytorch/pull/5475\r\n- https://github.com/pytorch/pytorch/pull/9401\r\n- https://github.com/pytorch/pytorch/pull/8689\r\n- https://github.com/pytorch/pytorch/pull/8919","created_at":"2018-08-07T14:43:21Z","updated_at":"2018-08-07T21:59:01Z","closed_at":null,"merged_at":null,"merge_commit_sha":"8c606bb71269f5169e7f78c11d1443dd072c03f9","assignee":null,"assignees":[],"requested_reviewers":[{"login":"zdevito","id":370202,"node_id":"MDQ6VXNlcjM3MDIwMg==","avatar_url":"https://avatars0.githubusercontent.com/u/370202?v=4","gravatar_id":"","url":"https://api.github.com/users/zdevito","html_url":"https://github.com/zdevito","followers_url":"https://api.github.com/users/zdevito/followers","following_url":"https://api.github.com/users/zdevito/following{/other_user}","gists_url":"https://api.github.com/users/zdevito/gists{/gist_id}","starred_url":"https://api.github.com/users/zdevito/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/zdevito/subscriptions","organizations_url":"https://api.github.com/users/zdevito/orgs","repos_url":"https://api.github.com/users/zdevito/repos","events_url":"https://api.github.com/users/zdevito/events{/privacy}","received_events_url":"https://api.github.com/users/zdevito/received_events","type":"User","site_admin":false},{"login":"soumith","id":1310570,"node_id":"MDQ6VXNlcjEzMTA1NzA=","avatar_url":"https://avatars0.githubusercontent.com/u/1310570?v=4","gravatar_id":"","url":"https://api.github.com/users/soumith","html_url":"https://github.com/soumith","followers_url":"https://api.github.com/users/soumith/followers","following_url":"https://api.github.com/users/soumith/following{/other_user}","gists_url":"https://api.github.com/users/soumith/gists{/gist_id}","starred_url":"https://api.github.com/users/soumith/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/soumith/subscriptions","organizations_url":"https://api.github.com/users/soumith/orgs","repos_url":"https://api.github.com/users/soumith/repos","events_url":"https://api.github.com/users/soumith/events{/privacy}","received_events_url":"https://api.github.com/users/soumith/received_events","type":"User","site_admin":false},{"login":"gchanan","id":3768583,"node_id":"MDQ6VXNlcjM3Njg1ODM=","avatar_url":"https://avatars2.githubusercontent.com/u/3768583?v=4","gravatar_id":"","url":"https://api.github.com/users/gchanan","html_url":"https://github.com/gchanan","followers_url":"https://api.github.com/users/gchanan/followers","following_url":"https://api.github.com/users/gchanan/following{/other_user}","gists_url":"https://api.github.com/users/gchanan/gists{/gist_id}","starred_url":"https://api.github.com/users/gchanan/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gchanan/subscriptions","organizations_url":"https://api.github.com/users/gchanan/orgs","repos_url":"https://api.github.com/users/gchanan/repos","events_url":"https://api.github.com/users/gchanan/events{/privacy}","received_events_url":"https://api.github.com/users/gchanan/received_events","type":"User","site_admin":false},{"login":"apaszke","id":4583066,"node_id":"MDQ6VXNlcjQ1ODMwNjY=","avatar_url":"https://avatars3.githubusercontent.com/u/4583066?v=4","gravatar_id":"","url":"https://api.github.com/users/apaszke","html_url":"https://github.com/apaszke","followers_url":"https://api.github.com/users/apaszke/followers","following_url":"https://api.github.com/users/apaszke/following{/other_user}","gists_url":"https://api.github.com/users/apaszke/gists{/gist_id}","starred_url":"https://api.github.com/users/apaszke/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/apaszke/subscriptions","organizations_url":"https://api.github.com/users/apaszke/orgs","repos_url":"https://api.github.com/users/apaszke/repos","events_url":"https://api.github.com/users/apaszke/events{/privacy}","received_events_url":"https://api.github.com/users/apaszke/received_events","type":"User","site_admin":false}],"requested_teams":[],"labels":[],"milestone":null,"commits_url":"https://api.github.com/repos/pytorch/pytorch/pulls/10301/commits","review_comments_url":"https://api.github.com/repos/pytorch/pytorch/pulls/10301/comments","review_comment_url":"https://api.github.com/repos/pytorch/pytorch/pulls/comments{/number}","comments_url":"https://api.github.com/repos/pytorch/pytorch/issues/10301/comments","statuses_url":"https://api.github.com/repos/pytorch/pytorch/statuses/b2b66c7c966debee5ffeefd76117a42526252ea6","head":{"label":"syed-ahmed:thcnumerics-refactor","ref":"thcnumerics-refactor","sha":"b2b66c7c966debee5ffeefd76117a42526252ea6","user":{"login":"syed-ahmed","id":8906225,"node_id":"MDQ6VXNlcjg5MDYyMjU=","avatar_url":"https://avatars1.githubusercontent.com/u/8906225?v=4","gravatar_id":"","url":"https://api.github.com/users/syed-ahmed","html_url":"https://github.com/syed-ahmed","followers_url":"https://api.github.com/users/syed-ahmed/followers","following_url":"https://api.github.com/users/syed-ahmed/following{/other_user}","gists_url":"https://api.github.com/users/syed-ahmed/gists{/gist_id}","starred_url":"https://api.github.com/users/sy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