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dc70e8175f
Summary: This is a retry of https://github.com/pytorch/pytorch/pull/94992 which was reverted due to CI issues. This PR adds a set of unintrepreted data types on PyTorch which can be used to implement experimental functionality out of core (think fp8, int4, int16 quant, etc). @bypass-github-export-checks Test Plan: ``` python test/test_quantization.py -k TestBits ``` Reviewers: Subscribers: Tasks: Tags: Fixes #ISSUE_NUMBER Pull Request resolved: https://github.com/pytorch/pytorch/pull/95860 Approved by: https://github.com/atalman
62 lines
1.4 KiB
C++
62 lines
1.4 KiB
C++
#pragma once
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#include <cstdint>
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#include <c10/macros/Macros.h>
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namespace c10 {
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/**
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* bits1x8 is an uninterpreted dtype of a tensor with 1 bit (packed to byte
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* boundary), without any semantics defined.
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*/
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struct alignas(1) bits1x8 {
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using underlying = uint8_t;
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uint8_t val_;
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bits1x8() = default;
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C10_HOST_DEVICE explicit bits1x8(uint8_t val) : val_(val) {}
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};
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/**
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* bits2x4 is an uninterpreted dtype of a tensor with 2 bits (packed to byte
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* boundary), without any semantics defined.
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*/
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struct alignas(1) bits2x4 {
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using underlying = uint8_t;
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uint8_t val_;
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bits2x4() = default;
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C10_HOST_DEVICE explicit bits2x4(uint8_t val) : val_(val) {}
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};
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/**
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* bits4x2 is an uninterpreted dtype of a tensor with 4 bits (packed to byte
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* boundary), without any semantics defined.
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*/
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struct alignas(1) bits4x2 {
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using underlying = uint8_t;
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uint8_t val_;
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bits4x2() = default;
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C10_HOST_DEVICE explicit bits4x2(uint8_t val) : val_(val) {}
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};
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/**
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* bits8 is an uninterpreted dtype of a tensor with 8 bits, without any
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* semantics defined.
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*/
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struct alignas(1) bits8 {
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uint8_t val_;
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bits8() = default;
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C10_HOST_DEVICE explicit bits8(uint8_t val) : val_(val) {}
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};
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/**
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* bits16 is an uninterpreted dtype of a tensor with 16 bits, without any
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* semantics defined.
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*/
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struct alignas(2) bits16 {
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uint16_t val_;
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bits16() = default;
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C10_HOST_DEVICE explicit bits16(uint16_t val) : val_(val) {}
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};
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} // namespace c10
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