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https://github.com/ROCm/composable_kernel.git
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abf13bdec1
[CK] Fix windows build issues ## Motivation Full build on Windows is currently broken due to compiler errors, this PR should help fix that. This is also holding up the following PR in the TheRock: https://github.com/ROCm/TheRock/pull/3382 ## Technical Details 1. I don't see a good reason to be nesting a windows include inside the ck_tile namespace. It was causing compiler errors too: Windows.h comes with min and max, which was conflicting with ck_tile::min and ck_tile::max, so I moved it out. I also defined NOMINMAX to prevent this inclusion in the future. 2. The TRUE/FALSE macros are already used by Windows.h, which causes an error. So I've opted for True/False. You can see this pattern in other rocm-libraries. 3. The M_PI macro isn't available, at least in the WIN32_LEAN_AND_MEAN context, from \<cmath\> on Windows. We'll be able to use std::numbers::v_pi\<float\> when we have C++20 support. 4. There was a missing \<chrono\> include. ## Test Plan Test locally and make sure this doesn't impact existing CI. ## Test Result Compiles locally and passes existing ci. ## Submission Checklist - [ x ] Look over the contributing guidelines at https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
90 lines
2.9 KiB
C++
90 lines
2.9 KiB
C++
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#pragma once
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#include "ck_tile/core.hpp"
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#include "ck_tile/host/host_tensor.hpp"
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#include <cassert>
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#include <cmath>
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#ifndef M_PI // Not there on windows...
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#define M_PI 3.141592653589793238462643383279502884
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#endif
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#include <functional>
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#include <iterator>
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#include <optional>
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#include <random>
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#include <tuple>
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// keep sync with RotaryEmbeddingEnum
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enum class rope_enum
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{
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none = 0,
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interleaved = 1,
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half_rotated = 2,
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};
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template <typename DataType>
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std::tuple<ck_tile::HostTensor<DataType>, ck_tile::HostTensor<DataType>>
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generate_rotary_cos_sin(ck_tile::index_t seqlen,
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ck_tile::index_t rotary_dim,
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std::optional<unsigned> seed = std::nullopt)
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{
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// return dummy tensors if we won't apply RoPE at all
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if(rotary_dim <= 0)
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{
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ck_tile::HostTensor<DataType> dummy({1, 1});
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return std::make_tuple(dummy, dummy);
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}
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std::mt19937 random_engine(seed.has_value() ? *seed : std::random_device{}());
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std::uniform_real_distribution<float> generator(0.0f, 1.0f);
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const ck_tile::index_t num_rows = seqlen * 2;
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const ck_tile::index_t num_cols = rotary_dim / 2;
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using std::begin, std::end;
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ck_tile::HostTensor<float> angle({num_rows, num_cols});
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std::generate(begin(angle), end(angle), [&] { return generator(random_engine) * 2 * M_PI; });
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ck_tile::HostTensor<DataType> cos({num_rows, num_cols});
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std::transform(begin(angle), end(angle), begin(cos), [](float origin_value) {
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return ck_tile::type_convert<DataType>(std::cos(origin_value));
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});
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ck_tile::HostTensor<DataType> sin({num_rows, num_cols});
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std::transform(begin(angle), end(angle), begin(sin), [](float origin_value) {
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return ck_tile::type_convert<DataType>(std::sin(origin_value));
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});
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return std::make_tuple(cos, sin);
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}
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template <typename DataType>
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std::tuple<ck_tile::HostTensor<DataType>, ck_tile::HostTensor<DataType>>
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slice_rotary_cos_sin(const ck_tile::HostTensor<DataType>& cos,
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const ck_tile::HostTensor<DataType>& sin,
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ck_tile::index_t seqlen_offset,
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ck_tile::index_t seqlen)
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{
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assert(cos.get_num_of_dimension() == 2 && sin.get_num_of_dimension() == 2);
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assert(cos.get_length(0) == sin.get_length(0) && cos.get_length(1) == sin.get_length(1));
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assert(static_cast<std::size_t>(seqlen_offset + seqlen) <= cos.get_length(0));
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const ck_tile::index_t num_rows = seqlen;
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const ck_tile::index_t num_cols = cos.get_length(1);
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ck_tile::HostTensor<DataType> cos_pt({num_rows, num_cols});
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cos_pt.ForEach([&](auto& self, auto i) { self(i) = cos(i[0] + seqlen_offset, i[1]); });
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ck_tile::HostTensor<DataType> sin_pt({num_rows, num_cols});
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sin_pt.ForEach([&](auto& self, auto i) { self(i) = sin(i[0] + seqlen_offset, i[1]); });
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return std::make_tuple(cos_pt, sin_pt);
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}
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