wehub-resource-sync
93 lines
3.4 KiB
Plaintext
93 lines
3.4 KiB
Plaintext
// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/phi/kernels/llm_int8_linear_kernel.h"
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#include "paddle/common/enforce.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/common/amp_type_traits.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/elementwise_add_kernel.h"
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#include "paddle/phi/kernels/funcs/broadcast_function.h"
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#include "paddle/phi/kernels/funcs/elementwise_functor.h"
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#if defined(PADDLE_WITH_CUDA)
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#include "paddle/phi/kernels/impl/llm_int8_matmul_kernel_impl.h"
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#endif
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namespace phi {
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template <typename T, typename Context>
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void llm_int8_compute(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& weight,
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const optional<DenseTensor>& bias,
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const DenseTensor& weight_scale,
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const float threshold,
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DenseTensor* out) {
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#if defined(PADDLE_WITH_CUDA)
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DenseTensor cublaslt_workspace;
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cublaslt_workspace.Resize({3000000});
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dev_ctx.template Alloc<int8_t>(&cublaslt_workspace);
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const auto x_dims = x.dims();
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const auto w_dims = weight.dims();
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const int64_t k_64 = w_dims[1];
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const int64_t n_64 = w_dims[0];
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PADDLE_ENFORCE_LE_INT_MAX(k_64, "k");
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PADDLE_ENFORCE_LE_INT_MAX(n_64, "n");
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const int64_t m_64 = x.numel() / k_64;
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PADDLE_ENFORCE_LE_INT_MAX(m_64, "m");
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const int k = static_cast<int>(k_64);
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const int n = static_cast<int>(n_64);
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const int m = static_cast<int>(m_64);
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// mk * transpose(nk) = mn
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llm_int8::LLMGemm<T>(dev_ctx,
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&weight,
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&x,
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&weight_scale,
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threshold,
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out,
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&cublaslt_workspace,
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"llm_int8_mat_mul",
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m,
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k,
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n);
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if (bias) {
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AddKernel<T, Context>(dev_ctx, *out, bias.get(), out);
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}
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#else
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PADDLE_THROW(common::errors::Unimplemented(
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"llm_int8_linear op needs paddle with cuda and cuda version >= 11.2"));
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#endif
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}
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template <typename T, typename Context>
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void LLMInt8LinearKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& weight,
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const optional<DenseTensor>& bias,
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const DenseTensor& weight_scale,
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const float threshold,
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DenseTensor* out) {
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dev_ctx.template Alloc<T>(out);
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llm_int8_compute<T, Context>(
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dev_ctx, x, weight, bias, weight_scale, threshold, out);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(llm_int8_linear,
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GPU,
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ALL_LAYOUT,
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phi::LLMInt8LinearKernel,
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phi::float16,
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phi::bfloat16) {}
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