wehub-resource-sync
69 lines
2.4 KiB
C++
69 lines
2.4 KiB
C++
// Copyright (c) 2025 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 <algorithm>
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#include <mutex>
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#include <unordered_map>
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#include "glog/logging.h"
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#include "paddle/phi/common/data_type.h"
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/core/tensor_utils.h"
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#include "paddle/common/enforce.h"
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#include "paddle/phi/kernels/addmm_kernel.h"
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#include "paddle/phi/kernels/elementwise_add_kernel.h"
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#include "paddle/phi/kernels/impl/matmul_kernel_impl.h"
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#include "paddle/phi/kernels/linear_v2_kernel.h"
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#include "paddle/phi/kernels/reshape_kernel.h"
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#include "paddle/phi/kernels/tile_kernel.h"
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#include "paddle/phi/backends/all_context.h"
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#include "paddle/phi/core/dense_tensor.h"
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#include "paddle/phi/core/enforce.h"
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#include "paddle/phi/core/scope_guard.h"
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namespace phi {
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template <typename T, typename Context>
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void LinearV2Kernel(const Context& dev_ctx,
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const DenseTensor& input,
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const DenseTensor& weight,
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const DenseTensor& bias,
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const bool transpose_weight,
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DenseTensor* out) {
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dev_ctx.template Alloc<T>(out);
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if (out->numel() == 0) {
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return;
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}
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// When in CPU, we use legacy linear_logic by default.
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// TODO(Pan Zhaowu): Adding more efficient kernel for CPU.
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std::vector<std::int64_t> input_dims_vec = vectorize(input.dims());
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std::vector<std::int64_t> weight_dims_vec = vectorize(weight.dims());
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MatMulFunction<Context, T>(dev_ctx,
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input,
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weight,
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input_dims_vec,
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weight_dims_vec,
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out,
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false,
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transpose_weight);
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AddKernel<T, Context>(dev_ctx, *out, bias, out);
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}
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} // namespace phi
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PD_REGISTER_KERNEL(
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linear_v2, CPU, ALL_LAYOUT, phi::LinearV2Kernel, float, double) {}
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