wehub-resource-sync
54 lines
1.9 KiB
C++
54 lines
1.9 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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#pragma once
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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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namespace phi {
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// we don't receive 2+d tensor as weight
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inline std::tuple<int64_t, int64_t, int64_t> canonicalize_dims(
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const DenseTensor& input,
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const DenseTensor& weight,
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const bool transpose_weight) {
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const auto input_dims = input.dims();
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const auto weight_dims = weight.dims();
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// We assume weight to be [K, N] if not tranasposed, [N, K] if transposed, [K]
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// if 1D
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const int64_t N = weight_dims.size() < 2 ? 1 : weight_dims[!transpose_weight];
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const int64_t K =
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weight_dims.size() < 2 ? weight_dims[0] : weight_dims[transpose_weight];
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int64_t M = input_dims.size() >= 2 ? input_dims[input_dims.size() - 2] : 1;
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if (input_dims.size() > 2) {
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// Accumulate the batch dims for input
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for (int64_t i = 0; i < input_dims.size() - 2; ++i) {
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M *= input_dims[i];
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}
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}
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return {M, N, K};
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}
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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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} // namespace phi
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