wehub-resource-sync
59 lines
1.7 KiB
C++
59 lines
1.7 KiB
C++
// Copyright (c) 2024 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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extern "C" {
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#include <xxhash.h>
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}
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#include <vector>
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#include "paddle/phi/core/kernel_registry.h"
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#include "paddle/phi/kernels/funcs/eigen/common.h"
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#include "paddle/phi/kernels/funcs/hash_utils.h"
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namespace phi {
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template <typename T, typename Context>
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void HashKernel(const Context& dev_ctx,
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const DenseTensor& x,
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int num_hash,
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int64_t mod_by,
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DenseTensor* out) {
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auto* out_t = out;
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auto* in_t = &x;
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auto in_dims = in_t->dims();
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std::vector<int64_t> out_dims;
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funcs::HashOutputSize(in_dims, out_dims, num_hash);
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out_t->Resize(out_dims);
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auto* output = dev_ctx.template Alloc<T>(out_t);
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auto seq_length = in_dims[0];
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auto last_dim = in_dims[in_dims.size() - 1];
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auto* input = in_t->data<T>();
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for (int idx = 0; idx < seq_length; ++idx) {
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for (int ihash = 0; ihash != num_hash; ++ihash) {
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output[idx * num_hash + ihash] =
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XXH64(input, sizeof(T) * last_dim, ihash) % mod_by;
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}
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input += last_dim;
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}
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out_t->set_lod(in_t->lod());
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}
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} // namespace phi
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