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66 lines
2.4 KiB
66 lines
2.4 KiB
// Copyright (c) 2019 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/fluid/platform/device_context.h>
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#include <algorithm>
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/memory/malloc.h"
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#include "paddle/fluid/operators/math/bert_encoder_functor.h"
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#include "paddle/fluid/operators/math/blas.h"
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namespace paddle {
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namespace operators {
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template <typename DeviceContext, typename T>
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class SkipLayerNormKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext &context) const override {
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using Tensor = framework::Tensor;
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auto *X = context.Input<framework::Tensor>("X");
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auto *Y = context.Input<framework::Tensor>("Y");
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auto *scale = context.Input<framework::Tensor>("Scale");
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auto *bias = context.Input<framework::Tensor>("Bias");
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auto *X_d = X->data<T>();
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auto *Y_d = Y->data<T>();
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auto *scale_d = scale->data<T>();
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auto *bias_d = bias->data<T>();
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float epsilon = context.Attr<float>("epsilon");
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int begin_norm_axis = context.Attr<int>("begin_norm_axis");
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auto *out = context.Output<framework::Tensor>("Out");
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out->Resize(X->dims());
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auto *output_d = out->mutable_data<T>(context.GetPlace());
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size_t num = 1;
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for (size_t i = 0; i < X->dims().size(); i++) {
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num *= X->dims()[i];
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}
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int hidden = X->dims()[2];
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auto &device_ctx = context.template device_context<DeviceContext>();
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operators::math::SkipLayerNormFunctor<T> skip_layer_norm_func;
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skip_layer_norm_func(num, hidden, X_d, Y_d, scale_d, bias_d, output_d,
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epsilon, device_ctx.stream());
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_CUDA_KERNEL(
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skip_layernorm,
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ops::SkipLayerNormKernel<paddle::platform::CUDADeviceContext, float>);
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