wehub-resource-sync
78 lines
2.7 KiB
C++
78 lines
2.7 KiB
C++
// 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/fused_softmax_mask_kernel.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/core/kernel_registry.h"
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namespace phi {
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namespace fusion {
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template <typename T, typename Context>
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void FusedSoftmaxMaskKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& mask,
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DenseTensor* out) {
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auto* x_data = x.data<T>();
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auto* mask_data = mask.data<T>();
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auto* y_data = dev_ctx.template Alloc<T>(out);
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auto x_dim = x.dims();
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auto mask_dim = mask.dims();
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PADDLE_ENFORCE_EQ(mask_dim[1],
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1,
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common::errors::InvalidArgument(
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"Input mask's second dim must be 1 "
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"received the second dimension of mask is %d",
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mask_dim[1]));
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// dim of x and mask must be equal
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for (size_t idx = 0; idx < 4; ++idx) {
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if (idx == 1) continue;
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PADDLE_ENFORCE_EQ(
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x_dim[idx],
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mask_dim[idx],
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common::errors::InvalidArgument(
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"Input x's %dth dim should be equal with input mask's %dth dim "
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"but "
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"received the %dth dimension of x and mask are not equal "
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"the %dth dim of x is %d, while the %dth dim of mask is %d.",
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idx,
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idx,
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idx,
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idx,
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x_dim[idx],
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idx,
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mask_dim[idx]));
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}
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std::vector<int64_t> x_shape = vectorize<int64_t>(x.dims());
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std::vector<int64_t> mask_shape = vectorize<int64_t>(mask.dims());
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// int softmax_with_mask(Context* ctx, const T* x, const T* mask, T* y, const
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// std::vector<int64_t>& x_shape, const std::vector<int64_t>& mask_shape);
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int r = xpu::softmax_with_mask(
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dev_ctx.x_context(), x_data, mask_data, y_data, x_shape, mask_shape);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "softmax_with_mask");
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}
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} // namespace fusion
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} // namespace phi
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PD_REGISTER_KERNEL(fused_softmax_mask,
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XPU,
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ALL_LAYOUT,
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phi::fusion::FusedSoftmaxMaskKernel,
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float) {}
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