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[PHI] Support bmm and bmm_grad in xpu (#45887)
* support bmm and bmm_grad in xpu * add error removal * test=kunlun * refactor code for better structure * test=kunlun * add fp16 kernel for bmm * test=kunlun
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// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. | ||
// | ||
// Licensed under the Apache License, Version 2.0 (the "License"); | ||
// you may not use this file except in compliance with the License. | ||
// You may obtain a copy of the License at | ||
// | ||
// http://www.apache.org/licenses/LICENSE-2.0 | ||
// | ||
// Unless required by applicable law or agreed to in writing, software | ||
// distributed under the License is distributed on an "AS IS" BASIS, | ||
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
// See the License for the specific language governing permissions and | ||
// limitations under the License. | ||
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#include "paddle/phi/kernels/bmm_grad_kernel.h" | ||
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#include "paddle/phi/kernels/xpu/bmm_xpu_utils.h" | ||
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namespace phi { | ||
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template <typename T, typename Context> | ||
void MatMul(const Context& dev_ctx, | ||
const DenseTensor& a, | ||
bool trans_a, | ||
const DenseTensor& b, | ||
bool trans_b, | ||
DenseTensor* out) { | ||
dev_ctx.template Alloc<T>(out); | ||
xpu::Context* xpu_ctx = dev_ctx.x_context(); | ||
if (std::is_same<paddle::platform::float16, T>::value) { | ||
MatMulXPUFunction<T, int16_t>(a, b, out, trans_a, trans_b, xpu_ctx); | ||
} else { | ||
if (std::getenv("XPU_PADDLE_FC_INT32") != nullptr) { | ||
MatMulXPUFunction<T, int32_t>(a, b, out, trans_a, trans_b, xpu_ctx); | ||
} else if (std::getenv("XPU_PADDLE_FC_LOCAL_INT16") != nullptr) { | ||
MatMulXPUFunction<T, float>(a, b, out, trans_a, trans_b, xpu_ctx); | ||
} else { | ||
MatMulXPUFunction<T, int16_t>(a, b, out, trans_a, trans_b, xpu_ctx); | ||
} | ||
} | ||
} | ||
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template <typename T, typename Context> | ||
void CalcInputGrad(const Context& dev_ctx, | ||
const DenseTensor& a, | ||
bool trans_a, | ||
const DenseTensor& b, | ||
bool trans_b, | ||
DenseTensor* out) { | ||
if (out == nullptr) return; | ||
MatMul<T, Context>(dev_ctx, a, trans_a, b, trans_b, out); | ||
} | ||
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template <typename T, typename Context> | ||
void BmmGradKernel(const Context& dev_ctx, | ||
const DenseTensor& x, | ||
const DenseTensor& y, | ||
const DenseTensor& out_grad, | ||
DenseTensor* x_grad, | ||
DenseTensor* y_grad) { | ||
DenseTensor x_help = x; | ||
DenseTensor y_help = y; | ||
DenseTensor out_grad_help = out_grad; | ||
ReshapeXYOutIntoMatrixSequence( | ||
&x_help, &y_help, &out_grad_help, false, false); | ||
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phi::DDim dx_dims; | ||
if (x_grad) { | ||
dx_dims = x_grad->dims(); | ||
if (dx_dims != x_help.dims()) { | ||
x_grad->Resize(x_help.dims()); | ||
} | ||
} | ||
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phi::DDim dy_dims; | ||
if (y_grad) { | ||
dy_dims = y_grad->dims(); | ||
if (dy_dims != y_help.dims()) { | ||
y_grad->Resize(y_help.dims()); | ||
} | ||
} | ||
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CalcInputGrad<T, Context>( | ||
dev_ctx, out_grad_help, false, y_help, true, x_grad); | ||
CalcInputGrad<T, Context>( | ||
dev_ctx, x_help, true, out_grad_help, false, y_grad); | ||
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if (x_grad) { | ||
if (dx_dims != x_help.dims()) { | ||
x_grad->Resize(dx_dims); | ||
} | ||
} | ||
if (y_grad) { | ||
if (dy_dims != y_help.dims()) { | ||
y_grad->Resize(dy_dims); | ||
} | ||
} | ||
} | ||
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} // namespace phi | ||
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PD_REGISTER_KERNEL(bmm_grad, | ||
XPU, | ||
ALL_LAYOUT, | ||
phi::BmmGradKernel, | ||
float, | ||
paddle::platform::float16) {} |
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