wehub-resource-sync
140 lines
4.8 KiB
C++
140 lines
4.8 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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#include "paddle/phi/kernels/put_along_axis_kernel.h"
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#include "paddle/common/layout.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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int64_t get_reduction_mode(const std::string& reduce) {
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if (reduce == "assign") {
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return 0;
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} else if (reduce == "add") {
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return 1;
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} else if (reduce == "multiply" || reduce == "mul") {
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return 2;
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} else if (reduce == "mean") {
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return 3;
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} else if (reduce == "amax") {
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return 4;
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} else if (reduce == "amin") {
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return 5;
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} else {
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PADDLE_THROW(errors::InvalidArgument(
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"can not support reduce: '%s' for put_along_axis kernel, only "
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"support reduce op: 'add', 'assign', 'mul', 'mean', 'amin', 'amax' and "
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"'multiply', the "
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"default reduce "
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"op is 'assign' ",
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reduce));
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}
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}
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template <typename T, typename Context>
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void PutAlongAxisKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const DenseTensor& index,
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const DenseTensor& value,
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int axis,
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const std::string& reduce,
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bool include_self,
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DenseTensor* out) {
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out->Resize(x.dims());
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dev_ctx.template Alloc<T>(out);
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if (x.numel() == 0 || index.numel() == 0) return;
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const auto& index_dtype = index.dtype();
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bool index_dtype_match =
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index_dtype == DataType::INT32 || index_dtype == DataType::INT64;
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PADDLE_ENFORCE_EQ(index_dtype_match,
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true,
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errors::InvalidArgument(
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"Input(Index) holds the wrong type, it holds %s, but "
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"desires to be %s or %s",
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DataTypeToString(index_dtype),
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DataTypeToString(DataType::INT32),
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DataTypeToString(DataType::INT64)));
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auto input_dtype = x.dtype();
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std::vector<int64_t> x_shape = vectorize<int64_t>(x.dims());
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std::vector<int64_t> index_shape = vectorize<int64_t>(index.dims());
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std::vector<int64_t> value_shape = vectorize<int64_t>(value.dims());
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using XPUType = typename XPUTypeTrait<T>::Type;
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int64_t reduce_mode = get_reduction_mode(reduce);
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bool invalid_input =
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(input_dtype == DataType::INT32 || input_dtype == DataType::INT64) &&
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(!include_self || reduce_mode > 2);
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PADDLE_ENFORCE_EQ(invalid_input,
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false,
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errors::InvalidArgument(
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"Only support include_self = true and reduce mode: "
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"'add', 'assign' and 'multiply' for int32/int64"));
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PADDLE_ENFORCE_EQ(index.dims().size(),
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value.dims().size(),
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errors::InvalidArgument(
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"The input(Index) and the input(Value) must have same "
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"rank, but received Index rank is %d, Value rank is %d",
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index.dims().size(),
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value.dims().size()));
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if (index_dtype == DataType::INT32) {
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int ret = xpu::paddle_put_along_axis(
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dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(x.data<T>()),
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reinterpret_cast<const XPUType*>(value.data<T>()),
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index.data<int32_t>(),
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reinterpret_cast<XPUType*>(out->data<T>()),
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x_shape,
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value_shape,
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index_shape,
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axis,
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reduce_mode,
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include_self);
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PADDLE_ENFORCE_XDNN_SUCCESS(ret, "paddle_put_along_axis");
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} else {
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int ret = xpu::paddle_put_along_axis(
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dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(x.data<T>()),
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reinterpret_cast<const XPUType*>(value.data<T>()),
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index.data<int64_t>(),
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reinterpret_cast<XPUType*>(out->data<T>()),
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x_shape,
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value_shape,
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index_shape,
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axis,
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reduce_mode,
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include_self);
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PADDLE_ENFORCE_XDNN_SUCCESS(ret, "paddle_put_along_axis");
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}
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}
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} // namespace phi
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PD_REGISTER_KERNEL(put_along_axis,
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XPU,
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ALL_LAYOUT,
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phi::PutAlongAxisKernel,
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float,
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int64_t,
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int,
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phi::float16,
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phi::bfloat16) {}
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