wehub-resource-sync
128 lines
4.2 KiB
C++
128 lines
4.2 KiB
C++
// 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.
|
|
|
|
#include "paddle/phi/kernels/split_kernel.h"
|
|
|
|
#include "paddle/phi/backends/onednn/onednn_reuse.h"
|
|
#include "paddle/phi/core/kernel_registry.h"
|
|
|
|
namespace phi {
|
|
|
|
bool SplitCheckIfOneDNNSupport(const KernelContext* dev_ctx) {
|
|
if (dev_ctx->InputAt<DenseTensor>(0).mem_desc().get_inner_nblks() == 0) {
|
|
return true;
|
|
}
|
|
return false;
|
|
}
|
|
|
|
const std::vector<int64_t> get_slice_strides(
|
|
const std::vector<int64_t>& out_vec_dims,
|
|
const dnnl::memory::desc& full_md,
|
|
int axis) {
|
|
auto strides = full_md.get_strides();
|
|
auto ndims = full_md.get_dims().size();
|
|
auto full_dims = full_md.get_dims();
|
|
auto split_stride = strides[axis];
|
|
std::vector<int64_t> slice_strides(ndims, split_stride);
|
|
for (size_t i = 0; i < ndims; ++i) {
|
|
slice_strides[i] = strides[i] > split_stride
|
|
? (strides[i] / full_dims[axis]) * out_vec_dims[axis]
|
|
: strides[i];
|
|
}
|
|
return slice_strides;
|
|
}
|
|
|
|
template <typename T, typename Context>
|
|
void SplitKernel(const Context& dev_ctx,
|
|
const DenseTensor& x,
|
|
const IntArray& sections,
|
|
const Scalar& split_axis,
|
|
std::vector<DenseTensor*> out) {
|
|
const auto& onednn_engine = dev_ctx.GetEngine();
|
|
|
|
int axis = split_axis.to<int>();
|
|
|
|
auto outs_number = out.size();
|
|
const auto x_dims = x.dims();
|
|
auto x_vec_dims = vectorize(x_dims);
|
|
|
|
dnnl::memory::data_type x_type = funcs::ToOneDNNDataType(x.dtype());
|
|
|
|
auto& astream = OneDNNContext::tls().get_stream();
|
|
|
|
std::vector<int64_t> offset(x_vec_dims.size(), 0);
|
|
funcs::ReorderOneDNNHandler reorder_handler(
|
|
x_vec_dims, x.dtype(), x_type, onednn_engine);
|
|
auto reorder_src_memory_p = reorder_handler.AcquireSrcMemory(
|
|
x.mem_desc(), funcs::to_void_cast(x.data<T>()));
|
|
|
|
for (size_t i = 0; i < outs_number; ++i) {
|
|
auto out_vec_dims = vectorize(out[i]->dims());
|
|
auto slice_mem_p = reorder_handler.AcquireSubmemory(
|
|
out_vec_dims, offset, reorder_src_memory_p);
|
|
|
|
auto reorder_dst_memory_p = reorder_handler.AcquireDstMemory(
|
|
out[i],
|
|
out_vec_dims,
|
|
get_slice_strides(out_vec_dims, x.mem_desc(), axis),
|
|
dev_ctx.GetPlace());
|
|
auto reorder_p =
|
|
reorder_handler.AcquireReorder(reorder_dst_memory_p, slice_mem_p);
|
|
|
|
reorder_p->execute(astream, *slice_mem_p, *reorder_dst_memory_p);
|
|
|
|
offset[axis] += sections.GetData()[i];
|
|
out[i]->set_mem_desc(reorder_dst_memory_p->get_desc());
|
|
}
|
|
astream.wait();
|
|
}
|
|
|
|
template <typename T, typename Context>
|
|
void SplitWithNumKernel(const Context& dev_ctx,
|
|
const DenseTensor& x,
|
|
int num,
|
|
const Scalar& axis_scalar,
|
|
std::vector<DenseTensor*> outs) {
|
|
int axis_value = axis_scalar.to<int>();
|
|
auto input_axis_dim = x.dims().at(axis_value);
|
|
const std::vector<int64_t> sections_vec(num, input_axis_dim / num);
|
|
|
|
IntArray sections(sections_vec);
|
|
SplitKernel<T, Context>(dev_ctx, x, sections, axis_scalar, outs);
|
|
}
|
|
|
|
} // namespace phi
|
|
|
|
PD_REGISTER_KERNEL(split,
|
|
OneDNN,
|
|
ONEDNN,
|
|
phi::SplitKernel,
|
|
float,
|
|
phi::bfloat16,
|
|
int8_t,
|
|
uint8_t) {
|
|
kernel->check_if_onednn_kernel_support_ = phi::SplitCheckIfOneDNNSupport;
|
|
}
|
|
|
|
PD_REGISTER_KERNEL(split_with_num,
|
|
OneDNN,
|
|
ONEDNN,
|
|
phi::SplitWithNumKernel,
|
|
float,
|
|
phi::bfloat16,
|
|
int8_t,
|
|
uint8_t) {
|
|
kernel->check_if_onednn_kernel_support_ = phi::SplitCheckIfOneDNNSupport;
|
|
}
|