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Added expand_v2 BF16/FP32 FWD/BWD kernels (#34284)
* added expand_v2 bf16/fp32 kernel * minor change * CI fix * added missing test file * added formatting * reduced binary size * CI fix
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| /* Copyright (c) 2021 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/fluid/platform/mkldnn_reuse.h" | ||
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| namespace { | ||
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| using paddle::framework::Tensor; | ||
| using paddle::framework::vectorize; | ||
| using paddle::framework::GradVarName; | ||
| using paddle::framework::ExecutionContext; | ||
| using paddle::platform::MKLDNNDeviceContext; | ||
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| template <typename T> | ||
| class ExpandMKLDNNKernel : public paddle::framework::OpKernel<T> { | ||
| public: | ||
| void Compute(const ExecutionContext& ctx) const override { | ||
| this->RunKernel(ctx); | ||
| } | ||
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| void RunKernel(const ExecutionContext& ctx) const { | ||
| const auto& dev_ctx = ctx.template device_context<MKLDNNDeviceContext>(); | ||
| const auto& onednn_engine = dev_ctx.GetEngine(); | ||
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| const auto* x = ctx.Input<Tensor>("X"); | ||
| auto* out = ctx.Output<Tensor>("Out"); | ||
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| auto x_vec_dims = vectorize(x->dims()); | ||
| auto out_vec_dims = vectorize(out->dims()); | ||
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| dnnl::memory::format_tag x_format_tag = x->format(); | ||
| if (x_vec_dims.size() != out_vec_dims.size()) { | ||
| x_format_tag = | ||
| GetExtendedFormatTag(x_vec_dims, out_vec_dims.size(), x_format_tag); | ||
| } | ||
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| out->set_format(x_format_tag); | ||
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| paddle::platform::BroadcastDataMKLDNNHandler<T> handler( | ||
| dnnl::algorithm::binary_add, dev_ctx, onednn_engine, ctx.GetPlace(), | ||
| out, x, 0.0f, 1.0f, ctx.InputName("X"), x_vec_dims); | ||
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| auto src_memory_p = handler.AcquireSrcMemory(x); | ||
| auto dst_memory_p = handler.AcquireDstMemory(out); | ||
| auto binary_p = handler.AcquireForwardPrimitive(); | ||
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| const std::unordered_map<int, dnnl::memory> args = { | ||
| {DNNL_ARG_SRC_0, *dst_memory_p}, | ||
| {DNNL_ARG_SRC_1, *src_memory_p}, | ||
| {DNNL_ARG_DST, *dst_memory_p}}; | ||
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| auto& astream = MKLDNNDeviceContext::tls().get_stream(); | ||
| binary_p->execute(astream, args); | ||
| astream.wait(); | ||
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| out->set_layout(paddle::framework::DataLayout::kMKLDNN); | ||
| out->set_format(paddle::platform::GetMKLDNNFormat(*dst_memory_p)); | ||
| } | ||
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| private: | ||
| dnnl::memory::format_tag GetExtendedFormatTag( | ||
| std::vector<int64_t>& dims, int new_size, | ||
| mkldnn::memory::format_tag format_tag) const { | ||
| mkldnn::memory::desc md(dims, paddle::platform::MKLDNNGetDataType<T>(), | ||
| format_tag); | ||
| std::vector<int64_t> new_dims(new_size, 1); | ||
| std::copy(dims.begin(), dims.end(), | ||
| new_dims.begin() + new_size - dims.size()); | ||
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| dims = std::move(new_dims); | ||
| return paddle::platform::GetMKLDNNFormat(md.reshape(dims)); | ||
| } | ||
| }; | ||
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| template <typename T> | ||
| class ExpandGradMKLDNNKernel : public paddle::framework::OpKernel<T> { | ||
| public: | ||
| void Compute(const ExecutionContext& ctx) const override { | ||
| this->RunKernel(ctx); | ||
| } | ||
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| void RunKernel(const ExecutionContext& ctx) const { | ||
| const auto& dev_ctx = ctx.template device_context<MKLDNNDeviceContext>(); | ||
| const auto& onednn_engine = dev_ctx.GetEngine(); | ||
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| auto* dout = ctx.Input<Tensor>(GradVarName("Out")); | ||
| auto* dx = ctx.Output<Tensor>(GradVarName("X")); | ||
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| auto dx_vec_dims = vectorize(dx->dims()); | ||
| auto dout_vec_dims = vectorize(dout->dims()); | ||
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| if (dx_vec_dims.size() != dout_vec_dims.size()) { | ||
| dx_vec_dims.insert(dx_vec_dims.begin(), | ||
| dout_vec_dims.size() - dx_vec_dims.size(), 1); | ||
| } | ||
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| auto& astream = MKLDNNDeviceContext::tls().get_stream(); | ||
| if (dout_vec_dims == dx_vec_dims) { | ||
| mkldnn::memory::data_type dout_type = | ||
| paddle::framework::ToMKLDNNDataType(dout->type()); | ||
| std::string key = paddle::platform::CreateKey( | ||
| dev_ctx, dout_vec_dims, dout->format(), dout->format(), dout_type); | ||
| paddle::platform::ReorderMKLDNNHandler reorder_handler( | ||
| dout_vec_dims, dout->type(), dout_type, dev_ctx, onednn_engine, key); | ||
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| auto reorder_src_memory_p = reorder_handler.AcquireSrcMemory( | ||
| dout->format(), paddle::platform::to_void_cast(dout->data<T>())); | ||
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| auto reorder_dst_memory_p = | ||
| reorder_handler.AcquireDstMemory(dx, dout->format(), ctx.GetPlace()); | ||
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| auto reorder_p = reorder_handler.AcquireReorder(reorder_src_memory_p, | ||
| reorder_dst_memory_p); | ||
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| reorder_p->execute(astream, *reorder_src_memory_p, *reorder_dst_memory_p); | ||
| astream.wait(); | ||
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| dx->set_layout(paddle::framework::DataLayout::kMKLDNN); | ||
| dx->set_format( | ||
| paddle::platform::GetMKLDNNFormat(reorder_dst_memory_p->get_desc())); | ||
| } else { | ||
| paddle::platform::ReductionMKLDNNHandler<T> handler( | ||
| dnnl::algorithm::reduction_sum, 0.0f, 0.0f, dev_ctx, onednn_engine, | ||
| ctx.GetPlace(), dout, dx, ctx.InputName("X"), dx_vec_dims); | ||
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| auto src_memory_p = handler.AcquireSrcMemory(dout); | ||
| auto dst_memory_p = handler.AcquireDstMemory(dx); | ||
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| std::unordered_map<int, dnnl::memory> reduction_args = { | ||
| {DNNL_ARG_SRC, *src_memory_p}, {DNNL_ARG_DST, *dst_memory_p}}; | ||
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| auto reduction_p = handler.AcquireForwardPrimitive(); | ||
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| reduction_p->execute(astream, reduction_args); | ||
| astream.wait(); | ||
| dx->set_layout(paddle::framework::DataLayout::kMKLDNN); | ||
| dx->set_format(paddle::platform::GetMKLDNNFormat( | ||
| dst_memory_p->get_desc().reshape(vectorize<int64_t>(dx->dims())))); | ||
| } | ||
| } | ||
| }; | ||
| } // anonymous namespace | ||
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| REGISTER_OP_KERNEL(expand_v2, MKLDNN, paddle::platform::CPUPlace, | ||
| ExpandMKLDNNKernel<float>, | ||
| ExpandMKLDNNKernel<paddle::platform::bfloat16>); | ||
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| REGISTER_OP_KERNEL(expand_v2_grad, MKLDNN, paddle::platform::CPUPlace, | ||
| ExpandGradMKLDNNKernel<float>, | ||
| ExpandGradMKLDNNKernel<paddle::platform::bfloat16>); |
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