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@ -15,6 +15,7 @@
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#include "mkldnn.hpp"
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#include "paddle/fluid/operators/activation_op.h"
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#include "paddle/fluid/operators/mkldnn_activation_op.h"
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#include "paddle/fluid/platform/mkldnn_helper.h"
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namespace paddle {
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namespace operators {
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@ -23,6 +24,18 @@ using paddle::framework::Tensor;
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using paddle::platform::MKLDNNDeviceContext;
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namespace {
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std::string gethash(const mkldnn::memory::dims &operand_dims,
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const mkldnn::algorithm algorithm) {
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auto dim2str = [](const mkldnn::memory::dims &operand_dims) {
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std::string dstr = "";
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for (size_t i = 0; i < operand_dims.size(); ++i) {
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dstr += std::to_string(operand_dims[i]) + "-";
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}
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return dstr;
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};
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return dim2str(operand_dims) + std::to_string(algorithm);
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}
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template <typename T, typename ExecContext>
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void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
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const T alpha = 0, const T beta = 0) {
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@ -37,42 +50,70 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
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const auto *src_data = src->template data<T>();
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auto *dst = ctx.template Output<Tensor>("Out");
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const T *dst_data = dst->template mutable_data<T>(ctx.GetPlace());
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T *dst_data = dst->template mutable_data<T>(ctx.GetPlace());
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// get memory dim
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PADDLE_ENFORCE(src->dims().size() == 2 || src->dims().size() == 4,
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"Input dim must be with 2 or 4");
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std::vector<int> src_tz = framework::vectorize2int(src->dims());
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// create memory description
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auto data_md = src_tz.size() == 2
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? platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
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mkldnn::memory::format::nc)
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: platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
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mkldnn::memory::format::nchw);
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// create memory primitives
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auto src_memory =
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mkldnn::memory({data_md, mkldnn_engine},
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static_cast<void *>(const_cast<float *>(src_data)));
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auto dst_memory =
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mkldnn::memory({data_md, mkldnn_engine},
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static_cast<void *>(const_cast<float *>(dst_data)));
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auto forward_desc = mkldnn::eltwise_forward::desc(
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mkldnn::prop_kind::forward_training, algorithm, data_md, alpha, beta);
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// save prim desc into global device context to be referred in backward path
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const std::string key = ctx.op().Output("Out");
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const std::string key_eltwise_pd = key + "@eltwise_pd";
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auto forward_pd = std::make_shared<mkldnn::eltwise_forward::primitive_desc>(
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forward_desc, mkldnn_engine);
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dev_ctx.SetBlob(key_eltwise_pd, forward_pd);
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auto eltwise = mkldnn::eltwise_forward(*forward_pd, src_memory, dst_memory);
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const std::string key = gethash(src_tz, algorithm);
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const std::string key_src_data =
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key + ctx.op().Output("Out") + "@eltwise_fwd_src_data";
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const std::string key_src_mem = key + "@eltwise_fwd_src_mem";
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const std::string key_dst_mem = key + "@eltwise_fwd_dst_mem";
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const std::string key_fwd = key + "@eltwise_fwd";
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auto p_fwd = std::static_pointer_cast<mkldnn::eltwise_forward>(
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dev_ctx.GetBlob(key_fwd));
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// save input data to be referred in backward path
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auto p_src_data = std::make_shared<const T *>(src_data);
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dev_ctx.SetBlob(key_src_data, p_src_data);
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if (p_fwd == nullptr) {
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// create memory description
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auto data_md = src_tz.size() == 2
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? platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
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mkldnn::memory::format::nc)
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: platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
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mkldnn::memory::format::nchw);
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// create memory primitives
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auto p_src_mem = std::make_shared<mkldnn::memory>(mkldnn::memory(
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{data_md, mkldnn_engine}, platform::to_void_cast(src_data)));
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dev_ctx.SetBlob(key_src_mem, p_src_mem);
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auto p_dst_mem = std::make_shared<mkldnn::memory>(mkldnn::memory(
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{data_md, mkldnn_engine}, platform::to_void_cast(dst_data)));
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dev_ctx.SetBlob(key_dst_mem, p_dst_mem);
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auto fwd_desc = mkldnn::eltwise_forward::desc(
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mkldnn::prop_kind::forward_training, algorithm, data_md, alpha, beta);
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auto p_fwd_pd = std::make_shared<mkldnn::eltwise_forward::primitive_desc>(
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fwd_desc, mkldnn_engine);
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const std::string key_fwd_pd = key + "eltwise_fwd_pd";
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dev_ctx.SetBlob(key_fwd_pd, p_fwd_pd);
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p_fwd = std::make_shared<mkldnn::eltwise_forward>(
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*p_fwd_pd, *(p_src_mem.get()), *(p_dst_mem.get()));
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dev_ctx.SetBlob(key_fwd, p_fwd);
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} else {
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// primitives already exist
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auto p_src_mem =
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std::static_pointer_cast<mkldnn::memory>(dev_ctx.GetBlob(key_src_mem));
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PADDLE_ENFORCE(p_src_mem != nullptr,
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"Fail to find eltwise p_src_mem in device context.");
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auto p_dst_mem =
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std::static_pointer_cast<mkldnn::memory>(dev_ctx.GetBlob(key_dst_mem));
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PADDLE_ENFORCE(p_dst_mem != nullptr,
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"Fail to find eltwise p_src_mem in device context.");
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p_src_mem->set_data_handle(platform::to_void_reinterpret_cast(src_data));
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p_dst_mem->set_data_handle(dst_data);
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}
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// push primitive to stream and wait until it's executed
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std::vector<mkldnn::primitive> pipeline = {eltwise};
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std::vector<mkldnn::primitive> pipeline = {*(p_fwd.get())};
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mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait();
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}
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@ -83,8 +124,7 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
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const auto &mkldnn_engine = dev_ctx.GetEngine();
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// get buffers
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const auto *x = ctx.template Input<Tensor>("X");
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const auto *src = x->template data<T>();
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const auto *out = ctx.template Input<Tensor>("Out");
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auto *dout = ctx.template Input<Tensor>(framework::GradVarName("Out"));
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const auto *diff_dst = dout->template data<T>();
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@ -94,45 +134,73 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
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const T *diff_src = dx->template mutable_data<T>(ctx.GetPlace());
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// get memory dim
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std::vector<int> src_tz = framework::vectorize2int(x->dims());
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// create memory description
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auto data_md = src_tz.size() == 2
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? platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
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mkldnn::memory::format::nc)
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: platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
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mkldnn::memory::format::nchw);
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// create memory primitives
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auto src_memory = mkldnn::memory(
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{data_md, mkldnn_engine}, static_cast<void *>(const_cast<float *>(src)));
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auto diff_src_memory =
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mkldnn::memory({data_md, mkldnn_engine},
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static_cast<void *>(const_cast<float *>(diff_src)));
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auto diff_dst_memory =
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mkldnn::memory({data_md, mkldnn_engine},
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static_cast<void *>(const_cast<float *>(diff_dst)));
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auto backward_desc =
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mkldnn::eltwise_backward::desc(algorithm, data_md, data_md, alpha, beta);
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// retrieve eltwise primitive desc from device context
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const std::string key = ctx.op().Input("Out");
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const std::string key_eltwise_pd = key + "@eltwise_pd";
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const std::shared_ptr<void> forward_pd = dev_ctx.GetBlob(key_eltwise_pd);
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PADDLE_ENFORCE(forward_pd != nullptr,
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"Fail to find eltwise_pd in device context");
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auto *p_forward_pd =
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static_cast<mkldnn::eltwise_forward::primitive_desc *>(forward_pd.get());
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auto eltwise_bwd_prim_desc = mkldnn::eltwise_backward::primitive_desc(
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backward_desc, mkldnn_engine, *p_forward_pd);
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auto eltwise_bwd = mkldnn::eltwise_backward(eltwise_bwd_prim_desc, src_memory,
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diff_dst_memory, diff_src_memory);
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std::vector<int> src_tz = framework::vectorize2int(out->dims());
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const std::string key = gethash(src_tz, algorithm);
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const std::string key_diff_src_mem = key + "@eltwise_diff_src_mem";
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const std::string key_diff_dst_mem = key + "@eltwise_diff_dst_mem";
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const std::string key_grad = key + "@eltwise_grad";
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const std::string key_src_data =
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key + ctx.op().Input("Out") + "@eltwise_fwd_src_data";
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const auto p_src_data =
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std::static_pointer_cast<T *>(dev_ctx.GetBlob(key_src_data));
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const std::string key_src_mem = key + "@eltwise_fwd_src_mem";
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auto p_src_mem =
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std::static_pointer_cast<mkldnn::memory>(dev_ctx.GetBlob(key_src_mem));
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p_src_mem->set_data_handle(*p_src_data.get());
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auto p_grad = std::static_pointer_cast<mkldnn::eltwise_forward::primitive>(
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dev_ctx.GetBlob(key_grad));
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if (p_grad == nullptr) {
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// create memory description
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auto data_md = src_tz.size() == 2
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? platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
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mkldnn::memory::format::nc)
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: platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
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mkldnn::memory::format::nchw);
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// create memory primitives
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std::shared_ptr<void> p_diff_src_mem =
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std::make_shared<mkldnn::memory>(mkldnn::memory(
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{data_md, mkldnn_engine}, platform::to_void_cast(diff_src)));
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dev_ctx.SetBlob(key_diff_src_mem, p_diff_src_mem);
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std::shared_ptr<void> p_diff_dst_mem =
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std::make_shared<mkldnn::memory>(mkldnn::memory(
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{data_md, mkldnn_engine}, platform::to_void_cast(diff_dst)));
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dev_ctx.SetBlob(key_diff_dst_mem, p_diff_dst_mem);
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auto bwd_desc = mkldnn::eltwise_backward::desc(algorithm, data_md, data_md,
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alpha, beta);
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const std::string key_fwd_pd = key + "eltwise_fwd_pd";
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auto *p_fwd_pd = static_cast<mkldnn::eltwise_forward::primitive_desc *>(
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dev_ctx.GetBlob(key_fwd_pd).get());
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auto eltwise_bwd_prim_desc = mkldnn::eltwise_backward::primitive_desc(
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bwd_desc, mkldnn_engine, *p_fwd_pd);
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p_grad = std::make_shared<mkldnn::eltwise_backward>(
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eltwise_bwd_prim_desc, *static_cast<mkldnn::memory *>(p_src_mem.get()),
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*(static_cast<mkldnn::memory *>(p_diff_dst_mem.get())),
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*(static_cast<mkldnn::memory *>(p_diff_src_mem.get())));
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} else {
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// primitives already exist
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auto p_diff_src_mem = std::static_pointer_cast<mkldnn::memory>(
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dev_ctx.GetBlob(key_diff_src_mem));
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auto p_diff_dst_mem = std::static_pointer_cast<mkldnn::memory>(
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dev_ctx.GetBlob(key_diff_dst_mem));
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p_diff_src_mem->set_data_handle(
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platform::to_void_reinterpret_cast(diff_src));
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p_diff_dst_mem->set_data_handle(
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platform::to_void_reinterpret_cast(diff_dst));
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}
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// push primitive to stream and wait until it's executed
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std::vector<mkldnn::primitive> pipeline = {eltwise_bwd};
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std::vector<mkldnn::primitive> pipeline = {*(p_grad.get())};
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mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait();
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}
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} // anonymous namespace
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yuyang18
7 years ago