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- Removed passing X from FWD to GRAD via device context (#18911)

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test=develop

- Extracted key generation from FWD and GRAD into separate function

test=develop

- Compilation fix

test=develop

- another compilation

test=develop
padding_in_crf
Jacek Czaja 6 years ago committed by Tao Luo
parent 22fa4c2d24
commit 5cf2d38594
2 changed files with 34 additions and 42 deletions
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60
paddle/fluid/operators/mkldnn/activation_mkldnn_op.cc
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@ -103,24 +103,8 @@ void eltwise_forward(const framework::ExecutionContext &ctx,
bool is_test = ctx.Attr<bool>("is_test");
std::string key = platform::MKLDNNHandler::GetHash(
src_tz, std::to_string(algorithm) + std::to_string(alpha) +
std::to_string(beta) + ctx.op().Input("X"));
// TODO(jczaja): Make it Thread safe
// save input data and layout to be referred in backward path
const std::string key_src_data = key + "@eltwise_fwd_src_data";
const std::string key_src_layout = key + "@eltwise_fwd_src_layout";
// Just in case some int8 models are run interchangebly
// with float models then format maybe diffrent
key += std::to_string(src_format);
const std::string key_src_mem = key + "@eltwise_fwd_src_mem";
auto p_src_data = std::make_shared<const T *>(x_data);
auto p_src_layout = std::make_shared<memory::format>(src_format);
if (!is_test) {
dev_ctx.SetBlob(key_src_data, p_src_data);
dev_ctx.SetBlob(key_src_layout, p_src_layout);
}
std::string key = platform::ActivationMKLDNNHandler::GetHash(
src_tz, algorithm, src_format, alpha, beta, ctx.op().Input("X"));
platform::ActivationMKLDNNHandler handler(dev_ctx, mkldnn_engine, key);
@ -133,11 +117,6 @@ void eltwise_forward(const framework::ExecutionContext &ctx,
algorithm, md, alpha, beta);
auto src_memory_p = handler.AcquireSrcMemory(md, to_void_cast<T>(x_data));
// jczaja: Workaround, src_memory_p is needed in BWD so it has
// to be accessible under key not dependant on TID
if (!is_test) {
dev_ctx.SetBlob(key_src_mem, src_memory_p);
}
auto dst_memory_p =
handler.AcquireDstMemoryFromPrimitive(to_void_cast<T>(y_data));
@ -158,6 +137,9 @@ void eltwise_grad(const framework::ExecutionContext &ctx,
auto &dev_ctx = ctx.template device_context<MKLDNNDeviceContext>();
const auto &mkldnn_engine = dev_ctx.GetEngine();
const auto *x = ctx.Input<Tensor>("X");
const T *x_data = x->data<T>();
const auto *diff_y = ctx.Input<Tensor>(framework::GradVarName("Out"));
auto *diff_x = ctx.Output<Tensor>(framework::GradVarName("X"));
@ -169,47 +151,41 @@ void eltwise_grad(const framework::ExecutionContext &ctx,
std::vector<int> diff_dst_tz = framework::vectorize2int(diff_y->dims());
// diff_dst and src dims should be the same
auto src_format =
diff_dst_tz.size() == 2 ? mkldnn::memory::format::nc : x->format();
auto diff_y_format =
diff_dst_tz.size() == 2 ? mkldnn::memory::format::nc : diff_y->format();
auto diff_dst_md = platform::MKLDNNMemDesc(
diff_dst_tz, platform::MKLDNNGetDataType<T>(), diff_y_format);
std::string key = platform::MKLDNNHandler::GetHash(
diff_dst_tz, std::to_string(algorithm) + std::to_string(alpha) +
std::to_string(beta) + ctx.op().Input("X"));
std::string key = platform::ActivationMKLDNNHandler::GetHash(
diff_dst_tz, algorithm, src_format, alpha, beta, ctx.op().Input("X"));
const std::string key_src_data = key + "@eltwise_fwd_src_data";
const std::string key_src_layout = key + "@eltwise_fwd_src_layout";
// Get Data from FWD op
const auto p_src_layout =
std::static_pointer_cast<memory::format>(dev_ctx.GetBlob(key_src_layout));
const auto p_src_data =
std::static_pointer_cast<T *>(dev_ctx.GetBlob(key_src_data));
key += std::to_string(*p_src_layout);
const std::string key_src_mem = key + "@eltwise_fwd_src_mem";
auto src_memory =
std::static_pointer_cast<mkldnn::memory>(dev_ctx.GetBlob(key_src_mem));
PADDLE_ENFORCE(src_memory != nullptr,
"Fail to find src_memory in device context");
src_memory->set_data_handle(*p_src_data);
auto src_md = platform::MKLDNNMemDesc(
diff_dst_tz, platform::MKLDNNGetDataType<T>(), src_format);
platform::ActivationMKLDNNHandler handler(dev_ctx, mkldnn_engine, key);
auto src_memory_p = handler.AcquireSrcMemory(src_md, to_void_cast<T>(x_data));
auto diff_dst_memory_p =
handler.AcquireDiffDstMemory(diff_dst_md, to_void_cast<T>(diff_y_data));
auto activation_backward_pd =
handler.AcquireActivationBackwardPrimitiveDescriptor(
algorithm, diff_dst_md, src_memory->get_primitive_desc().desc(),
algorithm, diff_dst_md, src_memory_p->get_primitive_desc().desc(),
alpha, beta);
auto diff_src_memory_p =
handler.AcquireDiffSrcMemoryFromPrimitive(diff_x_data);
auto activation_backward_p = handler.AcquireActivationBackward(
diff_src_memory_p, diff_dst_memory_p, src_memory);
diff_src_memory_p, diff_dst_memory_p, src_memory_p);
// push primitive to stream and wait until it's executed
std::vector<primitive> pipeline;

16
paddle/fluid/platform/mkldnn_reuse.h
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@ -433,6 +433,22 @@ class ActivationMKLDNNHandler : public MKLDNNHandler {
return eltwise_bwd_p;
}
static std::string GetHash(const memory::dims& input_dims,
const mkldnn::algorithm algorithm,
const mkldnn::memory::format fmt,
const float alpha, const float beta,
const std::string& suffix) {
std::string key;
key.reserve(platform::MKLDNNHandler::MaxKeyLength);
platform::MKLDNNHandler::AppendKeyDims(&key, input_dims);
platform::MKLDNNHandler::AppendKey(&key, std::to_string(algorithm));
platform::MKLDNNHandler::AppendKey(&key, std::to_string(fmt));
platform::MKLDNNHandler::AppendKey(&key, std::to_string(alpha));
platform::MKLDNNHandler::AppendKey(&key, std::to_string(beta));
platform::MKLDNNHandler::AppendKey(&key, suffix);
return key;
}
private:
std::shared_ptr<mkldnn::eltwise_forward::primitive_desc> activation_pd_;
std::shared_ptr<mkldnn::eltwise_backward::primitive_desc> activation_bwd_pd_;

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