add seq mode lstm

paddle/fluid/operators/fusion_lstm_op.cc

@@ -15,10 +15,14 @@ limitations under the License. */
 #include "paddle/fluid/operators/fusion_lstm_op.h"
 #include <string>
 #include "paddle/fluid/operators/math/blas.h"
+#include "paddle/fluid/operators/math/cpu_vec.h"
 #include "paddle/fluid/operators/math/detail/activation_functions.h"
 #include "paddle/fluid/operators/math/fc_compute.h"
 #include "paddle/fluid/operators/math/lstm_compute.h"
 #include "paddle/fluid/operators/math/sequence2batch.h"
+#include "paddle/fluid/platform/cpu_info.h"
+
+DEFINE_bool(seq_mode, true, "Use sequence mode");
 
 namespace paddle {
 namespace operators {
@@ -98,7 +102,12 @@ void FusionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
   ctx->ShareLoD("X", "Hidden");
   ctx->ShareLoD("X", "Cell");
 
-  int xx_width = x_dims[1] > wx_dims[1] ? wx_dims[1] : x_dims[1];
+  int xx_width;
+  if (FLAGS_seq_mode) {
+    xx_width = wx_dims[1];
+  } else {
+    xx_width = x_dims[1] > wx_dims[1] ? wx_dims[1] : x_dims[1];
+  }
   ctx->SetOutputDim("XX", {x_dims[0], xx_width});
   ctx->ShareLoD("X", "XX");
 }
@@ -205,10 +214,34 @@ inline void ReorderInitState(const DeviceContext& ctx,
   row_shuffle(ctx, src, index_lod, dst, indexed_src);
 }
 
-template <typename DeviceContext, typename T>
+template <typename T>
 class FuisonLSTMKernel : public framework::OpKernel<T> {
  public:
-  void Compute(const framework::ExecutionContext& ctx) const override {
+  void SeqCompute(const framework::ExecutionContext& ctx) const {
+    using DeviceContext = paddle::platform::CPUDeviceContext;
+    auto* x = ctx.Input<LoDTensor>("X");
+    auto* wx = ctx.Input<Tensor>("WeightX");
+    auto* wh = ctx.Input<Tensor>("WeightH");
+    auto* bias = ctx.Input<Tensor>("Bias");
+
+    auto* xx = ctx.Output<LoDTensor>("XX");
+
+    auto x_dims = x->dims();    // T x M
+    auto wh_dims = wh->dims();  // D x 4D
+    const int M = x_dims[1];    // x frame size
+    const int D4 = wh_dims[1];
+
+    const T* x_data = x->data<T>();
+    const T* wx_data = wx->data<T>();
+    T* xx_data = xx->mutable_data<T>(ctx.GetPlace());
+
+    auto blas = math::GetBlas<DeviceContext, T>(ctx);
+    math::FCCompute<DeviceContext, T>(blas, x_dims[0], D4, M, x_data, wx_data,
+                                      xx_data, bias->data<T>());
+  }
+
+  void BatchCompute(const framework::ExecutionContext& ctx) const {
+    using DeviceContext = platform::CPUDeviceContext;
     auto* x = ctx.Input<LoDTensor>("X");
     auto* wx = ctx.Input<Tensor>("WeightX");
     auto* wh = ctx.Input<Tensor>("WeightH");
@@ -339,6 +372,13 @@ class FuisonLSTMKernel : public framework::OpKernel<T> {
     // restore the output cell state in LoDTensor from the batch cell
     to_seq(dev_ctx, batch_cell, cell_out);
   }
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    if (FLAGS_seq_mode) {
+      SeqCompute(ctx);
+    } else {
+      BatchCompute(ctx);
+    }
+  }
 };
 
 }  // namespace operators
@@ -348,7 +388,5 @@ namespace ops = paddle::operators;
 REGISTER_OPERATOR(fusion_lstm, ops::FusionLSTMOp, ops::FusionLSTMOpMaker,
                   paddle::framework::DefaultGradOpDescMaker<true>);
 
-REGISTER_OP_CPU_KERNEL(
-    fusion_lstm,
-    ops::FuisonLSTMKernel<paddle::platform::CPUDeviceContext, float>,
-    ops::FuisonLSTMKernel<paddle::platform::CPUDeviceContext, double>);
+REGISTER_OP_CPU_KERNEL(fusion_lstm, ops::FuisonLSTMKernel<float>,
+                       ops::FuisonLSTMKernel<double>);