Merge pull request #13237 from tensor-tang/refine/op/peephole

refine fusion lstm/peephole and fusion gru

paddle/fluid/framework/ir/fc_lstm_fuse_pass.cc

@@ -11,6 +11,7 @@
 // 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/fluid/framework/ir/fc_lstm_fuse_pass.h"
 #include <string>
 #include "paddle/fluid/framework/lod_tensor.h"

paddle/fluid/operators/fusion_gru_op.cc

@@ -30,14 +30,7 @@ void FusionGRUOp::InferShape(framework::InferShapeContext* ctx) const {
                  "Input(WeightX) of GRU should not be null.");
   PADDLE_ENFORCE(ctx->HasInput("WeightH"),
                  "Input(WeightH) of GRU should not be null.");
-
   PADDLE_ENFORCE(ctx->HasOutput("XX"), "Output(XX) of GRU should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("ReorderedH0"),
-                 "Output(ReorderedH0) of GRU should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("BatchedInput"),
-                 "Output(BatchedInput) of GRU should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("BatchedOut"),
-                 "Output(BatchedOut) of GRU should not be null.");
   PADDLE_ENFORCE(ctx->HasOutput("Hidden"),
                  "Output(Hidden) of GRU should not be null.");
 
@@ -80,15 +73,20 @@ void FusionGRUOp::InferShape(framework::InferShapeContext* ctx) const {
   }
   framework::DDim out_dims({x_dims[0], frame_size});
   ctx->SetOutputDim("Hidden", out_dims);
-  ctx->SetOutputDim("BatchedInput", {x_dims[0], wx_dims[1]});
-  ctx->SetOutputDim("BatchedOut", out_dims);
   ctx->ShareLoD("X", "Hidden");
-
   int xx_width;
   if (ctx->Attrs().Get<bool>("use_seq")) {
     xx_width = wx_dims[1];
   } else {
     xx_width = x_dims[1] > wx_dims[1] ? wx_dims[1] : x_dims[1];
+    PADDLE_ENFORCE(ctx->HasOutput("ReorderedH0"),
+                   "Output(ReorderedH0) of GRU should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("BatchedInput"),
+                   "Output(BatchedInput) of GRU should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("BatchedOut"),
+                   "Output(BatchedOut) of GRU should not be null.");
+    ctx->SetOutputDim("BatchedInput", {x_dims[0], wx_dims[1]});
+    ctx->SetOutputDim("BatchedOut", out_dims);
   }
   ctx->SetOutputDim("XX", {x_dims[0], xx_width});
   ctx->ShareLoD("X", "XX");

paddle/fluid/operators/fusion_lstm_op.cc

@@ -38,16 +38,6 @@ void FusionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
                  "Output(Hidden) of LSTM should not be null.");
   PADDLE_ENFORCE(ctx->HasOutput("Cell"),
                  "Output(Cell) of LSTM should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("BatchedInput"),
-                 "Output(BatchedInput) of LSTM should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("BatchedHidden"),
-                 "Output(BatchedHidden) of LSTM should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("BatchedCell"),
-                 "Output(BatchedCell) of LSTM should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("ReorderedH0"),
-                 "Output(ReorderedH0) of LSTM should not be null.");
-  PADDLE_ENFORCE(ctx->HasOutput("ReorderedC0"),
-                 "Output(ReorderedC0) of LSTM should not be null.");
 
   auto x_dims = ctx->GetInputDim("X");
   PADDLE_ENFORCE_EQ(x_dims.size(), 2, "Input(X)'s rank must be 2.");
@@ -88,28 +78,36 @@ void FusionLSTMOp::InferShape(framework::InferShapeContext* ctx) const {
   PADDLE_ENFORCE_EQ(b_dims.size(), 2, "The rank of Input(Bias) should be 2.");
   PADDLE_ENFORCE_EQ(b_dims[0], 1,
                     "The first dimension of Input(Bias) should be 1.");
-
-  auto use_peepholes = ctx->Attrs().Get<bool>("use_peepholes");
-  PADDLE_ENFORCE_EQ(b_dims[1], (use_peepholes ? 7 : 4) * frame_size,
-                    "The second dimension of Input(Bias) should be "
-                    "7 * %d if enable peepholes connection or"
-                    "4 * %d if disable peepholes",
-                    frame_size, frame_size);
+  PADDLE_ENFORCE_EQ(
+      b_dims[1], (ctx->Attrs().Get<bool>("use_peepholes") ? 7 : 4) * frame_size,
+      "The second dimension of Input(Bias) should be "
+      "7 * %d if enable peepholes connection or"
+      "4 * %d if disable peepholes",
+      frame_size, frame_size);
 
   framework::DDim out_dims({x_dims[0], frame_size});
   ctx->SetOutputDim("Hidden", out_dims);
   ctx->SetOutputDim("Cell", out_dims);
-  ctx->SetOutputDim("BatchedInput", {x_dims[0], wx_dims[1]});
-  ctx->SetOutputDim("BatchedHidden", out_dims);
-  ctx->SetOutputDim("BatchedCell", out_dims);
   ctx->ShareLoD("X", "Hidden");
   ctx->ShareLoD("X", "Cell");
-
   int xx_width;
   if (ctx->Attrs().Get<bool>("use_seq")) {
     xx_width = wx_dims[1];
   } else {
     xx_width = x_dims[1] > wx_dims[1] ? wx_dims[1] : x_dims[1];
+    PADDLE_ENFORCE(ctx->HasOutput("BatchedInput"),
+                   "Output(BatchedInput) of LSTM should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("BatchedHidden"),
+                   "Output(BatchedHidden) of LSTM should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("BatchedCell"),
+                   "Output(BatchedCell) of LSTM should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("ReorderedH0"),
+                   "Output(ReorderedH0) of LSTM should not be null.");
+    PADDLE_ENFORCE(ctx->HasOutput("ReorderedC0"),
+                   "Output(ReorderedC0) of LSTM should not be null.");
+    ctx->SetOutputDim("BatchedInput", {x_dims[0], wx_dims[1]});
+    ctx->SetOutputDim("BatchedHidden", out_dims);
+    ctx->SetOutputDim("BatchedCell", out_dims);
   }
   ctx->SetOutputDim("XX", {x_dims[0], xx_width});
   ctx->ShareLoD("X", "XX");
@@ -232,18 +230,18 @@ class FuisonLSTMKernel : public framework::OpKernel<T> {
     act_cand = act_functor(act_cand_str);                                      \
   }
 
-#define INIT_BASE_INPUT_OUTPUT                          \
-  auto* x = ctx.Input<LoDTensor>("X");                  \
-  auto* h0 = ctx.Input<Tensor>("H0");                   \
-  auto* c0 = ctx.Input<Tensor>("C0");                   \
-  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* hidden_out = ctx.Output<LoDTensor>("Hidden");   \
-  auto* cell_out = ctx.Output<LoDTensor>("Cell");       \
-  bool use_peepholes = ctx.Attr<bool>("use_peepholes"); \
-  bool is_reverse = ctx.Attr<bool>("is_reverse");
+#define INIT_BASE_INPUT_OUTPUT                        \
+  auto* x = ctx.Input<LoDTensor>("X");                \
+  auto* h0 = ctx.Input<Tensor>("H0");                 \
+  auto* c0 = ctx.Input<Tensor>("C0");                 \
+  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* hidden_out = ctx.Output<LoDTensor>("Hidden"); \
+  auto* cell_out = ctx.Output<LoDTensor>("Cell");     \
+  bool is_reverse = ctx.Attr<bool>("is_reverse");     \
+  bool use_peepholes = ctx.Attr<bool>("use_peepholes");
 
 #define INIT_BASE_SIZES                  \
   auto x_dims = x->dims();   /* T x M*/  \
@@ -254,172 +252,183 @@ class FuisonLSTMKernel : public framework::OpKernel<T> {
   const int D3 = D * 3;                  \
   const int D4 = wh_dims[1];
 
+#define INIT_BASE_INPUT_DATAS                                        \
+  const T* x_data = x->data<T>();                                    \
+  const T* wx_data = wx->data<T>();                                  \
+  const T* wh_data = wh->data<T>();                                  \
+  /* diagonal weight*/                                               \
+  const T* wc_data = bias->data<T>() + D4;                           \
+  /* for peephole only*/                                             \
+  Tensor checked_cell;                                               \
+  T* checked_cell_data = nullptr;                                    \
+  auto place = ctx.GetPlace();                                       \
+  if (use_peepholes) {                                               \
+    /* w_ic * Ct-1, w_fc * Ct-1  ; w_oc * Ct => ih*/                 \
+    checked_cell_data = checked_cell.mutable_data<T>({2, D}, place); \
+  }
+
+/// Compute LSTM
+#define GEMM_WH_ADDON(bs, prev, out)                                           \
+  blas.GEMM(CblasNoTrans, CblasNoTrans, bs, D4, D, static_cast<T>(1), prev, D, \
+            wh_data, D4, static_cast<T>(1), out, D4)
+
+// gates: W_ch, W_ih, W_fh, W_oh
+#define GET_Ct(ct_1, gates, ct)                   \
+  /* C_t = C_t-1 * fgated + cand_gated * igated*/ \
+  act_cand(D, gates, gates);                      \
+  blas.VMUL(D, gates, gates + D, gates + D);      \
+  blas.VMUL(D, ct_1, gates + D2, gates + D2);     \
+  blas.VADD(D, gates + D, gates + D2, ct)
+
+#define GET_Ht(ct, gates, ht)        \
+  /* H_t = act_cell(C_t) * ogated */ \
+  act_cell(D, ct, gates + D2);       \
+  blas.VMUL(D, gates + D2, gates + D3, ht)
+
+#define GET_Ct_NOH0C0(gates, ct)     \
+  /* C_t = igated * cgated*/         \
+  act_gate(D, gates + D, gates + D); \
+  act_cand(D, gates, gates);         \
+  blas.VMUL(D, gates, gates + D, ct)
+
+#define COMPUTE_CtHt_NOH0C0(gates, ct, ht) \
+  GET_Ct_NOH0C0(gates, ct);                \
+  act_gate(D, gates + D3, gates + D3);     \
+  GET_Ht(ct, gates, ht)
+
+#define COMPUTE_CtHt_PEEPHOLE_NOH0C0(gates, ct, ht) \
+  GET_Ct_NOH0C0(gates, ct);                         \
+  /* get outgated, put W_oc * C_t on igated */      \
+  blas.VMUL(D, wc_data + D2, ct, gates + D);        \
+  blas.VADD(D, gates + D, gates + D3, gates + D3);  \
+  act_gate(D, gates + D3, gates + D3);              \
+  GET_Ht(ct, gates, ht)
+
+#define COMPUTE_CtHt(gates, ct_1, ct, ht) \
+  act_gate(D3, gates + D, gates + D);     \
+  GET_Ct(ct_1, gates, ct);                \
+  GET_Ht(ct, gates, ht)
+
+#define COMPUTE_CtHt_PEEPHOLE(gates, ct_1, ct, ht)        \
+  /* get fgated and igated*/                              \
+  blas.VMUL(D, wc_data, ct_1, checked_cell_data);         \
+  blas.VMUL(D, wc_data + D, ct_1, checked_cell_data + D); \
+  blas.VADD(D2, checked_cell_data, gates + D, gates + D); \
+  act_gate(D2, gates + D, gates + D);                     \
+  GET_Ct(ct_1, gates, ct);                                \
+  /* get ogated*/                                         \
+  blas.VMUL(D, wc_data + D2, ct, gates + D);              \
+  blas.VADD(D, gates + D, gates + D3, gates + D3);        \
+  act_gate(D, gates + D3, gates + D3);                    \
+  GET_Ht(ct, gates, ht)
+
   void SeqCompute(const framework::ExecutionContext& ctx) const {
     using DeviceContext = paddle::platform::CPUDeviceContext;
     INIT_BASE_INPUT_OUTPUT
     INIT_BASE_SIZES
     INIT_VEC_FUNC
+    INIT_BASE_INPUT_DATAS
 
     auto x_lod = x->lod();
     const int total_T = x_dims[0];
-    const int N = x_lod[0].size() - 1;  // batch size
-
-    const T* x_data = x->data<T>();
+    const int N = x_lod[0].size() - 1;
     const T* h0_data = h0 ? h0->data<T>() : nullptr;
     const T* c0_data = c0 ? c0->data<T>() : nullptr;
-    const T* bias_data = bias->data<T>();
-    const T* wc_data = bias_data + D4;  // w_ic, w_fc, w_oc
-    const T* wx_data = wx->data<T>();
-    const T* wh_data = wh->data<T>();
-
-    T* xx_data = xx->mutable_data<T>(ctx.GetPlace());
-    T* hidden_out_data = hidden_out->mutable_data<T>(ctx.GetPlace());
-    T* cell_out_data = cell_out->mutable_data<T>(ctx.GetPlace());
-
-    // use local variable
-    framework::DDim check_dims({3, D});
-    Tensor checked_cell;  // w_ic * Ct-1, w_fc * Ct-1, w_oc * Ct
-    auto checked_cell_data =
-        checked_cell.mutable_data<T>(check_dims, ctx.GetPlace());
-
+    T* xx_data = xx->mutable_data<T>(place);
+    T* h_out_data = hidden_out->mutable_data<T>(place);
+    T* c_out_data = cell_out->mutable_data<T>(place);
     auto blas = math::GetBlas<DeviceContext, T>(ctx);
     math::FCCompute<DeviceContext, T>(blas, total_T, D4, M, x_data, wx_data,
                                       xx_data, bias->data<T>());
+
     int xx_offset = D4;
     int gate_offset = D;
     if (is_reverse) {
       const int offset = (total_T - 1) * D;
       xx_data = xx_data + offset * 4;
-      hidden_out_data = hidden_out_data + offset;
-      cell_out_data = cell_out_data + offset;
+      h_out_data = h_out_data + offset;
+      c_out_data = c_out_data + offset;
       xx_offset = -D4;
       gate_offset = -D;
     }
 
-    auto move_step = [&]() {
-      xx_data = xx_data + xx_offset;
-      hidden_out_data = hidden_out_data + gate_offset;
-      cell_out_data = cell_out_data + gate_offset;
-    };
-
-    for (int i = 0; i < N; ++i) {
-      int bid = is_reverse ? N - 1 - i : i;
-      int seq_len = x_lod[0][bid + 1] - x_lod[0][bid];
-      const T* prev_c_data = nullptr;
-      const T* prev_h_data = nullptr;
-
-      int tstart = 0;
-      if (h0_data) {
-        prev_h_data = h0_data + bid * D;
-        prev_c_data = c0_data + bid * D;
-      } else {
-        // If step == 0 and there is no initialized hidden state, that is to say
-        // the H0 is zeros. Then W_h * H_t-1 can be skipped
-
-        // ~C_t
-        act_cand(D, xx_data, xx_data);
-        if (use_peepholes) {
-          // I_t, F_t
-          act_gate(D2, xx_data + D, xx_data + D);
-        } else {
-          // I_t, F_t, O_t
-          act_gate(D3, xx_data + D, xx_data + D);
-        }
-        // C_t = I_t * ~C_t
-        blas.VMUL(D, xx_data, xx_data + D, cell_out_data);
-
-        if (use_peepholes) {
-          // + W_oc * C_t for peephole connection
-          blas.VMUL(D, wc_data + D2, cell_out_data, checked_cell_data + D2);
-          blas.VADD(D, xx_data + D3, checked_cell_data + D2, xx_data + D3);
-          // O_t
-          act_gate(D, xx_data + D3, xx_data + D3);
-        }
-
-        // hidden out= act_state(cellout) * outgate
-        act_cell(D, cell_out_data, xx_data + D2);
-        // H_t = O_t * act_state(C_t)
-        blas.VMUL(D, xx_data + D2, xx_data + D3, hidden_out_data);
-
-        // prev
-        prev_h_data = hidden_out_data;
-        prev_c_data = cell_out_data;
-
-        tstart = 1;
-        move_step();
-      }
-
-      for (int step = tstart; step < seq_len; ++step) {
-        // + W_h * H_t-1
-        blas.GEMM(CblasNoTrans, CblasNoTrans, 1, D4, D, static_cast<T>(1),
-                  prev_h_data, D, wh_data, D4, static_cast<T>(1), xx_data, D4);
+#define MOVE_ONE_STEP                    \
+  prev_h_data = h_out_data;              \
+  prev_c_data = c_out_data;              \
+  xx_data = xx_data + xx_offset;         \
+  h_out_data = h_out_data + gate_offset; \
+  c_out_data = c_out_data + gate_offset
+
+#define PROCESS_H0C0_DEFINES                       \
+  int bid = is_reverse ? N - 1 - i : i;            \
+  int seq_len = x_lod[0][bid + 1] - x_lod[0][bid]; \
+  const T* prev_c_data = nullptr;                  \
+  const T* prev_h_data = nullptr;                  \
+  int tstart = 0
+
+#define PROCESS_H0C0_PEEPHOLE                                      \
+  PROCESS_H0C0_DEFINES;                                            \
+  if (h0_data) {                                                   \
+    prev_h_data = h0_data + bid * D;                               \
+    prev_c_data = c0_data + bid * D;                               \
+  } else {                                                         \
+    COMPUTE_CtHt_PEEPHOLE_NOH0C0(xx_data, c_out_data, h_out_data); \
+    MOVE_ONE_STEP;                                                 \
+    tstart = 1;                                                    \
+  }
 
-        // ~C_t
-        act_cand(D, xx_data, xx_data);
+#define PROCESS_H0C0                                      \
+  PROCESS_H0C0_DEFINES;                                   \
+  if (h0_data) {                                          \
+    prev_h_data = h0_data + bid * D;                      \
+    prev_c_data = c0_data + bid * D;                      \
+  } else {                                                \
+    COMPUTE_CtHt_NOH0C0(xx_data, c_out_data, h_out_data); \
+    MOVE_ONE_STEP;                                        \
+    tstart = 1;                                           \
+  }
 
-        if (use_peepholes) {
-          // + W_ic|W_fc * C_t-1 for peephole connection
-          blas.VMUL(D, wc_data, prev_c_data, checked_cell_data);
-          blas.VMUL(D, wc_data + D, prev_c_data, checked_cell_data + D);
-          blas.VADD(D2, xx_data + D, checked_cell_data, xx_data + D);
-          // I_t, F_t
-          act_gate(D2, xx_data + D, xx_data + D);
-        } else {
-          // I_t, F_t, O_t
-          act_gate(D3, xx_data + D, xx_data + D);
+    if (use_peepholes) {
+      for (int i = 0; i < N; ++i) {
+        PROCESS_H0C0_PEEPHOLE
+        for (int step = tstart; step < seq_len; ++step) {
+          GEMM_WH_ADDON(1, prev_h_data, xx_data);
+          COMPUTE_CtHt_PEEPHOLE(xx_data, prev_c_data, c_out_data, h_out_data);
+          MOVE_ONE_STEP;
         }
-
-        // F_t * C_t-1
-        blas.VMUL(D, xx_data + D2, prev_c_data, xx_data + D2);
-        // I_t * ~C_t
-        blas.VMUL(D, xx_data, xx_data + D, xx_data + D);
-        // C_t = F_t * C_t-1 + I_t * ~C_t
-        blas.VADD(D, xx_data + D, xx_data + D2, cell_out_data);
-
-        if (use_peepholes) {
-          // + W_oc * C_t for peephole connection
-          blas.VMUL(D, wc_data + D2, cell_out_data, checked_cell_data + D2);
-          blas.VADD(D, xx_data + D3, checked_cell_data + D2, xx_data + D3);
-          // O_t
-          act_gate(D, xx_data + D3, xx_data + D3);
+      }
+    } else {
+      for (int i = 0; i < N; ++i) {
+        PROCESS_H0C0
+        for (int step = tstart; step < seq_len; ++step) {
+          GEMM_WH_ADDON(1, prev_h_data, xx_data);
+          COMPUTE_CtHt(xx_data, prev_c_data, c_out_data, h_out_data);
+          MOVE_ONE_STEP;
         }
-
-        // hidden out= act_state(cellout) * outgate
-        act_cell(D, cell_out_data, xx_data + D2);
-        // H_t = O_t * act_state(C_t)
-        blas.VMUL(D, xx_data + D2, xx_data + D3, hidden_out_data);
-
-        // prev
-        prev_h_data = hidden_out_data;
-        prev_c_data = cell_out_data;
-
-        move_step();
-      }  // for each step in batch
-    }    // for each batch
+      }
+    }
+#undef PROCESS_H0C0_DEFINES
+#undef PROCESS_H0C0_PEEPHOLE
+#undef PROCESS_H0C0
+#undef MOVE_ONE_STEP
   }
 
   void BatchCompute(const framework::ExecutionContext& ctx) const {
     using DeviceContext = platform::CPUDeviceContext;
     INIT_BASE_INPUT_OUTPUT
-    if (x->lod()[0].size() == 2) {  // batch size == 1
+    if (x->lod()[0].size() == 2) {
       SeqCompute(ctx);
       return;
     }
     INIT_BASE_SIZES
     INIT_VEC_FUNC
+    INIT_BASE_INPUT_DATAS
 
     auto* reordered_h0 = ctx.Output<Tensor>("ReorderedH0");
     auto* reordered_c0 = ctx.Output<Tensor>("ReorderedC0");
     auto* batched_input = ctx.Output<LoDTensor>("BatchedInput");
     auto* batched_c_out = ctx.Output<LoDTensor>("BatchedCell");
     auto* batched_h_out = ctx.Output<LoDTensor>("BatchedHidden");
-
-    const T* x_data = x->data<T>();
-    const T* wx_data = wx->data<T>();
-    const T* wh_data = wh->data<T>();
-    const T* bias_data = bias->data<T>();
-    const T* wc_data = bias_data + D4;  // w_ic, w_fc, w_oc
-    auto place = ctx.GetPlace();
     T* xx_data = xx->mutable_data<T>(place);
     T* batched_input_data = batched_input->mutable_data<T>(place);
     T* batched_c_out_data = batched_c_out->mutable_data<T>(place);
@@ -427,12 +436,6 @@ class FuisonLSTMKernel : public framework::OpKernel<T> {
     hidden_out->mutable_data<T>(place);
     cell_out->mutable_data<T>(place);
 
-    // use local variable
-    framework::DDim check_dims({3, D});
-    Tensor checked_cell;  // w_ic * Ct-1, w_fc * Ct-1, w_oc * Ct
-    auto checked_cell_data =
-        checked_cell.mutable_data<T>(check_dims, ctx.GetPlace());
-
     math::LoDTensor2BatchFunctor<DeviceContext, T> to_batch;
     auto& dev_ctx = ctx.template device_context<DeviceContext>();
     auto blas = math::GetBlas<DeviceContext, T>(dev_ctx);
@@ -454,27 +457,17 @@ class FuisonLSTMKernel : public framework::OpKernel<T> {
     reordered_h0->Resize({max_bs, D});
     reordered_c0->Resize({max_bs, D});
 
-    T* prev_batch_h_data = nullptr;
-    T* prev_batch_c_data = nullptr;
-    T* cur_batch_in_data = batched_input_data;
-    T* cur_batch_h_out_data = batched_h_out_data;
-    T* cur_batch_c_out_data = batched_c_out_data;
-
-    auto move_step = [&](int bs) {
-      cur_batch_in_data += bs * D4;
-      cur_batch_c_out_data += bs * D;
-      cur_batch_h_out_data += bs * D;
-    };
-
     int tstart = 0;
+    T* prev_h_data = nullptr;
+    T* prev_c_data = nullptr;
     if (h0) {
       // reorder h0, c0
       T* reordered_h0_data = reordered_h0->mutable_data<T>(place);
       T* reordered_c0_data = reordered_c0->mutable_data<T>(place);
       const T* h0_data = h0->data<T>();
       const T* c0_data = c0->data<T>();
-      prev_batch_h_data = reordered_h0_data;
-      prev_batch_c_data = reordered_c0_data;
+      prev_h_data = reordered_h0_data;
+      prev_c_data = reordered_c0_data;
       size_t sz = sizeof(T) * D;
       for (int i = 0; i < max_bs; ++i) {
         std::memcpy(reordered_h0_data, h0_data + seq_order[i] * D, sz);
@@ -483,123 +476,80 @@ class FuisonLSTMKernel : public framework::OpKernel<T> {
         reordered_c0_data += D;
       }
     } else {
-      // Compute with no H0/C0
-      T* cur_in_data = cur_batch_in_data;
-      T* cur_c_out_data = cur_batch_c_out_data;
-      T* cur_h_out_data = cur_batch_h_out_data;
-
-      // If step == 0 and there is no initialized hidden state, that is to say
-      // the H0 is zeros. Then W_h * H_t-1 can be skiped
-
-      for (int i = 0; i < max_bs; ++i) {  // iterate each data in 1st batch
-        // ~C_t
-        act_cand(D, cur_in_data, cur_in_data);
-
-        if (use_peepholes) {
-          // I_t, F_t
-          act_gate(D2, cur_in_data + D, cur_in_data + D);
-        } else {
-          // I_t, F_t, O_t
-          act_gate(D3, cur_in_data + D, cur_in_data + D);
-        }
-
-        // C_t = I_t * ~C_t
-        blas.VMUL(D, cur_in_data, cur_in_data + D, cur_c_out_data);
-
+      // compute without h0, c0
+      T* cur_in_data = batched_input_data;
+      T* cur_h_out_data = batched_h_out_data;
+      T* cur_c_out_data = batched_c_out_data;
+      for (int i = 0; i < max_bs; ++i) {
+        GET_Ct_NOH0C0(cur_in_data, cur_c_out_data);
         if (use_peepholes) {
-          // + W_oc * C_t for peephole connection
-          blas.VMUL(D, wc_data + D2, cur_c_out_data, checked_cell_data + D2);
-          blas.VADD(D, cur_in_data + D3, checked_cell_data + D2,
-                    cur_in_data + D3);
-          // O_t
-          act_gate(D, cur_in_data + D3, cur_in_data + D3);
+          blas.VMUL(D, wc_data + D2, cur_c_out_data, cur_in_data + D);
+          blas.VADD(D, cur_in_data + D, cur_in_data + D3, cur_in_data + D3);
         }
-
-        // hidden out= act_state(cellout) * outgate
-        act_cell(D, cur_c_out_data, cur_in_data + D2);
-        // H_t = O_t * act_state(C_t)
-        blas.VMUL(D, cur_in_data + D2, cur_in_data + D3, cur_h_out_data);
-
-        // move to next data in the same batch
+        act_gate(D, cur_in_data + D3, cur_in_data + D3);
+        GET_Ht(cur_c_out_data, cur_in_data, cur_h_out_data);
         cur_in_data += D4;
         cur_c_out_data += D;
         cur_h_out_data += D;
       }
-
-      // move to data for next timestep
-      prev_batch_h_data = cur_batch_h_out_data;
-      prev_batch_c_data = cur_batch_c_out_data;
-      move_step(max_bs);
       tstart = 1;
+      prev_h_data = batched_h_out_data;
+      prev_c_data = batched_c_out_data;
     }
-
     const auto& batch_starts = batched_lod[0];
     const int max_seq_len = batch_starts.size() - 1;
-    for (int step = tstart; step < max_seq_len; ++step) {
-      const int cur_bs = batch_starts[step + 1] - batch_starts[step];
-      // + W_h * H_t-1
-      blas.GEMM(CblasNoTrans, CblasNoTrans, cur_bs, D4, D, static_cast<T>(1),
-                prev_batch_h_data, D, wh_data, D4, static_cast<T>(1),
-                cur_batch_in_data, D4);
-
-      T* cur_in_data = cur_batch_in_data;
-      T* cur_c_out_data = cur_batch_c_out_data;
-      T* cur_h_out_data = cur_batch_h_out_data;
-      T* prev_c_data = prev_batch_c_data;  // NULL if no C0 in step0
-      T* prev_h_data = prev_batch_h_data;  // NULL if no H0 in step0
-      auto next_data_in_batch = [&]() {
-        cur_in_data += D4;
-        cur_c_out_data += D;
-        cur_h_out_data += D;
-        prev_c_data = prev_c_data ? prev_c_data + D : nullptr;
-        prev_h_data = prev_h_data ? prev_h_data + D : nullptr;
-      };
-
-      for (int i = 0; i < cur_bs; ++i) {  // iterate each data in same batch
-        // ~C_t
-        act_cand(D, cur_in_data, cur_in_data);
-
-        if (use_peepholes) {
-          // + W_ic|W_fc * C_t-1 for peephole connection
-          blas.VMUL(D, wc_data, prev_c_data, checked_cell_data);
-          blas.VMUL(D, wc_data + D, prev_c_data, checked_cell_data + D);
-          blas.VADD(D2, cur_in_data + D, checked_cell_data, cur_in_data + D);
-          // I_t, F_t
-          act_gate(D2, cur_in_data + D, cur_in_data + D);
-        } else {
-          // I_t, F_t, O_t
-          act_gate(D3, cur_in_data + D, cur_in_data + D);
+    const int offset = tstart * max_bs * D;
+    batched_input_data = batched_input_data + offset * 4;
+    batched_h_out_data = batched_h_out_data + offset;
+    batched_c_out_data = batched_c_out_data + offset;
+
+#define DEFINE_CUR                        \
+  T* cur_in_data = batched_input_data;    \
+  T* cur_prev_c_data = prev_c_data;       \
+  T* cur_c_out_data = batched_c_out_data; \
+  T* cur_h_out_data = batched_h_out_data
+
+#define MOVE_ONE_BATCH  \
+  cur_in_data += D4;    \
+  cur_prev_c_data += D; \
+  cur_c_out_data += D;  \
+  cur_h_out_data += D
+
+#define MOVE_ONE_STEP                  \
+  prev_c_data = batched_c_out_data;    \
+  prev_h_data = batched_h_out_data;    \
+  batched_c_out_data = cur_c_out_data; \
+  batched_h_out_data = cur_h_out_data; \
+  batched_input_data = cur_in_data
+
+    if (use_peepholes) {
+      for (int step = tstart; step < max_seq_len; ++step) {
+        const int cur_bs = batch_starts[step + 1] - batch_starts[step];
+        GEMM_WH_ADDON(cur_bs, prev_h_data, batched_input_data);
+        DEFINE_CUR;
+        for (int i = 0; i < cur_bs; ++i) {
+          COMPUTE_CtHt_PEEPHOLE(cur_in_data, cur_prev_c_data, cur_c_out_data,
+                                cur_h_out_data);
+          MOVE_ONE_BATCH;
         }
-
-        // F_t * C_t-1
-        blas.VMUL(D, cur_in_data + D2, prev_c_data, cur_in_data + D2);
-        // I_t * ~C_t
-        blas.VMUL(D, cur_in_data, cur_in_data + D, cur_in_data + D);
-        // C_t = F_t * C_t-1 + I_t * ~C_t
-        blas.VADD(D, cur_in_data + D, cur_in_data + D2, cur_c_out_data);
-
-        if (use_peepholes) {
-          // + W_oc * C_t for peephole connection
-          blas.VMUL(D, wc_data + D2, cur_c_out_data, checked_cell_data + D2);
-          blas.VADD(D, cur_in_data + D3, checked_cell_data + D2,
-                    cur_in_data + D3);
-          // O_t
-          act_gate(D, cur_in_data + D3, cur_in_data + D3);
+        MOVE_ONE_STEP;
+      }
+    } else {
+      for (int step = tstart; step < max_seq_len; ++step) {
+        const int cur_bs = batch_starts[step + 1] - batch_starts[step];
+        GEMM_WH_ADDON(cur_bs, prev_h_data, batched_input_data);
+        DEFINE_CUR;
+        for (int i = 0; i < cur_bs; ++i) {
+          COMPUTE_CtHt(cur_in_data, cur_prev_c_data, cur_c_out_data,
+                       cur_h_out_data);
+          MOVE_ONE_BATCH;
         }
-
-        // hidden out= act_state(cellout) * outgate
-        act_cell(D, cur_c_out_data, cur_in_data + D2);
-        // H_t = O_t * act_state(C_t)
-        blas.VMUL(D, cur_in_data + D2, cur_in_data + D3, cur_h_out_data);
-
-        // move to next data in same batch
-        next_data_in_batch();
+        MOVE_ONE_STEP;
       }
-      // move to data for next timestep
-      prev_batch_h_data = cur_batch_h_out_data;
-      prev_batch_c_data = cur_batch_c_out_data;
-      move_step(cur_bs);
     }
+#undef MOVE_ONE_STEP
+#undef MOVE_ONE_BATCH
+#undef DEFINE_CUR
 
     math::Batch2LoDTensorFunctor<DeviceContext, T> to_seq;
     batched_h_out->set_lod(batched_lod);
@@ -615,6 +565,16 @@ class FuisonLSTMKernel : public framework::OpKernel<T> {
       BatchCompute(ctx);
     }
   }
+
+#undef COMPUTE_CtHt_PEEPHOLE
+#undef COMPUTE_CtHt
+#undef GET_Ct_NOH0C0
+#undef COMPUTE_CtHt_NOH0C0
+#undef COMPUTE_CtHt_PEEPHOLE_NOH0C0
+#undef GET_Ht
+#undef GET_Ct
+#undef GEMM_WH_ADDON
+#undef INIT_BASE_INPUT_DATAS
 #undef INIT_BASE_SIZES
 #undef INIT_BASE_INPUT_OUTPUT
 #undef INIT_VEC_FUNC

python/paddle/fluid/tests/unittests/test_fusion_lstm_op.py

@@ -53,12 +53,11 @@ class TestFusionLSTMOp(OpTest):
         self.M = 8
         self.D = 16
         self.has_initial_state = False
+        self.use_peepholes = False
         self.is_reverse = False
         self.act_gate = 'sigmoid'
         self.act_cell = 'tanh'
         self.act_cand = 'tanh'
-        self.use_peepholes = False
-        self.use_seq = False
         self.set_conf()
 
         T = sum(self.lod[0])
@@ -108,7 +107,6 @@ class TestFusionLSTMOp(OpTest):
         }
         self.attrs = {
             'use_peepholes': self.use_peepholes,
-            'use_seq': self.use_seq,
             'is_reverse': self.is_reverse,
             'gate_activation': self.act_gate,
             'cell_activation': self.act_cell,
@@ -178,50 +176,18 @@ class TestFusionLSTMOpPeepholesReverse(TestFusionLSTMOp):
         self.is_reverse = True
 
 
-class TestFusionLSTMOpPoopholesBS1(TestFusionLSTMOp):
+class TestFusionLSTMOpPeepholesInitReverse(TestFusionLSTMOp):
     def set_conf(self):
         self.use_peepholes = True
-        self.lod = [[3]]
-        self.D = 16
-
-
-class TestFusionLSTMOpSeqInit(TestFusionLSTMOp):
-    def set_conf(self):
-        self.use_seq = True
-        self.has_initial_state = True
-
-
-class TestFusionLSTMOpSeqReverse(TestFusionLSTMOp):
-    def set_conf(self):
-        self.use_seq = True
-        self.is_reverse = True
-
-
-class TestFusionLSTMOpSeqInitReverse(TestFusionLSTMOp):
-    def set_conf(self):
-        self.use_seq = True
         self.has_initial_state = True
         self.is_reverse = True
 
 
-class TestFusionLSTMOpSeqPeepholes(TestFusionLSTMOp):
+class TestFusionLSTMOpPeepholesBS1(TestFusionLSTMOp):
     def set_conf(self):
-        self.use_seq = True
         self.use_peepholes = True
-
-
-class TestFusionLSTMOpSeqPeepholesInit(TestFusionLSTMOp):
-    def set_conf(self):
-        self.use_seq = True
-        self.use_peepholes = True
-        self.has_initial_state = True
-
-
-class TestFusionLSTMOpSeqPeepholesReverse(TestFusionLSTMOp):
-    def set_conf(self):
-        self.use_seq = True
-        self.use_peepholes = True
-        self.is_reverse = True
+        self.lod = [[2]]
+        self.D = 8
 
 
 if __name__ == '__main__':