【Infer Symbolic Shape No.220】Add infer_symbol_shape for rnn (#68882)

* add rnn symbol infer

* fix dropout_state_shape

* fix op_test

* fix unused var

* fix no_check

* fix no_check

* fix

Author: AndPuQing

paddle/fluid/pir/dialect/operator/interface/infer_symbolic_shape/multiary_infer_sym.cc

@@ -3637,11 +3637,117 @@ bool RmsNormOpInferSymbolicShape(
   return true;
 }
 
-// bool RnnOpInferSymbolicShape(pir::Operation *op,
-//                              pir::InferSymbolicShapeContext *infer_context) {
-//   // pass
-//   return true;
-// }
+bool RnnOpInferSymbolicShape(pir::Operation *op,
+                             pir::InferSymbolicShapeContext *infer_context) {
+  const auto &x_shape_or_data =
+      infer_context->GetShapeOrDataForValue(op->operand_source(0));
+  const auto &pre_state_shape_or_data_list =
+      infer_context->GetShapeOrDataForValue(op->operand_source(1))
+          .dyn_cast<symbol::TensorListShapeOrDataDimExprs>();
+  const auto &sequence_length_shape_or_data =
+      infer_context->GetShapeOrDataForValue(op->operand_source(3));
+
+  const std::string &mode = op->attribute<pir::StrAttribute>("mode").AsString();
+  const bool &is_bidirec =
+      op->attribute<pir::BoolAttribute>("is_bidirec").data();
+  const int &hidden_size =
+      op->attribute<pir::Int32Attribute>("hidden_size").data();
+
+  const auto &x_shape = x_shape_or_data.shape();
+  PADDLE_ENFORCE_EQ(x_shape.size(),
+                    3,
+                    common::errors::InvalidArgument(
+                        "The rank of Input in RNN  must be 3. But "
+                        "received Input's rank is %d.",
+                        x_shape.size()));
+
+  if (!sequence_length_shape_or_data.isa<symbol::NullShapeOrDataDimExpr>()) {
+    const auto &sequence_length_shape = sequence_length_shape_or_data.shape();
+    infer_context->AddEqualCstr(x_shape[1], sequence_length_shape[0]);
+  }
+
+  PADDLE_ENFORCE_EQ(pre_state_shape_or_data_list[0].shape().size(),
+                    3,
+                    common::errors::InvalidArgument(
+                        "The rank of PreState in RNN  must be 3. But "
+                        "the received rank is %d.",
+                        pre_state_shape_or_data_list[0].shape().size()));
+  for (size_t i = 0; i < 3; ++i) {
+    details::BuildCstrEqForTensorListAlongAxis(
+        infer_context, pre_state_shape_or_data_list, i);
+  }
+  size_t i = 0;
+  for (; i < pre_state_shape_or_data_list.size(); ++i) {
+    infer_context->AddEqualCstr(x_shape[1],
+                                pre_state_shape_or_data_list[i].shape()[1]);
+  }
+  size_t num_state = mode == "LSTM" ? 2 : 1;
+  PADDLE_ENFORCE_EQ(i,
+                    num_state,
+                    common::errors::InvalidArgument(
+                        "The number of tensors in PreState of %s should be %d, "
+                        "but received %d.",
+                        mode,
+                        2,
+                        i));
+  std::vector<symbol::DimExpr> out_shape = x_shape;
+  out_shape[2] = is_bidirec
+                     ? symbol::DimExpr(static_cast<int64_t>(hidden_size) * 2)
+                     : symbol::DimExpr(static_cast<int64_t>(hidden_size));
+  infer_context->SetShapeOrDataForValue(
+      op->result(0),
+      symbol::ShapeOrDataDimExprs{
+          symbol::TensorShapeOrDataDimExprs(out_shape)});
+
+  size_t state_num = pre_state_shape_or_data_list.size();
+  symbol::TensorListShapeOrDataDimExprs state_shape_or_data_list;
+  for (size_t i = 0; i < state_num; ++i) {
+    state_shape_or_data_list.emplace_back(
+        pre_state_shape_or_data_list[i].shape());
+  }
+  infer_context->SetShapeOrDataForValue(
+      op->result(2), symbol::ShapeOrDataDimExprs{state_shape_or_data_list});
+
+  int gate_num = 4;
+  if (mode == "RNN_RELU" || mode == "RNN_TANH") {
+    gate_num = 1;
+  } else if (mode == "GRU") {
+    gate_num = 3;
+  }
+  const int &num_layers =
+      op->attribute<pir::Int32Attribute>("num_layers").data();
+
+  int hidden_date_idx = num_layers - 1;
+  if (mode == "LSTM") {
+    hidden_date_idx += (gate_num + 2) * num_layers;
+  } else if (mode == "GRU") {
+    hidden_date_idx += (gate_num + 1) * num_layers;
+  } else {
+    hidden_date_idx += gate_num * num_layers;
+  }
+  symbol::DimExpr block_size =
+      symbol::DimExpr(static_cast<int64_t>(num_state)) * x_shape[0] *
+      x_shape[1] * symbol::DimExpr(hidden_size);
+  std::vector<symbol::DimExpr> reserve_shape = {symbol::DimExpr(hidden_size),
+                                                block_size};
+  infer_context->SetShapeOrDataForValue(
+      op->result(3),
+      symbol::ShapeOrDataDimExprs{
+          symbol::TensorShapeOrDataDimExprs(reserve_shape)});
+
+  symbol::DimExpr dropout_state_shape = infer_context->GetNextSymName();
+
+  infer_context->SetShapeOrDataForValue(
+      op->result(1),
+      symbol::ShapeOrDataDimExprs{
+          symbol::TensorShapeOrDataDimExprs({dropout_state_shape})});
+  return true;
+}
+
+bool Rnn_OpInferSymbolicShape(pir::Operation *op,
+                              pir::InferSymbolicShapeContext *infer_context) {
+  return RnnOpInferSymbolicShape(op, infer_context);
+}
 
 // bool RoiPoolOpInferSymbolicShape(pir::Operation *op,
 //                                  pir::InferSymbolicShapeContext

paddle/fluid/pir/dialect/operator/interface/infer_symbolic_shape/multiary_infer_sym.h

@@ -111,7 +111,8 @@ OP_DECLARE_INFER_SYMBOLIC_SHAPE(RandomRouting)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(RandomRouting_)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(RmsNorm)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(RoiPool)
-// OP_DECLARE_INFER_SYMBOLIC_SHAPE(Rnn)
+OP_DECLARE_INFER_SYMBOLIC_SHAPE(Rnn)
+OP_DECLARE_INFER_SYMBOLIC_SHAPE(Rnn_)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(RoiAlign)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(SpectralNorm)
 OP_DECLARE_INFER_SYMBOLIC_SHAPE(SequenceConv)

paddle/phi/ops/yaml/ops.yaml

@@ -4192,7 +4192,7 @@
   optional : sequence_length
   intermediate : reserve
   view : (dropout_state_in -> dropout_state_out)
-  # interfaces : paddle::dialect::InferSymbolicShapeInterface
+  interfaces : paddle::dialect::InferSymbolicShapeInterface
 
 - op : roi_align
   args : (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height=1, int pooled_width=1, float spatial_scale=1.0, int sampling_ratio=-1, bool aligned=false)

test/legacy_test/test_rnn_op.py

@@ -173,7 +173,9 @@ def rocm_rnn_get_place():
 
     def test_output(self):
         self.check_output(
-            no_check_set=['Reserve', 'DropoutState'], check_pir=True
+            no_check_set=['Reserve', 'DropoutState'],
+            check_pir=True,
+            check_symbol_infer=False,
         )
 
     def set_attrs(self):