[PTen]Remove infershape of Reshape OP

paddle/fluid/framework/infershape_utils.cc

@@ -20,6 +20,7 @@ limitations under the License. */
 #include "paddle/fluid/framework/framework.pb.h"
 #include "paddle/fluid/framework/pten_utils.h"
 #include "paddle/fluid/platform/enforce.h"
+#include "paddle/phi/common/scalar_array.h"
 #include "paddle/phi/core/compat/arg_map_context.h"
 #include "paddle/phi/core/compat/convert_utils.h"
 #include "paddle/phi/core/compat/op_utils.h"
@@ -54,7 +55,12 @@ class InferShapeArgumentMappingContext : public phi::ArgumentMappingContext {
   }
 
   size_t InputSize(const std::string& name) const override {
-    return ctx_.Inputs(name).size();
+    if (ctx_.HasInputs(name)) {
+      return ctx_.Inputs(name).size();
+    } else if (ctx_.HasInput(name)) {
+      return 1;
+    }
+    return 0;
   }
 
   size_t OutputSize(const std::string& name) const override {
@@ -288,6 +294,16 @@ phi::InferMetaContext BuildInferMetaContext(InferShapeContext* ctx,
   auto& attr_names = std::get<1>(signature.args);
   auto& output_names = std::get<2>(signature.args);
 
+  auto kernels_map =
+      phi::KernelFactory::Instance().SelectKernelMap(signature.name);
+  if (kernels_map.size() == 0) {
+    PADDLE_THROW(
+        platform::errors::Unimplemented("Not find `%s` kernels when construct "
+                                        "InferMetaContext.",
+                                        signature.name));
+  }
+  auto attr_defs = kernels_map.cbegin()->second.args_def().attribute_defs();
+
   // TODO(chenweihang): support multiple inputs and outputs later
   phi::InferMetaContext infer_mete_context;
   for (auto& in_name : input_names) {
@@ -299,9 +315,70 @@ phi::InferMetaContext BuildInferMetaContext(InferShapeContext* ctx,
     }
   }
 
+  for (auto& out_name : output_names) {
+    if (ctx->HasOutput(out_name)) {
+      infer_meta_context.EmplaceBackOutput(std::make_shared<CompatMetaTensor>(
+          ctx->GetOutputVarPtrs(out_name)[0], ctx->IsRuntime()));
+    } else {
+      infer_meta_context.EmplaceBackOutput({nullptr});
+    }
+  }
   auto attr_reader = ctx->Attrs();
-  for (auto& attr_name : attr_names) {
-    if (ctx->HasAttr(attr_name)) {
+  for (size_t i = 0; i < attr_names.size(); ++i) {
+    auto attr_name = attr_names[i];
+    if (attr_defs[i].type_index == std::type_index(typeid(phi::ScalarArray))) {
+      // When attr is a vector_tensor or tensor, transform it to ScalarArray
+      if (ctx->HasInputs(attr_name) || ctx->HasInput(attr_name)) {
+        const auto& infershape_inputs = ctx->GetInputVarPtrs(attr_name);
+        if (ctx->IsRuntime()) {
+          // If is in runtime, we will get tensor's value for ScalarArray
+          // and push it into attrs
+          std::vector<Variable*> vars;
+          vars.reserve(infershape_inputs.size());
+          for (size_t i = 0; i < infershape_inputs.size(); i++) {
+            vars.push_back(BOOST_GET_CONST(Variable*, infershape_inputs[i]));
+          }
+          if (infershape_inputs.size() != 1) {
+            infer_meta_context.EmplaceBackAttr(
+                std::move(experimental::MakePtenScalarArrayFromVarList(vars)));
+          } else {
+            infer_meta_context.EmplaceBackAttr(
+                std::move(experimental::MakePtenScalarArrayFromVar(*vars[0])));
+          }
+        } else {
+          // If is not in runtime, we will set default value(-1) for ScalarArray
+          int64_t num_ele = 1;
+          std::vector<VarDesc*> vars;
+          vars.reserve(infershape_inputs.size());
+          for (size_t i = 0; i < infershape_inputs.size(); i++) {
+            vars.push_back(BOOST_GET_CONST(VarDesc*, infershape_inputs[i]));
+          }
+          for (auto& var : vars) {
+            const auto& tensor_dims = var->GetShape();
+            for (size_t i = 0; i < tensor_dims.size(); ++i) {
+              num_ele *= tensor_dims[i];
+            }
+          }
+          phi::ScalarArray tensor_attr(std::vector<int32_t>(num_ele, -1));
+          tensor_attr.SetFromTensor(true);
+          infer_meta_context.EmplaceBackAttr(std::move(tensor_attr));
+        }
+      } else if (ctx->HasAttr(attr_name)) {
+        auto& attr = attr_reader.GetAttr(attr_name);
+        if (std::type_index(attr.type()) ==
+            std::type_index(typeid(std::vector<int32_t>))) {
+          infer_meta_context.EmplaceBackAttr(std::move(
+              phi::ScalarArray(BOOST_GET_CONST(std::vector<int32_t>, attr))));
+        } else {
+          PADDLE_THROW(platform::errors::Unimplemented(
+              "Unsupported cast op attribute `%s` to ScalarArray when "
+              "construct KernelContext.",
+              attr_name));
+        }
+      }
+
+    } else if (ctx->HasAttr(attr_name)) {
+      // Emplace Back Attr according to the type of attr.
       auto& attr = attr_reader.GetAttr(attr_name);
       if (std::type_index(attr.type()) == std::type_index(typeid(bool))) {
         infer_meta_context.EmplaceBackAttr(BOOST_GET_CONST(bool, attr));
@@ -345,17 +422,6 @@ phi::InferMetaContext BuildInferMetaContext(InferShapeContext* ctx,
             "Unsupported attribute type is received when call "
             "InferShapeFunctor."));
       }
-    } else {
-      // do nothing
-    }
-  }
-
-  for (auto& out_name : output_names) {
-    if (ctx->HasOutput(out_name)) {
-      infer_meta_context.EmplaceBackOutput(std::make_shared<CompatMetaTensor>(
-          ctx->GetOutputVarPtrs(out_name)[0], ctx->IsRuntime()));
-    } else {
-      infer_meta_context.EmplaceBackOutput({nullptr});
     }
   }
 

paddle/fluid/framework/infershape_utils_test.cc

@@ -23,8 +23,11 @@ limitations under the License. */
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/framework/operator.h"
 #include "paddle/fluid/framework/program_desc.h"
+#include "paddle/phi/backends/cpu/cpu_context.h"
 #include "paddle/phi/core/compat/op_utils.h"
+#include "paddle/phi/core/dense_tensor.h"
 #include "paddle/phi/core/infermeta_utils.h"
+#include "paddle/phi/core/kernel_registry.h"
 
 namespace paddle {
 namespace framework {
@@ -93,6 +96,17 @@ phi::KernelSignature InferShapeUtilsTestOpArgumentMapping(
       {});
 }
 
+template <typename T, typename Context>
+void InferShapeUtilsTestKernel(
+    const Context& dev_ctx, const phi::DenseTensor& x, bool attr1, int attr2,
+    int64_t attr3, float attr4, const std::string& attr5,
+    const std::vector<bool>& attr6, const std::vector<int>& attr7,
+    const std::vector<int64_t>& attr8, const std::vector<float>& attr9,
+    const std::vector<double>& attr10, const std::vector<std::string>& attr11,
+    phi::DenseTensor* out) {
+  VLOG(6) << "Come into InferShapeUtilsTestKernel";
+}
+
 }  // namespace framework
 }  // namespace paddle
 
@@ -104,6 +118,9 @@ REGISTER_OPERATOR(infer_shape_utils_test,
                   paddle::framework::InferShapeUtilsTestOpMaker,
                   InferShapeUtilsTestInferShapeFunctor);
 
+PT_REGISTER_KERNEL(infer_shape_utils_test, CPU, ALL_LAYOUT,
+                   paddle::framework::InferShapeUtilsTestKernel, int) {}
+
 TEST(InferShapeUtilsTest, ALL) {
   paddle::framework::ProgramDesc prog;
   paddle::framework::proto::BlockDesc proto_block;

paddle/fluid/operators/reshape_op.cc

@@ -14,15 +14,19 @@ limitations under the License. */
 
 #include <string>
 
+#include "paddle/fluid/framework/infershape_utils.h"
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/framework/pten_utils.h"
 
 // only can include the headers in paddle/phi/api dirs
 #include "paddle/phi/api/lib/utils/tensor_utils.h"
 #include "paddle/phi/backends/cpu/cpu_context.h"
 #include "paddle/phi/common/scalar_array.h"
+#include "paddle/phi/core/infermeta_utils.h"
+#include "paddle/phi/infermeta/unary.h"
 #include "paddle/phi/kernels/reshape_grad_kernel.h"
 #include "paddle/phi/kernels/reshape_kernel.h"
+
 namespace paddle {
 namespace framework {
 class InferShapeContext;
@@ -472,22 +476,6 @@ class Reshape2Op : public ReshapeOp {
              const framework::VariableNameMap &outputs,
              const framework::AttributeMap &attrs)
       : ReshapeOp(type, inputs, outputs, attrs) {}
-
-  void InferShape(framework::InferShapeContext *ctx) const override {
-    PADDLE_ENFORCE_EQ(ctx->HasOutput("XShape"), true,
-                      platform::errors::InvalidArgument(
-                          "Output(XShape) of ReshapeOp should not be null."));
-    const auto &x_dims = ctx->GetInputDim("X");
-    std::vector<int64_t> xshape_dims(x_dims.size() + 1);
-    xshape_dims[0] = 0;
-    for (int i = 0; i < x_dims.size(); ++i) {
-      xshape_dims[i + 1] = x_dims[i];
-    }
-    ctx->SetOutputDim("XShape", phi::make_ddim(xshape_dims));
-    ctx->ShareLoD("X", /*->*/ "XShape");
-
-    ReshapeOp::InferShape(ctx);
-  }
 };
 
 class Reshape2OpMaker : public ReshapeOpMaker {
@@ -647,10 +635,14 @@ REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape_grad, float, ops::ReshapeGradKernel,
                                ops::ReshapeGradKernel, int,
                                ops::ReshapeGradKernel, int64_t,
                                ops::ReshapeGradKernel);
+
+DELCARE_INFER_SHAPE_FUNCTOR(reshape2, ReshapeInferShapeFunctor,
+                            PT_INFER_META(phi::ReshapeWithXShapeInferMeta));
+
 REGISTER_OPERATOR(reshape2, ops::Reshape2Op, ops::Reshape2OpMaker,
                   ops::Reshape2GradMaker<paddle::framework::OpDesc>,
                   ops::Reshape2GradMaker<paddle::imperative::OpBase>,
-                  ops::ReshapeOpInplaceInferer);
+                  ReshapeInferShapeFunctor, ops::ReshapeOpInplaceInferer);
 REGISTER_OPERATOR(reshape2_grad, ops::Reshape2GradOp,
                   ops::Reshape2DoubleGradMaker<paddle::framework::OpDesc>,
                   ops::Reshape2DoubleGradMaker<paddle::imperative::OpBase>,

paddle/phi/api/lib/utils/tensor_utils.cc

@@ -131,7 +131,7 @@ phi::ScalarArray MakePtenScalarArrayFromVarList(
   }
 
   phi::ScalarArray result{vector_data};
-  result.setInitByTensor(true);
+  result.SetFromTensor(true);
 
   return result;
 }

paddle/phi/common/scalar.h

@@ -25,7 +25,7 @@ namespace experimental {
 template <typename T>
 class ScalarBase {
  public:
-  bool IsInitByTensor() const { return is_init_by_tensor_; }
+  bool FromTensor() const { return is_from_tensor_; }
   // Constructor support implicit
   ScalarBase(double val) : dtype_(DataType::FLOAT64) {  // NOLINT
     data_.f64 = val;
@@ -104,7 +104,7 @@ class ScalarBase {
 
   // The Tensor must have one dim
   ScalarBase(const T& tensor) : dtype_(tensor.dtype()) {  // NOLINT
-    is_init_by_tensor_ = true;
+    is_from_tensor_ = true;
     PD_CHECK(
         tensor.numel() == 1,
         "The Scalar only supports Tensor with 1 element, but now Tensor has `",
@@ -196,7 +196,7 @@ class ScalarBase {
   friend void CopyScalar(const ScalarBase<T1>& src, ScalarBase<T2>* dst);
 
  private:
-  bool is_init_by_tensor_{false};
+  bool is_from_tensor_{false};
   DataType dtype_;
   union data {
     bool b;

paddle/phi/common/scalar_array.h

@@ -43,13 +43,13 @@ class ScalarArrayBase {
     AssignData(date_value, n);
   }
 
-  bool IsInitByTensor() const { return is_init_by_tensor_; }
+  bool FromTensor() const { return is_from_tensor_; }
 
-  void setInitByTensor(bool val) { is_init_by_tensor_ = val; }
+  void SetFromTensor(bool val) { is_from_tensor_ = val; }
 
   // The Tensor must have one dim
   ScalarArrayBase(const T& tensor) {  // NOLINT
-    is_init_by_tensor_ = true;
+    is_from_tensor_ = true;
     size_t n = tensor.numel();
     array_.reserve(n);
     switch (tensor.dtype()) {
@@ -71,7 +71,7 @@ class ScalarArrayBase {
 
   // The Tensor in vec must have only one element
   ScalarArrayBase(const std::vector<T>& tensor_list) {  // NOLINT
-    is_init_by_tensor_ = true;
+    is_from_tensor_ = true;
 
     for (size_t i = 0; i < tensor_list.size(); ++i) {
       DataType data_type = tensor_list[i].dtype();
@@ -117,7 +117,7 @@ class ScalarArrayBase {
   // TODO(zhangyunfei) Replace std::vector with a more efficient container
   // structure.
   std::vector<int64_t> array_;
-  bool is_init_by_tensor_{false};
+  bool is_from_tensor_{false};
 };
 
 using ScalarArray =

paddle/phi/core/kernel_utils.h

@@ -241,6 +241,10 @@ struct KernelImpl<Return (*)(DevCtx, Args...), kernel_fn> {
   PT_SPECIALIZE_KernelCallHelper_FOR_ATTRIBUTE(const ScalarArray&);
   PT_SPECIALIZE_KernelCallHelper_FOR_ATTRIBUTE(const std::vector<int>&);
   PT_SPECIALIZE_KernelCallHelper_FOR_ATTRIBUTE(const std::string&);
+  PT_SPECIALIZE_KernelCallHelper_FOR_ATTRIBUTE(const std::vector<bool>&);
+  PT_SPECIALIZE_KernelCallHelper_FOR_ATTRIBUTE(const std::vector<float>&);
+  PT_SPECIALIZE_KernelCallHelper_FOR_ATTRIBUTE(const std::vector<double>&);
+  PT_SPECIALIZE_KernelCallHelper_FOR_ATTRIBUTE(const std::vector<std::string>&);
 
   /* Output Helpers */
 

paddle/phi/infermeta/unary.cc

@@ -15,8 +15,8 @@ limitations under the License. */
 #include "paddle/phi/infermeta/unary.h"
 
 #include <set>
-
 #include "paddle/phi/common/data_type.h"
+#include "paddle/phi/core/enforce.h"
 #include "paddle/phi/core/infermeta_utils.h"
 
 namespace phi {
@@ -210,7 +210,7 @@ void InferMetaFromVecValue(const MetaTensor& x,
                            MetaTensor* out) {
   PADDLE_ENFORCE_EQ(!shape.empty(),
                     true,
-                    paddle::platform::errors::InvalidArgument(
+                    phi::errors::InvalidArgument(
                         "The parameter 'shape' in ReshapeOp must be set. "
                         "But received 'shape' is empty."));
   auto x_dims = x.dims();
@@ -227,8 +227,42 @@ void InferMetaFromVecValue(const MetaTensor& x,
 
 void ReshapeInferMeta(const MetaTensor& x,
                       const ScalarArray& shape,
-                      MetaTensor* out) {
-  InferMetaFromVecValue(x, shape.GetData(), out);
+                      MetaTensor* out,
+                      MetaConfig config) {
+  auto& shape_data = shape.GetData();
+  PADDLE_ENFORCE_NOT_NULL(out,
+                          phi::errors::InvalidArgument(
+                              "Output(Out) of ReshapeOp should not be null."));
+  if (!config.is_runtime && shape.FromTensor()) {
+    out->set_dims(phi::make_ddim(shape_data));
+    out->share_lod(x);
+    return;
+  }
+  PADDLE_ENFORCE_GT(shape_data.size(),
+                    0,
+                    phi::errors::InvalidArgument(
+                        "The shape's size in ReshapeOp can't be zero."));
+  InferMetaFromVecValue(x, shape_data, out);
+}
+
+void ReshapeWithXShapeInferMeta(const MetaTensor& x,
+                                const ScalarArray& shape,
+                                MetaTensor* xshape,
+                                MetaTensor* out,
+                                MetaConfig config) {
+  PADDLE_ENFORCE_NOT_NULL(
+      xshape,
+      phi::errors::InvalidArgument(
+          "Output(XShape) of ReshapeOp should not be null."));
+  const auto& x_dims = x.dims();
+  std::vector<int64_t> xshape_dims(x_dims.size() + 1);
+  xshape_dims[0] = 0;
+  for (int i = 0; i < x_dims.size(); ++i) {
+    xshape_dims[i + 1] = x_dims[i];
+  }
+  xshape->set_dims(phi::make_ddim(xshape_dims));
+  xshape->share_lod(x);
+  ReshapeInferMeta(x, shape, out, config);
 }
 
 /*  Why not use ReduceInferMeta directly?

paddle/phi/infermeta/unary.h

@@ -49,7 +49,14 @@ void InferMetaFromVecValue(const MetaTensor& x,
 
 void ReshapeInferMeta(const MetaTensor& x,
                       const ScalarArray& shape,
-                      MetaTensor* out);
+                      MetaTensor* out,
+                      MetaConfig config = MetaConfig());
+
+void ReshapeWithXShapeInferMeta(const MetaTensor& x,
+                                const ScalarArray& shape,
+                                MetaTensor* xshape,
+                                MetaTensor* out,
+                                MetaConfig config = MetaConfig());
 
 void ReduceInferMetaBase(const MetaTensor& x,
                          const std::vector<int64_t>& axis,

paddle/phi/kernels/cpu/split_kernel.cc

@@ -29,7 +29,7 @@ void SplitKernel(const Context& dev_ctx,
                  const Scalar& axis_scalar,
                  std::vector<DenseTensor*> outs) {
   // need to infershape output
-  if (num_or_sections.IsInitByTensor() || axis_scalar.IsInitByTensor()) {
+  if (num_or_sections.FromTensor() || axis_scalar.FromTensor()) {
     std::vector<MetaTensor> out_metas;
     for (size_t i = 0; i < outs.size(); ++i) {
       out_metas.push_back(outs[i]);