PaddlePaddle
diff --git a/‎paddle/fluid/framework/op_version_proto.cc
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+1Lines changed: 1 addition & 0 deletions b/‎paddle/fluid/framework/op_version_proto.cc
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+1Lines changed: 1 addition & 0 deletions
diff --git a/‎paddle/fluid/framework/program_converter.cc
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+84-1Lines changed: 84 additions & 1 deletion b/‎paddle/fluid/framework/program_converter.cc
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+84-1Lines changed: 84 additions & 1 deletion
diff --git a/‎paddle/fluid/ir_adaptor/translator/op_translator.cc
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+9-8Lines changed: 9 additions & 8 deletions b/‎paddle/fluid/ir_adaptor/translator/op_translator.cc
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+9-8Lines changed: 9 additions & 8 deletions
diff --git a/‎paddle/fluid/operators/ops_signature/assign_value_sig.cc
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+2-24Lines changed: 2 additions & 24 deletions b/‎paddle/fluid/operators/ops_signature/assign_value_sig.cc
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+2-24Lines changed: 2 additions & 24 deletions
diff --git a/‎paddle/fluid/pir/dialect/operator/ir/op_attribute.cc
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+4Lines changed: 4 additions & 0 deletions b/‎paddle/fluid/pir/dialect/operator/ir/op_attribute.cc
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+4Lines changed: 4 additions & 0 deletions
diff --git a/‎paddle/fluid/pir/dialect/operator/ir/op_attribute.h
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+3-1Lines changed: 3 additions & 1 deletion b/‎paddle/fluid/pir/dialect/operator/ir/op_attribute.h
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+3-1Lines changed: 3 additions & 1 deletion
diff --git a/‎paddle/fluid/pir/dialect/operator/utils/utils.h
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+6Lines changed: 6 additions & 0 deletions b/‎paddle/fluid/pir/dialect/operator/utils/utils.h
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+6Lines changed: 6 additions & 0 deletions
diff --git a/‎paddle/fluid/pybind/op_function_common.cc
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+17-4Lines changed: 17 additions & 4 deletions b/‎paddle/fluid/pybind/op_function_common.cc
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+17-4Lines changed: 17 additions & 4 deletions
diff --git a/‎paddle/phi/api/yaml/op_version.yaml
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+15Lines changed: 15 additions & 0 deletions b/‎paddle/phi/api/yaml/op_version.yaml
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+15Lines changed: 15 additions & 0 deletions
diff --git a/‎paddle/phi/api/yaml/static_ops.yaml
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+1-1Lines changed: 1 addition & 1 deletion b/‎paddle/phi/api/yaml/static_ops.yaml
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+1-1Lines changed: 1 addition & 1 deletion
@@ -21,6 +21,7 @@ namespace pb {
 const std::unordered_map<std::string, uint32_t>& GetLegacyOpVersions() {
   static std::unordered_map<std::string, uint32_t> op_versions = {
       {"not_equal", 1},
+      {"assign_value", 0},
       {"fake_channel_wise_dequantize_max_abs", 2},
       {"yolo_box", 1},
       {"data_norm", 1},
 
@@ -117,6 +117,41 @@ void ConvertSetValueOp(OpDesc* op) {
   }
 }
 
+void ConvertAssignValueOp(OpDesc* op) {
+  std::vector<paddle::experimental::Scalar> values = PADDLE_GET_CONST(
+      std::vector<paddle::experimental::Scalar>, op->GetAttr("values", false));
+  op->RemoveAttr("values");
+  op->SetAttr("bool_values", std::vector<int>());
+  op->SetAttr("fp32_values", std::vector<float>());
+  op->SetAttr("int32_values", std::vector<int>());
+  op->SetAttr("int64_values", std::vector<int64_t>());
+
+  phi::DataType dtype = phi::DataType::FLOAT32;
+  if (values.size()) {
+    dtype = values.at(0).dtype();
+  }
+
+  switch (dtype) {
+    case phi::DataType::BOOL:
+      op->SetAttr("bool_values", ExtractPlainVector<int>(values));
+      break;
+    case phi::DataType::FLOAT32:
+      op->SetAttr("fp32_values", ExtractPlainVector<float>(values));
+      break;
+    case phi::DataType::FLOAT64:
+      op->SetAttr("fp32_values", ExtractPlainVector<float>(values));
+      break;
+    case phi::DataType::INT32:
+      op->SetAttr("int32_values", ExtractPlainVector<int>(values));
+      break;
+    case phi::DataType::INT64:
+      op->SetAttr("int64_values", ExtractPlainVector<int64_t>(values));
+      break;
+    default:
+      PD_THROW("Invalid data type `", dtype, "`.");
+  }
+}
+
 void ConvertProgram(ProgramDesc* program) {
   PADDLE_ENFORCE_NOT_NULL(
       program,
@@ -144,6 +179,9 @@ void ConvertProgram(ProgramDesc* program) {
       if (op_type == "set_value" || op_type == "set_value_grad") {
         ConvertSetValueOp(op);
       }
+      if (op_type == "assign_value") {
+        ConvertAssignValueOp(op);
+      }
     }
   }
 }
@@ -204,6 +242,45 @@ void ConvertSetValueOp(OpDesc* op) {
   op->SetAttr("values", values);
 }
 
+void ConvertAssignValueOp(OpDesc* op) {
+  VLOG(3) << "convert old assign value op to new";
+  std::vector<paddle::experimental::Scalar> values;
+
+  if (op->HasAttr("bool_values")) {
+    std::vector<int> bool_values =
+        PADDLE_GET_CONST(std::vector<int>, op->GetAttr("bool_values", false));
+    if (bool_values.size()) {
+      values = WrapAsScalars(bool_values);
+    }
+    op->RemoveAttr("bool_values");
+  }
+  if (op->HasAttr("fp32_values")) {
+    std::vector<float> fp32_values =
+        PADDLE_GET_CONST(std::vector<float>, op->GetAttr("fp32_values", false));
+    if (fp32_values.size()) {
+      values = WrapAsScalars(fp32_values);
+    }
+    op->RemoveAttr("fp32_values");
+  }
+  if (op->HasAttr("int32_values")) {
+    std::vector<int> int32_values =
+        PADDLE_GET_CONST(std::vector<int>, op->GetAttr("int32_values", false));
+    if (int32_values.size()) {
+      values = WrapAsScalars(int32_values);
+    }
+    op->RemoveAttr("int32_values");
+  }
+  if (op->HasAttr("int64_values")) {
+    std::vector<int64_t> int64_values = PADDLE_GET_CONST(
+        std::vector<int64_t>, op->GetAttr("int64_values", false));
+    if (int64_values.size()) {
+      values = WrapAsScalars(int64_values);
+    }
+    op->RemoveAttr("int64_values");
+  }
+  op->SetAttr("values", values);
+}
+
 void ConvertProgram(ProgramDesc* program) {
   PADDLE_ENFORCE_NOT_NULL(
       program,
@@ -214,6 +291,7 @@ void ConvertProgram(ProgramDesc* program) {
   const std::unordered_map<std::string, uint32_t>& legacy_op_versions =
       legacy_op_results.second;
 
+  VLOG(3) << "is_legacy_program : " << is_legacy_program;
   if (!is_legacy_program) return;
 
   VLOG(3) << "Updating Program Version and OpVersionMap";
@@ -232,10 +310,15 @@ void ConvertProgram(ProgramDesc* program) {
     for (size_t j = 0; j < num_ops; j++) {
       OpDesc* op = block->Op(static_cast<int>(j));
       const std::string op_type = op->Type();
+
+      if (op_type == "assign_value") {
+        VLOG(3) << "Converting program from old to new, op_type=" << op_type;
+        ConvertAssignValueOp(op);
+      }
       if (!legacy_op_versions.count(op_type)) {
         continue;
       }
-
+      VLOG(3) << "Converting program from old to new, op_type=" << op_type;
       if (op_type == "set_value" || op_type == "set_value_grad") {
         ConvertSetValueOp(op);
       }
 
@@ -972,19 +972,20 @@ struct AssignValueOpTranscriber : public OpTranscriber {
         ctx, phi::Place(phi::AllocationType::UNDEFINED));
     attribute_map["place"] = attr_place;
 
-    int dtype = paddle::get<int>(op_desc.GetAttr("dtype"));
-
-    if (dtype == /*BOOL*/ 0) {
+    if (op_desc.HasAttr("bool_values")) {
       legacy_attr = op_desc.GetAttr("bool_values");
-    } else if (dtype == /*INT32*/ 2) {
-      legacy_attr = op_desc.GetAttr("int32_values");
-    } else if (dtype == /*FP32*/ 5) {
+    } else if (op_desc.HasAttr("fp32_values")) {
       legacy_attr = op_desc.GetAttr("fp32_values");
-    } else if (dtype == /*INT64*/ 3) {
+    } else if (op_desc.HasAttr("int32_values")) {
+      legacy_attr = op_desc.GetAttr("int32_values");
+    } else if (op_desc.HasAttr("int64_values")) {
       legacy_attr = op_desc.GetAttr("int64_values");
+    } else if (op_desc.HasAttr("values")) {
+      legacy_attr = op_desc.GetAttr("values");
     } else {
       IR_THROW(
-          "Op assign_value should have attribute `**_values` but not find");
+          "Op assign_value should have attribute `**_values` or `values` but "
+          "not find");
     }
 
     pir::Attribute attr_values = attribute_translator(
 
@@ -18,30 +18,8 @@ namespace phi {
 
 KernelSignature AssignValueOpArgumentMapping(
     const ArgumentMappingContext& ctx) {
-  // Here we must use `dtype` attr to determine which attr to use, we can't
-  // judge by whether the attr is empty, some unittests will failed
-  int dtype = paddle::any_cast<int>(ctx.Attr("dtype"));
-  // heer we can't depend on the fluid proto::VarType, so we use the dtype enum
-  // value directly, If the enum value is updated, the code also needs to be
-  // updated here, but the probability of updating the enum value is very low
-  if (dtype == /*BOOL*/ 0) {
-    return KernelSignature(
-        "assign_value", {}, {"shape", "dtype", "bool_values"}, {"Out"});
-  } else if (dtype == /*INT32*/ 2) {
-    return KernelSignature(
-        "assign_value", {}, {"shape", "dtype", "int32_values"}, {"Out"});
-  } else if (dtype == /*FP32*/ 5) {
-    return KernelSignature(
-        "assign_value", {}, {"shape", "dtype", "fp32_values"}, {"Out"});
-  } else if (dtype == /*FP64*/ 6) {
-    return KernelSignature(
-        "assign_value", {}, {"shape", "dtype", "fp64_values"}, {"Out"});
-  } else if (dtype == /*INT64*/ 3) {
-    return KernelSignature(
-        "assign_value", {}, {"shape", "dtype", "int64_values"}, {"Out"});
-  } else {
-    return KernelSignature("unregistered", {}, {}, {});
-  }
+  return KernelSignature(
+      "assign_value", {}, {"shape", "dtype", "values"}, {"Out"});
 }
 
 }  // namespace phi
 
@@ -43,6 +43,10 @@ phi::Scalar ScalarAttribute::data() {
     return phi::Scalar(dyn_cast<pir::BoolAttribute>().data());
   } else if (isa<pir::StrAttribute>()) {
     return phi::Scalar(dyn_cast<pir::StrAttribute>().AsString());
+  } else if (isa<pir::Complex64Attribute>()) {
+    return phi::Scalar(dyn_cast<pir::Complex64Attribute>().data());
+  } else if (isa<pir::Complex128Attribute>()) {
+    return phi::Scalar(dyn_cast<pir::Complex128Attribute>().data());
   } else {
     PADDLE_THROW(phi::errors::Unimplemented(
         "Unsupported ir attribute when casting it into "
 
@@ -50,7 +50,9 @@ class ScalarAttribute : public pir::Attribute {
            (val.type_id() == pir::Int32Attribute::type_id()) ||
            (val.type_id() == pir::IndexAttribute::type_id()) ||
            (val.type_id() == pir::Int64Attribute::type_id()) ||
-           (val.type_id() == pir::StrAttribute::type_id());
+           (val.type_id() == pir::StrAttribute::type_id()) ||
+           (val.type_id() == pir::Complex64Attribute::type_id()) ||
+           (val.type_id() == pir::Complex128Attribute::type_id());
   }
 
   static pir::Attribute get(pir::IrContext *ctx, phi::Scalar scalar) {
 
@@ -120,6 +120,12 @@ static inline pir::Attribute TransToIrAttribute(phi::Scalar scalar,
       return pir::Int64Attribute::get(ctx, scalar.to<int64_t>());
     case phi::DataType::BOOL:
       return pir::BoolAttribute::get(ctx, scalar.to<bool>());
+    case phi::DataType::COMPLEX64:
+      return pir::Complex64Attribute::get(
+          ctx, scalar.to<phi::dtype::complex<float>>());
+    case phi::DataType::COMPLEX128:
+      return pir::Complex128Attribute::get(
+          ctx, scalar.to<phi::dtype::complex<double>>());
     default:
       PADDLE_THROW(phi::errors::Unimplemented(
           "Unsupported phi data type `%s` when casting it into "
 
@@ -77,7 +77,7 @@ bool PyObject_CheckLongOrToLong(PyObject** obj) {
   }
 
   if (std::string(((PyTypeObject*)(*obj)->ob_type)->tp_name)  // NOLINT
-          .find("numpy") != std::string::npos) {
+          .find("numpy.int") != std::string::npos) {
     auto to = PyNumber_Long(*obj);
     if (to) {
       *obj = to;
@@ -95,8 +95,12 @@ bool PyObject_CheckFloatOrToFloat(PyObject** obj) {
        (((TensorObject*)(*obj))->tensor.numel() == 1))) {  // NOLINT
     return true;
   }
-  if (std::string(((PyTypeObject*)(*obj)->ob_type)->tp_name)  // NOLINT
-          .find("numpy") != std::string::npos) {
+  auto type_name =
+      std::string(reinterpret_cast<PyTypeObject*>((*obj)->ob_type)->tp_name);
+  VLOG(4) << "type_name: " << type_name;
+
+  if (type_name.find("numpy") != std::string::npos &&
+      type_name.find("numpy.complex") == std::string::npos) {
     auto to = PyNumber_Float(*obj);
     if (to) {
       *obj = to;
@@ -107,11 +111,15 @@ bool PyObject_CheckFloatOrToFloat(PyObject** obj) {
 }
 
 bool PyObject_CheckComplexOrToComplex(PyObject** obj) {
-  if (PyComplex_Check(*obj) || PyLong_Check(*obj) || PyFloat_Check(*obj) ||
+  if (PyComplex_Check(*obj) ||
       PyObject_TypeCheck(*obj, g_vartype_pytype) ||  // NOLINT
       PyObject_TypeCheck(*obj, p_tensor_type)) {     // NOLINT
     return true;
   }
+  if (std::string(((PyTypeObject*)(*obj)->ob_type)->tp_name)  // NOLINT
+          .find("numpy.complex") != std::string::npos) {
+    return true;
+  }
   // consider numpy cfloat & numpy cdouble?
   return false;
 }
@@ -242,10 +250,15 @@ double CastPyArg2Double(PyObject* obj,
 phi::dtype::complex<float> CastPyArg2Complex(PyObject* obj,
                                              const std::string& op_type,
                                              ssize_t arg_pos) {
+  PyTypeObject* type = obj->ob_type;
+  auto type_name = std::string(type->tp_name);
   if (PyComplex_Check(obj)) {
     double real = PyComplex_RealAsDouble(obj);
     double imag = PyComplex_ImagAsDouble(obj);
     return phi::dtype::complex<float>(real, imag);  // NOLINT
+  } else if (type_name == "numpy.complex64") {
+    Py_complex v = PyComplex_AsCComplex(obj);
+    return phi::dtype::complex<float>(v.real, v.imag);
   } else {
     PADDLE_THROW(platform::errors::InvalidArgument(
         "%s(): argument (position %d) must be "
 
@@ -55,6 +55,21 @@
         - delete_attr : atol
           comment : The attribute 'atol' is deleted. The reason why it is deleted is that
                     attributes do not support a float64 value and it is changed to a tensor.
+- op : assign_value
+  version :
+    - checkpoint : Upgrade assign_value, remove plain attributes in favor of generic attribute.
+      action :
+        - add_attr : values
+          comment : replace generic types with scalar.
+          default : std::vector<paddle::experimental::Scalar>()
+        - delete_attr : bool_values
+          comment : remove plain attributes.
+        - delete_attr : fp32_values
+          comment : remove plain attributes.
+        - delete_attr : int32_values
+          comment : remove plain attributes.
+        - delete_attr : int64_values
+          comment : remove plain attributes.
 
 - op : auc
   version :
 
@@ -90,7 +90,7 @@
   backward : assign_grad
 
 - op : assign_value
-  args : (int[] shape, DataType dtype, int[] bool_values = {}, float[] fp32_values = {}, double[] fp64_values = {}, int[] int32_values = {}, int64_t[] int64_values = {})
+  args : (int[] shape, DataType dtype, Scalar[] values = {})
   output : Tensor(out)
   infer_meta :
     func : AssignValueInferMeta