// 1. does not cause an error
// 2. preserves dtype and shape.
TEST_P(SavedVariableLoadingTest, LoadSavedVariableSuccessful) {
  auto& test_params = GetParam();
  DataType dtype = std::get<0>(test_params);
  TensorShape shape(std::get<1>(test_params));

  SavedVariable saved_variable;
  saved_variable.set_dtype(dtype);
  shape.AsProto(saved_variable.mutable_shape());

  std::unique_ptr<Variable> var;

                                           DataType dtype, TensorShape shape,
                                           const char* raw_device_name,
                                           ImmediateTensorHandlePtr* handle) {
  ImmediateOpPtr varhandle_op(ctx->CreateOperation());

  TF_RETURN_IF_ERROR(varhandle_op->Reset("VarHandleOp", raw_device_name));
  TF_RETURN_IF_ERROR(varhandle_op->SetAttrType("dtype", dtype));

	_type{"int16", 16, true},
	_type{"uint16", 16, false},
	_type{"int32", 32, true},
	_type{"uint32", 32, false},
	_type{"int64", 64, true},
	_type{"uint64", 64, false},
	_type{"int", 8 * uint(unsafe.Sizeof(int(0))), true},
	_type{"uint", 8 * uint(unsafe.Sizeof(uint(0))), false},
	_type{"uintptr", 8 * uint(unsafe.Sizeof((*byte)(nil))), false},
}

type binop struct {
	name string
	eval func(x, y *big.Int) *big.Int
}

				{
					Type:   cType,
					Status: v1.ConditionTrue,
				},
			},
		},
		{
			description: "replace",
			conditions: []v1.PodCondition{
				{
					Type:   cType,
					Status: v1.ConditionTrue,
				},
			},
			condition: v1.PodCondition{
				Type:   cType,
				Status: v1.ConditionFalse,
			},
			wantConditions: []v1.PodCondition{
				{
					Type:   cType,

// and returns an expression that yields the *runtime._type value
// representing that map type.
func MakeMapRType(pos src.XPos, n *ir.MakeExpr) ir.Node {
	assertOp(n, ir.OMAKEMAP)
	if hasRType(n, n.RType, "RType") {
		return n.RType
	}
	return mapRType(pos, n.Type())
}

// MakeSliceElemRType asserts that n is a "make" operation for a slice
// type, and returns an expression that yields the *runtime._type

using tsl::StatusOr;

// Converts the TensorFlow DataType 'dtype' into an MLIR (scalar) type.
Status ConvertDataType(DataType dtype, mlir::Builder builder, mlir::Type* type);

// Converts a scalar MLIR type to a TensorFlow Datatype.
Status ConvertScalarTypeToDataType(mlir::Type type, DataType* dtype);

// Converts an MLIR type to TensorFlow DataType. If 'type' is a scalar type, it

  mutex_lock ml(*variable->mu());
  OP_REQUIRES(
      context,
      !variable->is_initialized || variable->tensor()->dtype() == dtype_,
      errors::InvalidArgument(
          "Trying to assign variable with wrong dtype. Expected ",
          DataTypeString(variable->tensor()->dtype()), " got ",
          DataTypeString(dtype_)));
  variable->is_initialized = true;
  *variable->tensor() = value;
}

        dtype: DT_FLOAT
        tensor_shape {
          dim {
          }
        }
      }
    }
  }
}
node {
  name: "ParseExample/Const_1"
  op: "Const"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "value"
    value {
      tensor {
        dtype: DT_FLOAT
        tensor_shape {
          dim {
          }
        }
      }

                                           DataType dtype, TensorShape shape,
                                           const char* raw_device_name,
                                           ImmediateTensorHandlePtr* handle);

// Executes an AssignVariableOp using `ctx`, assigning the variable associated
// with `variable_handle` with `value`. `dtype` must be the datatype of the

// Restores a single non-partioned tensorhandle of dtype `dtype`, using
// checkpoint at `prefix`, with a value stored in `checkpoint_key`.
Status SingleRestore(ImmediateExecutionContext* ctx, const std::string& prefix,
                     const std::string& checkpoint_key, DataType dtype,
                     ImmediateTensorHandlePtr* out);

}  // namespace internal
}  // namespace tensorflow