text: # Licensed to the Apache Software Foundation (ASF) under one
  # or more contributor license agreements.  See the NOTICE file
  # distributed with this work for additional information
  # regarding copyright ownership.  The ASF licenses this file
  # to you under the Apache License, Version 2.0 (the
  # "License"); you may not use this file except in compliance
  # with the License.  You may obtain a copy of the License at
  #
  #   http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing,
  # software distributed under the License is distributed on an
  # "AS IS" BASIS, 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.
  """Type relation and function for type checking."""
  import tvm._ffi
  
  from .type import Type
  from . import _ffi_api
  
  
  @tvm._ffi.register_object("relay.TensorType")
  class TensorType(Type):
      """A concrete TensorType in Relay.
  
      This is the type assigned to tensors with a known dtype and shape.
      For example, a tensor of `float32` and `(5, 5)`.
  
      Parameters
      ----------
      shape : List[tvm.ir.PrimExpr]
          The shape of the Tensor
  
      dtype : Optional[str]
          The content data type.
      """
      def __init__(self, shape, dtype="float32"):
          self.__init_handle_by_constructor__(
              _ffi_api.TensorType, shape, dtype)
  
      @property
      def concrete_shape(self):
          """Get shape of the type as concrete tuple of int.
  
          Returns
          -------
          shape : List[int]
              The concrete shape of the Type.
  
          Raises
          ------
          TypeError : If the shape is symbolic
          """
          return tuple(int(x) for x in self.shape)
  