parameters: (x1_type, x2_type, prim_name=None)
docstring: Check input tensor types to be valid and confirm they are the same type for dot and batch dot ops.
docstring_summary: Check input tensor types to be valid and confirm they are the same type for dot and batch dot ops.
docstring_tokens: Check input tensor types to be valid and confirm they are the same type for dot and batch dot ops .
function: def _typecheck_input_dot(x1_type, x2_type, prim_name=None):
      """
      Check input tensor types to be valid and confirm they are the same type for dot and batch dot ops.
      """
      msg_prefix = f"For '{prim_name}', the" if prim_name else "The"
      const_utils.check_type_valid(x1_type, [mstype.float16, mstype.float32], 'x1')
      const_utils.check_type_valid(x2_type, [mstype.float16, mstype.float32], 'x2')
      if x1_type != x2_type:
          raise TypeError(f"{msg_prefix} inputs must be the same type, but got "
                          f"x1_type: {x1_type} and x2_type: {x2_type}.")
function_tokens: def _typecheck_input_dot ( x1_type , x2_type , prim_name = None ) : msg_prefix = f"For '{prim_name}', the" if prim_name else "The" const_utils . check_type_valid ( x1_type , [ mstype . float16 , mstype . float32 ] , 'x1' ) const_utils . check_type_valid ( x2_type , [ mstype . float16 , mstype . float32 ] , 'x2' ) if x1_type != x2_type : raise TypeError ( f"{msg_prefix} inputs must be the same type, but got " f"x1_type: {x1_type} and x2_type: {x2_type}." )