parameters: (op)
return_statement: return [tensor_util.constant_value_as_shape(op.inputs[0])]
docstring: Shape function for the Fill op.
  
    This op takes a vector of dimensions and a scalar, and produces a
    tensor with the given dimensions.
  
    Args:
      op: A Fill Operation.
  
    Returns:
      A single-element list containing the shape of the output.
  
    Raises:
      ValueError: If the shapes or arguments are known to be invalid.
docstring_summary: Shape function for the Fill op.
docstring_tokens: Shape function for the Fill op .
function: def _FillShape(op):
    """Shape function for the Fill op.
  
    This op takes a vector of dimensions and a scalar, and produces a
    tensor with the given dimensions.
  
    Args:
      op: A Fill Operation.
  
    Returns:
      A single-element list containing the shape of the output.
  
    Raises:
      ValueError: If the shapes or arguments are known to be invalid.
    """
    op.inputs[0].get_shape().assert_has_rank(1)
    op.inputs[1].get_shape().assert_has_rank(0)
    fill_dims = tensor_util.constant_value(op.inputs[0])
    if fill_dims is not None and any(d < 0 for d in fill_dims):
      raise ValueError("Fill dimensions must be >= 0")
    return [tensor_util.constant_value_as_shape(op.inputs[0])]
function_tokens: def _FillShape ( op ) : op . inputs [ 0 ] . get_shape ( ) . assert_has_rank ( 1 ) op . inputs [ 1 ] . get_shape ( ) . assert_has_rank ( 0 ) fill_dims = tensor_util . constant_value ( op . inputs [ 0 ] ) if fill_dims is not None and any ( d < 0 for d in fill_dims ) : raise ValueError ( "Fill dimensions must be >= 0" ) return [ tensor_util . constant_value_as_shape ( op . inputs [ 0 ] ) ]