parameters: (spec, inputs=None, input_shape=None, input_type=tf.float32)
docstring: Print a tree representing the spec.
  
    Args:
        spec: specification
        inputs: input to the spec construction (usually a Tensor)
        input_shape: optional shape of input
        input_type: type of the input tensor
docstring_summary: Print a tree representing the spec.
docstring_tokens: Print a tree representing the spec .
function: def tf_spec_print(spec, inputs=None, input_shape=None, input_type=tf.float32):
    """Print a tree representing the spec.
  
    Args:
        spec: specification
        inputs: input to the spec construction (usually a Tensor)
        input_shape: optional shape of input
        input_type: type of the input tensor
    """
  
    if inputs is None:
      inputs = tf.placeholder(input_type, input_shape)
    outputs = specs.create_net(spec, inputs)
    tf_print(outputs)
function_tokens: def tf_spec_print ( spec , inputs = None , input_shape = None , input_type = tf . float32 ) : if inputs is None : inputs = tf . placeholder ( input_type , input_shape ) outputs = specs . create_net ( spec , inputs ) tf_print ( outputs )