tf.contrib.layers.repeat(inputs, repetitions, layer, *args, **kwargs)

tf.contrib.layers.repeat(inputs, repetitions, layer, *args, **kwargs)

See the guide: Layers (contrib) > Higher level ops for building neural network layers

Applies the same layer with the same arguments repeatedly.

  y = repeat(x, 3, conv2d, 64, [3, 3], scope='conv1')
  # It is equivalent to:

  x = conv2d(x, 64, [3, 3], scope='conv1/conv1_1')
  x = conv2d(x, 64, [3, 3], scope='conv1/conv1_2')
  y = conv2d(x, 64, [3, 3], scope='conv1/conv1_3')

If the scope argument is not given in kwargs, it is set to layer.__name__, or layer.func.__name__ (for functools.partial objects). If neither __name__ nor func.__name__ is available, the layers are called with scope='stack'.

Args:

  • inputs: A Tensor suitable for layer.
  • repetitions: Int, number of repetitions.
  • layer: A layer with arguments (inputs, *args, **kwargs) *args: Extra args for the layer. **kwargs: Extra kwargs for the layer.

Returns:

a tensor result of applying the layer, repetitions times. Raises: * ValueError: if the op is unknown or wrong.

Defined in tensorflow/contrib/layers/python/layers/layers.py.