deodar | Классическая двухпанельная рабочая среда для О

def pool(
    input,  # pylint: disable=redefined-builtin
    window_shape,
    pooling_type,
    padding,
    dilation_rate=None,
    strides=None,
    name=None,
    data_format=None,
    dilations=None):
  """Performs an N-D pooling operation.

    

def static_rnn(cell,
               inputs,
               initial_state=None,
               dtype=None,
               sequence_length=None,
               scope=None):
  """Creates a recurrent neural network specified by RNNCell `cell`.

  The sim  

def exponential_power_convolution_kernel(
    grid_shape,
    length_scale,
    power=None,
    divisor=None,
    zero_inflation=None,
):
  """Make an exponentiated convolution kernel.

  In signal processing, a [kernel]
  (https://en.wikipedia.org/w