kfac/python/ops/fisher_blocks.py [1094:1134]:
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  def __init__(self,
               layer_collection,
               params,
               strides,
               padding,
               rate=None,
               data_format=None):
    """Creates a DepthwiseConvKFCBasicFB block.

    Args:
      layer_collection: The LayerCollection object which owns this block.
      params: Tensor of shape [filter_height, filter_width, in_channels,
        channel_multiplier].
      strides: List of 4 ints. Strides along all dimensions.
      padding: str. Padding method.
      rate: List of 4 ints or None. Rate for dilation along all dimensions.
      data_format: str or None. Format of input data.

    Raises:
      NotImplementedError: If parameters contains bias.
      ValueError: If filter is not 4-D.
      ValueError: If strides is not length-4.
      ValueError: If rates is not length-2.
      ValueError: If channels are not last dimension.
    """
    if isinstance(params, (tuple, list)):
      raise NotImplementedError("Bias not yet supported.")

    if params.shape.ndims != 4:
      raise ValueError("Filter must be 4-D.")

    if len(strides) != 4:
      raise ValueError("strides must account for 4 dimensions.")

    if rate is not None:
      if len(rate) != 2:
        raise ValueError("rate must only account for spatial dimensions.")
      rate = [1, rate[0], rate[1], 1]  # conv2d expects 4-element rate.

    if not utils.is_data_format_channel_last(data_format):
      raise ValueError("data_format must be channels-last.")
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kfac/python/ops/fisher_blocks.py [1163:1203]:
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  def __init__(self,
               layer_collection,
               params,
               strides,
               padding,
               rate=None,
               data_format=None):
    """Creates a DepthwiseConvKFCBasicFB block.

    Args:
      layer_collection: The LayerCollection object which owns this block.
      params: Tensor of shape [filter_height, filter_width, in_channels,
        channel_multiplier].
      strides: List of 4 ints. Strides along all dimensions.
      padding: str. Padding method.
      rate: List of 4 ints or None. Rate for dilation along all dimensions.
      data_format: str or None. Format of input data.

    Raises:
      NotImplementedError: If parameters contains bias.
      ValueError: If filter is not 4-D.
      ValueError: If strides is not length-4.
      ValueError: If rates is not length-2.
      ValueError: If channels are not last dimension.
    """
    if isinstance(params, (tuple, list)):
      raise NotImplementedError("Bias not yet supported.")

    if params.shape.ndims != 4:
      raise ValueError("Filter must be 4-D.")

    if len(strides) != 4:
      raise ValueError("strides must account for 4 dimensions.")

    if rate is not None:
      if len(rate) != 2:
        raise ValueError("rate must only account for spatial dimensions.")
      rate = [1, rate[0], rate[1], 1]  # conv2d expects 4-element rate.

    if not utils.is_data_format_channel_last(data_format):
      raise ValueError("data_format must be channels-last.")
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