tf.contrib.layers.max_pool2d

tf.contrib.layers.max_pool2d(
    inputs,
    kernel_size,
    stride=2,
    padding='VALID',
    data_format=DATA_FORMAT_NHWC,
    outputs_collections=None,
    scope=None
)

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

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

Adds a 2D Max Pooling op.

It is assumed that the pooling is done per image but not in batch or channels.

Args:

  • inputs: A 4-D tensor of shape [batch_size, height, width, channels] if data_format is NHWC, and [batch_size, channels, height, width] if data_format is NCHW.
  • kernel_size: A list of length 2: [kernel_height, kernel_width] of the pooling kernel over which the op is computed. Can be an int if both values are the same.
  • stride: A list of length 2: [stride_height, stride_width]. Can be an int if both strides are the same. Note that presently both strides must have the same value.
  • padding: The padding method, either 'VALID' or 'SAME'.
  • data_format: A string. NHWC (default) and NCHW are supported.
  • outputs_collections: The collections to which the outputs are added.
  • scope: Optional scope for name_scope.

Returns:

A Tensor representing the results of the pooling operation.

Raises:

  • ValueError: If data_format is neither NHWC nor NCHW.
  • ValueError: If 'kernel_size' is not a 2-D list