tf.contrib.layers.avg_pool3d

tf.contrib.layers.avg_pool3d(
inputs,
kernel_size,
stride=2,
data_format=DATA_FORMAT_NDHWC,
outputs_collections=None,
scope=None
)


Adds a 3D average pooling op.

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

Args:

• inputs: A 5-D tensor of shape [batch_size, depth, height, width, channels] if data_format is NDHWC, and [batch_size, channels, depth, height, width] if data_format is NCDHW.
• kernel_size: A list of length 3: [kernel_depth, 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 3: [stride_depth, 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. NDHWC (default) and NCDHW 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 NDHWC nor NCDHW.