Performs an N-D pooling operation.
tf.compat.v2.nn.pool( input, window_shape, pooling_type, strides=None, padding='VALID', data_format=None, dilations=None, name=None )
In the case that data_format
does not start with "NC", computes for 0 <= b < batch_size, 0 <= x[i] < output_spatial_shape[i], 0 <= c < num_channels:
output[b, x[0], ..., x[N-1], c] = REDUCE_{z[0], ..., z[N-1]} input[b, x[0] * strides[0] - pad_before[0] + dilation_rate[0]*z[0], ... x[N-1]*strides[N-1] - pad_before[N-1] + dilation_rate[N-1]*z[N-1], c],
where the reduction function REDUCE depends on the value of pooling_type
, and pad_before is defined based on the value of padding
as described in the "returns" section of tf.nn.convolution
for details. The reduction never includes out-of-bounds positions.
In the case that data_format
starts with "NC"
, the input
and output are simply transposed as follows:
pool(input, data_format, **kwargs) = tf.transpose(pool(tf.transpose(input, [0] + range(2,N+2) + [1]), **kwargs), [0, N+1] + range(1, N+1))
Args | |
---|---|
input | Tensor of rank N+2, of shape [batch_size] + input_spatial_shape + [num_channels] if data_format does not start with "NC" (default), or [batch_size, num_channels] + input_spatial_shape if data_format starts with "NC". Pooling happens over the spatial dimensions only. |
window_shape | Sequence of N ints >= 1. |
pooling_type | Specifies pooling operation, must be "AVG" or "MAX". |
strides | Optional. Sequence of N ints >= 1. Defaults to [1]N. If any value of strides is > 1, then all values of dilation_rate must be 1. |
padding | The padding algorithm, must be "SAME" or "VALID". Defaults to "SAME". See the "returns" section of tf.nn.convolution for details. |
data_format | A string or None. Specifies whether the channel dimension of the input and output is the last dimension (default, or if data_format does not start with "NC"), or the second dimension (if data_format starts with "NC"). For N=1, the valid values are "NWC" (default) and "NCW". For N=2, the valid values are "NHWC" (default) and "NCHW". For N=3, the valid values are "NDHWC" (default) and "NCDHW". |
dilations | Optional. Dilation rate. List of N ints >= 1. Defaults to [1]N. If any value of dilation_rate is > 1, then all values of strides must be 1. |
name | Optional. Name of the op. |
Returns | |
---|---|
Tensor of rank N+2, of shape [batch_size] + output_spatial_shape + [num_channels] if data_format is None or does not start with "NC", or [batch_size, num_channels] + output_spatial_shape if data_format starts with "NC", where If padding = "SAME": output_spatial_shape[i] = ceil(input_spatial_shape[i] / strides[i]) If padding = "VALID": output_spatial_shape[i] = ceil((input_spatial_shape[i] - (window_shape[i] - 1) * dilation_rate[i]) / strides[i]). |
Raises | |
---|---|
ValueError | if arguments are invalid. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/compat/v2/nn/pool