CIntToPy */

__GNUC__ */

* Called during search to add an element matching the criteria. * @return true if the search should be continued, false if the result

* Called during search to add an element matching the criteria. * @return true if the search should be continued, false if the results are * suf

* Called during search to add an element matching the criteria. * @return true if the search should be continued, false if the results are * suf

Add points to the set, Inserts all points from [start, end] */

Add points to the set, Inserts all points from [start, end] */

Add points to the set, Inserts all points from [start, end] */

at() with range check

2D avg pooling. Args: inputs: 4-D tensor BxHxWxC kernel_size: a list of 2 ints stride: a list of 2 ints Returns: Va

3D avg pooling. Args: inputs: 5-D tensor BxDxHxWxC kernel_size: a list of 3 ints stride: a list of 3 ints Returns:

Batch normalization on 2D convolutional maps. Args: inputs: Tensor, 4D BHWC input maps is_training: boolean tf.Varialbe, tr

* Builds the index */

* Builds the index */

* Builds the index */

1D convolution with non-linear operation. Args: inputs: 3-D tensor variable BxLxC num_output_channels: int kernel_size: int

2D convolution with non-linear operation. Args: inputs: 4-D tensor variable BxHxWxC num_output_channels: int kernel_size: a li

2D convolution transpose with non-linear operation. Args: inputs: 4-D tensor variable BxHxWxC num_output_channels: int kernel_

3D convolution with non-linear operation. Args: inputs: 5-D tensor variable BxDxHxWxC num_output_channels: int kernel_size: a

Takes the columns of the dataframe and builds a ply-like description Parameters ---------- name: str df: pandas DataFrame Retur

opperations