:py:mod:`conv_utils`
====================

.. py:module:: conv_utils

.. autoapi-nested-parse::

   Utilities used in convolutional layers.



Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   conv_utils.normalize_tuple
   conv_utils.normalize_padding
   conv_utils.convert_kernel
   conv_utils.conv_output_length
   conv_utils.conv_input_length
   conv_utils.deconv_length



.. py:function:: normalize_tuple(value, n, name)

   Transforms a single int or iterable of ints into an int tuple.

   # Arguments
       value: The value to validate and convert. Could be an int, or any iterable
         of ints.
       n: The size of the tuple to be returned.
       name: The name of the argument being validated, e.g. `strides` or
         `kernel_size`. This is only used to format error messages.

   # Returns
       A tuple of n integers.

   # Raises
       ValueError: If something else than an int/long or iterable thereof was
       passed.


.. py:function:: normalize_padding(value)


.. py:function:: convert_kernel(kernel)

   Converts a Numpy kernel matrix from Theano format to TensorFlow format.

   Also works reciprocally, since the transformation is its own inverse.

   # Arguments
       kernel: Numpy array (3D, 4D or 5D).

   # Returns
       The converted kernel.

   # Raises
       ValueError: in case of invalid kernel shape or invalid data_format.


.. py:function:: conv_output_length(input_length, filter_size, padding, stride, dilation=1)

   Determines output length of a convolution given input length.

   # Arguments
       input_length: integer.
       filter_size: integer.
       padding: one of `"same"`, `"valid"`, `"full"`.
       stride: integer.
       dilation: dilation rate, integer.

   # Returns
       The output length (integer).


.. py:function:: conv_input_length(output_length, filter_size, padding, stride)

   Determines input length of a convolution given output length.

   # Arguments
       output_length: integer.
       filter_size: integer.
       padding: one of `"same"`, `"valid"`, `"full"`.
       stride: integer.

   # Returns
       The input length (integer).


.. py:function:: deconv_length(dim_size, stride_size, kernel_size, padding, output_padding, dilation=1)

   Determines output length of a transposed convolution given input length.

   # Arguments
       dim_size: Integer, the input length.
       stride_size: Integer, the stride along the dimension of `dim_size`.
       kernel_size: Integer, the kernel size along the dimension of
           `dim_size`.
       padding: One of `"same"`, `"valid"`, `"full"`.
       output_padding: Integer, amount of padding along the output dimension,
           Can be set to `None` in which case the output length is inferred.
       dilation: dilation rate, integer.

   # Returns
       The output length (integer).