conv_utils

Utilities used in convolutional layers.

Module Contents

Functions

normalize_tuple(value, n, name)	Transforms a single int or iterable of ints into an int tuple.
normalize_padding(value)
convert_kernel(kernel)	Converts a Numpy kernel matrix from Theano format to TensorFlow format.
conv_output_length(input_length, filter_size, padding, stride, dilation=1)	Determines output length of a convolution given input length.
conv_input_length(output_length, filter_size, padding, stride)	Determines input length of a convolution given output length.
deconv_length(dim_size, stride_size, kernel_size, padding, output_padding, dilation=1)	Determines output length of a transposed convolution given input length.

conv_utils.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.

conv_utils.normalize_padding(value)

conv_utils.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.

conv_utils.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).

conv_utils.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).

conv_utils.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).