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complexnn/utils.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Contributors: Titouan Parcollet
# Authors: Dmitriy Serdyuk, Olexa Bilaniuk, Chiheb Trabelsi
import keras.backend as K
from keras.layers import Layer, Lambda
################
# Quaternions #
################
def get_rpart(x):
image_format = K.image_data_format()
ndim = K.ndim(x)
input_shape = K.shape(x)
if (image_format == 'channels_first' and ndim != 3) or ndim == 2:
input_dim = input_shape[1] // 4
return x[:, :input_dim]
input_dim = input_shape[-1] // 4
if ndim == 3:
return x[:, :, :input_dim]
elif ndim == 4:
return x[:, :, :, :input_dim]
elif ndim == 5:
return x[:, :, :, :, :input_dim]
def get_ipart(x):
image_format = K.image_data_format()
ndim = K.ndim(x)
input_shape = K.shape(x)
if (image_format == 'channels_first' and ndim != 3) or ndim == 2:
input_dim = input_shape[1] // 4
return x[:, input_dim:input_dim*2]
input_dim = input_shape[-1] // 4
if ndim == 3:
return x[:, :, input_dim:input_dim*2]
elif ndim == 4:
return x[:, :, :, input_dim:input_dim*2]
elif ndim == 5:
return x[:, :, :, :, input_dim:input_dim*2]
def get_jpart(x):
image_format = K.image_data_format()
ndim = K.ndim(x)
input_shape = K.shape(x)
if (image_format == 'channels_first' and ndim != 3) or ndim == 2:
input_dim = input_shape[1] // 4
return x[:, input_dim*2:input_dim*3]
input_dim = input_shape[-1] // 4
if ndim == 3:
return x[:, :, input_dim*2:input_dim*3]
elif ndim == 4:
return x[:, :, :, input_dim*2:input_dim*3]
elif ndim == 5:
return x[:, :, :, :, input_dim*2:input_dim*3]
def get_kpart(x):
image_format = K.image_data_format()
ndim = K.ndim(x)
input_shape = K.shape(x)
if (image_format == 'channels_first' and ndim != 3) or ndim == 2:
input_dim = input_shape[1] // 4
return x[:, input_dim*3:]
input_dim = input_shape[-1] // 4
if ndim == 3:
return x[:, :, input_dim*3:]
elif ndim == 4:
return x[:, :, :, input_dim*3:]
elif ndim == 5:
return x[:, :, :, :, input_dim*3:]
class GetR(Layer):
def call(self, inputs):
return get_rpart(inputs)
def compute_output_shape(self, input_shape):
return getpart_quaternion_output_shape(input_shape)
class GetI(Layer):
def call(self, inputs):
return get_ipart(inputs)
def compute_output_shape(self, input_shape):
return getpart_quaternion_output_shape(input_shape)
class GetJ(Layer):
def call(self, inputs):
return get_jpart(inputs)
def compute_output_shape(self, input_shape):
return getpart_quaternion_output_shape(input_shape)
class GetK(Layer):
def call(self, inputs):
return get_kpart(inputs)
def compute_output_shape(self, input_shape):
return getpart_quaternion_output_shape(input_shape)
def getpart_quaternion_output_shape(input_shape):
returned_shape = list(input_shape[:])
image_format = K.image_data_format()
ndim = len(returned_shape)
if (image_format == 'channels_first' and ndim != 3) or ndim == 2:
axis = 1
else:
axis = -1
returned_shape[axis] = returned_shape[axis] // 4
return tuple(returned_shape)
#
# GetReal/GetImag Lambda layer Implementation
#
def get_realpart(x):
image_format = K.image_data_format()
ndim = K.ndim(x)
input_shape = K.shape(x)
if (image_format == 'channels_first' and ndim != 3) or ndim == 2:
input_dim = input_shape[1] // 2
return x[:, :input_dim]
input_dim = input_shape[-1] // 2
if ndim == 3:
return x[:, :, :input_dim]
elif ndim == 4:
return x[:, :, :, :input_dim]
elif ndim == 5:
return x[:, :, :, :, :input_dim]
def get_imagpart(x):
image_format = K.image_data_format()
ndim = K.ndim(x)
input_shape = K.shape(x)
if (image_format == 'channels_first' and ndim != 3) or ndim == 2:
input_dim = input_shape[1] // 2
return x[:, input_dim:]
input_dim = input_shape[-1] // 2
if ndim == 3:
return x[:, :, input_dim:]
elif ndim == 4:
return x[:, :, :, input_dim:]
elif ndim == 5:
return x[:, :, :, :, input_dim:]
def get_abs(x):
real = get_realpart(x)
imag = get_imagpart(x)
return K.sqrt(real * real + imag * imag)
def getpart_output_shape(input_shape):
returned_shape = list(input_shape[:])
image_format = K.image_data_format()
ndim = len(returned_shape)
if (image_format == 'channels_first' and ndim != 3) or ndim == 2:
axis = 1
else:
axis = -1
returned_shape[axis] = returned_shape[axis] // 2
return tuple(returned_shape)
class GetReal(Layer):
def call(self, inputs):
return get_realpart(inputs)
def compute_output_shape(self, input_shape):
return getpart_output_shape(input_shape)
class GetImag(Layer):
def call(self, inputs):
return get_imagpart(inputs)
def compute_output_shape(self, input_shape):
return getpart_output_shape(input_shape)
class GetAbs(Layer):
def call(self, inputs):
return get_abs(inputs)
def compute_output_shape(self, input_shape):
return getpart_output_shape(input_shape)
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