def build_convolution(self, layer, previous_layer, last_output, **kwargs):
input_shape = previous_layer['output_shape']
layer['filter_shape'] = (
kwargs['n_kerns'],
input_shape[1],
kwargs['height'],
kwargs['width']
)
entity = Convolution.withoutFilters(
filter_shape=layer['filter_shape'],
image_shape=input_shape
)
layer['output_shape'] = entity.output_shape()
layer['image_shape'] = input_shape
layer['filter_shape'] = layer['filter_shape']
### Logging ###
self.logger.info("conv output shape")
self.logger.info(layer['output_shape'])
self.logger.info("conv image shape")
self.logger.info(layer['image_shape'])
self.logger.info("conv filter shape")
self.logger.info(layer['filter_shape'])
return (layer, entity)
y_a = np.append(a, np.zeros((50, 61)), 1)
t3_y_out_shared = theano.shared(value=y_a.astype(theano.config.floatX),
borrow=True)
filters_multi = theano.shared(value=filters_multi.reshape(
(115, 1, 8, 8)).eval().astype(theano.config.floatX),
borrow=True)
print("Convolve0")
print((50, ) + (1, ) + t3_images.shape[-2:])
nkernels = [115, 20]
conv0 = Convolution.withFilters(filter_shape=(nkernels[0], 1, 8, 8),
image_shape=(
batch_size,
1,
) + t3_images.shape[-2:],
filters=filters_multi)
fm0 = conv0.get_output(x)
next_filter = conv0.pipe_filter_shape(20, 4, 4)
next_img = conv0.pipe_image_shape
print("Next_filter conv0")
print(next_filter)
print(next_img)
print("Pool0")
pool0 = Pool((2, 2))
pool_out0 = pool0.get_output(fm0)
next_filter = pool0.pipe_filter_shape((nkernels[0], 1, 8, 8), 20, 4, 4)
next_img = pool0.pipe_image_shape((
value=y_a.astype(theano.config.floatX),
borrow=True
)
filters_multi = theano.shared(
value=filters_multi.reshape((115,1,8,8)).eval().astype(theano.config.floatX),
borrow=True
)
print("Convolve0")
print((50,) + (1,) + t3_images.shape[-2:])
nkernels=[115,20]
conv0 = Convolution.withFilters(
filter_shape=(nkernels[0], 1, 8, 8),
image_shape=(batch_size, 1,) + t3_images.shape[-2:],
filters=filters_multi
)
fm0 = conv0.get_output(x)
next_filter = conv0.pipe_filter_shape(20, 4, 4)
next_img = conv0.pipe_image_shape
print("Next_filter conv0")
print(next_filter)
print(next_img)
print("Pool0")
pool0 = Pool((2,2))
pool_out0 = pool0.get_output(fm0)
next_filter = pool0.pipe_filter_shape((nkernels[0], 1, 8, 8), 20, 4, 4)
next_img = pool0.pipe_image_shape(
