def build_pool(self, layer, previous_layer, last_output, **kwargs): entity = Pool(kwargs['shape']) if previous_layer['name'] == 'Convolution': layer['output_shape'] = entity.output_shape( previous_layer['output_shape'] ) else: layer['output_shape'] = ( previous_layer['output_shape'] / kwargs['shape'] ) ### Logging ### self.logger.info("pool output shape") self.logger.info(layer['output_shape']) return (layer, entity)
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(( batch_size, 1, ) + t3_images.shape[-2:], (nkernels[0], 1, 8, 8)) print("Next_filter pool0") print(next_filter) print(next_img) print("####") print((nkernels[1], nkernels[0], 4, 4)) print((batch_size, nkernels[0], 12, 12)) conv1 = Convolution.withoutFilters(filter_shape=(nkernels[1], nkernels[0], 4, 4), image_shape=(batch_size, nkernels[0], 12,
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( (batch_size, 1,) + t3_images.shape[-2:], (nkernels[0], 1, 8, 8) ) print("Next_filter pool0") print(next_filter) print(next_img) print("####") print((nkernels[1],nkernels[0],4,4)) print((batch_size, nkernels[0], 12, 12)) conv1 = Convolution.withoutFilters( filter_shape=(nkernels[1],nkernels[0],4,4), image_shape=(batch_size, nkernels[0], 12, 12)