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(