modules.py 文件源码

def compile(self, in_x, train_feed, eval_feed):
        in_height, in_width, in_nchannels = self.in_d 
        nfilters, filter_len, stride, padding, param_init_fn = [dom[i] 
                for (dom, i) in zip(self.domains, self.chosen)]

        # Creation and initialization of the parameters. Should take size of 
        # the filter into account.
        W = tf.Variable(
                param_init_fn( [filter_len, filter_len, in_nchannels, nfilters]) )
        b = tf.Variable(tf.zeros([nfilters]))

        # create the output and add the bias.
        out_yaux = tf.nn.conv2d(in_x, W, strides=[1, stride, stride, 1], padding=padding)
        out_y = tf.nn.bias_add(out_yaux, b)

        #print(in_x.get_shape(), self.get_outdim(), out_y.get_shape())

        return out_y