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我有一个函数，它以以下格式返回一个名为layer图像的变量：

我需要用.jpeg格式保存这些图像。在

到目前为止，我一直在考虑这样做：

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在会话中=tf.会议()# That means it will only scroll through my 300 images...

x_batch, y_true_batch = next_batch_size(train_batch_size)

feed_dict_train = {x: x_batch, y_true: y_true_batch}

result = session.run(fwrite, feed_dict=feed_dict_train)

但我得到了以下错误：InvalidArgumentError (see above for traceback): Input to reshape is a tensor with 76800 values, but the requested shape has 256

[[Node: Reshape_7 = Reshape[T=DT_UINT8, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](Cast_7, Reshape_7/shape)]]

我的占位符是：# Placeholder variable for the input images

x = tf.placeholder(tf.float32, shape=[None, img_size_flat], name='x')

# Reshape 'x'

x_image = tf.reshape(x, [-1, img_size, img_size, num_channels])

# Placeholder variable for the true labels associated with the images

y_true = tf.placeholder(tf.float32, shape=[None, num_classes], name='y_true')

你知道怎么解决这个问题吗？或者我可以用其他方法来保存图像吗？在