Keras Tensor 操作的时候,第一维度是“?”,所以特殊处理,让其batchsize可变
You just need to feed it in as a single example but in the batched shape. So that means adding an extra dimension to the shape e.g.
batch_size = 32 # set this to the actual size of your batch
tf.truncated_normal((batch_size, 784), mean=0.0, stddev=1.0, dtype=tf.float32, seed=None, name=None)
This way it will "fit" into the placeholder.
If you expect batch_size to change you can also use:
tf.truncated_normal(tf.shape(input_tensor), mean=0.0, stddev=1.0, dtype=tf.float32, seed=None, name=None)
Where input_tensor could be a placeholder or just whatever tensor is going to have this noise added to it.