github_39605284的博客

How to print tensor in Tensorflow custom estimator for debugging?

老版本：filename_queue = tf.train.string_input_producer([tfrecords_filename],num_epochs=None) #读入流中reader = tf.TFRecordReader()_, serialized_example = reader.read(filename_queue)features = tf.parse_single_example(serialized_example,

network.fit( x, y,batch_size=32, epochs=10, verbose=1, callbacks=None,validation_split=0.0, validation_data=None,shuffle=True, class_weight=None,sample_weight=None, initial_epoch=0)x：输入数据。如果模型只有一个输入，那么x的类型是numpyarray，如果模型有多个输入，那么x的类型应当为list，list的元素是

There is no real difference between the three, but sometimes one or the other may be more convenient:What’s the difference between using tf.expand_dims and tf.newaxis in Tensorflow?

tf.reduce_mean(input_tensor, axis=None, keep_dims=False, name=None, reduction_indices=None)Computes the mean of elements across dimensions of a tensor.Reduces input_tensor along the dimensions given in axis. Unless keep_dims is true, the rank of the ten