Tensorflow Argmax：“轴”和“尺寸”参数有什么区别？

Question

当前版本的Tensorflow Argmax没有指定“轴”和“维度”参数之间的区别。这是在给定official manual的唯一信息：

tf.argmax(input, axis=None, name=None, dimension=None) {#argmax} 

Returns the index with the largest value across axes of a tensor. 

Args: 

input: A Tensor. Must be one of the following types: float32, float64, int64, int32, uint8, uint16, int16, int8, complex64, complex128, qint8, quint8, qint32, half. 

axis: A Tensor. Must be one of the following types: int32, int64. int32, 0 <= axis < rank(input). Describes which axis of the input Tensor to reduce across. For vectors, use axis = 0. 

name: A name for the operation (optional). 

Returns: 

A Tensor of type int64. 

有人能澄清？哪一个实际上是减少的维度？

Answer 1

TensorFlow正在转换到使用axis而非dimension这是会很快被弃用：https://www.tensorflow.org/install/migration