질문이있다? TensorFlow 포럼 에서 커뮤니티와 연결

# tf.math.reduce_mean

Computes the mean of elements across dimensions of a tensor.

Reduces `input_tensor` along the dimensions given in `axis` by computing the mean of elements across the dimensions in `axis`. Unless `keepdims` is true, the rank of the tensor is reduced by 1 for each entry in `axis`. If `keepdims` is true, the reduced dimensions are retained with length 1.

If `axis` is None, all dimensions are reduced, and a tensor with a single element is returned.

#### For example:

````x = tf.constant([[1., 1.], [2., 2.]])`
`tf.reduce_mean(x)`
`<tf.Tensor: shape=(), dtype=float32, numpy=1.5>`
`tf.reduce_mean(x, 0)`
`<tf.Tensor: shape=(2,), dtype=float32, numpy=array([1.5, 1.5], dtype=float32)>`
`tf.reduce_mean(x, 1)`
`<tf.Tensor: shape=(2,), dtype=float32, numpy=array([1., 2.], dtype=float32)>`
```

`input_tensor` The tensor to reduce. Should have numeric type.
`axis` The dimensions to reduce. If `None` (the default), reduces all dimensions. Must be in the range ```[-rank(input_tensor), rank(input_tensor))```.
`keepdims` If true, retains reduced dimensions with length 1.
`name` A name for the operation (optional).

The reduced tensor.

#### Numpy Compatibility

Equivalent to np.mean

Please note that `np.mean` has a `dtype` parameter that could be used to specify the output type. By default this is `dtype=float64`. On the other hand, `tf.reduce_mean` has an aggressive type inference from `input_tensor`, for example:

````x = tf.constant([1, 0, 1, 0])`
`tf.reduce_mean(x)`
`<tf.Tensor: shape=(), dtype=int32, numpy=0>`
`y = tf.constant([1., 0., 1., 0.])`
`tf.reduce_mean(y)`
`<tf.Tensor: shape=(), dtype=float32, numpy=0.5>`
```
[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"필요한 정보가 없음" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"너무 복잡함/단계 수가 너무 많음" },{ "type": "thumb-down", "id": "outOfDate", "label":"오래됨" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"기타" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"이해하기 쉬움" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"문제가 해결됨" },{ "type": "thumb-up", "id": "otherUp", "label":"기타" }]