¡Reserva! Google I / O regresa del 18 al 20 de mayo

# tf.math.reduce_all

Computes the "logical and" of elements across dimensions of a tensor.

Reduces `input_tensor` along the dimensions given in `axis`. Unless `keepdims` is true, the rank of the tensor is reduced by 1 for each of the entries in `axis`, which must be unique. 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([[True,  True], [False, False]])
tf.reduce_all(x)  # False
tf.reduce_all(x, 0)  # [False, False]
tf.reduce_all(x, 1)  # [True, False]
``````

`input_tensor` The boolean tensor to reduce.
`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.all

[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Falta la información que necesito" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Muy complicado o demasiados pasos" },{ "type": "thumb-down", "id": "outOfDate", "label":"Desactualizado" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Otro" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Fácil de comprender" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Resolvió mi problema" },{ "type": "thumb-up", "id": "otherUp", "label":"Otro" }]