Computes the "logical and" of elements across dimensions of a tensor. (deprecated arguments)
tf.compat.v1.reduce_all( input_tensor, axis=None, keepdims=None, name=None, reduction_indices=None, keep_dims=None )
Reduces input_tensor
along the dimensions given 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.
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]
Args | |
---|---|
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). |
reduction_indices | The old (deprecated) name for axis. |
keep_dims | Deprecated alias for keepdims . |
Returns | |
---|---|
The reduced tensor. |
Equivalent to np.all
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/reduce_all