tf.compat.v1.reduce_all
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.
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]
| 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. |
Numpy Compatibility
Equivalent to np.all
© 2020 The TensorFlow Authors. All rights reserved.
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