TensorFlow 2 version
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View source on GitHub
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Computes the "logical and" of elements across dimensions of a tensor. (deprecated arguments)
tf.math.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
TensorFlow 2 version
View source on GitHub