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Computes tf.math.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
)
This is the reduction operation for the elementwise tf.math.logical_and
op.
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.math.reduce_all(x)
<tf.Tensor: shape=(), dtype=bool, numpy=False>
tf.math.reduce_all(x, 0)
<tf.Tensor: shape=(2,), dtype=bool, numpy=array([False, False])>
tf.math.reduce_all(x, 1)
<tf.Tensor: shape=(2,), dtype=bool, numpy=array([ 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