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tf.compat.v2.reduce_all

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

Aliases:

tf.compat.v2.reduce_all(
    input_tensor,
    axis=None,
    keepdims=False,
    name=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).

Returns:

The reduced tensor.

Numpy Compatibility

Equivalent to np.all