def all_op(input, dim=None, keepdim=False):
"""Computes if all elements in the input tensor to true.
Args:
input (oneflow.Tensor): the Input Tensor
dim (int, optional): the dimension to reduce. Default: `None`
keepdim (bool, optional): whether the output tensor has dim retained or not. Default: `False`
Returns:
Tensor(oneflow.Tensor(dtype=int8)): If :attr:`dim` is `None`, returns
the logical all value of all elements in the `input` tensor.
For example:
.. code-block:: python
>>> import oneflow as flow
>>> input = flow.arange(0, 3)
>>> flow.all(input)
tensor(False, dtype=oneflow.bool)
"""
axis_checked = _check_axis(dim, input.shape)
if len(axis_checked) == 0:
return input
return flow._C.reduce_all(input, axis=axis_checked, keepdims=keepdim)
def min_op(input, dim=None, keepdim=False):
axis_checked = _check_axis(dim, input.shape)
if len(axis_checked) == 0:
return input
if dim == None:
return flow._C.reduce_min(input, axis=axis_checked, keepdims=keepdim)
else:
return (
flow._C.reduce_min(input, axis=axis_checked, keepdims=keepdim),
input.argmin(dim=dim, keepdim=keepdim),
)
def prod_op(input, dim=None, keepdim=False):
axis_checked = _check_axis(dim, input.shape)
if len(axis_checked) == 0:
return input
return flow._C.reduce_prod(input, axis_checked, keepdim)
def mean_op(input, dim=None, keepdim=False):
axis_checked = _check_axis(dim, input.shape)
if len(axis_checked) == 0:
return input
return flow._C.reduce_mean(input, axis=axis_checked, keepdims=keepdim)