Source code for mars.tensor.reduction.all

#!/usr/bin/env python
# -*- coding: utf-8 -*-
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#      http://www.apache.org/licenses/LICENSE-2.0
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import numpy as np

from ... import opcodes as OperandDef
from ..datasource import tensor as astensor
from .core import TensorReduction, TensorReductionMixin


class TensorAll(TensorReduction, TensorReductionMixin):
    _op_type_ = OperandDef.ALL
    _func_name = 'all'

    def __init__(self, axis=None, keepdims=None, combine_size=None, stage=None, **kw):
        stage = self._rewrite_stage(stage)
        super().__init__(_axis=axis, _keepdims=keepdims,
                         _combine_size=combine_size, stage=stage, **kw)


[docs]def all(a, axis=None, out=None, keepdims=None, combine_size=None): """ Test whether all array elements along a given axis evaluate to True. Parameters ---------- a : array_like Input tensor or object that can be converted to a tensor. axis : None or int or tuple of ints, optional Axis or axes along which a logical AND reduction is performed. The default (`axis` = `None`) is to perform a logical AND over all the dimensions of the input array. `axis` may be negative, in which case it counts from the last to the first axis. If this is a tuple of ints, a reduction is performed on multiple axes, instead of a single axis or all the axes as before. out : Tensor, optional Alternate output tensor in which to place the result. It must have the same shape as the expected output and its type is preserved (e.g., if ``dtype(out)`` is float, the result will consist of 0.0's and 1.0's). See `doc.ufuncs` (Section "Output arguments") for more details. keepdims : bool, optional If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the input tensor. If the default value is passed, then `keepdims` will not be passed through to the `all` method of sub-classes of `ndarray`, however any non-default value will be. If the sub-classes `sum` method does not implement `keepdims` any exceptions will be raised. combine_size: int, optional The number of chunks to combine. Returns ------- all : Tensor, bool A new boolean or tensor is returned unless `out` is specified, in which case a reference to `out` is returned. See Also -------- Tensor.all : equivalent method any : Test whether any element along a given axis evaluates to True. Notes ----- Not a Number (NaN), positive infinity and negative infinity evaluate to `True` because these are not equal to zero. Examples -------- >>> import mars.tensor as mt >>> mt.all([[True,False],[True,True]]).execute() False >>> mt.all([[True,False],[True,True]], axis=0).execute() array([ True, False]) >>> mt.all([-1, 4, 5]).execute() True >>> mt.all([1.0, mt.nan]).execute() True """ a = astensor(a) if a.dtype == np.object_: dtype = a.dtype else: dtype = np.dtype(bool) op = TensorAll(axis=axis, dtype=dtype, keepdims=keepdims, combine_size=combine_size) return op(a, out=out)