code: 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 == 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)
  
file_path: mars/mars/tensor/reduction/all.py
imports: import numpy
  from ...None import opcodes
  from ..datasource import tensor
  from .core import TensorReduction, TensorReductionMixin
label_desc: Use image node_id 1 for calling a global function with example usage: all(a, axis, out, keepdims, combine_size) and returns: op