Source code for xorbits._mars.tensor.arithmetic.greater

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import numpy as np

from ... import opcodes as OperandDef
from ..utils import inject_dtype
from .core import TensorBinOp
from .utils import arithmetic_operand


@arithmetic_operand(sparse_mode="binary_and")
class TensorGreaterThan(TensorBinOp):
    _op_type_ = OperandDef.GT
    _func_name = "greater"


[docs]@inject_dtype(np.bool_) def greater(x1, x2, out=None, where=None, **kwargs): """ Return the truth value of (x1 > x2) element-wise. Parameters ---------- x1, x2 : array_like Input tensors. If ``x1.shape != x2.shape``, they must be broadcastable to a common shape (which may be the shape of one or the other). out : Tensor, None, or tuple of Tensor and None, optional A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or `None`, a freshly-allocated tensor is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. where : array_like, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs Returns ------- out : bool or Tensor of bool Array of bools, or a single bool if `x1` and `x2` are scalars. See Also -------- greater_equal, less, less_equal, equal, not_equal Examples -------- >>> import mars.tensor as mt >>> mt.greater([4,2],[2,2]).execute() array([ True, False]) If the inputs are ndarrays, then np.greater is equivalent to '>'. >>> a = mt.array([4,2]) >>> b = mt.array([2,2]) >>> (a > b).execute() array([ True, False]) """ op = TensorGreaterThan(**kwargs) return op(x1, x2, out=out, where=where)