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

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import numpy as np

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


@arithmetic_operand(sparse_mode="binary_or")
class TensorMod(TensorBinOp):
    _op_type_ = OperandDef.MOD
    _func_name = "mod"


[docs]@infer_dtype(np.mod) def mod(x1, x2, out=None, where=None, **kwargs): """ Return element-wise remainder of division. Computes the remainder complementary to the `floor_divide` function. It is equivalent to the Python modulus operator``x1 % x2`` and has the same sign as the divisor `x2`. The MATLAB function equivalent to ``np.remainder`` is ``mod``. .. warning:: This should not be confused with: * Python 3.7's `math.remainder` and C's ``remainder``, which computes the IEEE remainder, which are the complement to ``round(x1 / x2)``. * The MATLAB ``rem`` function and or the C ``%`` operator which is the complement to ``int(x1 / x2)``. Parameters ---------- x1 : array_like Dividend array. x2 : array_like Divisor array. 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 ------- y : Tensor The element-wise remainder of the quotient ``floor_divide(x1, x2)``. Returns a scalar if both `x1` and `x2` are scalars. See Also -------- floor_divide : Equivalent of Python ``//`` operator. divmod : Simultaneous floor division and remainder. fmod : Equivalent of the MATLAB ``rem`` function. divide, floor Notes ----- Returns 0 when `x2` is 0 and both `x1` and `x2` are (tensors of) integers. Examples -------- >>> import mars.tensor as mt >>> mt.remainder([4, 7], [2, 3]).execute() array([0, 1]) >>> mt.remainder(mt.arange(7), 5).execute() array([0, 1, 2, 3, 4, 0, 1]) """ op = TensorMod(**kwargs) return op(x1, x2, out=out, where=where)
remainder = mod @infer_dtype(np.mod, reverse=True) def rmod(x1, x2, **kwargs): op = TensorMod(**kwargs) return op.rcall(x1, x2)