mindspore.Tensor.remainder

Tensor.remainder(self, divisor) → Tensor

Computes the remainder of self divided by other element-wise. The result has the same sign as the divisor and its absolute value is less than that of other.

Supports broadcasting to a common shape and implicit type promotion.

\[remainder(input, other) = input - input.div(other, rounding\_mode="floor") * other\]

Note

Complex inputs are not supported. At least one input need to be tensor, but not both are bool tensors.

Parameters

  • self (Union[Tensor, numbers.Number, bool]) – The dividend is a numbers.Number or a bool or a tensor whose data type is number or bool_.

  • other (Union[Tensor, numbers.Number, bool]) – The divisor is a numbers.Number or a bool or a tensor whose data type is number or bool_ when the dividend is a tensor. When the dividend is Scalar, the divisor must be a Tensor whose data type is number or bool_.

Returns

Tensor, with dtype promoted and shape broadcasted.

Raises

  • TypeError – If self and other are not of types: (tensor, tensor), (tensor, number), (tensor, bool), (number, tensor) or (bool, tensor).

  • ValueError – If self and other are not broadcastable.

Supported Platforms:

Ascend

Examples

>>> import numpy as np
>>> from mindspore import Tensor
>>> x = Tensor(np.array([-4.0, 5.0, 6.0]).astype(np.float32))
>>> y = Tensor(np.array([3.0, 2.0, 3.0]).astype(np.float64))
>>> output = x.remainder(y)
>>> print(output)
[2.  1.  0.]