mindspore.ops.ListDiff

class mindspore.ops.ListDiff(out_idx=mstype.int32)[source]

Computes the difference between two lists of numbers.

Given a list x and a list y, this operation returns a list out that represents all values that are in x but not in y. The returned list out is sorted in the same order that the numbers appear in x (duplicates are preserved). This operation also returns a list idx that represents the position of each out element in x. In other words: out[i] = x[idx[i]] for i in [0, 1, ..., len(out) - 1] .

Parameters

out_idx (mindspore.dtype, optional) – The dtype of idx, an optioanal datatype of mindspore.dtype.int32 and mindspore.dtype.int64. Default: mindspore.dtype.int32.

Inputs:

  • x - A 1-D Tensor. Values to keep. type support list [float16, float32, float64, uint8, uint16, int8, int16, int32, int64]

  • y - A 1-D Tensor. Must have the same type as x. 1-D. Values to remove.

Outputs:

  • out - A 1-D Tensor. Has the same type as x.

  • idx - A 1-D Tensor of type out_idx.

Raises

  • ValueError – If x or y shape is not 1D.

  • TypeError – If x or y is not a Tensor.

  • TypeError – If x or y datetype not in support list.

  • TypeError – If x has different data type with y.

  • TypeError – If attr out_idx not in [mindspore.dtype.int32, mindspore.dtype.int64].

Supported Platforms:

GPU CPU

Examples

>>> x = Tensor(np.arange(1, 7, 1), dtype=mindspore.dtype.int32) # [1, 2, 3, 4, 5, 6]
>>> y = Tensor([1, 3, 5], dtype=mindspore.dtype.int32)
>>> op = ops.ListDiff() # out_idx default is mindspore.dtype.int32
>>> out, idx = op(x, y)
>>> print(out)
[2 4 6]
>>> print(idx)
[1 3 5]