mindspore.ops.CumSum
- class mindspore.ops.CumSum(exclusive=False, reverse=False)[source]
Computes the cumulative sum of input tensor along axis.
\[y_i = x_1 + x_2 + x_3 + ... + x_i\]- Parameters
- Inputs:
input (Tensor) - The input tensor to accumulate.
axis (int) - The axis to accumulate the tensor’s value. Only constant value is allowed. Must be in the range [-rank(input), rank(input)).
- Outputs:
Tensor, the shape of the output tensor is consistent with the input tensor’s.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> x = Tensor(np.array([[3, 4, 6, 10], [1, 6, 7, 9], [4, 3, 8, 7], [1, 3, 7, 9]]).astype(np.float32)) >>> cumsum = ops.CumSum() >>> # case 1: along the axis 0 >>> y = cumsum(x, 0) >>> print(y) [[ 3. 4. 6. 10.] [ 4. 10. 13. 19.] [ 8. 13. 21. 26.] [ 9. 16. 28. 35.]] >>> # case 2: along the axis 1 >>> y = cumsum(x, 1) >>> print(y) [[ 3. 7. 13. 23.] [ 1. 7. 14. 23.] [ 4. 7. 15. 22.] [ 1. 4. 11. 20.]] >>> # Next demonstrate exclusive and reverse, along axis 1 >>> # case 3: exclusive = True >>> cumsum = ops.CumSum(exclusive=True) >>> y = cumsum(x, 1) >>> print(y) [[ 0. 3. 7. 13.] [ 0. 1. 7. 14.] [ 0. 4. 7. 15.] [ 0. 1. 4. 11.]] >>> # case 4: reverse = True >>> cumsum = ops.CumSum(reverse=True) >>> y = cumsum(x, 1) >>> print(y) [[23. 20. 16. 10.] [23. 22. 16. 9.] [22. 18. 15. 7.] [20. 19. 16. 9.]]