mindspore.Tensor.cummax
- Tensor.cummax(axis)[source]
Returns a tuple (values,indices) where ‘values’ is the cumulative maximum value of self Tensor along the dimension axis, and indices is the index location of each maximum value.
\[\begin{split}\begin{array}{ll} \\ y{i} = max(x{1}, x{2}, ... , x{i}) \end{array}\end{split}\]- Parameters
axis (int) – The dimension to do the operation over. The value of axis must be in the range [-x.ndim, x.ndim - 1].
- Returns
tuple [Tensor], tuple of 2 Tensors, containing the cumulative maximum of elements and the index, The shape of each output tensor is the same as self Tensor.
- Raises
TypeError – If axis is not an int.
ValueError – If axis is out the range of [-x.ndim, x.ndim - 1].
- Supported Platforms:
GPU
CPU
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor >>> import mindspore.ops as ops >>> x = Tensor(np.array([[3, 4, 6, 10], [1, 6, 7, 9], [4, 3, 8, 7], [1, 3, 7, 9]]).astype(np.float32)) >>> output = x.cummax(axis=0) >>> print(output[0]) [[ 3. 4. 6. 10.] [ 3. 6. 7. 10.] [ 4. 6. 8. 10.] [ 4. 6. 8. 10.]] >>> print(output[1]) [[0 0 0 0] [0 1 1 0] [2 1 2 0] [2 1 2 0]]