# Differences with torch.Tensor.flip [](https://gitee.com/mindspore/docs/blob/r2.3.0rc2/docs/mindspore/source_en/note/api_mapping/pytorch_diff/flip.md) ## torch.Tensor.flip ```python torch.Tensor.flip(dims) ``` For more details, see [torch.Tensor.flip](https://pytorch.org/docs/1.8.1/tensors.html#torch.Tensor.flip). ## mindspore.Tensor.flip ```python mindspore.Tensor.flip(dims) ``` For more details, see [mindspore.Tensor.flip](https://www.mindspore.cn/docs/zh-CN/r2.3.0rc2/api_python/mindspore/Tensor/mindspore.Tensor.flip.html). ## Differences PyTorch: The `torch.Tensor.flip` interface has differences from `torch.flip`. Compared to `torch.flip`, `Tensor.flip` additionally supports scenarios where the `dims` input is of type int. MindSpore: The `mindspore.flip` and `mindspore.Tensor.flip` interfaces have the same functionality as `torch.flip` and do not support input of type int. | Categories | Subcategories | PyTorch | MindSpore | Differences | |----------|-------------|---------|-----------|------------| | Parameters | Parameter 1 | dims | dims | Same functionality, MindSpore does not support int input | ## Code Example ```python # PyTorch import numpy as np import torch input = torch.tensor(np.arange(1, 9).reshape((2, 2, 2))) output = input.flip(1) print(output) # tensor([[[3, 4], # [1, 2]], # # [[7, 8], # [5, 6]]]) # MindSpore import mindspore as ms import mindspore.ops as ops input = ms.Tensor(np.arange(1, 9).reshape((2, 2, 2))) output = input.flip((1, )) print(output) # [[[3 4] # [1 2]] # # [[7 8] # [5 6]]] ```