Function Differences with torch.nn.MaxPool3d

torch.nn.MaxPool3d(kernel_size, stride=None, padding=0, dilation=1, return_indices=False, ceil_mode=False)(input) -> Tensor

mindspore.nn.MaxPool3d(kernel_size=1, stride=1, pad_mode="valid", padding=0, dilation=1, return_indices=False, ceil_mode=False)(x) -> Tensor

import mindspore as ms
from mindspore import Tensor
import mindspore.nn as nn
import torch
import numpy as np

np_x = np.random.randint(0, 10, [1, 2, 4, 4, 5])

x = Tensor(np_x, ms.float32)
max_pool = nn.MaxPool3d(kernel_size=2, stride=1, pad_mode='pad', padding=1, dilation=1, return_indices=False)
output = max_pool(x)
result = output.shape
print(result)
# (1, 2, 5, 5, 6)
x = torch.tensor(np_x, dtype=torch.float32)
max_pool = torch.nn.MaxPool3d(kernel_size=2, stride=1, padding=1, dilation=1, return_indices=False)
output = max_pool(x)
result = output.shape
print(result)
# torch.Size([1, 2, 5, 5, 6])