import mindspore
from mindspore import ops
from mindspore import Tensor, nn
from mindspore.common.api import jit
from mindspore import context
import numpy as np

import torch


input = np.random.uniform(size=(16,3,10,32,32))

ms_input = Tensor(input, mindspore.float32)
conv3d = nn.Conv3d(in_channels=3, out_channels=32, kernel_size=(4, 3, 3), has_bias=True, pad_mode='valid')
ms_out = conv3d(ms_input)

torch_input = torch.Tensor(input)
m = torch.nn.Conv3d(3, 32,kernel_size=(4, 3, 3))
torch_out = m(torch_input)


# 失败
y = np.subtract(ms_out.asnumpy(), torch_out.detach().numpy())
w = np.where(np.abs(y) > 0.00004, 1, 0)
z = np.count_nonzero(w)