def test_nll_loss2d_sum(self):
inputs_ms = mindspore.Tensor(self.inputs_2d, mindspore.float32)
target_ms = mindspore.Tensor(self.target_2d, mindspore.int32)
res_ms = nll_loss_ms(inputs_ms, target_ms, reduction='sum')
inputs_pt = torch.tensor(self.inputs_2d)
target_pt = torch.tensor(self.target_2d)
res_pt = nll_loss_pt(inputs_pt, target_pt, reduction='sum')
assert np.allclose(res_ms.asnumpy(), res_pt, 1e-3, 1e-3)
def test_nll_loss_mean_ignore_index(self):
inputs_ms = mindspore.Tensor(self.inputs, mindspore.float32)
target_ms = mindspore.Tensor(self.target, mindspore.int32)
res_ms = nll_loss_ms(inputs_ms, target_ms, ignore_index=0)
inputs_pt = torch.tensor(self.inputs)
target_pt = torch.tensor(self.target)
res_pt = nll_loss_pt(inputs_pt, target_pt, ignore_index=0)
assert np.allclose(res_ms.asnumpy(), res_pt.numpy(), 1e-3, 1e-3)
def test_nll_loss2d(self):
inputs_ms = mindspore.Tensor(self.inputs_2d, mindspore.float32)
target_ms = mindspore.Tensor(self.target_2d, mindspore.int32)
res_ms = nll_loss_ms(inputs_ms, target_ms, reduction='none')
inputs_pt = torch.tensor(self.inputs_2d)
target_pt = torch.tensor(self.target_2d)
res_pt = nll_loss_pt(inputs_pt, target_pt, reduction='none')
print(res_ms.shape, res_pt.shape)
assert np.allclose(res_ms.asnumpy(), res_pt, atol=1e-3)
def test_nll_loss_sum_with_weight(self):
inputs_ms = mindspore.Tensor(self.inputs, mindspore.float32)
target_ms = mindspore.Tensor(self.target, mindspore.int32)
weight_ms = mindspore.Tensor(self.weight, mindspore.float32)
res_ms = nll_loss_ms(inputs_ms,
target_ms,
reduction='none',
weight=weight_ms)
inputs_pt = torch.tensor(self.inputs)
target_pt = torch.tensor(self.target)
weight_pt = torch.tensor(self.weight)
res_pt = nll_loss_pt(inputs_pt,
target_pt,
reduction='none',
weight=weight_pt)
assert np.allclose(res_ms.asnumpy(), res_pt.numpy(), 1e-3, 1e-3)