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fix unittest test nn cuda

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lucasdelimanogueira 2024-05-23 03:01:27 -03:00
parent d70e398773
commit 5946e6e1bd
1 changed files with 57 additions and 18 deletions
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75
tests/test_nn.py
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@ -26,8 +26,12 @@ class TestNNModuleLoss(unittest.TestCase):
loss_norch = loss_fn_norch.forward(predictions_norch, labels_norch)
loss_torch_result = utils.to_torch(loss_norch).to(self.device)
predictions_torch = torch.tensor([[1.1, 2, 3, 4], [1.1, 2, 3, 4]]).to(self.device)
labels_torch = torch.tensor([[1.1, 2, 3, 4], [1.1, 2, 3, 3]]).to(self.device)
predictions_torch = torch.tensor([[1.1, 2, 3, 4], [1.1, 2, 3, 4]])
labels_torch = torch.tensor([[1.1, 2, 3, 4], [1.1, 2, 3, 3]])
predictions_torch.to(self.device)
labels_torch.to(self.device)
loss_torch_expected = loss_fn_torch(predictions_torch, labels_torch)
self.assertTrue(utils.compare_torch(loss_torch_result, loss_torch_expected))
@ -38,8 +42,12 @@ class TestNNModuleLoss(unittest.TestCase):
loss_norch = loss_fn_norch.forward(predictions_norch, labels_norch)
loss_torch_result = utils.to_torch(loss_norch).to(self.device)
predictions_torch = torch.tensor([1.1, 2, 3, 4]).to(self.device)
labels_torch = torch.tensor([4, 3, 2.1, 1]).to(self.device)
predictions_torch = torch.tensor([1.1, 2, 3, 4])
labels_torch = torch.tensor([4, 3, 2.1, 1])
predictions_torch.to(self.device)
labels_torch.to(self.device)
loss_torch_expected = loss_fn_torch(predictions_torch, labels_torch)
self.assertTrue(utils.compare_torch(loss_torch_result, loss_torch_expected))
@ -58,8 +66,12 @@ class TestNNModuleLoss(unittest.TestCase):
loss_torch_result = utils.to_torch(loss_norch).to(self.device)
predictions_torch = torch.tensor([2.0, 1.0, 0.1]).to(self.device)
labels_torch = torch.tensor(0).to(self.device)
predictions_torch = torch.tensor([2.0, 1.0, 0.1])
labels_torch = torch.tensor(0)
predictions_torch.to(self.device)
labels_torch.to(self.device)
loss_torch_expected = loss_fn_torch(predictions_torch, labels_torch)
self.assertTrue(utils.compare_torch(loss_torch_result, loss_torch_expected))
@ -71,8 +83,12 @@ class TestNNModuleLoss(unittest.TestCase):
loss_torch_result = utils.to_torch(loss_norch).to(self.device)
predictions_torch = torch.tensor([[0.5, 1.5, 2.5], [1.0, 2.0, 3.0]]).to(self.device)
labels_torch = torch.tensor([2, 1]).to(self.device)
predictions_torch = torch.tensor([[0.5, 1.5, 2.5], [1.0, 2.0, 3.0]])
labels_torch = torch.tensor([2, 1])
predictions_torch.to(self.device)
labels_torch.to(self.device)
loss_torch_expected = loss_fn_torch(predictions_torch, labels_torch)
self.assertTrue(utils.compare_torch(loss_torch_result, loss_torch_expected))
@ -83,8 +99,12 @@ class TestNNModuleLoss(unittest.TestCase):
loss_norch = loss_fn_norch.forward(predictions_norch, labels_norch)
loss_torch_result = utils.to_torch(loss_norch).to(self.device)
predictions_torch = torch.tensor([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]).to(self.device)
labels_torch = torch.tensor([1, 2]).to(self.device)
predictions_torch = torch.tensor([[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])
labels_torch = torch.tensor([1, 2])
predictions_torch.to(self.device)
labels_torch.to(self.device)
loss_torch_expected = loss_fn_torch(predictions_torch, labels_torch)
self.assertTrue(utils.compare_torch(loss_torch_result, loss_torch_expected))
@ -95,8 +115,12 @@ class TestNNModuleLoss(unittest.TestCase):
loss_norch = loss_fn_norch.forward(predictions_norch, labels_norch)
loss_torch_result = utils.to_torch(loss_norch).to(self.device)
predictions_torch = torch.tensor([0.5, 0.2, 0.1]).to(self.device)
labels_torch = torch.tensor([1., 0, 0]).to(self.device)
predictions_torch = torch.tensor([0.5, 0.2, 0.1])
labels_torch = torch.tensor([1., 0, 0])
predictions_torch.to(self.device)
labels_torch.to(self.device)
loss_torch_expected = loss_fn_torch(predictions_torch, labels_torch)
self.assertTrue(utils.compare_torch(loss_torch_result, loss_torch_expected))
@ -107,8 +131,12 @@ class TestNNModuleLoss(unittest.TestCase):
loss_norch = loss_fn_norch.forward(predictions_norch, labels_norch)
loss_torch_result = utils.to_torch(loss_norch).to(self.device)
predictions_torch = torch.tensor([[0.5, 0.2, 0.1], [0.1, 0.5, 0.7]]).to(self.device)
labels_torch = torch.tensor([[1., 0, 0], [0, 1, 0]]).to(self.device)
predictions_torch = torch.tensor([[0.5, 0.2, 0.1], [0.1, 0.5, 0.7]])
labels_torch = torch.tensor([[1., 0, 0], [0, 1, 0]])
predictions_torch.to(self.device)
labels_torch.to(self.device)
loss_torch_expected = loss_fn_torch(predictions_torch, labels_torch)
self.assertTrue(utils.compare_torch(loss_torch_result, loss_torch_expected))
@ -133,7 +161,10 @@ class TestNNModuleActivationFn(unittest.TestCase):
sigmoid_norch = sigmoid_fn_norch.forward(x)
sigmoid_torch_result = utils.to_torch(sigmoid_norch).to(self.device)
x = torch.tensor([[1, 2, 3]]).to(self.device)
x = torch.tensor([[1, 2, 3]])
x.to(self.device)
sigmoid_torch_expected = sigmoid_fn_torch.forward(x)
self.assertTrue(utils.compare_torch(sigmoid_torch_result, sigmoid_torch_expected))
@ -143,7 +174,10 @@ class TestNNModuleActivationFn(unittest.TestCase):
sigmoid_norch = sigmoid_fn_norch.forward(x)
sigmoid_torch_result = utils.to_torch(sigmoid_norch).to(self.device)
x = torch.tensor([-1, 2, -3]).to(self.device)
x = torch.tensor([-1, 2, -3])
x.to(self.device)
sigmoid_torch_expected = sigmoid_fn_torch.forward(x)
self.assertTrue(utils.compare_torch(sigmoid_torch_result, sigmoid_torch_expected))
@ -153,7 +187,10 @@ class TestNNModuleActivationFn(unittest.TestCase):
sigmoid_norch = sigmoid_fn_norch.forward(x)
sigmoid_torch_result = utils.to_torch(sigmoid_norch).to(self.device)
x = torch.tensor([0, 0, 0]).to(self.device)
x = torch.tensor([0, 0, 0])
x.to(self.device)
sigmoid_torch_expected = sigmoid_fn_torch.forward(x)
self.assertTrue(utils.compare_torch(sigmoid_torch_result, sigmoid_torch_expected))
@ -180,7 +217,9 @@ class TestNNModuleActivationFn(unittest.TestCase):
for norch_input, torch_input in test_cases:
# Move tensors to the correct device
norch_input = norch_input.to(self.device)
torch_input = torch_input.to(self.device)
torch_input = torch_input
torch_input.to(self.device)
# Forward pass using norch
softmax_norch = softmax_fn_norch.forward(norch_input)