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on
Zero
Running
on
Zero
import unittest | |
import torch | |
from torch import nn | |
from diffusers.models.activations import get_activation | |
class ActivationsTests(unittest.TestCase): | |
def test_swish(self): | |
act = get_activation("swish") | |
self.assertIsInstance(act, nn.SiLU) | |
self.assertEqual(act(torch.tensor(-100, dtype=torch.float32)).item(), 0) | |
self.assertNotEqual(act(torch.tensor(-1, dtype=torch.float32)).item(), 0) | |
self.assertEqual(act(torch.tensor(0, dtype=torch.float32)).item(), 0) | |
self.assertEqual(act(torch.tensor(20, dtype=torch.float32)).item(), 20) | |
def test_silu(self): | |
act = get_activation("silu") | |
self.assertIsInstance(act, nn.SiLU) | |
self.assertEqual(act(torch.tensor(-100, dtype=torch.float32)).item(), 0) | |
self.assertNotEqual(act(torch.tensor(-1, dtype=torch.float32)).item(), 0) | |
self.assertEqual(act(torch.tensor(0, dtype=torch.float32)).item(), 0) | |
self.assertEqual(act(torch.tensor(20, dtype=torch.float32)).item(), 20) | |
def test_mish(self): | |
act = get_activation("mish") | |
self.assertIsInstance(act, nn.Mish) | |
self.assertEqual(act(torch.tensor(-200, dtype=torch.float32)).item(), 0) | |
self.assertNotEqual(act(torch.tensor(-1, dtype=torch.float32)).item(), 0) | |
self.assertEqual(act(torch.tensor(0, dtype=torch.float32)).item(), 0) | |
self.assertEqual(act(torch.tensor(20, dtype=torch.float32)).item(), 20) | |
def test_gelu(self): | |
act = get_activation("gelu") | |
self.assertIsInstance(act, nn.GELU) | |
self.assertEqual(act(torch.tensor(-100, dtype=torch.float32)).item(), 0) | |
self.assertNotEqual(act(torch.tensor(-1, dtype=torch.float32)).item(), 0) | |
self.assertEqual(act(torch.tensor(0, dtype=torch.float32)).item(), 0) | |
self.assertEqual(act(torch.tensor(20, dtype=torch.float32)).item(), 20) | |