update

README.md

@@ -1,4 +1,6 @@
 
 ```shell
+pip install lossers
+# or install from source
 pip install git+https://github.com/JiauZhang/lossers.git
 ```

examples/lpips_loss.py

@@ -0,0 +1,18 @@
+import torch
+from lossers.lpips import LPIPS
+
+
+loss_fn = LPIPS(net='vgg')
+source = torch.randn((1, 3, 32, 32), requires_grad=False)
+target = torch.randn((1, 3, 32, 32), requires_grad=True)
+optimizer = torch.optim.Adam([target], lr=1e-3, betas=(0.9, 0.999))
+
+for i in range(1000):
+    loss = loss_fn(source, target)
+    loss = 0
+    optimizer.zero_grad()
+    loss.backward()
+    optimizer.step()
+
+    if i % 10 == 0:
+        print('loss info:', loss.item())

lossers/math.py

@@ -13,4 +13,4 @@ def mse_loss(input, target, **kwargs):
     return F_.mse_loss(input, target, **kwargs)
 
 def l2_loss(input, target, **kwargs):
-    return F_.l2_loss(input, target, **kwargs)
+    return F_.mse_loss(input, target, **kwargs)

setup.py

@@ -2,13 +2,15 @@
 
 setup(
   name = 'lossers',
-  packages = find_packages(),
-  version = '0.0.3',
+  packages = find_packages(exclude=['examples']),
+  package_data={'': ['*/vgg_v0.1.pth']},
+  version = '0.0.4',
   license='MIT',
-  description = 'ML Loss Function',
+  description = 'ML/DL Loss Function',
   author = 'JiauZhang',
   author_email = 'jiauzhang@163.com',
   url = 'https://github.com/JiauZhang/lossers',
+  long_description=open("README.md", "r", encoding="utf-8").read(),
   long_description_content_type = 'text/markdown',
   keywords = [
     'artificial intelligence',
@@ -21,6 +23,6 @@
     'Intended Audience :: Developers',
     'Topic :: Scientific/Engineering :: Artificial Intelligence',
     'License :: OSI Approved :: MIT License',
-    'Programming Language :: Python :: 3.6',
+    'Programming Language :: Python :: 3.8',
   ],
 )