assert fix

README.md

@@ -4,7 +4,7 @@
 
 [![](http://img.shields.io/travis/dingguanglei/jdit.svg)](https://github.com/dingguanglei/jdit)
 [![Documentation Status](https://readthedocs.org/projects/jdit/badge/?version=latest)](https://jdit.readthedocs.io/en/latest/?badge=latest)
-[![codebeat badge](https://codebeat.co/badges/f8c6cfa5-5e6b-499c-b318-2656bc91cab0)](https://codebeat.co/projects/github-com-dingguanglei-jdit-master)
+[![Codacy Badge](https://api.codacy.com/project/badge/Grade/1a5aa0721e2f44ebb61b0b73627bbc90)](https://www.codacy.com/app/dingguanglei/jdit?utm_source=github.com&utm_medium=referral&utm_content=dingguanglei/jdit&utm_campaign=Badge_Grade)
 ![Packagist](https://img.shields.io/hexpm/l/plug.svg)
 ![pypi download](https://img.shields.io/pypi/dm/jdit.svg)
 
@@ -37,23 +37,25 @@ pip install -r requirements.txt
 ```
 ### From source
 This method is recommended, because you can keep the newest version.
-1. Clone from github
+1.  Clone from github
     ```
     git clone https://github.com/dingguanglei/jdit
     ```
-2. Setup
+
+2.  Setup
     By using `setup.py` to install the package.
     ```
     python setup.py bdist_wheel
     ```
-3. Install
+
+3.  Install
     You will find packages in `jdit/dist/`. Use pip to install.
     ```
     pip install dist/jdit-0.0.x-py3-none-any.whl
     ```
 
 ### From pip
-```
+``` {.sourceCode .bash}
 pip install jdit
 ```
 

jdit/assessment/fid.py

@@ -47,7 +47,7 @@
 from torch.nn.functional import adaptive_avg_pool2d
 
 
-class _InceptionV3(nn.Module):
+class InceptionV3(nn.Module):
     """Pretrained _InceptionV3 network returning feature maps"""
 
     # Index of default block of inception to return,
@@ -63,7 +63,7 @@ class _InceptionV3(nn.Module):
         }
 
     def __init__(self,
-                 output_blocks=[DEFAULT_BLOCK_INDEX],
+                 output_blocks=(DEFAULT_BLOCK_INDEX,),
                  resize_input=True,
                  normalize_input=True,
                  requires_grad=False):
@@ -89,7 +89,7 @@ def __init__(self,
             If true, parameters of the model require gradient. Possibly useful
             for finetuning the network
         """
-        super(_InceptionV3, self).__init__()
+        super(InceptionV3, self).__init__()
 
         self.resize_input = resize_input
         self.normalize_input = normalize_input
@@ -184,9 +184,10 @@ def forward(self, inp):
 
         return outp
 
+
 # ______________________________________________________________
 
-def compute_act_statistics_from_loader(dataloader:DataLoader, model, gpu_ids):
+def compute_act_statistics_from_loader(dataloader: DataLoader, model, gpu_ids):
     """
 
     :param dataloader:
@@ -414,4 +415,3 @@ def FID_score(source, target, sample_prop=1.0, gpu_ids=(), dim=2048, batchsize=1
 
     fid_value = calculate_frechet_distance(s_mu, s_sigma, t_mu, t_sigma)
     return fid_value
-