fix new linting rules

examples/DeepQNetwork/common.py

@@ -79,24 +79,22 @@ def eval_with_funcs(predictors, nr_eval, get_player_fn):
         k.start()
         time.sleep(0.1)  # avoid simulator bugs
     stat = StatCounter()
-    try:
-        for _ in tqdm(range(nr_eval), **get_tqdm_kwargs()):
-            r = q.get()
-            stat.feed(r)
-        logger.info("Waiting for all the workers to finish the last run...")
-        for k in threads:
-            k.stop()
-        for k in threads:
-            k.join()
-        while q.qsize():
-            r = q.get()
-            stat.feed(r)
-    except:
-        logger.exception("Eval")
-    finally:
-        if stat.count > 0:
-            return (stat.average, stat.max)
-        return (0, 0)
+
+    for _ in tqdm(range(nr_eval), **get_tqdm_kwargs()):
+        r = q.get()
+        stat.feed(r)
+    logger.info("Waiting for all the workers to finish the last run...")
+    for k in threads:
+        k.stop()
+    for k in threads:
+        k.join()
+    while q.qsize():
+        r = q.get()
+        stat.feed(r)
+
+    if stat.count > 0:
+        return (stat.average, stat.max)
+    return (0, 0)
 
 
 def eval_model_multithread(pred, nr_eval, get_player_fn):

examples/DeepQNetwork/expreplay.py

@@ -258,7 +258,7 @@ class ExpReplay(DataFlow, Callback):
             mean, max = v.average, v.max
             self.trainer.monitors.put_scalar('expreplay/mean_score', mean)
             self.trainer.monitors.put_scalar('expreplay/max_score', max)
-        except:
+        except Exception:
             logger.exception("Cannot log training scores.")
         v.reset()
 

examples/ResNet/load-resnet.py

@@ -152,7 +152,7 @@ def convert_param_name(param):
     for k, v in six.iteritems(param):
         try:
             newname = name_conversion(k)
-        except:
+        except Exception:
             logger.error("Exception when processing caffe layer {}".format(k))
             raise
         logger.info("Name Transform: " + k + ' --> ' + newname)

examples/tox.ini

 [flake8]
 max-line-length = 120
-ignore = F403,F401,F405,F841,E401,E402
+ignore = F403,F401,F405,F841,E4,E741,E742,E743
 exclude = private,
 				  FasterRCNN/utils

tensorpack/callbacks/inference.py

@@ -38,7 +38,7 @@ class Inferencer(Callback):
         for k, v in six.iteritems(ret):
             try:
                 v = float(v)
-            except:
+            except ValueError:
                 logger.warn("{} returns a non-scalar statistics!".format(type(self).__name__))
                 continue
             else:

tensorpack/callbacks/param.py

@@ -199,7 +199,7 @@ class HumanHyperParamSetter(HyperParamSetter):
             dic = {str(k): float(v) for k, v in lines}
             ret = dic[self.param.readable_name]
             return ret
-        except:
+        except Exception:
             logger.warn(
                 "Cannot find {} in {}".format(
                     self.param.readable_name, self.file_name))

tensorpack/dataflow/common.py

@@ -129,7 +129,7 @@ class BatchData(ProxyDataFlow):
                 else:
                     try:
                         tp = dt.dtype
-                    except:
+                    except AttributeError:
                         raise TypeError("Unsupported type to batch: {}".format(type(dt)))
                 try:
                     result.append(
@@ -144,7 +144,7 @@ class BatchData(ProxyDataFlow):
                     try:
                         # open an ipython shell if possible
                         import IPython as IP; IP.embed()    # noqa
-                    except:
+                    except ImportError:
                         pass
         return result
 

tensorpack/dataflow/dataset/ilsvrc.py

@@ -247,7 +247,7 @@ class ILSVRC12(ILSVRC12Files):
                     cnt += 1
                 except KeyboardInterrupt:
                     raise
-                except:
+                except Exception:
                     ret.append(None)
             logger.info("{}/{} images have bounding box.".format(cnt, len(imglist)))
         return ret

tensorpack/dataflow/prefetch.py

@@ -61,7 +61,7 @@ def _zmq_catch_error(name):
             raise DataFlowTerminated()
         else:
             raise
-    except:
+    except Exception:
         raise
 
 
@@ -110,7 +110,7 @@ class _MultiProcessZMQDataFlow(DataFlow):
             x.terminate()
         try:
             print("{} successfully cleaned-up.".format(type(self).__name__))
-        except:
+        except Exception:
             pass
 
 
@@ -347,7 +347,7 @@ class MultiThreadMapData(ProxyDataFlow):
                         return
                     # cannot ignore None here. will lead to unsynced send/recv
                     self.outq.put(self.func(dp))
-            except:
+            except Exception:
                 if self.stopped():
                     pass        # skip duplicated error messages
                 else:

tensorpack/models/shape_utils.py

@@ -16,7 +16,7 @@ class StaticDynamicAxis(object):
         try:
             st = f(self.static)
             return StaticDynamicAxis(st, st)
-        except:
+        except TypeError:
             return StaticDynamicAxis(None, f(self.dynamic))
 
     def __str__(self):
@@ -53,7 +53,7 @@ class StaticDynamicShape(object):
                 self.static[axis] = st
                 self.dynamic[axis] = StaticLazyAxis(st)
                 return
-            except:
+            except TypeError:
                 pass
         self.static[axis] = None
         dyn = self.dynamic[axis]

tensorpack/train/base.py

@@ -193,7 +193,7 @@ class Trainer(object):
                 logger.info("Training was stopped.")
             except KeyboardInterrupt:
                 logger.info("Detected Ctrl-C and exiting main loop.")
-            except:
+            except Exception:
                 raise
             finally:
                 self._callbacks.after_train()

tensorpack/trainv1/base.py

@@ -273,7 +273,7 @@ class Trainer(object):
                 logger.info("Training was stopped.")
             except KeyboardInterrupt:
                 logger.info("Detected Ctrl-C and exiting main loop.")
-            except:
+            except Exception:
                 raise
             finally:
                 self._callbacks.after_train()

tensorpack/user_ops/test-recv-op.py

@@ -15,7 +15,7 @@ from tensorpack.user_ops.zmq_recv import (  # noqa
 
 try:
     num = int(sys.argv[1])
-except:
+except ValueError:
     num = 2
 
 ENDPOINT = 'ipc://test-pipe'

tensorpack/utils/fs.py

@@ -53,7 +53,7 @@ def download(url, dir, filename=None):
             fpath, _ = urllib.request.urlretrieve(url, fpath, reporthook=hook(t))
         statinfo = os.stat(fpath)
         size = statinfo.st_size
-    except:
+    except IOError:
         logger.error("Failed to download {}".format(url))
         raise
     assert size > 0, "Download an empty file!"

tensorpack/utils/loadcaffe.py

@@ -135,7 +135,7 @@ def get_caffe_pb():
                 version = version.decode('utf-8')
                 version = float('.'.join(version.split(' ')[1].split('.')[:2]))
                 assert version >= 2.7, "Require protoc>=2.7 for Python3"
-            except:
+            except Exception:
                 logger.exception("protoc --version gives: " + str(version))
                 raise
 

tox.ini

 [flake8]
 max-line-length = 120
-ignore = E265
+ignore = E265,E741,E742,E743
 exclude = .git,
 					tensorpack/__init__.py,
 					setup.py,