bug fix

mmcv/torchpack/hooks/optimizer_stepper.py

@@ -5,17 +5,14 @@ from .hook import Hook
 
 class OptimizerHook(Hook):
 
-    def __init__(self, grad_clip=False, max_norm=35, norm_type=2):
+    def __init__(self, grad_clip=None):
         self.grad_clip = grad_clip
-        self.max_norm = max_norm
-        self.norm_type = norm_type
 
     def after_train_iter(self, runner):
         runner.optimizer.zero_grad()
         runner.outputs['loss'].backward()
-        if self.grad_clip:
+        if self.grad_clip is not None:
             clip_grad.clip_grad_norm_(
                 filter(lambda p: p.requires_grad, runner.model.parameters()),
-                max_norm=self.max_norm,
-                norm_type=self.norm_type)
+                **self.grad_clip)
         runner.optimizer.step()

mmcv/torchpack/parallel.py

@@ -2,6 +2,7 @@ import multiprocessing
 
 import torch
 
+import mmcv
 from .io import load_checkpoint
 
 
@@ -61,8 +62,7 @@ def parallel_test(model_cls,
         idx_queue.put(i)
 
     results = [None for _ in range(len(dataset))]
-    import cvbase as cvb
-    prog_bar = cvb.ProgressBar(task_num=len(dataset))
+    prog_bar = mmcv.ProgressBar(task_num=len(dataset))
     for _ in range(len(dataset)):
         idx, res = result_queue.get()
         results[idx] = res