for #330, use tqdm.auto in trainer (#752)

* use tqdm.auto in trainer

This will import the ipywidgets version of tqdm if available. This works nicely in notebooks by not filling up the log.

In the terminal it will use the same old tqdm.

We might also want to consider passing in the tqdm we want as an argument since there may be some edge cases where ipywidgets is available but the interface doesn't support it (e.g. vscode?) or isn't working. In which case people will get a warning message, but may want to configure it themselves.

* use `from tqdm.auto` in eval loop

* indents

pytorch_lightning/trainer/evaluation_loop.py

@@ -127,7 +127,7 @@ import sys
 from abc import ABC, abstractmethod
 
 import torch
-import tqdm
+from tqdm.auto import tqdm
 
 from pytorch_lightning.utilities.debugging import MisconfigurationException
 
@@ -293,9 +293,9 @@ class TrainerEvaluationLoopMixin(ABC):
         # main progress bar will already be closed when testing so initial position is free
         position = 2 * self.process_position + (not test)
         desc = 'Testing' if test else 'Validating'
-        pbar = tqdm.tqdm(desc=desc, total=max_batches, leave=test, position=position,
-                         disable=not self.show_progress_bar, dynamic_ncols=True,
-                         unit='batch', file=sys.stdout)
+        pbar = tqdm(desc=desc, total=max_batches, leave=test, position=position,
+                    disable=not self.show_progress_bar, dynamic_ncols=True,
+                    unit='batch', file=sys.stdout)
         setattr(self, f'{"test" if test else "val"}_progress_bar', pbar)
 
         # run evaluation