MAINT: remove message of checking apex.amp module

The original propose of that message is to let users know gradient
accumulation and mixed precision training is supported but `apex`
is required.

With an attention brought up by issue #45, the following things are
confirmed:

- Gradient accumulation can still work properly without `apex.amp`.
  And that's why it would fall back on normal `loss.backward()` when
  `apex.amp` is not available or `amp.initialize()` wasn't called.

- When mixed precision training is required, that is to say model
  and optimizer are wrapped by `amp.initialize()`, `amp.scale_loss()`
  will be adopted automatically in current implementation.

Therefore, it seems that message of checking `apex.amp` module is
not necessary anymore.

README.md

@@ -87,12 +87,15 @@ accumulation_steps = desired_batch_size // real_batch_size
 dataset = ...
 
 # Beware of the `batch_size` used by `DataLoader`
-trainloader = DataLoader(dataset, batch_size=real_bs, shuffle=True)
+trainloader = DataLoader(dataset, batch_size=real_batch_size, shuffle=True)
 
 model = ...
 criterion = ...
 optimizer = ...
 
+# (Optional) With this setting, `amp.scale_loss()` will be adopted automatically.
+# model, optimizer = amp.initialize(model, optimizer, opt_level='O1')
+
 lr_finder = LRFinder(model, optimizer, criterion, device="cuda")
 lr_finder.range_test(trainloader, end_lr=10, num_iter=100, step_mode="exp", accumulation_steps=accumulation_steps)
 lr_finder.plot()

torch_lr_finder/lr_finder.py

@@ -15,17 +15,7 @@
 
     IS_AMP_AVAILABLE = True
 except ImportError:
-    import logging
-
-    logging.basicConfig()
-    logger = logging.getLogger(__name__)
-    logger.warning(
-        "To enable mixed precision training, please install `apex`. "
-        "Or you can re-install this package by the following command:\n"
-        '  pip install torch-lr-finder -v --global-option="amp"'
-    )
     IS_AMP_AVAILABLE = False
-    del logging
 
 
 class DataLoaderIter(object):