added option to change default tensor

pytorch_lightning/models/trainer.py

@@ -7,6 +7,9 @@ from pytorch_lightning.root_module.model_saving import TrainerIO
 from torch.optim.lr_scheduler import MultiStepLR
 import pdb
 
+
+
+
 try:
     from apex import amp
     APEX_AVAILABLE = True
@@ -83,6 +86,7 @@ class Trainer(TrainerIO):
         use_amp = True
         self.use_amp = use_amp and APEX_AVAILABLE
         if self.use_amp:
+            self.amp_handle = amp.init(enabled=True)
             print('using 16bit precision')
 
     def __determine_data_use_amount(self, train_percent_check, val_percent_check, test_percent_check, overfit_pct):
@@ -219,14 +223,14 @@ class Trainer(TrainerIO):
         # filter out the weights that were done on gpu so we can load on good old cpus
         self.optimizers = model.configure_optimizers()
 
-        if self.use_amp:
-            # An example
-            self.model, optimizer = amp.initialize(
-                self.model, self.optimizers[0], opt_level="O2",
-                keep_batchnorm_fp32=True, loss_scale="dynamic"
-            )
-            self.optimizers[0] = optimizer
-            model.trainer = self
+        # if self.use_amp:
+        #     An example
+            # self.model, optimizer = amp.initialize(
+            #     self.model, self.optimizers[0], opt_level="O2",
+            #     keep_batchnorm_fp32=True, loss_scale="dynamic"
+            # )
+            # self.optimizers[0] = optimizer
+            # model.trainer = self
 
         # add lr schedulers
         if self.lr_scheduler_milestones is not None:
@@ -370,7 +374,7 @@ class Trainer(TrainerIO):
         # backward pass
         if self.use_amp:
             for optimizer in self.optimizers:
-                with amp.scale_loss(loss, optimizer) as scaled_loss:
+                with self.amp_handle.scale_loss(loss, optimizer) as scaled_loss:
                     scaled_loss.backward()
         else:
             loss.backward()

setup.py

@@ -7,7 +7,7 @@ from setuptools import setup, find_packages
 # http://blog.ionelmc.ro/2014/05/25/python-packaging/
 setup(
     name="pytorch-lightning",
-    version='0.1.dev1721',
+    version='0.1.dev1722',
     description="The Keras for ML researchers using PyTorch",
     author="William Falcon",
     author_email="waf2107@columbia.edu",