Merge pull request #378 from torchsynth/torch-range

Updating torch.range to torch.arange
torchsynth · Aug 18, 2022 · a51a36c · a51a36c
2 parents 23d6411 + 4bf6187
commit a51a36c
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Showing 4 changed files with 6 additions and 6 deletions.
diff --git a/.github/workflows/codecov.yml b/.github/workflows/codecov.yml
@@ -31,7 +31,7 @@ jobs:
       run: |
         # Limit to coverage of source files in current directory
         coverage run -m examples.examples --source=.
-        coverage xml
+        coverage xml --omit "*_remote_module_non_scriptable.py"
     - name: Upload coverage to Codecov
       uses: codecov/codecov-action@v1.2.0
       with:

diff --git a/setup.py b/setup.py
@@ -41,7 +41,7 @@
         "numpy",
         "scipy",
         "torch>=1.8",
-        "pytorch-lightning",
+        "pytorch-lightning>=1.4",
         # pypi release (only master) doesn't support OrderedDict typing
         # "typing-extensions",
     ],

diff --git a/torchsynth/profile.py b/torchsynth/profile.py
@@ -110,7 +110,7 @@ def run_lightning_module(
         # Run module with profiling
         pr = cProfile.Profile()
         pr.enable()
-        trainer.test(module, test_dataloaders=dataloader)
+        trainer.test(module, dataloaders=dataloader)
         pr.disable()
 
         s = io.StringIO()
@@ -132,7 +132,7 @@ def run_lightning_module(
             print(s.getvalue())
 
     else:
-        trainer.test(module, test_dataloaders=dataloader)
+        trainer.test(module, dataloaders=dataloader)
 
 
 def main():

diff --git a/torchsynth/synth.py b/torchsynth/synth.py
@@ -239,9 +239,9 @@ def _batch_idx_to_is_train(
         Determine which samples are training examples if batch_idx is provided
         """
         if batch_idx is not None:
-            idxs = torch.range(
+            idxs = torch.arange(
                 self.batch_size * batch_idx,
-                self.batch_size * (batch_idx + 1) - 1,
+                self.batch_size * (batch_idx + 1),
                 device=self.device,
             )
             assert len(idxs) == self.batch_size