[feat] Support custom filesystems in LightningModule.to_torchscript (#7617)

* [feat] Support custom filesystems in LightningModule.to_torchscript

* Update CHANGELOG.md

* Update test_torchscript.py

* Update test_torchscript.py

* Update CHANGELOG.md

* Update test_torchscript.py

Author: ananthsub

CHANGELOG.md

@@ -9,6 +9,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Added
 
+- Added support to `LightningModule.to_torchscript` for saving to custom filesystems with fsspec ([#7617](https://github.com/PyTorchLightning/pytorch-lightning/pull/7617))
+
+
 - Added `KubeflowEnvironment` for use with the `PyTorchJob` operator in Kubeflow
 
 

pytorch_lightning/core/lightning.py

@@ -40,6 +40,7 @@
 from pytorch_lightning.core.step_result import Result
 from pytorch_lightning.utilities import rank_zero_deprecation, rank_zero_warn
 from pytorch_lightning.utilities.apply_func import apply_to_collection, convert_to_tensors
+from pytorch_lightning.utilities.cloud_io import get_filesystem
 from pytorch_lightning.utilities.device_dtype_mixin import DeviceDtypeModuleMixin
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.parsing import AttributeDict, collect_init_args, save_hyperparameters
@@ -1860,7 +1861,9 @@ def to_torchscript(
         self.train(mode)
 
         if file_path is not None:
-            torch.jit.save(torchscript_module, file_path)
+            fs = get_filesystem(file_path)
+            with fs.open(file_path, "wb") as f:
+                torch.jit.save(torchscript_module, f)
 
         return torchscript_module
 

tests/models/test_torchscript.py

@@ -12,9 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import os
+
+import fsspec
 import pytest
 import torch
+from fsspec.implementations.local import LocalFileSystem
 
+from pytorch_lightning.utilities.cloud_io import get_filesystem
 from tests.helpers import BoringModel
 from tests.helpers.advanced_models import BasicGAN, ParityModuleRNN
 from tests.helpers.datamodules import MNISTDataModule
@@ -139,6 +144,34 @@ def test_torchscript_save_load(tmpdir, modelclass):
     assert torch.allclose(next(script.parameters()), next(loaded_script.parameters()))
 
 
+@pytest.mark.parametrize("modelclass", [
+    BoringModel,
+    ParityModuleRNN,
+    BasicGAN,
+])
+@RunIf(min_torch="1.5.0")
+def test_torchscript_save_load_custom_filesystem(tmpdir, modelclass):
+    """ Test that scripted LightningModule is correctly saved and can be loaded with custom filesystems. """
+
+    _DUMMY_PRFEIX = "dummy"
+    _PREFIX_SEPARATOR = "://"
+
+    class DummyFileSystem(LocalFileSystem):
+        ...
+
+    fsspec.register_implementation(_DUMMY_PRFEIX, DummyFileSystem, clobber=True)
+
+    model = modelclass()
+    output_file = os.path.join(_DUMMY_PRFEIX, _PREFIX_SEPARATOR, tmpdir, "model.pt")
+    script = model.to_torchscript(file_path=output_file)
+
+    fs = get_filesystem(output_file)
+    with fs.open(output_file, "rb") as f:
+        loaded_script = torch.jit.load(f)
+
+    assert torch.allclose(next(script.parameters()), next(loaded_script.parameters()))
+
+
 def test_torchcript_invalid_method(tmpdir):
     """Test that an error is thrown with invalid torchscript method"""
     model = BoringModel()