Add support for Python 3.10-12

.github/workflows/test.yml

@@ -24,7 +24,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [Ubuntu, macOS, Windows]
-        python-version: [3.8, 3.9]
+        python-version: ['3.9', '3.10', '3.11', '3.12']
 
     steps:
       - name: Checkout

.pre-commit-config.yaml

@@ -14,7 +14,7 @@ repos:
     rev: v3.15.2
     hooks:
       - id: pyupgrade
-        args: [--py36-plus]
+        args: [--py39-plus]
 
   - repo: https://github.com/PyCQA/isort
     rev: 5.13.2

README.md

@@ -28,7 +28,7 @@ Existing time series analysis libraries include [statsmodels](https://www.statsm
 
 ### Installation Requirements
 
-TorchTS supports Python 3.8+ and has the following dependencies:
+TorchTS supports Python 3.9+ and has the following dependencies:
 
 - [PyTorch](https://pytorch.org/)
 - [PyTorch Lightning](https://pytorchlightning.ai/)

pyproject.toml

@@ -20,19 +20,19 @@ classifiers = [
 ]
 
 [tool.poetry.dependencies]
-python = ">=3.8,<3.10"
-torch = "^1.4"
-pytorch-lightning = "^1.2"
-scipy = "^1.7.1"
+python = ">=3.9,<3.13"
+torch = "^2.2.2"
+pytorch-lightning = "^2.2.3"
+scipy = "^1.13.0"
 
 [tool.poetry.group.test.dependencies]
-pytest = "^7.0.1"
-pytest-cov = "^3.0.0"
-pytest-mock = "^3.7.0"
-pre-commit = "^2.17.0"
+pytest = "^8.2.0"
+pytest-cov = "^5.0.0"
+pytest-mock = "^3.14.0"
+pre-commit = "^3.7.0"
 
 [tool.poetry.group.docs.dependencies]
-sphinx = "^4.4.0"
+sphinx = "^7.3.7"
 asteroid-sphinx-theme = "^0.0.3"
 
 [build-system]

tests/nn/test_ode.py

@@ -90,7 +90,7 @@ def test_step_backward(euler_model):
     model, _ = euler_model
     loss = model._step(batch, 0, 0)
     assert (loss.item() - (1.2 - 1.1) ** 2) < 1e-6
-    model.backward(loss, None, 0)
+    model.backward(loss)
     model.optimizer(model.parameters()).step()
     coeffs = model.get_coeffs()
     assert coeffs["alpha"] < 2
@@ -99,6 +99,7 @@ def test_step_backward(euler_model):
 def test_fit(euler_model):
     """Test the step and backward function"""
     torch.manual_seed(0)
+    torch.set_default_device("cpu")
     model, _ = euler_model
     model.fit(torch.Tensor([[1.0]]), torch.Tensor([[1.1]]), max_epochs=1, batch_size=1)
     coeffs = model.get_coeffs()

tests/test_model.py

@@ -59,6 +59,7 @@ def test_step(mocker):
 
 def test_train():
     torch.manual_seed(0)
+    torch.set_default_device("cpu")
 
     slope_init = 2
     intercept_init = -1

torchts/nn/models/ode.py

@@ -162,6 +162,6 @@ def _step(self, batch, batch_idx, num_batches):
         loss = self.criterion(predictions, y)
         return loss
 
-    def backward(self, loss, optimizer, optimizer_idx):
+    def backward(self, loss):
         # use retain_graph=True to mitigate RuntimeError
         loss.backward(retain_graph=True)