Fix types, add mypy to workflow (#42)

*Description of changes:* Fix some type checking issues, add mypy to
github workflow, apply black


By submitting this pull request, I confirm that you can use, modify,
copy, and redistribute this contribution, under the terms of your
choice.

.github/workflows/ci.yml

@@ -3,23 +3,44 @@ name: CI
 on: [push, pull_request]
 
 jobs:
+  type-check:
+    strategy:
+      max-parallel: 4
+      fail-fast: false
+      matrix:
+        python-version: ["3.11"]
+        platform: [ubuntu-latest]
+
+    runs-on: ${{ matrix.platform }}
+
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install dependencies
+        run: pip install ".[typecheck]"
+      - name: Type checks with mypy
+        run: mypy src test
+
   test:
     strategy:
       max-parallel: 4
       fail-fast: false
       matrix:
-        python-version: ['3.11']
+        python-version: ["3.11"]
         platform: [ubuntu-latest]
 
     runs-on: ${{ matrix.platform }}
 
     steps:
-    - uses: actions/checkout@v3
-    - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v4
-      with:
-        python-version: ${{ matrix.python-version }}
-    - name: Install dependencies
-      run: pip install ".[test]"
-    - name: Test with pytest
-      run: pytest
+      - uses: actions/checkout@v4
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install dependencies
+        run: pip install ".[test]"
+      - name: Test with pytest
+        run: pytest

pyproject.toml

@@ -2,18 +2,16 @@
 name = "chronos"
 version = "1.1.0"
 requires-python = ">=3.8"
-license = {file = "LICENSE"}
+license = { file = "LICENSE" }
 dependencies = [
-  "torch~=2.1",  # package was tested on 2.2
-  "transformers~=4.31",
-  "accelerate"
+    "torch~=2.1",         # package was tested on 2.2
+    "transformers~=4.31",
+    "accelerate",
 ]
 
 [project.optional-dependencies]
-test = [
-    "pytest~=8.0",
-    "numpy~=1.21"
-]
+test = ["pytest~=8.0", "numpy~=1.21"]
+typecheck = ["mypy~=1.9"]
 
 [tool.mypy]
 ignore_missing_imports = true

src/chronos/chronos.py

@@ -367,9 +367,9 @@ def embed(
             or the length of the longest time series, if a list of 1D tensors was
             provided, and the extra 1 is for EOS.
         """
-        context = self._prepare_and_validate_context(context=context)
+        context_tensor = self._prepare_and_validate_context(context=context)
         token_ids, attention_mask, tokenizer_state = self.tokenizer.input_transform(
-            context
+            context_tensor
         )
         embeddings = self.model.encode(
             input_ids=token_ids.to(self.model.device),
@@ -424,7 +424,7 @@ def predict(
             Tensor of sample forecasts, of shape
             (batch_size, num_samples, prediction_length).
         """
-        context = self._prepare_and_validate_context(context=context)
+        context_tensor = self._prepare_and_validate_context(context=context)
 
         if prediction_length is None:
             prediction_length = self.model.config.prediction_length
@@ -443,7 +443,9 @@ def predict(
         remaining = prediction_length
 
         while remaining > 0:
-            token_ids, attention_mask, scale = self.tokenizer.input_transform(context)
+            token_ids, attention_mask, scale = self.tokenizer.input_transform(
+                context_tensor
+            )
             samples = self.model(
                 token_ids.to(self.model.device),
                 attention_mask.to(self.model.device),
@@ -463,7 +465,9 @@ def predict(
             if remaining <= 0:
                 break
 
-            context = torch.cat([context, prediction.median(dim=1).values], dim=-1)
+            context_tensor = torch.cat(
+                [context_tensor, prediction.median(dim=1).values], dim=-1
+            )
 
         return torch.cat(predictions, dim=-1)
 

test/test_chronos.py

@@ -59,7 +59,7 @@ def test_tokenizer_fixed_data(
 
     samples = tokenizer.output_transform(
         torch.arange(n_special_tokens, n_tokens).unsqueeze(0).repeat(batch_size, 1, 1),
-        decoding_context=scale,
+        tokenizer_state=scale,
     )
 
     assert (samples[:, 0, [0, -1]] == context).all()
@@ -119,7 +119,7 @@ def test_tokenizer_random_data(use_eos_token: bool):
     assert samples.shape == (2, 10, 4)
 
 
-def validate_tensor(samples: torch.Tensor, shape: Tuple[int, int, int]) -> None:
+def validate_tensor(samples: torch.Tensor, shape: Tuple[int, ...]) -> None:
     assert isinstance(samples, torch.Tensor)
     assert samples.shape == shape