Merge pull request #11 from ethanweber/tancik/github_linting

Update Github action

.github/workflows/code_checks.yml

@@ -1,4 +1,4 @@
-name: Python application
+name: Check code for formating and run tests.
 
 on:
   push:
@@ -25,6 +25,13 @@ jobs:
         python -m pip install --upgrade pip
         pip install -r environment/requirements.txt
         python setup.py develop
+    - name: Run Black
+      uses: psf/black@stable
+      with:
+        options: "--check --verbose --line-length=120"
+    - name: Python Pylint
+      run: |
+        pylint mattport --max-line-length=120 --generated-members=numpy.*,torch.*,cv2.*,cv.* --good-names=i,j,x,y,lr --disable=too-many-arguments
     - name: Test with pytest
       run: |
         pytest tests

.github/workflows/lint.yml

@@ -1,29 +0,0 @@
-name: Lint
-
-on: 
-  push:
-    paths:
-      - '*.py'
-  pull_request:
-    paths:
-      - '*.py'
-
-jobs:
-  format_and_lint:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Setup Python
-        uses: actions/setup-python@v1
-        with:
-          python-version: 3.8.12
-          architecture: x64
-      - name: Checkout PyTorch
-        uses: actions/checkout@master
-      - name: Run Black
-        uses: psf/black@stable
-        with:
-          options: "--check --verbose --line-length=120"
-      - name: Python Pylint GitHub Action
-        uses: vcoder4c/git_pylint@v3
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.vscode/settings.json

@@ -19,7 +19,9 @@
     "python.testing.unittestEnabled": false,
     "python.testing.pytestEnabled": true,
     "python.linting.pylintArgs": [
-        "--generated-members=numpy.* ,torch.* ,cv2.* , cv.*",
-        "--max-line-length=120"
+        "--generated-members=numpy.*,torch.*,cv2.*,cv.*",
+        "--max-line-length=120",
+        "--good-names=i,j,x,y,lr",
+        "--disable=too-many-arguments"
     ],
 }

mattport/nerf/dataset/dataset.py

@@ -15,12 +15,7 @@ class Dataset(torch.utils.data.Dataset):
         torch (_type_): _description_
     """
 
-    def __init__(
-        self,
-        data_directory: str,
-        dataset_type: str,
-        scene: str
-    ):
+    def __init__(self, data_directory: str, dataset_type: str, scene: str):
         """_summary_
 
         Args:
@@ -33,7 +28,6 @@ class Dataset(torch.utils.data.Dataset):
         self.dataset_type = dataset_type
         self.scene = scene
 
-
     def __len__(self):
         pass
 

mattport/nerf/modules/__init__.py

@@ -1,2 +1,3 @@
+"""init modules"""
 from .encoding import Encoding
 from .mlp import MLP

mattport/nerf/modules/encoding.py

@@ -131,8 +131,8 @@ class RFFEncoding(Encoding):
         Returns:
             TensorType[..., "output_dim"]: Output values will be between -1 and 1
         """
-        B = torch.normal(mean=0, std=self.scale, size=(self.in_dim, self.num_frequencies))
-        scaled_inputs = in_tensor @ B  # [..., "num_frequencies"]
+        b_matrix = torch.normal(mean=0, std=self.scale, size=(self.in_dim, self.num_frequencies))
+        scaled_inputs = in_tensor @ b_matrix  # [..., "num_frequencies"]
         encoded_inputs = torch.cat([torch.sin(scaled_inputs), torch.cos(scaled_inputs)], axis=-1)
         return encoded_inputs
 

mattport/nerf/modules/mlp.py

@@ -1,3 +1,6 @@
+"""
+Multi Layer Perceptron
+"""
 from typing import Optional
 
 from torch import nn

mattport/nerf/optimizer.py

@@ -24,3 +24,7 @@ class Optimizer:
             NotImplementedError: _description_
         """
         raise NotImplementedError
+
+    def test2(self):
+        """Summary"""
+        raise NotImplementedError

mattport/nerf/sampler.py

@@ -2,11 +2,12 @@
 Collection of sampling strategies
 """
 from typing import NamedTuple
-from torchtyping import TensorType
-from torch import nn
-import torch
-import nerf.cameras as cameras
 
+import torch
+from torch import nn
+from torchtyping import TensorType
+
+from mattport.nerf import cameras
 
 RaySamples = NamedTuple(
     "RaySamples", [("locations", TensorType[..., "num_samples", 3]), ("deltas", TensorType[..., "num_samples"])]

mattport/nerf/trainer.py

@@ -3,10 +3,9 @@ Code to train model.
 """
 from mattport.nerf.dataset.build import build_dataset
 from mattport.nerf.optimizer import Optimizer
-from mattport.nerf.graph import Graph
 
 
-class Trainer(object):
+class Trainer:
     """Training class"""
 
     def __init__(self, config: dict):
@@ -23,7 +22,8 @@ class Trainer(object):
 
     def setup_graph(self):
         """_summary_"""
-        self.graph = Graph()
+        # self.graph = Graph()
+        raise NotImplementedError
 
     def setup_optimizer(self):
         """_summary_"""

tests/nerf/test_graph.py

@@ -173,13 +173,17 @@ def test_ordering():
     assert np.array_equal(target, order)
 
     test_repeated_graph.modules_config["mlp_0"]["inputs"][1] = "encoder_1"
-    test_repeated_graph.modules_config["encoder_1"] = {"class_name": "Encoding", "inputs": ["x"], "meta_data": {"out_dim": 8}}
+    test_repeated_graph.modules_config["encoder_1"] = {
+        "class_name": "Encoding",
+        "inputs": ["x"],
+        "meta_data": {"out_dim": 8},
+    }
     order = test_repeated_graph.get_module_order()
-    assert order.index('mlp_0') > order.index('encoder_0') and order.index('mlp_0') > order.index('encoder_1')
+    assert order.index("mlp_0") > order.index("encoder_0") and order.index("mlp_0") > order.index("encoder_1")
 
     test_complex_graph = Graph(create_complex_graph())
     _ = test_complex_graph.construct_graph()
     order = test_complex_graph.get_module_order()
-    assert order.index('mlp_2') > order.index('mlp_0')
-    assert order.index('mlp_2') > order.index('encoder_0')
-    assert order.index('mlp_3') > order.index('encoder_0')
+    assert order.index("mlp_2") > order.index("mlp_0")
+    assert order.index("mlp_2") > order.index("encoder_0")
+    assert order.index("mlp_3") > order.index("encoder_0")