Update

.github/workflows/lint.yml

@@ -10,6 +10,26 @@ on:
       - cron: '0 0 1 * *'
 
 jobs:
+  pylint:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - name: Set up Python
+        uses: actions/setup-python@v3
+        with:
+          python-version: 3.10
+      - name: Install CSC 791
+        run: |
+          python3 -m pip install --upgrade pip
+          pip3 install -r requirements.txt
+      - name: Run pylint
+        run: |
+          pylint proj1/proj1.py
+          pylint proj2/proj2.py
+          pylint proj3/proj3.py
+          pylint proj3/model.py
+          pylint proj4/proj4.py
+          # pylint final/final.py
   lint:
     runs-on: ubuntu-latest
     steps:

final/final.py

@@ -46,7 +46,7 @@
 
 # pylint: disable=redefined-outer-name,invalid-name,import-outside-toplevel,too-many-lines
 # pylint: disable=too-many-arguments,too-many-locals,not-callable,too-many-branches
-# pylint: disable=too-many-statements,pointless-exception-statement,protected-access
+# pylint: disable=too-many-statements,pointless-exception-statement,protected-access,fixme
 
 from model import (
     FMEN,
@@ -800,7 +800,8 @@ def prune(
 
         if logging:
             with open(
-                f"logs/{pruner.__class__.__name__}_{upscale_factor}_{model.__class__.__name__ }.csv",
+                f"logs/{pruner.__class__.__name__}_{upscale_factor}\
+                    _{model.__class__.__name__ }.csv",
                 "a",
                 encoding="utf-8",
             ) as fh:

proj1/job-gpu

@@ -1,7 +1,7 @@
 #!/bin/bash
 #SBATCH -N 1
 #SBATCH -n 1
-#SBATCH -p rome
+#SBATCH -p a6000
 #SBATCH -t 24:00:00
 
 nvidia-smi

proj1/proj1.py

@@ -74,7 +74,7 @@
     # defaults to True.
     torch.backends.cudnn.allow_tf32 = True
 
-    torch.backends.cuda.matmul.allow_fp16_reduced_precision_reduction = True
+    torch.backends.cuda.matmul.allow_fp16_reduced_precision_reduction = False
 
 
 class Net(nn.Module):
@@ -199,7 +199,7 @@ def load_data(train_kwargs, test_kwargs, mnist=True):
 
 
 def train_models(resnet=False, retrain=False):
-    """ "Train the models"""
+    """Train the models"""
     train_kwargs = {"batch_size": batch_size}
     test_kwargs = {"batch_size": test_batch_size}
 
@@ -606,6 +606,7 @@ def benchmark(device, pruner_name, resnet=False):
 
     if args.train:
         train_models(resnet=True, retrain=False)
+        train_models(resnet=False, retrain=False)
 
     elif args.prune:
         if device.type == "mps":

requirements.txt

@@ -7,6 +7,7 @@ nvidia-tensorrt
 tensorboard<=2.80
 torchviz>=0.0.2
 black
+pylint
 numpy
 pandas
 matplotlib