Merge pull request #17 from naotoo1/feature/workflows-update

Feature/workflows update

.github/workflows/macos.yml

@@ -0,0 +1,42 @@
+on:
+    push:
+        branches:
+            - main
+    pull_request:
+        branches:
+            - main
+
+name: macOS build
+jobs:
+    test-macOS:
+        runs-on: ${{ matrix.os }}
+        name: ${{ matrix.os }} (${{ matrix.python-version}})
+        strategy:
+            fail-fast: false
+            matrix:
+              os: ["macOS-latest"]
+              python-version: ["3.10","3.11"]
+        steps:
+          - name: Checkout code
+            uses: actions/checkout@v3
+            with:
+                lfs: true
+          - name: Set up Python
+            uses: actions/setup-python@v4
+            with:
+              python-version: ${{ matrix.python-version}}
+          - name: Install dependencies
+            run: |
+                python -m pip install --upgrade pip
+                pip install -r requirements.txt
+                pip install --user -r requirements_dev.txt
+          - name: Test with pytest
+            run: |
+                python -m unittest discover test/
+                python -m pytest test/
+          - name: Train example
+            run: |
+                python train.py --data_name cifar10 --model iglvq --train_norm lpips-l2 --test_norm l1 --feature_extraction --prune --prune_mode easy --prune_fraction 0.8
+                
+          
+

.github/workflows/ubuntu.yml

@@ -0,0 +1,43 @@
+on:
+    push:
+        branches:
+            - main
+    pull_request:
+        branches:
+            - main
+
+name: Linux build
+jobs:
+    py-check:
+        runs-on: ${{ matrix.config.os }}
+        name: ${{ matrix.config.os }} (${{ matrix.config.py }})
+        strategy:
+            fail-fast: false
+            matrix:
+                config:
+                    - { os: ubuntu-latest, py: "3.10" }
+                    - { os: ubuntu-latest, py: "3.11" }
+        steps:
+            - name: Checkout Code
+              uses: actions/checkout@v3
+              with:
+                lfs: true
+            - name: Setup Python
+              uses: actions/setup-python@v4
+              with:
+                  python-version: ${{ matrix.config.py }}
+            - name: Install dependencies
+              run: |
+                  python -m pip install --upgrade pip
+                  pip install --user -r requirements.txt
+                  pip install --user -r requirements_dev.txt
+            - name: Module-TEST
+              run: |
+                  python -m unittest discover test/
+                  python -m pytest test/
+            - name: Train example
+              run: |
+                python train.py --data_name cifar10 --model iglvq --train_norm lpips-l2 --test_norm l1 --feature_extraction --prune --prune_mode easy --prune_fraction 0.8
+                
+          
+

.github/workflows/windows.yml

@@ -0,0 +1,44 @@
+on:
+    push:
+        branches:
+            - main
+    pull_request:
+        branches:
+            - main
+
+name: Windows build
+
+jobs:
+    test-windows:
+        runs-on: ${{ matrix.os }}
+        name: ${{ matrix.os }} (${{ matrix.python-version}})
+        strategy:
+            fail-fast: false
+            matrix:
+              os: ["windows-latest"]
+              python-version: ["3.10","3.11"]
+        steps:
+          - name: Checkout code
+            uses: actions/checkout@v3
+            with:
+                lfs: true
+          - name: Install miniconda
+            uses: conda-incubator/setup-miniconda@v2
+            with:
+              auto-activate-base: true
+              python-version: ${{ matrix.python-version}}
+          - name: Install dependencies
+            run: |
+                python -m pip install --upgrade pip
+                pip install -r requirements.txt
+                pip install --user -r requirements_dev.txt
+          - name: Test with pytest
+            run: |
+                python -m unittest discover test/
+                python -m pytest test/
+          - name: Train example
+            run: |
+                python train.py --data_name cifar10 --model iglvq --train_norm lpips-l2 --test_norm l1 --feature_extraction --prune --prune_mode easy --prune_fraction 0.8
+                
+          
+

evaluate.py

@@ -45,7 +45,7 @@ def get_lowerbound_certification(
     condition1 = q_norm in ["lpips-linf", "lpips-l2", "lpips-l1"]
     match condition1:
         case True:
-            device = "cuda"
+            device ="cuda" if torch.cuda.is_available() else  "cpu"
         case False:
             device = "cpu"
 
@@ -105,7 +105,7 @@ def get_upperbound_certification(
     condition1 = q_norm in ["lpips-linf", "lpips-l2", "lpips-l1"]
     match condition1:
         case True:
-            device = "cuda"
+           device ="cuda" if torch.cuda.is_available() else  "cpu"
         case False:
             device = "cpu"
 

requirements_dev.txt

@@ -0,0 +1,2 @@
+autopep8==2.0.2
+pytest==7.0.1

test/test_perceptual_metric.py

@@ -1,5 +1,5 @@
 """Test Suite for Perceptual metric"""
-
+import torch
 from distance import lpips_distance
 from train_utils import get_data, Dataset
 
@@ -9,7 +9,11 @@
     test_size=0.3,
 )
 x_test = access_data.X_test
-x_test = x_test.to("cuda")
+if torch.cuda.is_available():
+    x_test = x_test.to("cuda")
+else:
+    x_test = x_test.to(torch.device("cpu"))
+# x_test = x_test.to("cuda")
 
 
 input_0 = x_test[0].reshape(1, 32, 32, 3)

test/test_psi_mapping.py

@@ -13,7 +13,11 @@
 
 # get image data
 access_data = get_data(dataset="cifar10", test_size=0.3)
-x_test = access_data.X_test.to("cuda")
+if torch.cuda.is_available():
+    x_test = access_data.X_test.to("cuda")
+else:
+    x_test = access_data.X_test.to(torch.device("cpu"))
+# x_test = access_data.X_test.to("cuda")
 
 # reshape the input
 input_0 = x_test[0].reshape(1, 32, 32, 3)
@@ -34,9 +38,17 @@ def test_normalization_factor_1(self):
                 torch.sqrt(torch.sum(feature_layer**2, dim=1, keepdim=True))
                 + self.epsilon
             )
-            self.assertIsInstance(
+            if torch.cuda.is_available():
+                self.assertIsInstance(
                 normalization_factor_1[0][0][0][0], torch.cuda.FloatTensor
-            )
+                )
+            else:
+                self.assertIsInstance(
+                normalization_factor_1[0][0][0][0], torch.FloatTensor
+                )
+            # self.assertIsInstance(
+            #     normalization_factor_1[0][0][0][0], torch.cuda.FloatTensor
+            # )
             self.assertEqual(torch.sum(normalization_factor_1, dim=0).any(), 1)
 
     def test_normalization_factor_2(self):