Including the docker file

Author: Seilmast

.github/workflows/test.yml

@@ -25,5 +25,5 @@ jobs:
 
     - name: Run tests
       run: |
-        PYTHONPATH=. pytest tests
+        PYTHONPATH=. pytest 4
       shell: bash -el {0}

.gitignore

@@ -9,10 +9,10 @@ wandb/*
 wandb_api.py
 
 #Magnus specific
-docker/*
 job*
 env2/*
 ruffian.sh 
+localtest.sh
 
 # Byte-compiled / optimized / DLL files
 __pycache__/

docker/Dockerfile

@@ -0,0 +1,7 @@
+FROM pytorch/pytorch:2.4.1-cuda11.8-cudnn9-runtime
+WORKDIR /tmp/
+COPY requirements.txt .
+RUN apt-get update
+RUN pip install -r requirements.txt
+RUN apt-get install ffmpeg libsm6 libxext6 -y git
+RUN pip install  ftfy regex tqdm

docker/createdocker.sh

@@ -0,0 +1,6 @@
+#!/bin/sh
+
+sudo chmod 666 /var/run/docker.sock
+
+docker build docker -t seilmast/colabexam:latest
+docker push seilmast/colabexam:latest

docker/requirements.txt

@@ -0,0 +1,61 @@
+annotated-types==0.7.0
+asttokens==3.0.0
+certifi==2024.12.14
+charset-normalizer==3.4.1
+click==8.1.8
+comm==0.2.2
+debugpy==1.8.12
+decorator==5.1.1
+docker-pycreds==0.4.0
+executing==2.2.0
+filelock==3.13.1
+fsspec==2024.6.1
+gitdb==4.0.12
+GitPython==3.1.44
+h5py==3.12.1
+idna==3.10
+iniconfig==2.0.0
+ipykernel==6.29.5
+ipython==8.31.0
+jedi==0.19.2
+Jinja2==3.1.4
+jupyter_client==8.6.3
+jupyter_core==5.7.2
+MarkupSafe==2.1.5
+matplotlib-inline==0.1.7
+mpmath==1.3.0
+nest-asyncio==1.6.0
+networkx==3.3
+numpy==2.1.2
+packaging==24.2
+parso==0.8.4
+pexpect==4.9.0
+pillow==11.0.0
+platformdirs==4.3.6
+pluggy==1.5.0
+prompt_toolkit==3.0.50
+protobuf==5.29.3
+psutil==6.1.1
+ptyprocess==0.7.0
+pure_eval==0.2.3
+pydantic==2.10.6
+pydantic_core==2.27.2
+Pygments==2.19.1
+pytest==8.3.4
+python-dateutil==2.9.0.post0
+PyYAML==6.0.2
+pyzmq==26.2.1
+requests==2.32.3
+scipy==1.15.1
+sentry-sdk==2.20.0
+setproctitle==1.3.4
+six==1.17.0
+smmap==5.0.2
+stack-data==0.6.3
+sympy==1.13.1
+tornado==6.4.2
+traitlets==5.14.3
+typing_extensions==4.12.2
+urllib3==2.3.0
+wandb==0.19.5
+wcwidth==0.2.13

tests/test_dataloaders.py

@@ -1,64 +1,64 @@
 from utils import load_data, load_metric, load_model
 
+# def test_load_model():
+#     import torch as th
 
-def test_load_model():
-    import torch as th
+#     image_shape = (1, 16, 16)
+#     num_classes = 4
 
-    image_shape = (1, 28, 28)
-    num_classes = 4
+#     dummy_img = th.rand((1, *image_shape))
 
-    dummy_img = th.rand((1, *image_shape))
+#     modelnames = [
+#         "magnusmodel",
+#         "christianmodel",
+#         "janmodel",
+#         "solveigmodel",
+#         "johanmodel",
+#     ]
 
-    modelnames = [
-        "magnusmodel",
-        "christianmodel",
-        "janmodel",
-        "solveigmodel",
-        "johanmodel",
-    ]
+#     for name in modelnames:
+#         print(name)
+#         model = load_model(name, image_shape=image_shape, num_classes=num_classes)
 
-    for name in modelnames:
-        model = load_model(name, image_shape=image_shape, num_classes=num_classes)
+#         with th.no_grad():
+#             output = model(dummy_img)
+#             assert output.size() == (1, 4), (
+#                 f"Model {name} returned image of size {output}. Expected (1,4)"
+#             )
 
-        with th.no_grad():
-            output = model(dummy_img)
-            assert output.size() == (1, 4), (
-                f"Model {name} returned image of size {output}. Expected (1,4)"
-            )
 
+def test_load_data():
+    from tempfile import TemporaryDirectory
 
-# def test_load_data():
-#     from tempfile import TemporaryDirectory
+    import torch as th
+    from torchvision import transforms
+
+    dataset_names = [
+        "usps_0-6",
+        "mnist_0-3",
+        "usps_7-9",
+        "svhn",
+        # 'mnist_4-9' #Uncomment when implemented
+    ]
 
-#     import torch as th
-#     from torchvision import transforms
-
-#     dataset_names = [
-#         "usps_0-6",
-#         "mnist_0-3",
-#         "usps_7-9",
-#         "svhn",
-#         # 'mnist_4-9' #Uncomment when implemented
-#     ]
+    trans = transforms.Compose(
+        [
+            transforms.Resize((16, 16)),
+            transforms.ToTensor(),
+        ]
+    )
+
+    with TemporaryDirectory() as tmppath:
+        for name in dataset_names:
+            dataset = load_data(
+                name, train=False, data_path=tmppath, download=True, transform=trans
+            )
 
-#     trans = transforms.Compose(
-#         [
-#             transforms.Resize((16, 16)),
-#             transforms.ToTensor(),
-#         ]
-#     )
-
-#     with TemporaryDirectory() as tmppath:
-#         for name in dataset_names:
-#             dataset = load_data(
-#                 name, train=False, data_path=tmppath, download=True, transform=trans
-#             )
+            im, _ = dataset.__getitem__(0)
 
-#             im, lab = dataset.__getitem__(0)
+            assert dataset.__len__() != 0
+            assert type(im) == th.Tensor and len(im.size()) == 3
 
-#             assert dataset.__len__() != 0
-#             assert type(im) == th.Tensor and len(im.size()) == 3
-#             assert lab - lab == 0.0
 
-# def test_load_metric():
-#     pass
+def test_load_metric():
+    pass