Training for 1 epoch, still need to fix evaluation step

dvc.lock

@@ -13,21 +13,33 @@ process_data:
     size: 2626
   outs:
   - path: src/data/processed/
-    md5: 38e5a1b51dfd29c0f313779b2f3d4540.dir
-    size: 234696354
+    md5: 9a1f43f46e8b1c387532e994e721d57d.dir
+    size: 197717291
     nfiles: 2898
 train:
-  cmd: python3 src/code/training.py src/data/processed
+  cmd: python3 src/code/training.py src/data/processed/train
   deps:
+  - path: src/code/custom_data_loading.py
+    md5: e04501397e3333bcec07eb8ef633b234
+    size: 2172
+  - path: src/code/params.yml
+    md5: 2263ca2167c1bb4b0f53a9aedb5f238e
+    size: 217
   - path: src/code/training.py
-    md5: 9634e85cffa3cf72d3d3d7739e40969e
-    size: 1645
-  - path: src/data/processed/
-    md5: d98a9647a37ab431bfa35815eb4afda0.dir
-    size: 232903470
-    nfiles: 2898
+    md5: e3dff7f4b59e4ebf818d7631d3e6803a
+    size: 1683
+  - path: src/data/processed/train
+    md5: 9956d748dcadc3abadd1ff966a6e2b92.dir
+    size: 109120921
+    nfiles: 1590
   outs:
+  - path: logs/train_metrics.csv
+    md5: 3504c0db314c5d285f3254f198a85a09
+    size: 103963
+  - path: logs/train_params.yml
+    md5: a2663346b17d042e5da48991fcf62771
+    size: 886
   - path: src/models/
-    md5: 18d26ed378b1b5ac61425afe153fc076.dir
-    size: 494926829
+    md5: 8969d16fb5b908cbfb6b54dffbf20efc.dir
+    size: 494926837
     nfiles: 1

logs/train_params.yml

@@ -0,0 +1,25 @@
+DAGsHubLogger: true
+Learner: <fastai.learner.Learner object at 0x7f949b510cc0>
+ParamScheduler: true
+ProgressCallback: true
+Recorder: {add_time: true, train_metrics: false, valid_metrics: true}
+TrainEvalCallback: true
+batch per epoch: 159
+batch size: 4
+dataset.tfms: '[Pipeline: PILBase.create, Pipeline: get_y_fn -> PILBase.create]'
+device: cuda
+dls.after_batch: "Pipeline: IntToFloatTensor -- {'div': 255.0, 'div_mask': 1} -> Normalize\
+  \ -- {'mean': tensor([[[[0.4850]],\n\n         [[0.4560]],\n\n         [[0.4060]]]],\
+  \ device='cuda:0'), 'std': tensor([[[[0.2290]],\n\n         [[0.2240]],\n\n    \
+  \     [[0.2250]]]], device='cuda:0'), 'axes': (0, 2, 3)}"
+dls.after_item: 'Pipeline: ToTensor'
+dls.before_batch: 'Pipeline: '
+frozen: true
+frozen idx: 2
+input 1 dim 1: 4
+input 1 dim 2: 3
+input 1 dim 3: 480
+input 1 dim 4: 640
+model parameters: 41221268
+n_inp: 1
+success: true

src/code/eval.py

@@ -29,10 +29,13 @@ if __name__ == "__main__":
     learner = learner.load('model')
 
     print("Running model on test data...")
-    inputs, predictions, targets, decoded = learner.get_preds(dl=test_dl,
-                                                              with_input=True,
-                                                              with_decoded=True)
+    inputs = learner.get_preds(dl=test_dl,
+                               with_input=True,
+                               with_decoded=True,
+                               save_preds=Path('src/eval/preds'),
+                               save_targs=Path('src/eval/targs'))[0]
     # FastAI magic to retrieve image values
+    print("Decoding test data...")
     inputs = (inputs,)
     decoded_predictions = learner.dls.decode(inputs + tuplify(decoded))[1]
     decoded_targets = learner.dls.decode(inputs + tuplify(targets))[1]