Merge pull request #73 from DIVA-DIA/dev

release version 0.1.1

.github/workflows/ci-testing.yml

@@ -69,10 +69,23 @@ jobs:
       if: success()
       run: |
         coverage html
+        coverage xml
 
     - name: Code coverage results upload
       if: success()
       uses: actions/upload-artifact@v2
       with:
         name: code-coverage-report_${{ runner.os }}_py${{ matrix.python-version }}
         path: htmlcov/
+
+    - name: Upload coverage to Codecov
+      uses: codecov/codecov-action@v1
+      if: always()
+      # see: https://github.com/actions/toolkit/issues/399
+      continue-on-error: true
+      with:
+        token: ${{ secrets.CODECOV_TOKEN }}
+        file: coverage.xml
+        flags: cpu,pytest
+        name: Base-coverage
+        fail_ci_if_error: false

conda_env_gpu.yaml

@@ -11,5 +11,8 @@ dependencies:
   - pytorch=1.8.1
   - torchvision=0.9.1
   - pandas=1.3.2
+  - numpy=1.19.2
+  - pillow=7.2.0
+  - tqdm=4.60.0
   - pip:
       - -r requirements.txt

configs/datamodule/cb55_10_cropped_datamodule.yaml

@@ -6,4 +6,4 @@ crop_size: 256
 num_workers: 4
 batch_size: 16
 shuffle: True
-drop_last_batch: True
+drop_last: True

configs/datamodule/cb55_cropped_datamodule.yaml

@@ -5,4 +5,4 @@ crop_size: 256
 num_workers: 4
 batch_size: 16
 shuffle: True
-drop_last_batch: True
+drop_last: True

configs/experiment/cb55_full_run_unet.yaml

@@ -4,18 +4,27 @@
 # python run.py +experiment=exp_example_full
 
 defaults:
-    - override /loss: crossentropyloss.yaml
-    - override /trainer: null  # override trainer to null so it's not loaded from main config defaults...
-    - override /task: semantic_segmentation_task.yaml
-    - override /model/backbone: unet_model.yaml
-    - override /model/header: identity.yaml
-    - override /datamodule: null
-    - override /metric: hisdbiou.yaml
+    - /plugins: default.yaml
+    - /task: semantic_segmentation_task.yaml
+    - /loss: crossentropyloss.yaml
+    - /metric: hisdbiou.yaml
+    - /model/backbone: unet_model.yaml
+    - /model/header: identity.yaml
+    - /optimizer: adam.yaml
+    - /callbacks:
+          - check_compatibility.yaml
+          - model_checkpoint.yaml
+    - /logger:
+          - wandb.yaml # set logger here or use command line (e.g. `python run.py logger=wandb`)
+          - csv.yaml
 
 # we override default configurations with nulls to prevent them from loading at all
 # instead we define all modules and their paths directly in this config,
 # so everything is stored in one place for more readibility
 
+train: True
+test: True
+
 trainer:
     _target_: pytorch_lightning.Trainer
     gpus: -1
@@ -24,6 +33,11 @@ trainer:
     max_epochs: 50
     precision: 16
 
+task:
+    confusion_matrix_log_every_n_epoch: 10
+    confusion_matrix_val: True
+    confusion_matrix_test: True
+
 datamodule:
     _target_: src.datamodules.hisDBDataModule.DIVAHisDBDataModule.DIVAHisDBDataModuleCropped
 
@@ -32,14 +46,18 @@ datamodule:
     num_workers: 4
     batch_size: 16
     shuffle: True
-    drop_last_batch: True
+    drop_last: True
 
 callbacks:
     model_checkpoint:
+        monitor: "val/hisdbiou"
+        mode: "max"
         filename: ${checkpoint_folder_name}cb55-full-unet
+#    watch_model:
+#        log_freq: 1000
 
 logger:
     wandb:
         name: 'cb55-full-unet'
-        tags: ["best_model", "USL"]
+        tags: ["best_model", "USL", "baseline"]
         group: 'baseline'

configs/experiment/development_baby_unet_cb55_10.yaml

@@ -14,11 +14,7 @@ defaults:
     - /callbacks:
           - check_compatibility.yaml
           - model_checkpoint.yaml
-          - conf_mat_val_wandb.yaml
-          - conf_mat_test_wandb.yaml
           - watch_model_wandb.yaml
-          - f1_precision_recall_heatmap_wandb.yaml
-          - upload_checkpoint_wandb.yaml
     - /logger:
           - wandb.yaml # set logger here or use command line (e.g. `python run.py logger=wandb`)
           - csv.yaml
@@ -41,6 +37,11 @@ trainer:
     weights_summary: full
     precision: 16
 
+task:
+    confusion_matrix_log_every_n_epoch: 1
+    confusion_matrix_val: True
+    confusion_matrix_test: True
+
 datamodule:
     _target_: src.datamodules.hisDBDataModule.DIVAHisDBDataModule.DIVAHisDBDataModuleCropped
 
@@ -49,7 +50,7 @@ datamodule:
     num_workers: 4
     batch_size: 16
     shuffle: True
-    drop_last_batch: True
+    drop_last: True
 
 callbacks:
     model_checkpoint:

configs/optimizer/adagrad.yaml

@@ -0,0 +1,9 @@
+# explanation of the different parameters: https://pytorch.org/docs/stable/generated/torch.optim.Adagrad.html#torch.optim.Adagrad
+
+_target_: torch.optim.Adagrad
+
+lr: 1e-3
+lr_decay: 0
+weight_decay: 0
+initial_accumulator_value: 0
+eps: 1e-10

configs/optimizer/adamax.yaml

@@ -0,0 +1,10 @@
+# explanation of the different parameters: https://pytorch.org/docs/stable/generated/torch.optim.Adamax.html#torch.optim.Adamax
+
+_target_: torch.optim.Adamax
+
+lr: 1e-3
+betas:
+    - 0.9
+    - 0.999
+eps: 1e-8
+weight_decay: 0

configs/optimizer/adamw.yaml

@@ -0,0 +1,11 @@
+# explanation of the different parameters: https://pytorch.org/docs/stable/generated/torch.optim.AdamW.html#torch.optim.AdamW
+
+_target_: torch.optim.AdamW
+
+lr: 1e-3
+betas:
+    - 0.9
+    - 0.999
+eps: 1e-8
+weight_decay: 0.01
+amsgrad: False

pytest.ini

@@ -1,2 +1,3 @@
 [pytest]
-python_files=tests/*.py
+python_files=tests/*.py
+filterwarnings = ignore::UserWarning

requirements.txt

@@ -3,7 +3,6 @@ torch==1.8.1
 torchvision>=0.9.1
 pytorch-lightning>=1.4.4
 lightning-bolts>=0.3.2
-gym==0.18.0
 torchmetrics>=0.5.0
 
 # --------- hydra --------- #

src/callbacks/model_callbacks.py

@@ -65,6 +65,7 @@ class CheckBackboneHeaderCompatibility(Callback):
     def __init__(self):
         self.checked = False
 
+    @rank_zero_only
     def setup(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", stage: Optional[str] = None) -> None:
         if self.checked:
             return