MileStone: DANN working for MNIST -> MNISTM

Source MNIST acc 99%
Target MNISTM acc 93% (no label)
---
Note: without adaptation MNISTM acc 50%

.gitignore

@@ -1,129 +1,142 @@
-# Byte-compiled / optimized / DLL files
-__pycache__/
-*.py[cod]
-*$py.class
-
-# C extensions
-*.so
-
-# Distribution / packaging
-.Python
-build/
-develop-eggs/
-dist/
-downloads/
-eggs/
-.eggs/
-lib/
-lib64/
-parts/
-sdist/
-var/
-wheels/
-pip-wheel-metadata/
-share/python-wheels/
-*.egg-info/
-.installed.cfg
-*.egg
-MANIFEST
-
-# PyInstaller
-#  Usually these files are written by a python script from a template
-#  before PyInstaller builds the exe, so as to inject date/other infos into it.
-*.manifest
-*.spec
-
-# Installer logs
-pip-log.txt
-pip-delete-this-directory.txt
-
-# Unit test / coverage reports
-htmlcov/
-.tox/
-.nox/
-.coverage
-.coverage.*
-.cache
-nosetests.xml
-coverage.xml
-*.cover
-*.py,cover
-.hypothesis/
-.pytest_cache/
-
-# Translations
-*.mo
-*.pot
-
-# Django stuff:
-*.log
-local_settings.py
-db.sqlite3
-db.sqlite3-journal
-
-# Flask stuff:
-instance/
-.webassets-cache
-
-# Scrapy stuff:
-.scrapy
-
-# Sphinx documentation
-docs/_build/
-
-# PyBuilder
-target/
-
-# Jupyter Notebook
-.ipynb_checkpoints
-
-# IPython
-profile_default/
-ipython_config.py
-
-# pyenv
-.python-version
-
-# pipenv
-#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
-#   However, in case of collaboration, if having platform-specific dependencies or dependencies
-#   having no cross-platform support, pipenv may install dependencies that don't work, or not
-#   install all needed dependencies.
-#Pipfile.lock
-
-# PEP 582; used by e.g. github.com/David-OConnor/pyflow
-__pypackages__/
-
-# Celery stuff
-celerybeat-schedule
-celerybeat.pid
-
-# SageMath parsed files
-*.sage.py
-
-# Environments
-.env
-.venv
-env/
-venv/
-ENV/
-env.bak/
-venv.bak/
-
-# Spyder project settings
-.spyderproject
-.spyproject
-
-# Rope project settings
-.ropeproject
-
-# mkdocs documentation
-/site
-
-# mypy
-.mypy_cache/
-.dmypy.json
-dmypy.json
-
-# Pyre type checker
-.pyre/
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+#Torch checkpoint
+*.pth
+*.pt
+
+#checkpoints and model saving
+saved/
+
+#data
+data/
+
+#vscode workspace
+*.code-workspace

base/base_trainer.py

@@ -8,12 +8,14 @@ class BaseTrainer:
     """
     Base class for all trainers
     """
-    def __init__(self, model, criterion, metric_ftns, optimizer, config):
+
+    def __init__(self, model, metric_ftns, optimizer, config):
         self.config = config
-        self.logger = config.get_logger('trainer', config['trainer']['verbosity'])
+        self.logger = config.get_logger(
+            'trainer', config['trainer']['verbosity'])
 
         self.model = model
-        self.criterion = criterion
+        #self.criterion = criterion
         self.metric_ftns = metric_ftns
         self.optimizer = optimizer
 
@@ -39,8 +41,9 @@ def __init__(self, model, criterion, metric_ftns, optimizer, config):
 
         self.checkpoint_dir = config.save_dir
 
-        # setup visualization writer instance                
-        self.writer = TensorboardWriter(config.log_dir, self.logger, cfg_trainer['tensorboard'])
+        # setup visualization writer instance
+        self.writer = TensorboardWriter(
+            config.log_dir, self.logger, cfg_trainer['tensorboard'])
 
         if config.resume is not None:
             self._resume_checkpoint(config.resume)
@@ -52,6 +55,7 @@ def _train_epoch(self, epoch):
 
         :param epoch: Current epoch number
         """
+        # Implement in child method instead
         raise NotImplementedError
 
     def train(self):
@@ -76,7 +80,8 @@ def train(self):
                 try:
                     # check whether model performance improved or not, according to specified metric(mnt_metric)
                     improved = (self.mnt_mode == 'min' and log[self.mnt_metric] <= self.mnt_best) or \
-                               (self.mnt_mode == 'max' and log[self.mnt_metric] >= self.mnt_best)
+                               (self.mnt_mode ==
+                                'max' and log[self.mnt_metric] >= self.mnt_best)
                 except KeyError:
                     self.logger.warning("Warning: Metric '{}' is not found. "
                                         "Model performance monitoring is disabled.".format(self.mnt_metric))
@@ -115,7 +120,8 @@ def _save_checkpoint(self, epoch, save_best=False):
             'monitor_best': self.mnt_best,
             'config': self.config
         }
-        filename = str(self.checkpoint_dir / 'checkpoint-epoch{}.pth'.format(epoch))
+        filename = str(self.checkpoint_dir /
+                       'checkpoint-epoch{}.pth'.format(epoch))
         torch.save(state, filename)
         self.logger.info("Saving checkpoint: {} ...".format(filename))
         if save_best:
@@ -148,4 +154,5 @@ def _resume_checkpoint(self, resume_path):
         else:
             self.optimizer.load_state_dict(checkpoint['optimizer'])
 
-        self.logger.info("Checkpoint loaded. Resume training from epoch {}".format(self.start_epoch))
+        self.logger.info(
+            "Checkpoint loaded. Resume training from epoch {}".format(self.start_epoch))