Data Loaders and Stuff

.gitignore.txt

@@ -0,0 +1,161 @@
+# My Local Settings
+
+/data/
+
+# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio and WebStorm
+# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
+
+/.idea/
+
+# CMake
+cmake-build-*/
+
+# File-based project format
+*.iws
+
+# IntelliJ
+out/
+
+# mpeltonen/sbt-idea plugin
+.idea_modules/
+
+# JIRA plugin
+atlassian-ide-plugin.xml
+
+
+# Crashlytics plugin (for Android Studio and IntelliJ)
+com_crashlytics_export_strings.xml
+crashlytics.properties
+crashlytics-build.properties
+fabric.properties
+
+# Created by https://www.gitignore.io/api/python
+# Edit at https://www.gitignore.io/?templates=python
+
+### Python ###
+# 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
+.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
+
+# celery beat schedule file
+celerybeat-schedule
+
+# 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/
+
+# End of https://www.gitignore.io/api/python

networks/modules.py

@@ -31,7 +31,7 @@ class LightningModuleOverrides:
         return self.network.forward(x)
 
     @data_loader
-    def tng_dataloader(self):
+    def train_dataloader(self):
         num_workers = 0 # os.cpu_count() // 2
         return DataLoader(DataContainer(os.path.join('data', 'training'), self.size, self.step),
                           shuffle=True, batch_size=10000, num_workers=num_workers)
@@ -73,6 +73,17 @@ class LightningModule(pl.LightningModule, ABC):
         # REQUIRED
         raise NotImplementedError
 
+    @abstractmethod
+    def configure_optimizers(self):
+        # REQUIRED
+        raise NotImplementedError
+
+    @pl.data_loader
+    def train_dataloader(self):
+        # REQUIRED
+        raise NotImplementedError
+
+    """
     def validation_step(self, batch, batch_nb):
         # OPTIONAL
         pass
@@ -81,19 +92,6 @@ class LightningModule(pl.LightningModule, ABC):
         # OPTIONAL
         pass
 
-    @abstractmethod
-    def configure_optimizers(self):
-        # REQUIRED
-        raise NotImplementedError
-
-    @pl.data_loader
-    def tng_dataloader(self):
-        # REQUIRED
-        raise NotImplementedError
-        # return DataLoader(MNIST(os.getcwd(), train=True, download=True,
-        # transform=transforms.ToTensor()), batch_size=32)
-
-    """
     @pl.data_loader
     def val_dataloader(self):
         # OPTIONAL

output/AE_Model/Sun_Sep_29_12-35-27_2019/default/version_0/meta.experiment

@@ -0,0 +1 @@
+{"name": "default", "version": 0, "tags_path": "C:\\Users\\steff\\Google Drive\\LMU\\Research\\ae_toolbox_torch\\output\\AE_Model\\Sun_Sep_29_12-35-27_2019\\default\\version_0/meta_tags.csv", "metrics_path": "C:\\Users\\steff\\Google Drive\\LMU\\Research\\ae_toolbox_torch\\output\\AE_Model\\Sun_Sep_29_12-35-27_2019\\default\\version_0/metrics.csv", "autosave": false, "description": null, "created_at": "2019-09-29 10:35:27.965484", "exp_hash": "default_v0"}

output/AE_Model/Sun_Sep_29_12-35-27_2019/default/version_0/meta_tags.csv

@@ -0,0 +1,8 @@
+key,value
+step,5
+features,6
+size,9
+latent_dim,2
+model,AE_Model
+refresh,False
+future_predictions,False

output/AE_Model/Sun_Sep_29_12-35-27_2019/default/version_0/metrics.csv

@@ -0,0 +1,2 @@
+loss,epoch,created_at
+1.454,0.0,2019-09-29 10:41:14.039965

output/AE_Model/Sun_Sep_29_12-44-13_2019/default/version_0/meta.experiment

@@ -0,0 +1 @@
+{"name": "default", "version": 0, "tags_path": "C:\\Users\\steff\\Google Drive\\LMU\\Research\\ae_toolbox_torch\\output\\AE_Model\\Sun_Sep_29_12-44-13_2019\\default\\version_0/meta_tags.csv", "metrics_path": "C:\\Users\\steff\\Google Drive\\LMU\\Research\\ae_toolbox_torch\\output\\AE_Model\\Sun_Sep_29_12-44-13_2019\\default\\version_0/metrics.csv", "autosave": false, "description": null, "created_at": "2019-09-29 10:44:13.614075", "exp_hash": "default_v0"}

output/AE_Model/Sun_Sep_29_12-44-13_2019/default/version_0/meta_tags.csv

@@ -0,0 +1,8 @@
+key,value
+step,5
+features,6
+size,9
+latent_dim,2
+model,AE_Model
+refresh,False
+future_predictions,True

output/AE_Model/Sun_Sep_29_12-44-13_2019/default/version_0/metrics.csv

@@ -0,0 +1 @@
+

output/AE_Model/Sun_Sep_29_12-44-29_2019/default/version_0/meta.experiment

@@ -0,0 +1 @@
+{"name": "default", "version": 0, "tags_path": "C:\\Users\\steff\\Google Drive\\LMU\\Research\\ae_toolbox_torch\\output\\AE_Model\\Sun_Sep_29_12-44-29_2019\\default\\version_0/meta_tags.csv", "metrics_path": "C:\\Users\\steff\\Google Drive\\LMU\\Research\\ae_toolbox_torch\\output\\AE_Model\\Sun_Sep_29_12-44-29_2019\\default\\version_0/metrics.csv", "autosave": false, "description": null, "created_at": "2019-09-29 10:44:29.534657", "exp_hash": "default_v0"}

output/AE_Model/Sun_Sep_29_12-44-29_2019/default/version_0/meta_tags.csv

@@ -0,0 +1,8 @@
+key,value
+step,5
+features,6
+size,9
+latent_dim,2
+model,AE_Model
+refresh,False
+future_predictions,True

output/AE_Model/Sun_Sep_29_12-44-29_2019/default/version_0/metrics.csv

@@ -0,0 +1,3 @@
+loss,epoch,created_at
+1.372,0.0,2019-09-29 10:44:34.492200
+0.267,1.0,2019-09-29 10:54:22.294891

output/SAAE_Model/Sun_Sep_29_12-54-18_2019/default/version_0/meta.experiment

@@ -0,0 +1 @@
+{"name": "default", "version": 0, "tags_path": "C:\\Users\\steff\\Google Drive\\LMU\\Research\\ae_toolbox_torch\\output\\SAAE_Model\\Sun_Sep_29_12-54-18_2019\\default\\version_0/meta_tags.csv", "metrics_path": "C:\\Users\\steff\\Google Drive\\LMU\\Research\\ae_toolbox_torch\\output\\SAAE_Model\\Sun_Sep_29_12-54-18_2019\\default\\version_0/metrics.csv", "autosave": false, "description": null, "created_at": "2019-09-29 10:54:18.863108", "exp_hash": "default_v0"}

output/SAAE_Model/Sun_Sep_29_12-54-18_2019/default/version_0/meta_tags.csv

@@ -0,0 +1,8 @@
+key,value
+step,5
+features,6
+size,9
+latent_dim,2
+model,SAAE_Model
+refresh,False
+future_predictions,True

output/SAAE_Model/Sun_Sep_29_12-54-18_2019/default/version_0/metrics.csv

@@ -0,0 +1,48 @@
+loss,epoch,created_at
+0.471,0.0,2019-09-29 10:54:25.127533
+0.076,1.0,2019-09-29 11:04:46.930249
+0.069,2.0,2019-09-29 11:14:02.826272
+0.089,3.0,2019-09-29 11:23:11.776641
+0.068,4.0,2019-09-29 11:32:19.540023
+0.066,5.0,2019-09-29 11:41:27.129607
+0.067,6.0,2019-09-29 11:50:33.679401
+0.071,7.0,2019-09-29 11:59:38.747566
+0.068,8.0,2019-09-29 12:08:46.713434
+0.067,9.0,2019-09-29 12:17:55.462982
+0.07,10.0,2019-09-29 12:27:03.690029
+0.066,11.0,2019-09-29 12:36:10.274328
+0.066,12.0,2019-09-29 12:45:17.844777
+0.064,13.0,2019-09-29 12:54:25.440055
+0.064,14.0,2019-09-29 13:03:32.662178
+0.063,15.0,2019-09-29 13:12:39.334202
+0.063,16.0,2019-09-29 13:21:45.282941
+0.063,17.0,2019-09-29 13:30:50.702369
+0.062,18.0,2019-09-29 13:39:56.479320
+0.062,19.0,2019-09-29 13:49:03.009732
+0.062,20.0,2019-09-29 13:58:09.206604
+0.062,21.0,2019-09-29 14:07:16.674273
+0.062,22.0,2019-09-29 14:16:32.081830
+0.061,23.0,2019-09-29 14:25:47.816996
+0.061,24.0,2019-09-29 14:34:59.053729
+0.061,25.0,2019-09-29 14:44:12.326646
+0.061,26.0,2019-09-29 14:53:20.545392
+0.061,27.0,2019-09-29 15:02:29.076439
+0.061,28.0,2019-09-29 15:11:40.214715
+0.061,29.0,2019-09-29 15:20:47.708415
+0.061,30.0,2019-09-29 15:29:55.151460
+0.061,31.0,2019-09-29 15:39:02.450643
+0.061,32.0,2019-09-29 15:48:13.678387
+0.061,33.0,2019-09-29 15:57:22.619685
+0.061,34.0,2019-09-29 16:06:32.276767
+0.061,35.0,2019-09-29 16:15:39.175331
+0.061,36.0,2019-09-29 16:24:48.090009
+0.061,37.0,2019-09-29 16:33:53.686359
+0.061,38.0,2019-09-29 16:43:01.209447
+0.061,39.0,2019-09-29 16:52:09.086088
+0.061,40.0,2019-09-29 17:01:17.997290
+0.06,41.0,2019-09-29 17:10:24.687865
+0.061,42.0,2019-09-29 17:19:33.252531
+0.061,43.0,2019-09-29 17:28:40.294962
+0.06,44.0,2019-09-29 17:37:50.408505
+0.06,45.0,2019-09-29 17:46:57.046547
+0.06,46.0,2019-09-29 17:56:05.325744

run_models.py

@@ -22,9 +22,9 @@ args.add_argument('--step', default=5)
 args.add_argument('--features', default=6)
 args.add_argument('--size', default=9)
 args.add_argument('--latent_dim', default=2)
-args.add_argument('--model', default='AE_Model')
+args.add_argument('--model', default='SAAE_Model')
 args.add_argument('--refresh', type=strtobool, default=False)
-args.add_argument('--future_predictions', type=strtobool, default=False)
+args.add_argument('--future_predictions', type=strtobool, default=True)
 
 
 class AE_Model(AutoEncoder_LO, LightningModule):
@@ -102,7 +102,7 @@ if __name__ == '__main__':
     trainer = Trainer(experiment=exp,
                       max_nb_epochs=250,
                       gpus=[0],
-                      add_log_row_interval=1000,
+                      row_log_interval=1000,
                       # checkpoint_callback=checkpoint_callback
                       )