Merge pull request #89 from theislab/tf2_compatibility

- structural changes to batchglm necessary before tf2 code merge
- introduction of numpy backend

Author: davidsebfischer

.gitignore

@@ -12,7 +12,8 @@ resources/*
 **/__pycache__
 **/.DS_Store
 batchglm.egg-info
-**/*.ipynb
+#**/*.ipynb
+tutorials
 
 !**/.gitignore
 

batchglm/api/__init__.py

@@ -1,8 +1,8 @@
-from .. import __version__
-from ..log_cfg import logger, unconfigure_logging, setup_logging
-
-from . import models
 from . import data
+from . import models
 from . import typing
 from . import utils
-from .. import pkg_constants
+
+from .. import __version__
+from ..log_cfg import logger, unconfigure_logging, setup_logging
+from .. import pkg_constants

batchglm/api/models/__init__.py

@@ -1,3 +1,2 @@
-from . import glm_nb
-from . import glm_norm
-from . import glm_beta
+from . import numpy
+from . import tf1

batchglm/api/models/numpy/__init__.py

@@ -0,0 +1 @@
+from . import glm_nb

batchglm/api/models/numpy/glm_nb.py

@@ -0,0 +1,2 @@
+from batchglm.models.glm_nb import InputDataGLM, Model, Simulator
+from batchglm.train.numpy.glm_nb import Estimator

batchglm/api/models/tf1/__init__.py

@@ -0,0 +1,3 @@
+from . import glm_beta
+from . import glm_nb
+from . import glm_norm

batchglm/api/models/glm_beta.py batchglm/api/models/tf1/glm_beta.pybatchglm/api/models/glm_beta.py renamed to batchglm/api/models/tf1/glm_beta.py

@@ -1,2 +1,2 @@
 from batchglm.models.glm_beta import InputDataGLM, Model, Simulator
-from batchglm.train.tf.glm_beta import Estimator
+from batchglm.train.tf1.glm_beta import Estimator

batchglm/api/models/glm_nb.py batchglm/api/models/tf1/glm_nb.pybatchglm/api/models/glm_nb.py renamed to batchglm/api/models/tf1/glm_nb.py

@@ -1,2 +1,2 @@
 from batchglm.models.glm_nb import InputDataGLM, Model, Simulator
-from batchglm.train.tf.glm_nb import Estimator
+from batchglm.train.tf1.glm_nb import Estimator

batchglm/api/models/glm_norm.py batchglm/api/models/tf1/glm_norm.pybatchglm/api/models/glm_norm.py renamed to batchglm/api/models/tf1/glm_norm.py

@@ -1,2 +1,2 @@
 from batchglm.models.glm_norm import InputDataGLM, Model, Simulator
-from batchglm.train.tf.glm_norm import Estimator
+from batchglm.train.tf1.glm_norm import Estimator

batchglm/models/base/estimator.py

@@ -89,7 +89,7 @@ def initialize(self, **kwargs):
         pass
 
     @abc.abstractmethod
-    def train(self, learning_rate=None, **kwargs):
+    def train(self, **kwargs):
         """
         Starts the training routine
         """
@@ -103,31 +103,6 @@ def finalize(self, **kwargs):
         """
         pass
 
-    def train_sequence(self, training_strategy=TrainingStrategy.AUTO):
-        """
-        Starts a sequence of training routines
-
-        :param training_strategy: List of dicts or enum with parameters which will be passed to self.train().
-
-                - `training_strategy = [ {"learning_rate": 0.5}, {"learning_rate": 0.05} ]` is equivalent to
-                    `self.train(learning_rate=0.5); self.train(learning_rate=0.05);`
-
-                - Can also be an enum: self.TrainingStrategy.[AUTO|DEFAULT|EXACT|QUICK|...]
-                - Can also be a str: "[AUTO|DEFAULT|EXACT|QUICK|...]"
-        """
-        if isinstance(training_strategy, Enum):
-            training_strategy = training_strategy.value
-        elif isinstance(training_strategy, str):
-            training_strategy = self.TrainingStrategy[training_strategy].value
-
-        if training_strategy is None:
-            training_strategy = self.TrainingStrategy.DEFAULT.value
-
-        for idx, d in enumerate(training_strategy):
-            logger.info("Beginning with training sequence #%d", idx + 1)
-            self.train(**d)
-            logger.info("Training sequence #%d complete", idx + 1)
-
     def _plot_coef_vs_ref(
             self,
             true_values: np.ndarray,