fix: rename tensorflow to keras

configs/ops/prediction/op_prediction_base.yaml

@@ -1,5 +1,5 @@
 model_loader:
-  _target_: niceml.dlframeworks.tensorflow.kerasmodelloader.KerasModelLoader
+  _target_: niceml.dlframeworks.keras.kerasmodelloader.KerasModelLoader
 prediction_steps: ${niceml.to_int:${oc.env:PREDICTION_STEPS,null}}
 prediction_function:
-  _target_: niceml.dlframeworks.tensorflow.predictionfunctions.keraspredictionfunction.KerasPredictionFunction
+  _target_: niceml.dlframeworks.keras.predictionfunctions.keraspredictionfunction.KerasPredictionFunction

configs/ops/train/callbacks/callbacks_base.yaml

@@ -4,12 +4,12 @@
 
 _target_: niceml.mlcomponents.callbacks.callbackinitializer.CallbackInitializer
 callback_list:
-  - _target_: niceml.dlframeworks.tensorflow.callbacks.callback_factories.InitCallbackFactory
+  - _target_: niceml.dlframeworks.keras.callbacks.callback_factories.InitCallbackFactory
     callback:
-      _target_: niceml.dlframeworks.tensorflow.callbacks.nancheckcallback.LossNanCheckCallback
-  - _target_: niceml.dlframeworks.tensorflow.callbacks.callback_factories.LoggingOutputCallbackFactory
+      _target_: niceml.dlframeworks.keras.callbacks.nancheckcallback.LossNanCheckCallback
+  - _target_: niceml.dlframeworks.keras.callbacks.callback_factories.LoggingOutputCallbackFactory
 callback_dict:
   save_model:
     # Stores the model after each epoch
-    _target_: niceml.dlframeworks.tensorflow.callbacks.callback_factories.ModelCallbackFactory
+    _target_: niceml.dlframeworks.keras.callbacks.callback_factories.ModelCallbackFactory
     model_subfolder: models/model-id_{short_id}-ep{epoch:03d}.hdf5

configs/ops/train/op_train_cls_binary.yaml

@@ -25,12 +25,12 @@ data_validation:
     sub_dir: validation
   set_name: validation
 model:
-  _target_: niceml.dlframeworks.tensorflow.models.mobilenet.OwnMobileNetModel
+  _target_: niceml.dlframeworks.keras.models.mobilenet.OwnMobileNetModel
   final_activation: sigmoid
 learner:
-  _target_: niceml.dlframeworks.tensorflow.learners.defaultlearner.DefaultLearner
+  _target_: niceml.dlframeworks.keras.learners.keraslearner.KerasLearner
   model_compiler:
-    _target_: niceml.dlframeworks.tensorflow.modelcompiler.defaultmodelcompiler.DefaultModelCompiler
+    _target_: niceml.dlframeworks.keras.modelcompiler.defaultmodelcompiler.DefaultModelCompiler
     loss: binary_crossentropy
     # Optimizer used in the experiment
     optimizer:

configs/ops/train/op_train_objdet.yaml

@@ -18,30 +18,30 @@ data_description:
     height: 1024
 
 model:
-  _target_: niceml.dlframeworks.tensorflow.models.retinanet.RetinaNetFactory
+  _target_: niceml.dlframeworks.keras.models.retinanet.RetinaNetFactory
 
 learner:
-  _target_: niceml.dlframeworks.tensorflow.learners.defaultlearner.DefaultLearner
+  _target_: niceml.dlframeworks.keras.learners.keraslearner.KerasLearner
   model_compiler:
-    _target_: niceml.dlframeworks.tensorflow.modelcompiler.defaultmodelcompiler.DefaultModelCompiler
+    _target_: niceml.dlframeworks.keras.modelcompiler.defaultmodelcompiler.DefaultModelCompiler
     run_eagerly: ${niceml.to_bool:${oc.env:RUN_EAGERLY,false}}
     loss:
-      _target_: niceml.dlframeworks.tensorflow.losses.objdetlosses.CombinationLoss
+      _target_: niceml.dlframeworks.keras.losses.objdetlosses.CombinationLoss
       weights: [5000.0,0.1]
       losses:
-        - _target_: niceml.dlframeworks.tensorflow.losses.objdetlosses.RetinaNetClsLoss
-        - _target_: niceml.dlframeworks.tensorflow.losses.objdetlosses.RetinaNetBoxLoss
+        - _target_: niceml.dlframeworks.keras.losses.objdetlosses.RetinaNetClsLoss
+        - _target_: niceml.dlframeworks.keras.losses.objdetlosses.RetinaNetBoxLoss
     # Optimizer is used in the experiment
     optimizer:
       _target_: tensorflow.keras.optimizers.RMSprop
       learning_rate: 0.0001
     metrics:
-      - _target_: niceml.dlframeworks.tensorflow.losses.objdetlosses.RetinaNetClsLoss
-      - _target_: niceml.dlframeworks.tensorflow.losses.objdetlosses.RetinaNetBoxLoss
-      - _target_: niceml.dlframeworks.tensorflow.metrics.objdetmetrics.AvgPosPredObjDet
-      - _target_: niceml.dlframeworks.tensorflow.metrics.objdetmetrics.AvgPosTargetCountObjDet
-      - _target_: niceml.dlframeworks.tensorflow.metrics.objdetmetrics.AvgNegTargetCountObjDet
-      - _target_: niceml.dlframeworks.tensorflow.metrics.objdetmetrics.AvgNegPredObjDet
+      - _target_: niceml.dlframeworks.keras.losses.objdetlosses.RetinaNetClsLoss
+      - _target_: niceml.dlframeworks.keras.losses.objdetlosses.RetinaNetBoxLoss
+      - _target_: niceml.dlframeworks.keras.metrics.objdetmetrics.AvgPosPredObjDet
+      - _target_: niceml.dlframeworks.keras.metrics.objdetmetrics.AvgPosTargetCountObjDet
+      - _target_: niceml.dlframeworks.keras.metrics.objdetmetrics.AvgNegTargetCountObjDet
+      - _target_: niceml.dlframeworks.keras.metrics.objdetmetrics.AvgNegPredObjDet
 
 
 data_train:

configs/ops/train/op_train_reg.yaml

@@ -23,17 +23,17 @@ data_validation:
   subset_name: validation
   df_filename: numbers_tabular_data_validation.parq
 model:
-  _target_: niceml.dlframeworks.tensorflow.models.mlp.OwnMLP
+  _target_: niceml.dlframeworks.keras.models.mlp.OwnMLP
   activation: tanh
   final_activation: tanh
   hidden_layers:
     - 25
     - 35
     - 12
 learner:
-  _target_: niceml.dlframeworks.tensorflow.learners.defaultlearner.DefaultLearner
+  _target_: niceml.dlframeworks.keras.learners.keraslearner.KerasLearner
   model_compiler:
-    _target_: niceml.dlframeworks.tensorflow.modelcompiler.defaultmodelcompiler.DefaultModelCompiler
+    _target_: niceml.dlframeworks.keras.modelcompiler.defaultmodelcompiler.DefaultModelCompiler
     loss: mse
     # Optimizer used in the experiment
     optimizer:

configs/ops/train/op_train_semseg.yaml

@@ -19,39 +19,39 @@ data_description:
     max_number: 3
 
 model:
-  _target_: niceml.dlframeworks.tensorflow.models.unets.mobilenetv2_unet
+  _target_: niceml.dlframeworks.keras.models.unets.mobilenetv2_unet
   use_input_scale: true
   allow_preconvolution: true
   activation: sigmoid
   alpha: 1.0
   downscale_layer_factory:
-    _target_: niceml.dlframeworks.tensorflow.models.layerfactory.DownscaleConvBlockFactory
+    _target_: niceml.dlframeworks.keras.models.layerfactory.DownscaleConvBlockFactory
     channel_list: [128, 128, 128]
   post_layer_factory:
-    _target_: niceml.dlframeworks.tensorflow.models.layerfactory.Conv2DBlockFactory
+    _target_: niceml.dlframeworks.keras.models.layerfactory.Conv2DBlockFactory
     channel_list: [1024, 1024]
     kernel_size: 1
     dropout_values: [0.25, 0.25]
 
 learner:
-  _target_: niceml.dlframeworks.tensorflow.learners.defaultlearner.DefaultLearner
+  _target_: niceml.dlframeworks.keras.learners.keraslearner.KerasLearner
   model_compiler:
-    _target_: niceml.dlframeworks.tensorflow.modelcompiler.defaultmodelcompiler.DefaultModelCompiler
+    _target_: niceml.dlframeworks.keras.modelcompiler.defaultmodelcompiler.DefaultModelCompiler
     run_eagerly: ${niceml.to_bool:${oc.env:RUN_EAGERLY,false}}
     loss:
-      _target_: niceml.dlframeworks.tensorflow.losses.semseglosses.SemSegFocalLoss
+      _target_: niceml.dlframeworks.keras.losses.semseglosses.SemSegFocalLoss
       alpha: 0.25
       gamma: 2.0
     # Optimizer is used in the experiment
     optimizer:
       _target_: tensorflow.keras.optimizers.RMSprop
       learning_rate: 0.0001
     metrics:
-      - _target_: niceml.dlframeworks.tensorflow.kerasmetrics.MeanIoU
-      - _target_: niceml.dlframeworks.tensorflow.metrics.semsegmetrics.AvgPosPredSemSeg
-      - _target_: niceml.dlframeworks.tensorflow.metrics.semsegmetrics.AvgNegPredSemSeg
-      - _target_: niceml.dlframeworks.tensorflow.metrics.semsegmetrics.AvgPosTargetCountSemSeg
-      - _target_: niceml.dlframeworks.tensorflow.metrics.semsegmetrics.AvgNegTargetCountSemSeg
+      - _target_: niceml.dlframeworks.keras.kerasmetrics.MeanIoU
+      - _target_: niceml.dlframeworks.keras.metrics.semsegmetrics.AvgPosPredSemSeg
+      - _target_: niceml.dlframeworks.keras.metrics.semsegmetrics.AvgNegPredSemSeg
+      - _target_: niceml.dlframeworks.keras.metrics.semsegmetrics.AvgPosTargetCountSemSeg
+      - _target_: niceml.dlframeworks.keras.metrics.semsegmetrics.AvgNegTargetCountSemSeg
 
 data_train:
   datainfo_listing:

docs/write-custom-pipeline.md

@@ -111,14 +111,14 @@ data_validation:
     sub_dir: validation
   set_name: validation
 model:
-  _target_: niceml.dlframeworks.tensorflow.models.mobilenet.OwnMobileNetModel
+  _target_: niceml.dlframeworks.keras.models.mobilenet.OwnMobileNetModel
   final_activation: sigmoid
 model_load_custom_objects:
   _target_: niceml.mlcomponents.modelcompiler.modelcustomloadobjects.ModelCustomLoadObjects
 learner:
-  _target_: niceml.dlframeworks.tensorflow.learners.defaultlearner.DefaultLearner
+  _target_: niceml.dlframeworks.keras.learners.defaultlearner.DefaultLearner
   model_compiler:
-    _target_: niceml.dlframeworks.tensorflow.modelcompiler.defaultmodelcompiler.DefaultModelCompiler
+    _target_: niceml.dlframeworks.keras.modelcompiler.defaultmodelcompiler.DefaultModelCompiler
     loss: binary_crossentropy
     # Optimizer used in the experiment
     optimizer:

niceml/dashboard/cam.py

@@ -62,7 +62,7 @@ def _load_model(exp: ExperimentData):
         exp: experiment (ExperimentData)
 
     Returns:
-        tensorflow model
+        keras model
     """
 
     model = load_model(exp.get_model_path())
@@ -92,7 +92,7 @@ def create_heatmap(
     generates heatmap using last conv layer "conv" specified in create_model section
 
     Args:
-        model: tensorflow Model
+        model: keras Model
         img: image as numpy array
         class_idx: class index of output tensor
         layer_name: last conv layer name - DEFAULT: "conv"

niceml/dlframeworks/tensorflow/callbacks/callback_factories.py → niceml/dlframeworks/keras/callbacks/callback_factories.py

@@ -4,8 +4,8 @@
 from pathlib import Path
 from typing import Any, List
 
-from niceml.dlframeworks.tensorflow.callbacks.csvlogger import CSVLogger
-from niceml.dlframeworks.tensorflow.callbacks.modelcheckpoint import ModelCheckpoint
+from niceml.dlframeworks.keras.callbacks.csvlogger import CSVLogger
+from niceml.dlframeworks.keras.callbacks.modelcheckpoint import ModelCheckpoint
 from niceml.experiments.experimentcontext import ExperimentContext
 from niceml.utilities.factoryutils import subs_path_and_create_folder
 from niceml.utilities.fsspec.locationutils import join_location_w_path
@@ -96,6 +96,6 @@ def create_callback(self, exp_context: ExperimentContext):
         Path(filepath).mkdir(exist_ok=True, parents=False)
 
         # pylint: disable=import-outside-toplevel
-        from niceml.dlframeworks.tensorflow.callbacks.cam_callback import CamCallback
+        from niceml.dlframeworks.keras.callbacks.cam_callback import CamCallback
 
         return CamCallback(output_dir=filepath, images=self.images)

niceml/dlframeworks/tensorflow/learners/defaultlearner.py → niceml/dlframeworks/keras/learners/keraslearner.py

@@ -20,8 +20,8 @@
 
 
 # pylint: disable=too-few-public-methods
-class DefaultLearner(Learner):
-    """default learner for keras/tensorflow models"""
+class KerasLearner(Learner):
+    """default learner for keras/keras models"""
 
     def __init__(
         self,

niceml/dlframeworks/tensorflow/losses/categoricalfocalloss.py → niceml/dlframeworks/keras/losses/categoricalfocalloss.py

@@ -24,7 +24,7 @@ def __init__(self, alpha: Union[float, List[float]], gamma: float = 2.0, **kwarg
         gamma: float
             gamma value of the paper
         kwargs:
-            all parameters are applied to tensorflow loss
+            all parameters are applied to keras loss
         """
         super().__init__(**kwargs)
         self.alpha = np.array(alpha, dtype=np.float32)

niceml/dlframeworks/tensorflow/modelcompiler/defaultmodelcompiler.py → niceml/dlframeworks/keras/modelcompiler/defaultmodelcompiler.py

@@ -1,4 +1,4 @@
-"""Module for model compilers in tensorflow"""
+"""Module for model compilers in keras"""
 from typing import Any, List, Union
 
 from niceml.data.datadescriptions.datadescription import DataDescription
@@ -8,7 +8,7 @@
 
 
 class DefaultModelCompiler(ModelCompiler):  # pylint: disable=too-few-public-methods
-    """Simplest model compiler for tensorflow"""
+    """Simplest model compiler for keras"""
 
     def __init__(
         self, loss: Union[str, dict], metrics: List, optimizer: dict, **kwargs
@@ -32,7 +32,7 @@ def compile(
 
 
 class ComplexModelCompiler(ModelCompiler):  # pylint: disable=too-few-public-methods
-    """Complex model compiler for tensorflow"""
+    """Complex model compiler for keras"""
 
     def __init__(
         self,

niceml/dlframeworks/tensorflow/models/clsmodelfactory.py → niceml/dlframeworks/keras/models/clsmodelfactory.py

@@ -8,7 +8,7 @@
 from niceml.data.datadescriptions.outputdatadescriptions import (
     OutputVectorDataDescription,
 )
-from niceml.dlframeworks.tensorflow.models.premodellayers import add_premodel_layers
+from niceml.dlframeworks.keras.models.premodellayers import add_premodel_layers
 from niceml.mlcomponents.models.modelfactory import ModelFactory
 from niceml.utilities.commonutils import check_instance
 from niceml.utilities.imagesize import ImageSize

niceml/dlframeworks/tensorflow/models/mlp.py → niceml/dlframeworks/keras/models/mlp.py

@@ -1,4 +1,4 @@
-"""Module for ownmlp for tensorflow model"""
+"""Module for ownmlp for keras model"""
 from typing import Any, List
 
 from tensorflow.keras import Sequential, layers  # pylint: disable=import-error

niceml/dlframeworks/tensorflow/models/retinanet.py → niceml/dlframeworks/keras/models/retinanet.py

@@ -19,7 +19,7 @@
 from niceml.data.datadescriptions.outputdatadescriptions import (
     OutputObjDetDataDescription,
 )
-from niceml.dlframeworks.tensorflow.models.premodellayers import add_premodel_layers
+from niceml.dlframeworks.keras.models.premodellayers import add_premodel_layers
 from niceml.mlcomponents.models.modelfactory import ModelFactory
 from niceml.utilities.commonutils import check_instance
 from niceml.utilities.imagesize import ImageSize

niceml/dlframeworks/tensorflow/models/unets.py → niceml/dlframeworks/keras/models/unets.py

@@ -14,8 +14,8 @@
 from niceml.data.datadescriptions.outputdatadescriptions import (
     OutputImageDataDescription,
 )
-from niceml.dlframeworks.tensorflow.models.layerfactory import LayerFactory
-from niceml.dlframeworks.tensorflow.models.premodellayers import add_premodel_layers
+from niceml.dlframeworks.keras.models.layerfactory import LayerFactory
+from niceml.dlframeworks.keras.models.premodellayers import add_premodel_layers
 from niceml.mlcomponents.models.modelfactory import ModelFactory
 from niceml.utilities.commonutils import check_instance
 

niceml/dlframeworks/tensorflow/optimizers/schedules/cycliclrschedule.py → niceml/dlframeworks/keras/optimizers/schedules/cycliclrschedule.py

@@ -11,6 +11,13 @@ class CyclicLRSchedule(LearningRateSchedule):
     """Cyclic learning rate schedule"""
 
     def __init__(self, max_lr: float, cycle_size: int, min_lr: Optional[float] = None):
+        """
+        Constructor for CyclicLRSchedule
+        Args:
+            max_lr: maximum learning rate
+            cycle_size: steps per cycle
+            min_lr: minimum learning rate (default: max_lr / 10)
+        """
         super().__init__()
         self.max_lr = max_lr
         self.cycle_size = cycle_size

niceml/mlcomponents/callbacks/callbackinitializer.py

@@ -1,7 +1,7 @@
 """Module for CallbackInitializer"""
 from typing import Dict, List, Optional
 
-from niceml.dlframeworks.tensorflow.callbacks.callback_factories import CallbackFactory
+from niceml.dlframeworks.keras.callbacks.callback_factories import CallbackFactory
 from niceml.experiments.experimentcontext import ExperimentContext
 
 
@@ -13,11 +13,17 @@ def __init__(
         callback_list: Optional[List[CallbackFactory]] = None,
         callback_dict: Optional[Dict[str, CallbackFactory]] = None,
     ):
+        """
+        Constructor for CallbackInitializer
+        Args:
+            callback_list: A list of callback factories
+            callback_dict: A dict of callback factories
+        """
         self.callback_list = callback_list or []
         self.callback_dict = callback_dict or {}
 
     def __call__(self, exp_context: ExperimentContext) -> List:
-        cur_cb: CallbackFactory
+        """Initializes the callbacks"""
         callback_list = self.callback_list + list(self.callback_dict.values())
         cb_init_list = [cur_cb.create_callback(exp_context) for cur_cb in callback_list]
         return cb_init_list