rename GeneartorMaster to GeneratorBase

docs/requirements.txt

@@ -1,9 +1,8 @@
 torch
 tensorflow-cpu
+sphinx>=8
 sphinx_rtd_theme>=3.0.0a0
 sphinx-prompt
 sphinx-copybutton
-
-sphinx>=8
 nbsphinx
 ipykernel

docs/source/neuralnets/basic_usage.rst

@@ -7,13 +7,13 @@ Available astroNN Neural Net Classes
 --------------------------------------
 
 All astroNN Neural Nets are inherited from some child classes which inherited NeuralNetBase, NeuralNetBase also
-relies relies on two major component, `Normalizer` and `GeneratorMaster`
+relies relies on two major component, `Normalizer` and `GeneratorBase`
 
 ::
 
     Normalizer (astroNN.nn.utilities.normalizer.Normalizer)
 
-    GeneratorMaster (astroNN.nn.utilities.generator.GeneratorMaster)
+    GeneratorBase (astroNN.nn.utilities.generator.GeneratorBase)
     ├── CNNDataGenerator
     ├── Bayesian_DataGenerator
     └── CVAE_DataGenerator

docs/source/quick_start.rst

@@ -32,7 +32,7 @@ or if you want to install it in editable mode, you can run:
 Prerequisites
 ---------------
 
-``astroNN`` requires Python 3.9 or above. The following packages are required which will be installed automatically when you install ``astroNN``:
+``astroNN`` requires Python 3.10 or above. The following packages are required which will be installed automatically when you install ``astroNN``:
 
 .. literalinclude:: ../../requirements.txt
 
@@ -225,7 +225,7 @@ How to set environment variable on different operating system: `Guide here`_
 A dedicated project folder is recommended to run astroNN, always run astroNN under the root of project folder. So that
 astroNN will always create folder for every neural network you run under the same place. Just as below
 
-.. image:: astronn_master_folder.PNG
+.. image:: astronn_folder.png
    :scale: 50 %
 
 .. _Guide here: https://www.schrodinger.com/kb/1842

src/astroNN/models/base_bayesian_cnn.py

@@ -23,7 +23,7 @@
 from astroNN.nn.metrics import categorical_accuracy, binary_accuracy
 from astroNN.nn.numpy import sigmoid
 from astroNN.nn.utilities import Normalizer
-from astroNN.nn.utilities.generator import GeneratorMaster
+from astroNN.nn.utilities.generator import GeneratorBase
 from astroNN.shared.dict_tools import dict_np_to_dict_list, list_to_dict
 
 from astroNN.nn.losses import (
@@ -40,7 +40,7 @@
 Adam = keras.optimizers.Adam
 
 
-class BayesianCNNDataGenerator(GeneratorMaster):
+class BayesianCNNDataGenerator(GeneratorBase):
     """
     To generate data to NN
 
@@ -108,7 +108,7 @@ def on_epoch_end(self):
         )
 
 
-class BayesianCNNPredDataGenerator(GeneratorMaster):
+class BayesianCNNPredDataGenerator(GeneratorBase):
     """
     To generate data to NN for prediction
 
@@ -934,7 +934,7 @@ def predict(self, input_data, inputs_err=None, batch_size=None):
         }
 
     def predict_dataset(self, file):
-        class BayesianCNNPredDataGeneratorV2(GeneratorMaster):
+        class BayesianCNNPredDataGeneratorV2(GeneratorBase):
             def __init__(
                 self,
                 batch_size,

src/astroNN/models/base_cnn.py

@@ -14,7 +14,7 @@
 from astroNN.nn.losses import mean_squared_error, mean_absolute_error, mean_error
 from astroNN.nn.metrics import categorical_accuracy, binary_accuracy
 from astroNN.nn.utilities import Normalizer
-from astroNN.nn.utilities.generator import GeneratorMaster
+from astroNN.nn.utilities.generator import GeneratorBase
 from astroNN.shared.dict_tools import dict_np_to_dict_list, list_to_dict
 from sklearn.model_selection import train_test_split
 
@@ -26,7 +26,7 @@
 Adam = keras.optimizers.Adam
 
 
-class CNNDataGenerator(GeneratorMaster):
+class CNNDataGenerator(GeneratorBase):
     """
     To generate data to NN
 
@@ -92,7 +92,7 @@ def on_epoch_end(self):
         )
 
 
-class CNNPredDataGenerator(GeneratorMaster):
+class CNNPredDataGenerator(GeneratorBase):
     """
     To generate data to NN for prediction
 

src/astroNN/models/base_vae.py

@@ -15,7 +15,7 @@
     mean_squared_reconstruction_error,
 )
 from astroNN.nn.utilities import Normalizer
-from astroNN.nn.utilities.generator import GeneratorMaster
+from astroNN.nn.utilities.generator import GeneratorBase
 from astroNN.shared.dict_tools import dict_np_to_dict_list, list_to_dict
 from sklearn.model_selection import train_test_split
 
@@ -24,7 +24,7 @@
 Adam = keras.optimizers.Adam
 
 
-class CVAEDataGenerator(GeneratorMaster):
+class CVAEDataGenerator(GeneratorBase):
     """
     To generate data to NN
 
@@ -88,7 +88,7 @@ def on_epoch_end(self):
         )
 
 
-class CVAEPredDataGenerator(GeneratorMaster):
+class CVAEPredDataGenerator(GeneratorBase):
     """
     To generate data to NN for prediction
 

src/astroNN/nn/utilities/generator.py

@@ -2,13 +2,8 @@
 
 import keras
 
-try:
-    from keras.trainers.data_adapters.py_dataset_adapter import PyDataset
-except ImportError:
-    from keras.src.trainers.data_adapters.py_dataset_adapter import PyDataset
 
-
-class GeneratorMaster(PyDataset):
+class GeneratorBase(keras.utils.PyDataset):
     """
     | Top-level class of astroNN data pipeline to generate data for NNs.