Remove unused modules

astroNN/models/apogee_models.py

@@ -13,8 +13,6 @@
     MCDropout,
     BoolMask,
     StopGrad,
-    KLDivergenceLayer,
-    TensorInput,
     VAESampling,
 )
 from astroNN.nn.losses import (

astroNN/models/base_bayesian_cnn.py

@@ -3,40 +3,35 @@
 import time
 import warnings
 from abc import ABC
-from packaging import version
 
 import numpy as np
 from tqdm import tqdm
 from tensorflow import keras as tfk
-from astroNN.config import MAGIC_NUMBER, MULTIPROCESS_FLAG
+from astroNN.config import MULTIPROCESS_FLAG
 from astroNN.config import _astroNN_MODEL_NAME
-from astroNN.datasets import H5Loader
 from astroNN.models.base_master_nn import NeuralNetMaster
 from astroNN.nn.callbacks import VirutalCSVLogger
 from astroNN.nn.layers import FastMCInference
 from astroNN.nn.losses import (
     mean_absolute_error,
     mean_error,
-    mean_squared_error,
     zeros_loss,
 )
 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.shared.warnings import deprecated, deprecated_copy_signature
+from astroNN.shared.warnings import deprecated_copy_signature
 from astroNN.shared.nn_tools import gpu_availability
 from astroNN.shared.dict_tools import dict_np_to_dict_list, list_to_dict
 
 from astroNN.nn.losses import (
     bayesian_binary_crossentropy_wrapper,
-    bayesian_binary_crossentropy_var_wrapper,
 )
 from astroNN.nn.losses import (
     bayesian_categorical_crossentropy_wrapper,
-    bayesian_categorical_crossentropy_var_wrapper,
 )
-from astroNN.nn.losses import mse_lin_wrapper, mse_var_wrapper
+from astroNN.nn.losses import mse_lin_wrapper
 
 from sklearn.model_selection import train_test_split
 import tensorflow as tf

astroNN/models/base_vae.py

@@ -12,19 +12,15 @@
 from astroNN.models.base_master_nn import NeuralNetMaster
 from astroNN.nn.callbacks import VirutalCSVLogger
 from astroNN.nn.losses import (
-    mean_squared_error,
-    mean_error,
-    mean_absolute_error,
     mean_squared_reconstruction_error,
 )
 from astroNN.nn.utilities import Normalizer
 from astroNN.nn.utilities.generator import GeneratorMaster
 from astroNN.shared.dict_tools import dict_np_to_dict_list, list_to_dict
-from astroNN.shared.warnings import deprecated, deprecated_copy_signature
+from astroNN.shared.warnings import deprecated_copy_signature
 from sklearn.model_selection import train_test_split
 import tensorflow as tf
 from tensorflow.python.keras.engine import data_adapter
-from tensorflow.python.util import nest
 
 regularizers = tfk.regularizers
 ReduceLROnPlateau = tfk.callbacks.ReduceLROnPlateau

astroNN/nn/losses.py

@@ -4,7 +4,6 @@
 
 import tensorflow as tf
 from tensorflow import keras as tfk
-from tensorflow.python.ops.losses import util as tf_losses_util
 
 from astroNN.config import MAGIC_NUMBER
 from astroNN.nn import nn_obj_lookup

astroNN/nn/metrics.py

@@ -1,7 +1,6 @@
 # ---------------------------------------------------------------#
 #   astroNN.nn.metrics: metrics
 # ---------------------------------------------------------------#
-import tensorflow as tf
 
 from astroNN.nn.losses import binary_accuracy, binary_accuracy_from_logits
 from astroNN.nn.losses import categorical_accuracy
@@ -11,10 +10,7 @@
 from astroNN.nn.losses import mean_percentage_error
 from astroNN.nn.losses import mean_squared_error
 from astroNN.nn.losses import mean_squared_logarithmic_error
-from astroNN.nn.losses import median
 from astroNN.nn.losses import median_absolute_deviation
-from astroNN.nn.losses import median_error
-from astroNN.nn.losses import mad_std
 
 # Just alias functions
 mse = mean_squared_error

astroNN/shared/patch_util.py

@@ -7,7 +7,7 @@
 import logging
 import re
 
-from os.path import exists, isfile, abspath
+from os.path import exists, isfile
 import os
 import shutil
 import itertools