Solve get_source_inputs related errors

classification_models/keras.py

@@ -1,4 +1,5 @@
-import keras
+# import keras
+from tensorflow import keras
 from .models_factory import ModelsFactory
 
 

classification_models/models/resnet.py

@@ -5,6 +5,7 @@
 from ._common_blocks import ChannelSE
 from .. import get_submodules_from_kwargs
 from ..weights import load_model_weights
+from tensorflow.keras.utils import get_source_inputs
 
 backend = None
 layers = None
@@ -209,10 +210,16 @@ def ResNet(model_params, input_shape=None, input_tensor=None, include_top=True,
     if input_tensor is None:
         img_input = layers.Input(shape=input_shape, name='data')
     else:
-        if not backend.is_keras_tensor(input_tensor):
-            img_input = layers.Input(tensor=input_tensor, shape=input_shape)
-        else:
-            img_input = input_tensor
+        """ Commented to solve following error:
+        ValueError: Unexpectedly found an instance of type 
+        `<class 'tensorflow.python.keras.engine.keras_tensor.KerasTensor'>`. 
+        Expected a symbolic tensor instance.
+        """
+        # if not backend.is_keras_tensor(input_tensor):
+        #     img_input = layers.Input(tensor=input_tensor, shape=input_shape)
+        # else:
+        #     img_input = input_tensor
+        img_input = input_tensor
 
     # choose residual block type
     ResidualBlock = model_params.residual_block
@@ -266,7 +273,11 @@ def ResNet(model_params, input_shape=None, input_tensor=None, include_top=True,
 
     # Ensure that the model takes into account any potential predecessors of `input_tensor`.
     if input_tensor is not None:
-        inputs = keras_utils.get_source_inputs(input_tensor)
+        """ Modified to solve following error:
+        module 'keras.utils' has no attribute 'get_source_inputs'
+        """
+        # inputs = keras_utils.get_source_inputs(input_tensor)
+        inputs = get_source_inputs(input_tensor)
     else:
         inputs = img_input
 

classification_models/weights.py

@@ -1,4 +1,5 @@
 from . import get_submodules_from_kwargs
+from tensorflow.keras.utils import get_file
 
 __all__ = ['load_model_weights']
 
@@ -22,7 +23,11 @@ def load_model_weights(model, model_name, dataset, classes, include_top, **kwarg
             raise ValueError('If using `weights` and `include_top`'
                              ' as true, `classes` should be {}'.format(weights['classes']))
 
-        weights_path = keras_utils.get_file(
+        """ Modified to solve following error:
+        module 'keras.utils' has no attribute 'get_file'
+        """
+        # weights_path = keras_utils.get_file(
+        weights_path = get_file(
             weights['name'],
             weights['url'],
             cache_subdir='models',