keras-hub

import keras from keras_hub import KerasLayer import tensorflow as tf # Required for data types and model building # This code block demonstrates the intended usage of keras-hub (0.27.1). # It is NOT runnable with modern Python (3.8+) or Keras 3.x without # specific, older TensorFlow/Keras versions and their corresponding # Python environment. # For a runnable example using modern Keras, see the 'warnings' section below. try: # Example: Use a pre-trained image feature vector module from TensorFlow Hub # Note: The actual module URL would need to be valid for the TensorFlow Hub # version compatible with keras-hub 0.27.1 (circa 2019). feature_extractor_url = "https://tfhub.dev/google/imagenet/mobilenet_v2_100_224/feature_vector/4" # Create a KerasLayer from the Hub module # keras-hub's KerasLayer defaults trainable=False hub_layer = KerasLayer(feature_extractor_url, input_shape=(224, 224, 3)) # Build a simple Keras model model = keras.Sequential([ keras.Input(shape=(224, 224, 3)), hub_layer, keras.layers.Dense(2, activation='softmax') ]) model.summary() print(f"KerasLayer trainable: {hub_layer.trainable}") except ImportError: print("\n'keras-hub' or its dependencies not found. This library is abandoned.") print("Install with 'pip install keras-hub' requires older Python/TensorFlow environment.") except Exception as e: print(f"\nAn error occurred during keras-hub usage (likely due to environment incompatibility): {e}") # --- Modern Keras/TensorFlow Hub approach (RECOMMENDED) --- # For current environments, use tensorflow_hub directly: # import tensorflow_hub as hub # import keras # # feature_extractor_url_modern = "https://tfhub.dev/google/efficientnet/b0/feature-vector/1" # Example modern URL # hub_layer_modern = hub.KerasLayer(feature_extractor_url_modern, trainable=False, input_shape=(224, 224, 3)) # model_modern = keras.Sequential([ # keras.Input(shape=(224, 224, 3)), # hub_layer_modern, # keras.layers.Dense(2, activation='softmax') # ]) # model_modern.summary()