To load a Keras model from a JSON file, you can use the model_from_json
function from the keras.models
module. This is achieved by importing the function with from keras.models import model_from_json
.
from keras.models import model_from_json
```markdown
# Import the required Keras module
from keras.models import model_from_json as load_model_json
# TODO: Implement a function to save the model in JSON format
def save_model(model, model_path):
model_json = model.to_json()
with open(model_path, 'w') as f:
f.write(model_json)
# TODO: Implement a function to load the model from JSON format
def load_saved_model(model_path):
try:
with open(model_path, 'r') as f:
model_json = f.read()
return model_from_json(model_json)
except FileNotFoundError:
print("Model file not found at the specified path.")
return None
# Example usage:
if __name__ == "__main__":
# Load the model from JSON
loaded_model = load_saved_model('model.json')
if loaded_model:
print("Model loaded successfully.")
else:
print("Failed to load the model.")
```
This refactored code includes:
1. Renamed the import statement to a more descriptive alias (`load_model_json`) for clarity.
2. Added two functions for saving and loading the model from JSON format.
3. Included TODO comments to indicate areas of the code that need to be expanded.
4. Implemented error handling for loading the model from JSON, catching the `FileNotFoundError` exception and printing a corresponding error message.
5. Added an example usage section to demonstrate how to use the `load_saved_model` function.
6. Formatted the code with consistent indentation and spacing for readability.
from keras.models import model_from_json
This line imports the model_from_json
function from the keras.models
module. This function is used to load a Keras model from a JSON file.