def convert_from_yaml_config(yamlConfig):
model = None
if 'OnnxModel' in yamlConfig:
if __onnx_enabled__:
model = onnx_to_hls(yamlConfig)
else:
raise Exception("ONNX not found. Please install ONNX.")
elif 'PytorchModel' in yamlConfig:
if __pytorch_enabled__:
model = pytorch_to_hls(yamlConfig)
else:
raise Exception("PyTorch not found. Please install PyTorch.")
elif 'TensorFlowModel' in yamlConfig:
if __tensorflow_enabled__:
model = tf_to_hls(yamlConfig)
else:
raise Exception("TensorFlow not found. Please install TensorFlow.")
else:
model = keras_to_hls(yamlConfig)
return model
def convert_from_config(config):
"""Convert to hls4ml model based on the provided configuration.
Arguments:
config: A string containing the path to the YAML configuration file on
the filesystem or a dict containig the parsed configuration.
Returns:
HLSModel: hls4ml model.
"""
if isinstance(config, str):
yamlConfig = parse_yaml_config(config)
else:
yamlConfig = config
model = None
if 'OnnxModel' in yamlConfig:
if __onnx_enabled__:
model = onnx_to_hls(yamlConfig)
else:
raise Exception("ONNX not found. Please install ONNX.")
elif 'PytorchModel' in yamlConfig:
if __pytorch_enabled__:
model = pytorch_to_hls(yamlConfig)
else:
raise Exception("PyTorch not found. Please install PyTorch.")
elif 'TensorFlowModel' in yamlConfig:
if __tensorflow_enabled__:
model = tf_to_hls(yamlConfig)
else:
raise Exception("TensorFlow not found. Please install TensorFlow.")
else:
model = keras_to_hls(yamlConfig)
return model