Python TensorFlowServingModel Beispiele

Beispiel #1

Datei: pipeline_invoke_tfserving.py Projekt: sunkarimahidhar85/models

def _initialize_upon_import():
    """ Initialize / Restore Model Object."""
    return TensorFlowServingModel(host='localhost',
                                  port=9000,
                                  model_name='tfserving',
                                  model_signature_name=None,
                                  timeout_seconds=10.0)

Beispiel #2

Datei: pipeline_predict.py Projekt: melatonin355/models

def _initialize_upon_import() -> TensorFlowServingModel:
    ''' Initialize / Restore Model Object.
    '''
    return TensorFlowServingModel(host='localhost',
                                  port=9000,
                                  model_name='inception',
                                  model_signature_name='predict_images',
                                  timeout_seconds=10.0)

Beispiel #3

def _initialize_upon_import() -> TensorFlowServingModel:
    ''' Initialize / Restore Model Object.
    '''
    return TensorFlowServingModel(host='localhost',
                                  port=9000,
                                  model_name='basicdnn',
                                  model_signature_name=None,
                                  timeout_seconds=10.0)

Beispiel #4

def _initialize_upon_import() -> TensorFlowServingModel:
    ''' Initialize / Restore Model Object.
    '''
    return TensorFlowServingModel(host='localhost',
                                  port=9000,
                                  model_name=os.environ['PIPELINE_MODEL_NAME'],
                                  model_signature_name=None,
                                  timeout_seconds=10.0)

Beispiel #5

Datei: pipeline_predict.py Projekt: ccortezb/models

def _initialize_upon_import() -> TensorFlowServingModel:
    ''' Initialize / Restore Model Object.
    '''
    return TensorFlowServingModel(host='localhost',
                                  port=9000,
                                  model_name=os.environ['PIPELINE_MODEL_NAME'],
                                  inputs_name='inputs',
                                  outputs_name='outputs',
                                  timeout=100)

Beispiel #6

def _initialize_upon_import() -> TensorFlowServingModel:
    ''' Initialize / Restore Model Object.
    '''
    return TensorFlowServingModel(host='localhost',
                                  port=9000,
                                  model_name='mnist',
                                  inputs_name='inputs',
                                  outputs_name='outputs',
                                  timeout=100)