def predict(
user_model: Any,
request: Union[prediction_pb2.SeldonMessage, List, Dict]) \
-> Union[prediction_pb2.SeldonMessage, List, Dict]:
"""
Call the user model to get a prediction and package the response
Parameters
----------
user_model
User defined class instance
request
The incoming request
Returns
-------
The prediction
"""
is_proto = isinstance(request, prediction_pb2.SeldonMessage)
if hasattr(user_model, "predict_rest") and not is_proto:
logger.warning("predict_rest is deprecated. Please use predict_raw")
return user_model.predict_rest(request)
elif hasattr(user_model, "predict_grpc") and is_proto:
logger.warning("predict_grpc is deprecated. Please use predict_raw")
return user_model.predict_grpc(request)
else:
if hasattr(user_model, "predict_raw"):
try:
return user_model.predict_raw(request)
except SeldonNotImplementedError:
pass
if is_proto:
(features, meta, datadef,
data_type) = extract_request_parts(request)
client_response = client_predict(user_model,
features,
datadef.names,
meta=meta)
return construct_response(user_model, False, request,
client_response)
else:
(features, meta, datadef,
data_type) = extract_request_parts_json(request)
class_names = datadef[
"names"] if datadef and "names" in datadef else []
client_response = client_predict(user_model,
features,
class_names,
meta=meta)
return construct_response_json(user_model, False, request,
client_response)
def predict(
user_model: Any,
request: Union[prediction_pb2.SeldonMessage, List, Dict, bytes],
seldon_metrics: SeldonMetrics,
) -> Union[prediction_pb2.SeldonMessage, List, Dict, bytes]:
"""
Call the user model to get a prediction and package the response
Parameters
----------
user_model
User defined class instance
request
The incoming request
Returns
-------
The prediction
"""
# TODO: Find a way to choose predict_rest or predict_grpc when payload is
# not decoded
is_proto = isinstance(request, prediction_pb2.SeldonMessage)
if hasattr(user_model, "predict_rest") and not is_proto:
logger.warning("predict_rest is deprecated. Please use predict_raw")
return user_model.predict_rest(request)
elif hasattr(user_model, "predict_grpc") and is_proto:
logger.warning("predict_grpc is deprecated. Please use predict_raw")
return user_model.predict_grpc(request)
else:
if hasattr(user_model, "predict_raw"):
try:
response = user_model.predict_raw(request)
handle_raw_custom_metrics(response, seldon_metrics, is_proto,
PREDICT_METRIC_METHOD_TAG)
return response
except SeldonNotImplementedError:
pass
if is_proto:
(features, meta, datadef,
data_type) = extract_request_parts(request)
client_response = client_predict(user_model,
features,
datadef.names,
meta=meta)
metrics = client_custom_metrics(
user_model,
seldon_metrics,
PREDICT_METRIC_METHOD_TAG,
client_response.metrics,
)
return construct_response(
user_model,
False,
request,
client_response.data,
meta,
metrics,
client_response.tags,
)
else:
(features, meta, datadef,
data_type) = extract_request_parts_json(request)
class_names = datadef[
"names"] if datadef and "names" in datadef else []
client_response = client_predict(user_model,
features,
class_names,
meta=meta)
metrics = client_custom_metrics(
user_model,
seldon_metrics,
PREDICT_METRIC_METHOD_TAG,
client_response.metrics,
)
return construct_response_json(
user_model,
False,
request,
client_response.data,
meta,
metrics,
client_response.tags,
)
