def test_prepare_get_metadata_output():
inputs = {'tensor_input': Layer('FP32', (1, 1, 1), 'NCHW')}
outputs = {'tensor_output': Layer('FP32', (1, 1, 1), 'NCHW')}
model_keys = {'inputs': {'name': 'tensor_input'},
'outputs': {'output_name': 'tensor_output'}}
output = prepare_get_metadata_output(
inputs=inputs, outputs=outputs, model_keys=model_keys)
assert "tensorflow/serving/predict" == output.method_name
def test_prepare_get_metadata_output():
inputs = {'tensor': (1, 1, 1)}
outputs = ['tensor_output']
model_keys = {
'inputs': {
'name': 'tensor'
},
'outputs': {
'output_name': 'tensor_output'
}
}
output = prepare_get_metadata_output(inputs=inputs,
outputs=outputs,
model_keys=model_keys)
assert "tensorflow/serving/predict" == output.method_name
def GetModelMetadata(self, request, context):
# check if model with was requested
# is available on server with proper version
logger.debug("MODEL_METADATA, get request: {}".format(request))
model_name = request.model_spec.name
requested_version = request.model_spec.version.value
valid_model_spec, version = check_availability_of_requested_model(
models=self.models,
requested_version=requested_version,
model_name=model_name)
if not valid_model_spec:
context.set_code(StatusCode.NOT_FOUND)
context.set_details(
WRONG_MODEL_SPEC.format(model_name, requested_version))
logger.debug("MODEL_METADATA, invalid model spec from request")
return get_model_metadata_pb2.GetModelMetadataResponse()
target_engine = self.models[model_name].engines[version]
target_engine.in_use.acquire()
metadata_signature_requested = request.metadata_field[0]
if 'signature_def' != metadata_signature_requested:
context.set_code(StatusCode.INVALID_ARGUMENT)
context.set_details(
INVALID_METADATA_FIELD.format(metadata_signature_requested))
logger.debug("MODEL_METADATA, invalid signature def")
target_engine.in_use.release()
return get_model_metadata_pb2.GetModelMetadataResponse()
inputs = target_engine.net.inputs
outputs = target_engine.net.outputs
signature_def = prepare_get_metadata_output(
inputs=inputs,
outputs=outputs,
model_keys=target_engine.model_keys)
response = get_model_metadata_pb2.GetModelMetadataResponse()
model_data_map = get_model_metadata_pb2.SignatureDefMap()
model_data_map.signature_def['serving_default'].CopyFrom(signature_def)
response.metadata['signature_def'].Pack(model_data_map)
response.model_spec.name = model_name
response.model_spec.version.value = version
logger.debug("MODEL_METADATA created a response for {} - {}".format(
model_name, version))
target_engine.in_use.release()
return response
def on_get(self, req, resp, model_name, requested_version=0):
logger.debug("MODEL_METADATA, get request: {}, {}".format(
model_name, requested_version))
valid_model_spec, version = check_availability_of_requested_model(
models=self.models,
requested_version=requested_version,
model_name=model_name)
if not valid_model_spec:
resp.status = falcon.HTTP_NOT_FOUND
logger.debug("MODEL_METADATA, invalid model spec from request")
err_out_json = {
'error': WRONG_MODEL_SPEC.format(model_name, requested_version)
}
resp.body = json.dumps(err_out_json)
return
target_engine = self.models[model_name].engines[version]
target_engine.in_use.acquire()
inputs = target_engine.net.inputs
outputs = target_engine.net.outputs
signature_def = prepare_get_metadata_output(
inputs=inputs,
outputs=outputs,
model_keys=target_engine.model_keys)
response = get_model_metadata_pb2.GetModelMetadataResponse()
model_data_map = get_model_metadata_pb2.SignatureDefMap()
model_data_map.signature_def['serving_default'].CopyFrom(signature_def)
response.metadata['signature_def'].Pack(model_data_map)
response.model_spec.name = model_name
response.model_spec.version.value = version
logger.debug("MODEL_METADATA created a response for {} - {}".format(
model_name, version))
target_engine.in_use.release()
resp.status = falcon.HTTP_200
resp.body = MessageToJson(response)
