def train_status(self, request: PluginRequest[TrainStatusPluginInput],
model: ThirdPartyModel) -> Response[TrainPluginOutput]:
"""Since trainable can't be assumed to be asynchronous, the trainer is responsible for uploading its own model file."""
logging.debug(f"train {request}")
# Create a Response object at the top with a Task attached. This will let us stream back updates
# TODO: This is very non-intuitive. We should improve this.
response = Response(status=Task(task_id=request.task_id))
# Call train status
train_plugin_output = model.train_status(request.data)
if train_plugin_output.training_complete:
# Save the model with the `default` handle.
archive_path_in_steamship = model.save_remote(
client=self.client,
plugin_instance_id=request.plugin_instance_id)
# Set the model location on the plugin output.
train_plugin_output.archive_path = archive_path_in_steamship
# Set the response on the `data` field of the object
response.set_data(json=train_plugin_output)
logging.info(response.dict(by_alias=True))
return response
def train(self, request: PluginRequest[TrainPluginInput],
model: ThirdPartyModel) -> Response[TrainPluginOutput]:
"""Since trainable can't be assumed to be asynchronous, the trainer is responsible for uploading its own model file."""
logging.debug(f"train {request}")
# Create a Response object at the top with a Task attached. This will let us stream back updates
# TODO: This is very non-intuitive. We should improve this.
response = Response(status=Task(task_id=request.task_id))
# Train the model
train_plugin_input = request.data
train_plugin_output = model.train(train_plugin_input)
# Set the response on the `data` field of the object
response.set_data(json=train_plugin_output)
logging.info(response.dict(by_alias=True))
return response
