EdgeClient.inferences.run

EdgeClient.inferences.run(model_identifier: str, model_version: str, input_sources: List[InputSource], explain=False, tags=None)

This method provides a synchronous way to run an inference. This is simply a convenience function that is equivalent to the perform_inference and block_until_complete methods run sequentially.

Parameters

Parameter	Type	Description	Example
`model_identifier`	`str`	The model identifier.	`'ed542963de'`
`model_version`	`str`	The model version string in semantic version format.	`'1.0.1'`
`input_sources`	`List[InputSource]`	A list of input sources of type `InputSource`	`[InputSource(key="input.txt", text="Today is a great day.")]`
`explain`	`bool`	If the model supports explainability, flag this job to return an explanation of the predictions	`True`
`tags`	`Mapping[str, str]`	An arbitrary set of key/value tags to associate with this inference.

Returns

A Inference object returned from Inference API

Examples

from modzy import EdgeClient
from modzy.edge import InputSource

image_bytes = open("image_path.jpg", "rb").read()
input_object = InputSource(
    key="image", # input filename defined by model author
    data=image_bytes,
) 

client =  EdgeClient('localhost', 55000)
client.connect()
inference = client.inferences.run("<model-id>", "<model-version>", input_object, explain=False, tags=None)
results = inference.result.outputs
client.close()