deepmux-python

deepmux is a PaaS solution to effortlessly deploy trained machine learning models on the cloud and generate predictions without setting up any hardware.

At the moment only pytorch models are supported.

Installation

pip install deepmux==0.2.4

Quickstart

Creating model

Initialize a model and upload it to deepmux servers

from deepmux import create_model

model = create_model(<YOUR PYTORCH MODEL>, <MODEL_NAME>, <SHAPE OF INPUT DATA>, <SHAPE OF OUTPUT DATA>, <TOKEN>)

Getting model by name

On your production server you can simply get model by it's name.

from deepmux import get_model

model = get_model(<MODEL NAME>, <TOKEN>)

Executing model on your import

After initializing your model with create_model or get_model you can run the model. All computations will be performed on deepmux infrastucture.

output = model.run(<YOUR INPUT>)

Complete example on a model from PyTorch Hub

import numpy as np
import torch

from deepmux import create_model

token = "<YOUR_TOKEN>"

pytorch_model = torch.hub.load('pytorch/vision:v0.5.0', 'squeezenet1_0', pretrained=True)

deepmux_model = create_model(
    pytorch_model,
    model_name='my_model',
    input_shape=[1, 3, 227, 227],
    output_shape=[1, 1000],
    token=token)

dummy_input = np.zeros([1, 3, 227, 227], dtype=np.float32)

output = deepmux_model.run(dummy_input)

Getting token

Currently, deepmux is in closed testing. You can get your own token by contacting tna0y or alexsaplin.

yarosl4v/deepmux-python