Skip to main content

The official python cient of EasyTensor

Project description

EasyTensor

The official python client for EasyTensor.

Installation

Pretty straightforward.

pip install easytensor

Usage

Once you have a model exported to your local storage, you can upload it to easytensor in one line of code.

TensorFlow

Exporting and uploading a model

import easytensor
import os
export_path = os.path.join(os.getcwd(), "my_model")
print("export_path: {}".format(export_path))

# Export the model
tf.keras.models.save_model(
    model,
    export_path,
    overwrite=True,
    include_optimizer=True,
    save_format=None,
    signatures=None,
    options=None
)

# Upload it to easytensor.
model_id, access_token = easytensor.tensorflow.upload_model("My first model", export_path)
print("model ID:", model_id)
print("access token:", access_token)

Running prediction on the cloud

from pprint import pprint
import requests
response = requests.post(
    "https://app.easytensor.com/query/",
    json={
        "instances": [
            image_to_predict.numpy().tolist()
        ]
    },
    headers={"accessToken": access_token}
)
print("Response from server:")
pprint(response.json())

Examples

The library comes with a few example Jupyter notebooks that walk you through a few possible workflows. They are helpful if you are starting out with ML or remote model prediction.

Requirements

For Mac
brew install python@3.8
For Ubuntu
sudo apt install python3.8 python3.8-dev

To run the examples, create a python virtual env, and install jupyter notebook.

# install virtualenv
pip3 install virtualenv

# create a virtualenv with python3.8 in ~/virtualenv-3.8
virtualenv --python=$(which python3.8) ~/virtualenv-3.8

# activate the virtual env
source ~/virtualenv-3.8/bin/activate

# install jupyter notebook and necessary widgets
pip install notebook ipywidgets

# run jupyter notebook
jupyter notebook

Questions and Help

If you have any querstions about how EasyTensor works or want help with serving your ML model, please contact me directly at kamal@easytensor.com. I'm here to help!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

easytensor-0.0.6.tar.gz (9.9 kB view details)

Uploaded Source

Built Distribution

easytensor-0.0.6-py3-none-any.whl (13.0 kB view details)

Uploaded Python 3

File details

Details for the file easytensor-0.0.6.tar.gz.

File metadata

  • Download URL: easytensor-0.0.6.tar.gz
  • Upload date:
  • Size: 9.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.8.8

File hashes

Hashes for easytensor-0.0.6.tar.gz
Algorithm Hash digest
SHA256 e989e17b599c1721ad1de59ef26e995796d14c76eed2c9b2704502856b2bc5a9
MD5 f4612eb86fc62ac851c8aa09d88bcded
BLAKE2b-256 feed0a99426cd5560e001c87f4545646d1c53a5c45c5271f4c83a35cf19c6d99

See more details on using hashes here.

File details

Details for the file easytensor-0.0.6-py3-none-any.whl.

File metadata

  • Download URL: easytensor-0.0.6-py3-none-any.whl
  • Upload date:
  • Size: 13.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.8.8

File hashes

Hashes for easytensor-0.0.6-py3-none-any.whl
Algorithm Hash digest
SHA256 03f84d6883ac9b83a27673e72cb851b0a10e8926f86042daedccd371e6383cd5
MD5 be56b4611b0054d39d32b7124abd5c9a
BLAKE2b-256 6235231f878a0920fb33211b7cafde138aa7d1b943ad8740823237aca0527241

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page