gradient-sdk 0.0.1

Gradient ML SDK

Gradient ML SDK

This is SDK to work with Paperspace infrastructure.

Remember: For now this SDK is not prepared to work on machines outside of Paperspace infrastructure!

Requirements

This SDK works with Python 3.5+ version.

You can install it with:

pip install gradient-sdk

How to use it

1. Multinode

For now we only support TensorFlow.

get_tf_config()

This function will set TF_CONFIG when run on machines in Paperspace infrastructure. If there would be any problem with configuration of this environment variable in machines then will be raised ConfigError with message.

Example of usage:

from gradient_sdk import get_tf_config

get_tf_config()

Hyper Tune

For now we only support Hyperopt

hyper_tune

Function that run hyper tune. This function accept arguments:

• train_model User model to tune
• hparam_def User definition (scope) of search space. To set this value you can look at hyperopt documentation.
• algo Search algorithm. Default set to tpe.suggest from hyperopt
• max_ecals Allow up to this many function evaluations before returning. Default set to 25.
• func Function that will run hyper tune. Default set to fmin from hyperopt. Do not change it if you do not know what you are doing

This function return dict with information about tune process. It also can raise ConfigError exception where there is no connection to mongo db. You do not need to worry about setting your version of mongo db because it will be set in Paperspace infrastructure for hyper parameter tune.

Example of usage:

from gradient_sdk import hyper_tune

# Prepare model and search scope

# minimal version
argmin1 = hyper_tune(model, scope)

# pass more arguments
argmin2 = hyper_tune(model, scope, algo=tpe.suggest, max_evals=100)

Utility functions

get_mongo_conn_str

Function to check and construct mongo db connection string.

If there are some problems with values to prepare connection string to mongo db there is raised ConfigError with message.

It will return connection string to mongo db.

Example of usage:

from gradient_sdk import get_mongo_conn_str

conn_str = get_mongo_conn_str()

data_dir

Function to retrieve path to job space.

Example of usage:

from gradient_sdk import data_dir

job_space = data_dir()

model_dir

Function to retrieve path to model space.

Example of usage:

from gradient_sdk import model_dir

model_path = model_dir(model_name)

export_dir

Function to retrieve path for model export.

Example of usage:

from gradient_sdk import export_dir

model_path = export_dir(model_name)

worker_hosts

Function to retrieve information about worker hosts.

Example of usage:

from gradient_sdk import worker_hosts

model_path = worker_hosts()

ps_hosts

Function to retrieve information about paperspace hosts.

Example of usage:

from gradient_sdk import ps_hosts

model_path = ps_hosts()

task_index

Function to retrieve information about task index.

Example of usage:

from gradient_sdk import task_index

model_path = task_index()

job_name

Function to retrieve information about job name.

Example of usage:

from gradient_sdk import job_name

model_path = job_name()