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Structure, sample, and savor hyperparameter searches

Project description

pyrameter

pyrameter is a library for designing hierarchical parameter searches with continuous and discrete domains, and then search those spaces.

  1. Installation
  2. Dependencies
  3. A Short Example

Installation

$ git clone https://github.com/jeffkinnison/pyrameter
$ cd pyrameter
$ pip install .

Dependencies

  • numpy
  • scipy
  • scikit-learn
  • pymongo
  • dill
  • six

A Short Example

import math
import pyrameter

# Minimize the sin function
def objective(params):
    return math.sin(params['x'])

# Uniformly sample values over [0, pi]
space = {
    'x': pyrameter.uniform(0, math.pi),

}

# Set up the search with an experiment key, the domains to search, and
# random search to generate values.
opt = pyrameter.FMin('sin_exp', space, 'random')

# Try 1000 values of x and store the result.
for i in range(1000):
    trial = opt.generate()
    trial.objective = objective(trial.hyperparameters)

# Print the x that minimized sin
print(opt.optimum)

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