arg_parse_tutorial

发表于

Python

argpase module

Convert a PyTorch model to Tensorflow using ONNX

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import argparse

# Training settings
parser = argparse.ArgumentParser(description='PyTorch MNIST Example')
parser.add_argument('--batch-size', type=int, default=64, metavar='N',
                    help='input batch size for training (default: 64)')
parser.add_argument('--test-batch-size', type=int, default=1000, metavar='N',
                    help='input batch size for testing (default: 1000)')
parser.add_argument('--epochs', type=int, default=10, metavar='N',
                    help='number of epochs to train (default: 10)')
parser.add_argument('--lr', type=float, default=0.01, metavar='LR',
                    help='learning rate (default: 0.01)')
parser.add_argument('--momentum', type=float, default=0.5, metavar='M',
                    help='SGD momentum (default: 0.5)')
parser.add_argument('--no-cuda', action='store_true', default=False,
                    help='disables CUDA training')
parser.add_argument('--seed', type=int, default=1, metavar='S',
                    help='random seed (default: 1)')
parser.add_argument('--log-interval', type=int, default=10, metavar='N',
                    help='how many batches to wait before logging training status')

# 这相当于在程序中人工指定一些args的取值
# Train this model with 60 epochs and after process every 300 batches log the train status
args = parser.parse_args(['--epochs', '60', '--log-interval', '300'])
...
train_loader = torch.utils.data.DataLoader(
    datasets.MNIST('../data', train=True, download=True,
                    transform=transforms.Compose([
                        transforms.ToTensor(),
                        transforms.Normalize((0.1307,), (0.3081,))
                    ])),
    batch_size=args.batch_size, shuffle=True, **kwargs)

gflags

basic_usage

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#!/usr/bin/env python
"""Example for basic usage of the flags library."""

from google.apputils import app
import gflags

FLAGS = gflags.FLAGS

# Flag names are globally defined!  So in general, we need to be
# careful to pick names that are unlikely to be used by other libraries.
# If there is a conflict, we'll get an error at import time.
gflags.DEFINE_string('name', 'Mr. President', 'your name')
gflags.DEFINE_integer('age', None, 'your age in years', lower_bound=0)
gflags.DEFINE_boolean('debug', False, 'produces debugging output')
gflags.DEFINE_enum('job', 'running', ['running', 'stopped'], 'job status')


def main(argv):
  if FLAGS.debug:
    print 'non-flag arguments:', argv
  print 'Happy Birthday', FLAGS.name
  if FLAGS.age is not None:
    print 'You are %d years old, and your job is %s' % (FLAGS.age, FLAGS.job)

if __name__ == '__main__':
  app.run()