flags {tfruns} | R Documentation |
Flags for a training run
Description
Define the flags (name, type, default value, description) which paramaterize a training run. Optionally read overrides of the default values from a "flags.yml" config file and/or command line arguments.
Usage
flags(
...,
config = Sys.getenv("R_CONFIG_ACTIVE", unset = "default"),
file = "flags.yml",
arguments = commandArgs(TRUE)
)
flag_numeric(name, default, description = NULL)
flag_integer(name, default, description = NULL)
flag_boolean(name, default, description = NULL)
flag_string(name, default, description = NULL)
Arguments
... |
One or more flag definitions |
config |
The configuration to use. Defaults to the active configuration
for the current environment (as specified by the |
file |
The flags YAML file to read |
arguments |
The command line arguments (as a character vector) to be parsed. |
name |
Flag name |
default |
Flag default value |
description |
Flag description |
Value
Named list of training flags
Config File Flags
Config file flags are defined a YAML configuration file (by default named "flags.yml"). Flags can either appear at the top-level of the YAML or can be inclued in named configuration sections (see the config package for details).
Command Line Flags
Command line flags should be of the form --key=value
or
--key value
. The values are assumed to be valid yaml
and
will be converted using yaml.load()
.
Examples
## Not run:
library(tfruns)
# define flags and parse flag values from flags.yml and the command line
FLAGS <- flags(
flag_numeric('learning_rate', 0.01, 'Initial learning rate.'),
flag_integer('max_steps', 5000, 'Number of steps to run trainer.'),
flag_string('data_dir', 'MNIST-data', 'Directory for training data'),
flag_boolean('fake_data', FALSE, 'If true, use fake data for testing')
)
## End(Not run)