def configure_global_options(config_parser: configargparse.ArgParser) -> None:
config_parser.add_argument(
"-d",
"--debug",
required=False,
default=False,
action="store_true",
help="Enable debug messages.",
)
config_parser.add_argument("--version",
action="version",
version=f"{app_name} {get_version()}")
config_parser.add_argument(
"-b",
"--build-engine",
required=False,
default="helm3",
type=BuildEngineType,
help="Select the build engine used for building your chart.",
)
steps_group = config_parser.add_mutually_exclusive_group()
steps_group.add_argument(
"--steps",
nargs="+",
help=f"List of steps to execute. Available steps: {ALL_STEPS}",
required=False,
default=["all"],
)
steps_group.add_argument(
"--skip-steps",
nargs="+",
help=f"List of steps to skip. Available steps: {ALL_STEPS}",
required=False,
default=[],
)
def add_param_arguments(ap=None, arg_default=None): # arguments with possible format-specific parameter values
def add_argument(a, *args, **kwargs):
return a.add_argument(*args, **kwargs)
def add(a, *args, default=None, func=add_argument, **kwargs):
arg = func(a, *args, default=default if arg_default is None else arg_default, **kwargs)
try:
RESTORED_ARGS.add(arg.dest)
except AttributeError:
RESTORED_ARGS.update(get_group_arg_names(arg))
def add_boolean(a, *args, **kwargs):
add(a, *args, func=add_boolean_option, **kwargs)
if not ap:
ap = ArgParser()
group = ap.add_argument_group(title="Node labels")
add(group, "--max-node-labels", type=int, default=0, help="max number of node labels to allow")
add(group, "--max-node-categories", type=int, default=0, help="max node categories to allow")
add(group, "--min-node-label-count", type=int, default=2, help="min number of occurrences for a label")
add_boolean(group, "use-gold-node-labels", "gold node labels when parsing")
add_boolean(group, "wikification", "use Spotlight to wikify any named node")
add_boolean(group, "node-labels", "prediction of node labels, if supported by format", default=True)
group = ap.add_argument_group(title="Structural constraints")
add_boolean(group, "linkage", "linkage nodes and edges")
add_boolean(group, "implicit", "implicit nodes and edges")
add_boolean(group, "remote", "remote edges", default=True)
add_boolean(group, "constraints", "scheme-specific rules", default=True)
add_boolean(group, "require-connected", "constraint that output graph must be connected")
add(group, "--orphan-label", default="orphan", help="edge label to use for nodes without parents")
add(group, "--max-action-ratio", type=float, default=100, help="max action/terminal ratio")
add(group, "--max-node-ratio", type=float, default=10, help="max node/terminal ratio")
add(group, "--max-height", type=int, default=20, help="max graph height")
group = ap.add_mutually_exclusive_group()
add(group, "--swap", choices=(REGULAR, COMPOUND), default=REGULAR, help="swap transitions")
add(group, "--no-swap", action="store_false", dest="swap", help="exclude swap transitions")
add(ap, "--max-swap", type=int, default=15, help="if compound swap enabled, maximum swap size")
group = ap.add_argument_group(title="General classifier training parameters")
add(group, "--learning-rate", type=float, help="rate for model weight updates (default: by trainer/1)")
add(group, "--learning-rate-decay", type=float, default=0, help="learning rate decay per iteration")
add(group, "--swap-importance", type=float, default=1, help="learning rate factor for Swap")
add(group, "--max-training-per-format", type=int, help="max number of training passages per format per iteration")
add_boolean(group, "missing-node-features", "allow node features to be missing if not available", default=True)
add(group, "--omit-features", help="string of feature properties to omit, out of " + FEATURE_PROPERTIES)
add_boolean(group, "curriculum", "sort training passages by action prediction accuracy in previous epoch")
group = ap.add_argument_group(title="Perceptron parameters")
add(group, "--min-update", type=int, default=5, help="minimum #updates for using a feature")
SPARSE_ARG_NAMES.update(get_group_arg_names(group))
group = ap.add_argument_group(title="Neural network parameters")
add(group, "--word-dim-external", type=int, default=300, help="dimension for external word embeddings")
add(group, "--word-vectors", help="file to load external word embeddings from (default: GloVe)")
add(group, "--vocab", help="file mapping integer ID to word form (to avoid loading spaCy), or '-' to use word form")
add_boolean(group, "update-word-vectors", "external word vectors in training parameters", default=True)
add(group, "--word-dim", type=int, default=0, help="dimension for learned word embeddings")
add(group, "--lemma-dim", type=int, default=200, help="dimension for lemma embeddings")
add(group, "--tag-dim", type=int, default=20, help="dimension for fine POS tag embeddings")
add(group, "--pos-dim", type=int, default=20, help="dimension for coarse/universal POS tag embeddings")
add(group, "--dep-dim", type=int, default=10, help="dimension for dependency relation embeddings")
add(group, "--edge-label-dim", type=int, default=20, help="dimension for edge label embeddings")
add(group, "--node-label-dim", type=int, default=0, help="dimension for node label embeddings")
add(group, "--node-category-dim", type=int, default=0, help="dimension for node category embeddings")
add(group, "--punct-dim", type=int, default=1, help="dimension for separator punctuation embeddings")
add(group, "--action-dim", type=int, default=3, help="dimension for input action type embeddings")
add(group, "--ner-dim", type=int, default=3, help="dimension for input entity type embeddings")
add(group, "--shape-dim", type=int, default=3, help="dimension for word shape embeddings")
add(group, "--prefix-dim", type=int, default=2, help="dimension for word prefix embeddings")
add(group, "--suffix-dim", type=int, default=3, help="dimension for word suffix embeddings")
add(group, "--output-dim", type=int, default=50, help="dimension for output action embeddings")
add(group, "--layer-dim", type=int, default=50, help="dimension for hidden layers")
add(group, "--layers", type=int, default=2, help="number of hidden layers")
add(group, "--lstm-layer-dim", type=int, default=500, help="dimension for LSTM hidden layers")
add(group, "--lstm-layers", type=int, default=0, help="number of LSTM hidden layers")
add(group, "--embedding-layer-dim", type=int, default=500, help="dimension for layers before LSTM")
add(group, "--embedding-layers", type=int, default=1, help="number of layers before LSTM")
add(group, "--activation", choices=ACTIVATIONS, default=DEFAULT_ACTIVATION, help="activation function")
add(group, "--init", choices=INITIALIZERS, default=DEFAULT_INITIALIZER, help="weight initialization")
add(group, "--minibatch-size", type=int, default=200, help="mini-batch size for optimization")
add(group, "--optimizer", choices=TRAINERS, default=DEFAULT_TRAINER, help="algorithm for optimization")
add(group, "--loss", choices=LOSSES, default=DEFAULT_LOSS, help="loss function for training")
add(group, "--max-words-external", type=int, default=250000, help="max external word vectors to use")
add(group, "--max-words", type=int, default=10000, help="max number of words to keep embeddings for")
add(group, "--max-lemmas", type=int, default=3000, help="max number of lemmas to keep embeddings for")
add(group, "--max-tags", type=int, default=100, help="max number of fine POS tags to keep embeddings for")
add(group, "--max-pos", type=int, default=100, help="max number of coarse POS tags to keep embeddings for")
add(group, "--max-deps", type=int, default=100, help="max number of dep labels to keep embeddings for")
add(group, "--max-edge-labels", type=int, default=15, help="max number of edge labels for embeddings")
add(group, "--max-puncts", type=int, default=5, help="max number of punctuations for embeddings")
add(group, "--max-action-types", type=int, default=10, help="max number of action types for embeddings")
add(group, "--max-action-labels", type=int, default=100, help="max number of action labels to allow")
add(group, "--max-ner-types", type=int, default=18, help="max number of entity types to allow")
add(group, "--max-shapes", type=int, default=30, help="max number of word shapes to allow")
add(group, "--max-prefixes", type=int, default=30, help="max number of 1-character word prefixes to allow")
add(group, "--max-suffixes", type=int, default=500, help="max number of 3-character word suffixes to allow")
add(group, "--word-dropout", type=float, default=0.2, help="word dropout parameter")
add(group, "--word-dropout-external", type=float, default=0, help="word dropout for word vectors")
add(group, "--lemma-dropout", type=float, default=0.2, help="lemma dropout parameter")
add(group, "--tag-dropout", type=float, default=0.2, help="fine POS tag dropout parameter")
add(group, "--pos-dropout", type=float, default=0.2, help="coarse POS tag dropout parameter")
add(group, "--dep-dropout", type=float, default=0.5, help="dependency label dropout parameter")
add(group, "--node-label-dropout", type=float, default=0.2, help="node label dropout parameter")
add(group, "--node-dropout", type=float, default=0.1, help="probability to drop features for a whole node")
add(group, "--dropout", type=float, default=0.4, help="dropout parameter between layers")
add(group, "--max-length", type=int, default=120, help="maximum length of input sentence")
add(group, "--rnn", choices=["None"] + list(RNNS), default=DEFAULT_RNN, help="type of recurrent neural network")
add(group, "--gated", type=int, nargs="?", default=2, help="gated input to BiRNN and MLP")
NN_ARG_NAMES.update(get_group_arg_names(group))
return ap
def add_param_arguments(
ap=None,
arg_default=None
): # arguments with possible format-specific parameter values
def add_argument(a, *args, **kwargs):
return a.add_argument(*args, **kwargs)
def add(a, *args, default=None, func=add_argument, **kwargs):
arg = func(a,
*args,
default=default if arg_default is None else arg_default,
**kwargs)
try:
RESTORED_ARGS.add(arg.dest)
except AttributeError:
RESTORED_ARGS.update(get_group_arg_names(arg))
def add_boolean(a, *args, **kwargs):
add(a, *args, func=add_boolean_option, **kwargs)
if not ap:
ap = ArgParser()
group = ap.add_argument_group(title="Node labels")
add(group,
"--max-node-labels",
type=int,
default=0,
help="max number of node labels to allow")
add(group,
"--max-node-categories",
type=int,
default=0,
help="max node categories to allow")
add(group,
"--min-node-label-count",
type=int,
default=2,
help="min number of occurrences for a label")
add_boolean(group, "use-gold-node-labels", "gold node labels when parsing")
add_boolean(group, "wikification",
"use Spotlight to wikify any named node")
add_boolean(group,
"node-labels",
"prediction of node labels, if supported by format",
default=True)
group = ap.add_argument_group(title="Structural constraints")
add_boolean(group, "linkage", "linkage nodes and edges")
add_boolean(group, "implicit", "implicit nodes and edges")
add_boolean(group, "remote", "remote edges", default=True)
add_boolean(group, "constraints", "scheme-specific rules", default=True)
add_boolean(group, "require-connected",
"constraint that output graph must be connected")
add(group,
"--orphan-label",
default="orphan",
help="edge label to use for nodes without parents")
add(group,
"--max-action-ratio",
type=float,
default=100,
help="max action/terminal ratio")
add(group,
"--max-node-ratio",
type=float,
default=10,
help="max node/terminal ratio")
add(group, "--max-height", type=int, default=20, help="max graph height")
group = ap.add_mutually_exclusive_group()
add(group,
"--swap",
choices=(REGULAR, COMPOUND),
default=REGULAR,
help="swap transitions")
add(group,
"--no-swap",
action="store_false",
dest="swap",
help="exclude swap transitions")
add(ap,
"--max-swap",
type=int,
default=15,
help="if compound swap enabled, maximum swap size")
group = ap.add_argument_group(
title="General classifier training parameters")
add(group,
"--learning-rate",
type=float,
help="rate for model weight updates (default: by trainer/1)")
add(group,
"--learning-rate-decay",
type=float,
default=0,
help="learning rate decay per iteration")
add(group,
"--swap-importance",
type=float,
default=1,
help="learning rate factor for Swap")
add(group,
"--max-training-per-format",
type=int,
help="max number of training passages per format per iteration")
add_boolean(group,
"missing-node-features",
"allow node features to be missing if not available",
default=True)
add(group,
"--omit-features",
help="string of feature properties to omit, out of " +
FEATURE_PROPERTIES)
add_boolean(
group, "curriculum",
"sort training passages by action prediction accuracy in previous epoch"
)
group = ap.add_argument_group(title="Perceptron parameters")
add(group,
"--min-update",
type=int,
default=5,
help="minimum #updates for using a feature")
SPARSE_ARG_NAMES.update(get_group_arg_names(group))
group = ap.add_argument_group(title="Neural network parameters")
add(group,
"--word-dim-external",
type=int,
default=300,
help="dimension for external word embeddings")
add(group,
"--word-vectors",
help="file to load external word embeddings from (default: GloVe)")
add(group,
"--vocab",
help=
"file mapping integer ID to word form (to avoid loading spaCy), or '-' to use word form"
)
add_boolean(group,
"update-word-vectors",
"external word vectors in training parameters",
default=True)
add(group,
"--word-dim",
type=int,
default=0,
help="dimension for learned word embeddings")
add(group,
"--lemma-dim",
type=int,
default=200,
help="dimension for lemma embeddings")
add(group,
"--tag-dim",
type=int,
default=20,
help="dimension for fine POS tag embeddings")
add(group,
"--pos-dim",
type=int,
default=20,
help="dimension for coarse/universal POS tag embeddings")
add(group,
"--dep-dim",
type=int,
default=10,
help="dimension for dependency relation embeddings")
add(group,
"--edge-label-dim",
type=int,
default=20,
help="dimension for edge label embeddings")
add(group,
"--node-label-dim",
type=int,
default=0,
help="dimension for node label embeddings")
add(group,
"--node-category-dim",
type=int,
default=0,
help="dimension for node category embeddings")
add(group,
"--punct-dim",
type=int,
default=1,
help="dimension for separator punctuation embeddings")
add(group,
"--action-dim",
type=int,
default=3,
help="dimension for input action type embeddings")
add(group,
"--ner-dim",
type=int,
default=3,
help="dimension for input entity type embeddings")
add(group,
"--shape-dim",
type=int,
default=3,
help="dimension for word shape embeddings")
add(group,
"--prefix-dim",
type=int,
default=2,
help="dimension for word prefix embeddings")
add(group,
"--suffix-dim",
type=int,
default=3,
help="dimension for word suffix embeddings")
add(group,
"--output-dim",
type=int,
default=50,
help="dimension for output action embeddings")
add(group,
"--layer-dim",
type=int,
default=50,
help="dimension for hidden layers")
add(group, "--layers", type=int, default=2, help="number of hidden layers")
add(group,
"--lstm-layer-dim",
type=int,
default=500,
help="dimension for LSTM hidden layers")
add(group,
"--lstm-layers",
type=int,
default=0,
help="number of LSTM hidden layers")
add(group,
"--embedding-layer-dim",
type=int,
default=500,
help="dimension for layers before LSTM")
add(group,
"--embedding-layers",
type=int,
default=1,
help="number of layers before LSTM")
add(group,
"--activation",
choices=ACTIVATIONS,
default=DEFAULT_ACTIVATION,
help="activation function")
add(group,
"--init",
choices=INITIALIZERS,
default=DEFAULT_INITIALIZER,
help="weight initialization")
add(group,
"--minibatch-size",
type=int,
default=200,
help="mini-batch size for optimization")
add(group,
"--optimizer",
choices=TRAINERS,
default=DEFAULT_TRAINER,
help="algorithm for optimization")
add(group,
"--loss",
choices=LOSSES,
default=DEFAULT_LOSS,
help="loss function for training")
add(group,
"--max-words-external",
type=int,
default=250000,
help="max external word vectors to use")
add(group,
"--max-words",
type=int,
default=10000,
help="max number of words to keep embeddings for")
add(group,
"--max-lemmas",
type=int,
default=3000,
help="max number of lemmas to keep embeddings for")
add(group,
"--max-tags",
type=int,
default=100,
help="max number of fine POS tags to keep embeddings for")
add(group,
"--max-pos",
type=int,
default=100,
help="max number of coarse POS tags to keep embeddings for")
add(group,
"--max-deps",
type=int,
default=100,
help="max number of dep labels to keep embeddings for")
add(group,
"--max-edge-labels",
type=int,
default=15,
help="max number of edge labels for embeddings")
add(group,
"--max-puncts",
type=int,
default=5,
help="max number of punctuations for embeddings")
add(group,
"--max-action-types",
type=int,
default=10,
help="max number of action types for embeddings")
add(group,
"--max-action-labels",
type=int,
default=100,
help="max number of action labels to allow")
add(group,
"--max-ner-types",
type=int,
default=18,
help="max number of entity types to allow")
add(group,
"--max-shapes",
type=int,
default=30,
help="max number of word shapes to allow")
add(group,
"--max-prefixes",
type=int,
default=30,
help="max number of 1-character word prefixes to allow")
add(group,
"--max-suffixes",
type=int,
default=500,
help="max number of 3-character word suffixes to allow")
add(group,
"--word-dropout",
type=float,
default=0.2,
help="word dropout parameter")
add(group,
"--word-dropout-external",
type=float,
default=0,
help="word dropout for word vectors")
add(group,
"--lemma-dropout",
type=float,
default=0.2,
help="lemma dropout parameter")
add(group,
"--tag-dropout",
type=float,
default=0.2,
help="fine POS tag dropout parameter")
add(group,
"--pos-dropout",
type=float,
default=0.2,
help="coarse POS tag dropout parameter")
add(group,
"--dep-dropout",
type=float,
default=0.5,
help="dependency label dropout parameter")
add(group,
"--node-label-dropout",
type=float,
default=0.2,
help="node label dropout parameter")
add(group,
"--node-dropout",
type=float,
default=0.1,
help="probability to drop features for a whole node")
add(group,
"--dropout",
type=float,
default=0.4,
help="dropout parameter between layers")
add(group,
"--max-length",
type=int,
default=120,
help="maximum length of input sentence")
add(group,
"--rnn",
choices=["None"] + list(RNNS),
default=DEFAULT_RNN,
help="type of recurrent neural network")
add(group,
"--gated",
type=int,
nargs="?",
default=2,
help="gated input to BiRNN and MLP")
NN_ARG_NAMES.update(get_group_arg_names(group))
return ap
def _create_parser():
parser = ArgParser(prog='releaser',
default_config_files=['.releaser'],
auto_env_var_prefix='releaser_')
parser.add_argument('--config', is_config_file=True)
parser.add_argument('--repository',
dest='repo',
type=Repo,
default=Repo(Path.cwd()))
parser.add_argument('--preprod-url', dest='preprod_url', default=None)
parser.add_argument('--release-branch', default='master')
parser.add_argument('--app-name')
parser.add_argument('--release-date', default='today')
parser.add_argument('--issue-tracker-url')
next_version_group = parser.add_mutually_exclusive_group()
next_version_group.add_argument('--build',
action='store_const',
const='BUILD',
env_var='RELEASER_NEXT_VERSION',
dest='next_version')
next_version_group.add_argument('--patch',
action='store_const',
const='PATCH',
env_var='RELEASER_NEXT_VERSION',
dest='next_version')
next_version_group.add_argument('--minor',
action='store_const',
const='MINOR',
env_var='RELEASER_NEXT_VERSION',
dest='next_version')
next_version_group.add_argument('--major',
action='store_const',
const='MAJOR',
env_var='RELEASER_NEXT_VERSION',
dest='next_version')
next_version_group.set_defaults(next_version='MINOR')
subparsers = parser.add_subparsers(dest='command')
versions_subparser = subparsers.add_parser('versions')
subparsers.add_parser('changes')
subparsers.add_parser('draft')
subparsers.add_parser('tag')
parser.add_argument('--template-mail',
type=Path,
dest='template_mail_path',
default=ROOT / 'releaser/templates/mail.md.j2')
parser.add_argument('--template-tag',
type=Path,
dest='template_tag_path',
default=ROOT / 'releaser/templates/tag.md.j2')
parser.add_argument('--template-changes',
type=Path,
dest='template_changes_path',
default=ROOT / 'releaser/templates/changes.md.j2')
parser.add_argument('--start', default='today @ 21:45')
parser.add_argument('--end', default='today @ 22:15')
parser.set_defaults(command='changes')
versions_subparser.add_argument('n',
nargs='?',
type=int,
default=999999999)
return parser
