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Remove a component from the pipeline. name (unicode): Name of the component to remove. RETURNS (tuple): A `(name, component)` tuple of the removed component. DOCS: https://spacy.io/api/language#remove_pipe
def remove_pipe(self, name): """Remove a component from the pipeline. name (unicode): Name of the component to remove. RETURNS (tuple): A `(name, component)` tuple of the removed component. DOCS: https://spacy.io/api/language#remove_pipe """ if name not in self.pipe_nam...
Update the models in the pipeline. docs (iterable): A batch of `Doc` objects. golds (iterable): A batch of `GoldParse` objects. drop (float): The droput rate. sgd (callable): An optimizer. RETURNS (dict): Results from the update. DOCS: https://spacy.io/api/language#upda...
def update(self, docs, golds, drop=0.0, sgd=None, losses=None, component_cfg=None): """Update the models in the pipeline. docs (iterable): A batch of `Doc` objects. golds (iterable): A batch of `GoldParse` objects. drop (float): The droput rate. sgd (callable): An optimizer. ...
Make a "rehearsal" update to the models in the pipeline, to prevent forgetting. Rehearsal updates run an initial copy of the model over some data, and update the model so its current predictions are more like the initial ones. This is useful for keeping a pre-trained model on-track, even...
def rehearse(self, docs, sgd=None, losses=None, config=None): """Make a "rehearsal" update to the models in the pipeline, to prevent forgetting. Rehearsal updates run an initial copy of the model over some data, and update the model so its current predictions are more like the initial on...
Can be called before training to pre-process gold data. By default, it handles nonprojectivity and adds missing tags to the tag map. docs_golds (iterable): Tuples of `Doc` and `GoldParse` objects. YIELDS (tuple): Tuples of preprocessed `Doc` and `GoldParse` objects.
def preprocess_gold(self, docs_golds): """Can be called before training to pre-process gold data. By default, it handles nonprojectivity and adds missing tags to the tag map. docs_golds (iterable): Tuples of `Doc` and `GoldParse` objects. YIELDS (tuple): Tuples of preprocessed `Doc` and...
Allocate models, pre-process training data and acquire a trainer and optimizer. Used as a contextmanager. get_gold_tuples (function): Function returning gold data component_cfg (dict): Config parameters for specific components. **cfg: Config parameters. RETURNS: An optimizer. ...
def begin_training(self, get_gold_tuples=None, sgd=None, component_cfg=None, **cfg): """Allocate models, pre-process training data and acquire a trainer and optimizer. Used as a contextmanager. get_gold_tuples (function): Function returning gold data component_cfg (dict): Config paramet...
Continue training a pre-trained model. Create and return an optimizer, and initialize "rehearsal" for any pipeline component that has a .rehearse() method. Rehearsal is used to prevent models from "forgetting" their initialised "knowledge". To perform rehearsal, collect samples of text ...
def resume_training(self, sgd=None, **cfg): """Continue training a pre-trained model. Create and return an optimizer, and initialize "rehearsal" for any pipeline component that has a .rehearse() method. Rehearsal is used to prevent models from "forgetting" their initialised "knowledge"....
Replace weights of models in the pipeline with those provided in the params dictionary. Can be used as a contextmanager, in which case, models go back to their original weights after the block. params (dict): A dictionary of parameters keyed by model ID. **cfg: Config parameters. ...
def use_params(self, params, **cfg): """Replace weights of models in the pipeline with those provided in the params dictionary. Can be used as a contextmanager, in which case, models go back to their original weights after the block. params (dict): A dictionary of parameters keyed by mo...
Process texts as a stream, and yield `Doc` objects in order. texts (iterator): A sequence of texts to process. as_tuples (bool): If set to True, inputs should be a sequence of (text, context) tuples. Output will then be a sequence of (doc, context) tuples. Defaults to False. ...
def pipe( self, texts, as_tuples=False, n_threads=-1, batch_size=1000, disable=[], cleanup=False, component_cfg=None, ): """Process texts as a stream, and yield `Doc` objects in order. texts (iterator): A sequence of texts to process. ...
Save the current state to a directory. If a model is loaded, this will include the model. path (unicode or Path): Path to a directory, which will be created if it doesn't exist. exclude (list): Names of components or serialization fields to exclude. DOCS: https://spacy.io/...
def to_disk(self, path, exclude=tuple(), disable=None): """Save the current state to a directory. If a model is loaded, this will include the model. path (unicode or Path): Path to a directory, which will be created if it doesn't exist. exclude (list): Names of components o...
Loads state from a directory. Modifies the object in place and returns it. If the saved `Language` object contains a model, the model will be loaded. path (unicode or Path): A path to a directory. exclude (list): Names of components or serialization fields to exclude. RETURNS (L...
def from_disk(self, path, exclude=tuple(), disable=None): """Loads state from a directory. Modifies the object in place and returns it. If the saved `Language` object contains a model, the model will be loaded. path (unicode or Path): A path to a directory. exclude (list): Names...
Serialize the current state to a binary string. exclude (list): Names of components or serialization fields to exclude. RETURNS (bytes): The serialized form of the `Language` object. DOCS: https://spacy.io/api/language#to_bytes
def to_bytes(self, exclude=tuple(), disable=None, **kwargs): """Serialize the current state to a binary string. exclude (list): Names of components or serialization fields to exclude. RETURNS (bytes): The serialized form of the `Language` object. DOCS: https://spacy.io/api/language#to_...
Load state from a binary string. bytes_data (bytes): The data to load from. exclude (list): Names of components or serialization fields to exclude. RETURNS (Language): The `Language` object. DOCS: https://spacy.io/api/language#from_bytes
def from_bytes(self, bytes_data, exclude=tuple(), disable=None, **kwargs): """Load state from a binary string. bytes_data (bytes): The data to load from. exclude (list): Names of components or serialization fields to exclude. RETURNS (Language): The `Language` object. DOCS: htt...
Restore the pipeline to its state when DisabledPipes was created.
def restore(self): """Restore the pipeline to its state when DisabledPipes was created.""" current, self.nlp.pipeline = self.nlp.pipeline, self.original_pipeline unexpected = [name for name, pipe in current if not self.nlp.has_pipe(name)] if unexpected: # Don't change the pip...
Yields all available rules. :type rules_paths: [Path] :rtype: Iterable[Rule]
def get_loaded_rules(rules_paths): """Yields all available rules. :type rules_paths: [Path] :rtype: Iterable[Rule] """ for path in rules_paths: if path.name != '__init__.py': rule = Rule.from_path(path) if rule.is_enabled: yield rule
Yields all rules import paths. :rtype: Iterable[Path]
def get_rules_import_paths(): """Yields all rules import paths. :rtype: Iterable[Path] """ # Bundled rules: yield Path(__file__).parent.joinpath('rules') # Rules defined by user: yield settings.user_dir.joinpath('rules') # Packages with third-party rules: for path in sys.path: ...
Returns all enabled rules. :rtype: [Rule]
def get_rules(): """Returns all enabled rules. :rtype: [Rule] """ paths = [rule_path for path in get_rules_import_paths() for rule_path in sorted(path.glob('*.py'))] return sorted(get_loaded_rules(paths), key=lambda rule: rule.priority)
Yields sorted commands without duplicates. :type corrected_commands: Iterable[thefuck.types.CorrectedCommand] :rtype: Iterable[thefuck.types.CorrectedCommand]
def organize_commands(corrected_commands): """Yields sorted commands without duplicates. :type corrected_commands: Iterable[thefuck.types.CorrectedCommand] :rtype: Iterable[thefuck.types.CorrectedCommand] """ try: first_command = next(corrected_commands) yield first_command exc...
Returns generator with sorted and unique corrected commands. :type command: thefuck.types.Command :rtype: Iterable[thefuck.types.CorrectedCommand]
def get_corrected_commands(command): """Returns generator with sorted and unique corrected commands. :type command: thefuck.types.Command :rtype: Iterable[thefuck.types.CorrectedCommand] """ corrected_commands = ( corrected for rule in get_rules() if rule.is_match(command) ...
Fixes previous command. Used when `thefuck` called without arguments.
def fix_command(known_args): """Fixes previous command. Used when `thefuck` called without arguments.""" settings.init(known_args) with logs.debug_time('Total'): logs.debug(u'Run with settings: {}'.format(pformat(settings))) raw_command = _get_raw_command(known_args) try: ...
Gets command output from shell logger.
def get_output(script): """Gets command output from shell logger.""" with logs.debug_time(u'Read output from external shell logger'): commands = _get_last_n(const.SHELL_LOGGER_LIMIT) for command in commands: if command['command'] == script: lines = _get_output_lines(c...
Returns list of history entries.
def _get_history_lines(self): """Returns list of history entries.""" history_file_name = self._get_history_file_name() if os.path.isfile(history_file_name): with io.open(history_file_name, 'r', encoding='utf-8', errors='ignore') as history_file: ...
Split the command using shell-like syntax.
def split_command(self, command): """Split the command using shell-like syntax.""" encoded = self.encode_utf8(command) try: splitted = [s.replace("??", "\\ ") for s in shlex.split(encoded.replace('\\ ', '??'))] except ValueError: splitted = encoded.split(' ') ...
Return a shell-escaped version of the string s.
def quote(self, s): """Return a shell-escaped version of the string s.""" if six.PY2: from pipes import quote else: from shlex import quote return quote(s)
Returns the name and version of the current shell
def info(self): """Returns the name and version of the current shell""" proc = Popen(['fish', '--version'], stdout=PIPE, stderr=DEVNULL) version = proc.stdout.read().decode('utf-8').split()[-1] return u'Fish Shell {}'.format(version)
Puts command script to shell history.
def _put_to_history(self, command_script): """Puts command script to shell history.""" history_file_name = self._get_history_file_name() if os.path.isfile(history_file_name): with open(history_file_name, 'a') as history: entry = self._get_history_line(command_script) ...
To get brew default commands on local environment
def _get_brew_commands(brew_path_prefix): """To get brew default commands on local environment""" brew_cmd_path = brew_path_prefix + BREW_CMD_PATH return [name[:-3] for name in os.listdir(brew_cmd_path) if name.endswith(('.rb', '.sh'))]
To get tap's specific commands https://github.com/Homebrew/homebrew/blob/master/Library/brew.rb#L115
def _get_brew_tap_specific_commands(brew_path_prefix): """To get tap's specific commands https://github.com/Homebrew/homebrew/blob/master/Library/brew.rb#L115""" commands = [] brew_taps_path = brew_path_prefix + TAP_PATH for user in _get_directory_names_only(brew_taps_path): taps = _get_dir...
Returns the name and version of the current shell
def info(self): """Returns the name and version of the current shell""" proc = Popen(['zsh', '-c', 'echo $ZSH_VERSION'], stdout=PIPE, stderr=DEVNULL) version = proc.stdout.read().decode('utf-8').strip() return u'ZSH {}'.format(version)
Resolves git aliases and supports testing for both git and hub.
def git_support(fn, command): """Resolves git aliases and supports testing for both git and hub.""" # supports GitHub's `hub` command # which is recommended to be used with `alias git=hub` # but at this point, shell aliases have already been resolved if not is_app(command, 'git', 'hub'): ret...
Yields actions for pressed keys.
def read_actions(): """Yields actions for pressed keys.""" while True: key = get_key() # Handle arrows, j/k (qwerty), and n/e (colemak) if key in (const.KEY_UP, const.KEY_CTRL_N, 'k', 'e'): yield const.ACTION_PREVIOUS elif key in (const.KEY_DOWN, const.KEY_CTRL_P, 'j...
Returns: - the first command when confirmation disabled; - None when ctrl+c pressed; - selected command. :type corrected_commands: Iterable[thefuck.types.CorrectedCommand] :rtype: thefuck.types.CorrectedCommand | None
def select_command(corrected_commands): """Returns: - the first command when confirmation disabled; - None when ctrl+c pressed; - selected command. :type corrected_commands: Iterable[thefuck.types.CorrectedCommand] :rtype: thefuck.types.CorrectedCommand | None """ try: sele...
Create a spawned process. Modified version of pty.spawn with terminal size support.
def _spawn(shell, master_read): """Create a spawned process. Modified version of pty.spawn with terminal size support. """ pid, master_fd = pty.fork() if pid == pty.CHILD: os.execlp(shell, shell) try: mode = tty.tcgetattr(pty.STDIN_FILENO) tty.setraw(pty.STDIN_FILENO)...
Logs shell output to the `output`. Works like unix script command with `-f` flag.
def shell_logger(output): """Logs shell output to the `output`. Works like unix script command with `-f` flag. """ if not os.environ.get('SHELL'): logs.warn("Shell logger doesn't support your platform.") sys.exit(1) fd = os.open(output, os.O_CREAT | os.O_TRUNC | os.O_RDWR) os....
Get output of the script. :param script: Console script. :type script: str :param expanded: Console script with expanded aliases. :type expanded: str :rtype: str
def get_output(script, expanded): """Get output of the script. :param script: Console script. :type script: str :param expanded: Console script with expanded aliases. :type expanded: str :rtype: str """ if shell_logger.is_available(): return shell_logger.get_output(script) ...
Adds arguments to parser.
def _add_arguments(self): """Adds arguments to parser.""" self._parser.add_argument( '-v', '--version', action='store_true', help="show program's version number and exit") self._parser.add_argument( '-a', '--alias', nargs='?', ...
It's too dangerous to use `-y` and `-r` together.
def _add_conflicting_arguments(self): """It's too dangerous to use `-y` and `-r` together.""" group = self._parser.add_mutually_exclusive_group() group.add_argument( '-y', '--yes', '--yeah', action='store_true', help='execute fixed command without confirmation...
Prepares arguments by: - removing placeholder and moving arguments after it to beginning, we need this to distinguish arguments from `command` with ours; - adding `--` before `command`, so our parse would ignore arguments of `command`.
def _prepare_arguments(self, argv): """Prepares arguments by: - removing placeholder and moving arguments after it to beginning, we need this to distinguish arguments from `command` with ours; - adding `--` before `command`, so our parse would ignore arguments of `command`....
Get custom npm scripts.
def get_scripts(): """Get custom npm scripts.""" proc = Popen(['npm', 'run-script'], stdout=PIPE) should_yeild = False for line in proc.stdout.readlines(): line = line.decode() if 'available via `npm run-script`:' in line: should_yeild = True continue if ...
Fills `settings` with values from `settings.py` and env.
def init(self, args=None): """Fills `settings` with values from `settings.py` and env.""" from .logs import exception self._setup_user_dir() self._init_settings_file() try: self.update(self._settings_from_file()) except Exception: exception("Can'...
Returns Path object representing the user config resource
def _get_user_dir_path(self): """Returns Path object representing the user config resource""" xdg_config_home = os.environ.get('XDG_CONFIG_HOME', '~/.config') user_dir = Path(xdg_config_home, 'thefuck').expanduser() legacy_user_dir = Path('~', '.thefuck').expanduser() # For back...
Returns user config dir, create it when it doesn't exist.
def _setup_user_dir(self): """Returns user config dir, create it when it doesn't exist.""" user_dir = self._get_user_dir_path() rules_dir = user_dir.joinpath('rules') if not rules_dir.is_dir(): rules_dir.mkdir(parents=True) self.user_dir = user_dir
Loads settings from file.
def _settings_from_file(self): """Loads settings from file.""" settings = load_source( 'settings', text_type(self.user_dir.joinpath('settings.py'))) return {key: getattr(settings, key) for key in const.DEFAULT_SETTINGS.keys() if hasattr(settings, key)}
Transforms rules list from env-string to python.
def _rules_from_env(self, val): """Transforms rules list from env-string to python.""" val = val.split(':') if 'DEFAULT_RULES' in val: val = const.DEFAULT_RULES + [rule for rule in val if rule != 'DEFAULT_RULES'] return val
Gets priority pairs from env.
def _priority_from_env(self, val): """Gets priority pairs from env.""" for part in val.split(':'): try: rule, priority = part.split('=') yield rule, int(priority) except ValueError: continue
Transforms env-strings to python.
def _val_from_env(self, env, attr): """Transforms env-strings to python.""" val = os.environ[env] if attr in ('rules', 'exclude_rules'): return self._rules_from_env(val) elif attr == 'priority': return dict(self._priority_from_env(val)) elif attr in ('wait...
Loads settings from env.
def _settings_from_env(self): """Loads settings from env.""" return {attr: self._val_from_env(env, attr) for env, attr in const.ENV_TO_ATTR.items() if env in os.environ}
Loads settings from args.
def _settings_from_args(self, args): """Loads settings from args.""" if not args: return {} from_args = {} if args.yes: from_args['require_confirmation'] = not args.yes if args.debug: from_args['debug'] = args.debug if args.repeat: ...
When arguments order is wrong first argument will be destination.
def _get_destination(script_parts): """When arguments order is wrong first argument will be destination.""" for part in script_parts: if part not in {'ln', '-s', '--symbolic'} and os.path.exists(part): return part
Removes sudo before calling fn and adds it after.
def sudo_support(fn, command): """Removes sudo before calling fn and adds it after.""" if not command.script.startswith('sudo '): return fn(command) result = fn(command.update(script=command.script[5:])) if result and isinstance(result, six.string_types): return u'sudo {}'.format(resul...
Tries to kill the process otherwise just logs a debug message, the process will be killed when thefuck terminates. :type proc: Process
def _kill_process(proc): """Tries to kill the process otherwise just logs a debug message, the process will be killed when thefuck terminates. :type proc: Process """ try: proc.kill() except AccessDenied: logs.debug(u'Rerun: process PID {} ({}) could not be terminated'.format( ...
Returns `True` if we can get output of the command in the `settings.wait_command` time. Command will be killed if it wasn't finished in the time. :type popen: Popen :rtype: bool
def _wait_output(popen, is_slow): """Returns `True` if we can get output of the command in the `settings.wait_command` time. Command will be killed if it wasn't finished in the time. :type popen: Popen :rtype: bool """ proc = Process(popen.pid) try: proc.wait(settings.wait_slo...
Runs the script and obtains stdin/stderr. :type script: str :type expanded: str :rtype: str | None
def get_output(script, expanded): """Runs the script and obtains stdin/stderr. :type script: str :type expanded: str :rtype: str | None """ env = dict(os.environ) env.update(settings.env) is_slow = shlex.split(expanded) in settings.slow_commands with logs.debug_time(u'Call: {}; wi...
Reads script output from log. :type script: str :rtype: str | None
def get_output(script): """Reads script output from log. :type script: str :rtype: str | None """ if six.PY2: logs.warn('Experimental instant mode is Python 3+ only') return None if 'THEFUCK_OUTPUT_LOG' not in os.environ: logs.warn("Output log isn't specified") ...
Gets the packages that provide the given command using `pkgfile`. If the command is of the form `sudo foo`, searches for the `foo` command instead.
def get_pkgfile(command): """ Gets the packages that provide the given command using `pkgfile`. If the command is of the form `sudo foo`, searches for the `foo` command instead. """ try: command = command.strip() if command.startswith('sudo '): command = command[5:] ...
Returns a list of the child directories of the given parent directory
def _get_sub_dirs(parent): """Returns a list of the child directories of the given parent directory""" return [child for child in os.listdir(parent) if os.path.isdir(os.path.join(parent, child))]
Attempt to rebuild the path string by spellchecking the directories. If it fails (i.e. no directories are a close enough match), then it defaults to the rules of cd_mkdir. Change sensitivity by changing MAX_ALLOWED_DIFF. Default value is 0.6
def get_new_command(command): """ Attempt to rebuild the path string by spellchecking the directories. If it fails (i.e. no directories are a close enough match), then it defaults to the rules of cd_mkdir. Change sensitivity by changing MAX_ALLOWED_DIFF. Default value is 0.6 """ dest = comma...
Returns new command with replaced fields. :rtype: Command
def update(self, **kwargs): """Returns new command with replaced fields. :rtype: Command """ kwargs.setdefault('script', self.script) kwargs.setdefault('output', self.output) return Command(**kwargs)
Creates instance of `Command` from a list of script parts. :type raw_script: [basestring] :rtype: Command :raises: EmptyCommand
def from_raw_script(cls, raw_script): """Creates instance of `Command` from a list of script parts. :type raw_script: [basestring] :rtype: Command :raises: EmptyCommand """ script = format_raw_script(raw_script) if not script: raise EmptyCommand ...
Creates rule instance from path. :type path: pathlib.Path :rtype: Rule
def from_path(cls, path): """Creates rule instance from path. :type path: pathlib.Path :rtype: Rule """ name = path.name[:-3] with logs.debug_time(u'Importing rule: {};'.format(name)): rule_module = load_source(name, str(path)) priority = getattr...
Returns `True` when rule enabled. :rtype: bool
def is_enabled(self): """Returns `True` when rule enabled. :rtype: bool """ if self.name in settings.exclude_rules: return False elif self.name in settings.rules: return True elif self.enabled_by_default and ALL_ENABLED in settings.rules: ...
Returns `True` if rule matches the command. :type command: Command :rtype: bool
def is_match(self, command): """Returns `True` if rule matches the command. :type command: Command :rtype: bool """ if command.output is None and self.requires_output: return False try: with logs.debug_time(u'Trying rule: {};'.format(self.name))...
Returns generator with corrected commands. :type command: Command :rtype: Iterable[CorrectedCommand]
def get_corrected_commands(self, command): """Returns generator with corrected commands. :type command: Command :rtype: Iterable[CorrectedCommand] """ new_commands = self.get_new_command(command) if not isinstance(new_commands, list): new_commands = (new_com...
Returns fixed commands script. If `settings.repeat` is `True`, appends command with second attempt of running fuck in case fixed command fails again.
def _get_script(self): """Returns fixed commands script. If `settings.repeat` is `True`, appends command with second attempt of running fuck in case fixed command fails again. """ if settings.repeat: repeat_fuck = '{} --repeat {}--force-command {}'.format( ...
Runs command from rule for passed command. :type old_cmd: Command
def run(self, old_cmd): """Runs command from rule for passed command. :type old_cmd: Command """ if self.side_effect: self.side_effect(old_cmd, self.script) if settings.alter_history: shell.put_to_history(self.script) # This depends on correct se...
Returns parent process pid.
def _get_shell_pid(): """Returns parent process pid.""" proc = Process(os.getpid()) try: return proc.parent().pid except TypeError: return proc.parent.pid
Records shell pid to tracker file.
def _record_first_run(): """Records shell pid to tracker file.""" info = {'pid': _get_shell_pid(), 'time': time.time()} mode = 'wb' if six.PY2 else 'w' with _get_not_configured_usage_tracker_path().open(mode) as tracker: json.dump(info, tracker)
Returns `True` when we know that `fuck` called second time.
def _is_second_run(): """Returns `True` when we know that `fuck` called second time.""" tracker_path = _get_not_configured_usage_tracker_path() if not tracker_path.exists(): return False current_pid = _get_shell_pid() with tracker_path.open('r') as tracker: try: info = j...
Returns `True` when alias already in shell config.
def _is_already_configured(configuration_details): """Returns `True` when alias already in shell config.""" path = Path(configuration_details.path).expanduser() with path.open('r') as shell_config: return configuration_details.content in shell_config.read()
Adds alias to shell config.
def _configure(configuration_details): """Adds alias to shell config.""" path = Path(configuration_details.path).expanduser() with path.open('a') as shell_config: shell_config.write(u'\n') shell_config.write(configuration_details.content) shell_config.write(u'\n')
Shows useful information about how-to configure alias on a first run and configure automatically on a second. It'll be only visible when user type fuck and when alias isn't configured.
def main(): """Shows useful information about how-to configure alias on a first run and configure automatically on a second. It'll be only visible when user type fuck and when alias isn't configured. """ settings.init() configuration_details = shell.how_to_configure() if ( configur...
Caches previous calls to the function.
def memoize(fn): """Caches previous calls to the function.""" memo = {} @wraps(fn) def wrapper(*args, **kwargs): if not memoize.disabled: key = pickle.dumps((args, kwargs)) if key not in memo: memo[key] = fn(*args, **kwargs) value = memo[key] ...
Adds default values to settings if it not presented. Usage: @default_settings({'apt': '/usr/bin/apt'}) def match(command): print(settings.apt)
def default_settings(params): """Adds default values to settings if it not presented. Usage: @default_settings({'apt': '/usr/bin/apt'}) def match(command): print(settings.apt) """ def _default_settings(fn, command): for k, w in params.items(): settings....
Returns closest match or just first from possibilities.
def get_closest(word, possibilities, cutoff=0.6, fallback_to_first=True): """Returns closest match or just first from possibilities.""" possibilities = list(possibilities) try: return difflib_get_close_matches(word, possibilities, 1, cutoff)[0] except IndexError: if fallback_to_first: ...
Overrides `difflib.get_close_match` to controle argument `n`.
def get_close_matches(word, possibilities, n=None, cutoff=0.6): """Overrides `difflib.get_close_match` to controle argument `n`.""" if n is None: n = settings.num_close_matches return difflib_get_close_matches(word, possibilities, n, cutoff)
Replaces command line argument.
def replace_argument(script, from_, to): """Replaces command line argument.""" replaced_in_the_end = re.sub(u' {}$'.format(re.escape(from_)), u' {}'.format(to), script, count=1) if replaced_in_the_end != script: return replaced_in_the_end else: return scr...
Helper for *_no_command rules.
def replace_command(command, broken, matched): """Helper for *_no_command rules.""" new_cmds = get_close_matches(broken, matched, cutoff=0.1) return [replace_argument(command.script, broken, new_cmd.strip()) for new_cmd in new_cmds]
Returns `True` if command is call to one of passed app names.
def is_app(command, *app_names, **kwargs): """Returns `True` if command is call to one of passed app names.""" at_least = kwargs.pop('at_least', 0) if kwargs: raise TypeError("got an unexpected keyword argument '{}'".format(kwargs.keys())) if len(command.script_parts) > at_least: retur...
Specifies that matching script is for on of app names.
def for_app(*app_names, **kwargs): """Specifies that matching script is for on of app names.""" def _for_app(fn, command): if is_app(command, *app_names, **kwargs): return fn(command) else: return False return decorator(_for_app)
Caches function result in temporary file. Cache will be expired when modification date of files from `depends_on` will be changed. Only functions should be wrapped in `cache`, not methods.
def cache(*depends_on): """Caches function result in temporary file. Cache will be expired when modification date of files from `depends_on` will be changed. Only functions should be wrapped in `cache`, not methods. """ def cache_decorator(fn): @memoize @wraps(fn) def ...
Creates single script from a list of script parts. :type raw_script: [basestring] :rtype: basestring
def format_raw_script(raw_script): """Creates single script from a list of script parts. :type raw_script: [basestring] :rtype: basestring """ if six.PY2: script = ' '.join(arg.decode('utf-8') for arg in raw_script) else: script = ' '.join(raw_script) return script.strip()
Decides actions given observations information, and takes them in environment. :param brain_info: A dictionary of brain names and BrainInfo from environment. :return: an ActionInfo containing action, memories, values and an object to be passed to add experiences
def get_action(self, brain_info: BrainInfo) -> ActionInfo: """ Decides actions given observations information, and takes them in environment. :param brain_info: A dictionary of brain names and BrainInfo from environment. :return: an ActionInfo containing action, memories, values and an o...
Executes model. :param feed_dict: Input dictionary mapping nodes to input data. :param out_dict: Output dictionary mapping names to nodes. :return: Dictionary mapping names to input data.
def _execute_model(self, feed_dict, out_dict): """ Executes model. :param feed_dict: Input dictionary mapping nodes to input data. :param out_dict: Output dictionary mapping names to nodes. :return: Dictionary mapping names to input data. """ network_out = self.se...
Gets current model step. :return: current model step.
def get_current_step(self): """ Gets current model step. :return: current model step. """ step = self.sess.run(self.model.global_step) return step
Saves the model :param steps: The number of steps the model was trained for :return:
def save_model(self, steps): """ Saves the model :param steps: The number of steps the model was trained for :return: """ with self.graph.as_default(): last_checkpoint = self.model_path + '/model-' + str(steps) + '.cptk' self.saver.save(self.sess, ...
Exports latest saved model to .nn format for Unity embedding.
def export_model(self): """ Exports latest saved model to .nn format for Unity embedding. """ with self.graph.as_default(): target_nodes = ','.join(self._process_graph()) ckpt = tf.train.get_checkpoint_state(self.model_path) freeze_graph.freeze_graph(...
Gets the list of the output nodes present in the graph for inference :return: list of node names
def _process_graph(self): """ Gets the list of the output nodes present in the graph for inference :return: list of node names """ all_nodes = [x.name for x in self.graph.as_graph_def().node] nodes = [x for x in all_nodes if x in self.possible_output_nodes] logger...
Resets all the local local_buffers
def reset_local_buffers(self): """ Resets all the local local_buffers """ agent_ids = list(self.keys()) for k in agent_ids: self[k].reset_agent()
Appends the buffer of an agent to the update buffer. :param agent_id: The id of the agent which data will be appended :param key_list: The fields that must be added. If None: all fields will be appended. :param batch_size: The number of elements that must be appended. If None: All of them will b...
def append_update_buffer(self, agent_id, key_list=None, batch_size=None, training_length=None): """ Appends the buffer of an agent to the update buffer. :param agent_id: The id of the agent which data will be appended :param key_list: The fields that must be added. If None: all fields wi...
Appends the buffer of all agents to the update buffer. :param key_list: The fields that must be added. If None: all fields will be appended. :param batch_size: The number of elements that must be appended. If None: All of them will be. :param training_length: The length of the samples that must ...
def append_all_agent_batch_to_update_buffer(self, key_list=None, batch_size=None, training_length=None): """ Appends the buffer of all agents to the update buffer. :param key_list: The fields that must be added. If None: all fields will be appended. :param batch_size: The number of eleme...
Launches training session. :param process_queue: Queue used to send signal back to main. :param sub_id: Unique id for training session. :param run_seed: Random seed used for training. :param run_options: Command line arguments for training.
def run_training(sub_id: int, run_seed: int, run_options, process_queue): """ Launches training session. :param process_queue: Queue used to send signal back to main. :param sub_id: Unique id for training session. :param run_seed: Random seed used for training. :param run_options: Command line a...
Get an action using this trainer's current policy. :param curr_info: Current BrainInfo. :return: The ActionInfo given by the policy given the BrainInfo.
def get_action(self, curr_info: BrainInfo) -> ActionInfo: """ Get an action using this trainer's current policy. :param curr_info: Current BrainInfo. :return: The ActionInfo given by the policy given the BrainInfo. """ self.trainer_metrics.start_experience_collection_time...
Saves text to Tensorboard. Note: Only works on tensorflow r1.2 or above. :param key: The name of the text. :param input_dict: A dictionary that will be displayed in a table on Tensorboard.
def write_tensorboard_text(self, key, input_dict): """ Saves text to Tensorboard. Note: Only works on tensorflow r1.2 or above. :param key: The name of the text. :param input_dict: A dictionary that will be displayed in a table on Tensorboard. """ try: ...
A dict from brain name to the brain's curriculum's lesson number.
def lesson_nums(self): """A dict from brain name to the brain's curriculum's lesson number.""" lesson_nums = {} for brain_name, curriculum in self.brains_to_curriculums.items(): lesson_nums[brain_name] = curriculum.lesson_num return lesson_nums
Attempts to increments all the lessons of all the curriculums in this MetaCurriculum. Note that calling this method does not guarantee the lesson of a curriculum will increment. The lesson of a curriculum will only increment if the specified measure threshold defined in the curriculum ha...
def increment_lessons(self, measure_vals, reward_buff_sizes=None): """Attempts to increments all the lessons of all the curriculums in this MetaCurriculum. Note that calling this method does not guarantee the lesson of a curriculum will increment. The lesson of a curriculum will only inc...
Sets all the curriculums in this meta curriculum to a specified lesson number. Args: lesson_num (int): The lesson number which all the curriculums will be set to.
def set_all_curriculums_to_lesson_num(self, lesson_num): """Sets all the curriculums in this meta curriculum to a specified lesson number. Args: lesson_num (int): The lesson number which all the curriculums will be set to. """ for _, curriculum in sel...
Get the combined configuration of all curriculums in this MetaCurriculum. Returns: A dict from parameter to value.
def get_config(self): """Get the combined configuration of all curriculums in this MetaCurriculum. Returns: A dict from parameter to value. """ config = {} for _, curriculum in self.brains_to_curriculums.items(): curr_config = curriculum.get_conf...
Sends a signal to reset the unity environment. :return: AllBrainInfo : A data structure corresponding to the initial reset state of the environment.
def reset(self, config=None, train_mode=True, custom_reset_parameters=None) -> AllBrainInfo: """ Sends a signal to reset the unity environment. :return: AllBrainInfo : A data structure corresponding to the initial reset state of the environment. """ if config is None: ...
Provides the environment with an action, moves the environment dynamics forward accordingly, and returns observation, state, and reward information to the agent. :param value: Value estimates provided by agents. :param vector_action: Agent's vector action. Can be a scalar or vector of int/floats...
def step(self, vector_action=None, memory=None, text_action=None, value=None, custom_action=None) -> AllBrainInfo: """ Provides the environment with an action, moves the environment dynamics forward accordingly, and returns observation, state, and reward information to the agent. :param ...
Converts arrays to list. :param arr: numpy vector. :return: flattened list.
def _flatten(cls, arr) -> List[float]: """ Converts arrays to list. :param arr: numpy vector. :return: flattened list. """ if isinstance(arr, cls.SCALAR_ACTION_TYPES): arr = [float(arr)] if isinstance(arr, np.ndarray): arr = arr.tolist() ...
Collects experience information from all external brains in environment at current step. :return: a dictionary of BrainInfo objects.
def _get_state(self, output: UnityRLOutput) -> (AllBrainInfo, bool): """ Collects experience information from all external brains in environment at current step. :return: a dictionary of BrainInfo objects. """ _data = {} global_done = output.global_done for brain_...