# coding: utf8 from __future__ import unicode_literals, print_function import os import ujson import pip import importlib import regex as re from pathlib import Path import sys import textwrap import random import numpy import io import dill from collections import OrderedDict import msgpack import msgpack_numpy msgpack_numpy.patch() import ujson from .symbols import ORTH from .compat import cupy, CudaStream, path2str, basestring_, input_, unicode_ from .compat import copy_array, normalize_string_keys LANGUAGES = {} _data_path = Path(__file__).parent / 'data' def get_lang_class(lang): """Import and load a Language class. lang (unicode): Two-letter language code, e.g. 'en'. RETURNS (Language): Language class. """ global LANGUAGES if not lang in LANGUAGES: try: module = importlib.import_module('.lang.%s' % lang, 'spacy') except ImportError: raise ImportError("Can't import language %s from spacy.lang." %lang) LANGUAGES[lang] = getattr(module, module.__all__[0]) return LANGUAGES[lang] def set_lang_class(name, cls): """Set a custom Language class name that can be loaded via get_lang_class. name (unicode): Name of Language class. cls (Language): Language class. """ global LANGUAGES LANGUAGES[name] = cls def get_data_path(require_exists=True): """Get path to spaCy data directory. require_exists (bool): Only return path if it exists, otherwise None. RETURNS (Path or None): Data path or None. """ if not require_exists: return _data_path else: return _data_path if _data_path.exists() else None def set_data_path(path): """Set path to spaCy data directory. path (unicode or Path): Path to new data directory. """ global _data_path _data_path = ensure_path(path) def ensure_path(path): """Ensure string is converted to a Path. path: Anything. If string, it's converted to Path. RETURNS: Path or original argument. """ if isinstance(path, basestring_): return Path(path) else: return path def load_model(name, **overrides): """Load a model from a shortcut link, package or data path. name (unicode): Package name, shortcut link or model path. **overrides: Specific overrides, like pipeline components to disable. RETURNS (Language): `Language` class with the loaded model. """ data_path = get_data_path() if not data_path or not data_path.exists(): raise IOError("Can't find spaCy data path: %s" % path2str(data_path)) if isinstance(name, basestring_): if (data_path / name).exists(): # in data dir or shortcut spec = importlib.util.spec_from_file_location('model', data_path / name) cls = importlib.util.module_from_spec(spec) spec.loader.exec_module(cls) return cls.load(**overrides) if is_package(name): # installed as package cls = importlib.import_module(name) return cls.load(**overrides) if Path(name).exists(): # path to model data directory model_path = Path(name) meta = get_package_meta(model_path) cls = get_lang_class(meta['lang']) nlp = cls(pipeline=meta.get('pipeline', True), meta=meta) return nlp.from_disk(model_path, **overrides) elif hasattr(name, 'exists'): # Path or Path-like to model data meta = get_package_meta(name) cls = get_lang_class(meta['lang']) nlp = cls(pipeline=meta.get('pipeline', True), meta=meta) return nlp.from_disk(name, **overrides) raise IOError("Can't find model '%s'" % name) def load_model_from_init_py(init_file, **overrides): """Helper function to use in the `load()` method of a model package's __init__.py. init_file (unicode): Path to model's __init__.py, i.e. `__file__`. **overrides: Specific overrides, like pipeline components to disable. RETURNS (Language): `Language` class with loaded model. """ model_path = Path(init_file).parent meta = get_model_meta(model_path) data_dir = '%s_%s-%s' % (meta['lang'], meta['name'], meta['version']) data_path = model_path / data_dir if not model_path.exists(): raise ValueError("Can't find model directory: %s" % path2str(data_path)) cls = get_lang_class(meta['lang']) nlp = cls(pipeline=meta.get('pipeline', True), meta=meta) return nlp.from_disk(data_path, **overrides) def get_model_meta(path): """Get model meta.json from a directory path and validate its contents. path (unicode or Path): Path to model directory. RETURNS (dict): The model's meta data. """ model_path = ensure_path(path) if not model_path.exists(): raise ValueError("Can't find model directory: %s" % path2str(model_path)) meta_path = model_path / 'meta.json' if not meta_path.is_file(): raise IOError("Could not read meta.json from %s" % meta_path) meta = read_json(meta_path) for setting in ['lang', 'name', 'version']: if setting not in meta: raise IOError('No %s setting found in model meta.json' % setting) return meta def is_package(name): """Check if string maps to a package installed via pip. name (unicode): Name of package. RETURNS (bool): True if installed package, False if not. """ packages = pip.get_installed_distributions() for package in packages: if package.project_name.replace('-', '_') == name: return True return False def get_package_path(name): """Get the path to an installed package. name (unicode): Package name. RETURNS (Path): Path to installed package. """ # Here we're importing the module just to find it. This is worryingly # indirect, but it's otherwise very difficult to find the package. pkg = importlib.import_module(name) return Path(pkg.__file__).parent def is_in_jupyter(): """Check if user is running spaCy from a Jupyter notebook by detecting the IPython kernel. Mainly used for the displaCy visualizer. RETURNS (bool): True if in Jupyter, False if not. """ try: cfg = get_ipython().config if cfg['IPKernelApp']['parent_appname'] == 'ipython-notebook': return True except NameError: return False return False def get_cuda_stream(require=False): # TODO: Error and tell to install chainer if not found # Requires GPU return CudaStream() if CudaStream is not None else None def get_async(stream, numpy_array): if cupy is None: return numpy_array else: array = cupy.ndarray(numpy_array.shape, order='C', dtype=numpy_array.dtype) array.set(numpy_array, stream=stream) return array def itershuffle(iterable, bufsize=1000): """Shuffle an iterator. This works by holding `bufsize` items back and yielding them sometime later. Obviously, this is not unbiased – but should be good enough for batching. Larger bufsize means less bias. From https://gist.github.com/andres-erbsen/1307752 iterable (iterable): Iterator to shuffle. bufsize (int): Items to hold back. YIELDS (iterable): The shuffled iterator. """ iterable = iter(iterable) buf = [] try: while True: for i in range(random.randint(1, bufsize-len(buf))): buf.append(iterable.next()) random.shuffle(buf) for i in range(random.randint(1, bufsize)): if buf: yield buf.pop() else: break except StopIteration: random.shuffle(buf) while buf: yield buf.pop() raise StopIteration _PRINT_ENV = False def set_env_log(value): global _PRINT_ENV _PRINT_ENV = value def env_opt(name, default=None): if type(default) is float: type_convert = float else: type_convert = int if 'SPACY_' + name.upper() in os.environ: value = type_convert(os.environ['SPACY_' + name.upper()]) if _PRINT_ENV: print(name, "=", repr(value), "via", "$SPACY_" + name.upper()) return value elif name in os.environ: value = type_convert(os.environ[name]) if _PRINT_ENV: print(name, "=", repr(value), "via", '$' + name) return value else: if _PRINT_ENV: print(name, '=', repr(default), "by default") return default def read_regex(path): path = ensure_path(path) with path.open() as file_: entries = file_.read().split('\n') expression = '|'.join(['^' + re.escape(piece) for piece in entries if piece.strip()]) return re.compile(expression) def compile_prefix_regex(entries): if '(' in entries: # Handle deprecated data expression = '|'.join(['^' + re.escape(piece) for piece in entries if piece.strip()]) return re.compile(expression) else: expression = '|'.join(['^' + piece for piece in entries if piece.strip()]) return re.compile(expression) def compile_suffix_regex(entries): expression = '|'.join([piece + '$' for piece in entries if piece.strip()]) return re.compile(expression) def compile_infix_regex(entries): expression = '|'.join([piece for piece in entries if piece.strip()]) return re.compile(expression) def update_exc(base_exceptions, *addition_dicts): """Update and validate tokenizer exceptions. Will overwrite exceptions. base_exceptions (dict): Base exceptions. *addition_dicts (dict): Exceptions to add to the base dict, in order. RETURNS (dict): Combined tokenizer exceptions. """ exc = dict(base_exceptions) for additions in addition_dicts: for orth, token_attrs in additions.items(): if not all(isinstance(attr[ORTH], unicode_) for attr in token_attrs): msg = "Invalid value for ORTH in exception: key='%s', orths='%s'" raise ValueError(msg % (orth, token_attrs)) described_orth = ''.join(attr[ORTH] for attr in token_attrs) if orth != described_orth: raise ValueError("Invalid tokenizer exception: ORTH values " "combined don't match original string. " "key='%s', orths='%s'" % (orth, described_orth)) # overlap = set(exc.keys()).intersection(set(additions)) # assert not overlap, overlap exc.update(additions) exc = expand_exc(exc, "'", "’") return exc def expand_exc(excs, search, replace): """Find string in tokenizer exceptions, duplicate entry and replace string. For example, to add additional versions with typographic apostrophes. excs (dict): Tokenizer exceptions. search (unicode): String to find and replace. replace (unicode): Replacement. RETURNS (dict): Combined tokenizer exceptions. """ def _fix_token(token, search, replace): fixed = dict(token) fixed[ORTH] = fixed[ORTH].replace(search, replace) return fixed new_excs = dict(excs) for token_string, tokens in excs.items(): if search in token_string: new_key = token_string.replace(search, replace) new_value = [_fix_token(t, search, replace) for t in tokens] new_excs[new_key] = new_value return new_excs def normalize_slice(length, start, stop, step=None): if not (step is None or step == 1): raise ValueError("Stepped slices not supported in Span objects." "Try: list(tokens)[start:stop:step] instead.") if start is None: start = 0 elif start < 0: start += length start = min(length, max(0, start)) if stop is None: stop = length elif stop < 0: stop += length stop = min(length, max(start, stop)) assert 0 <= start <= stop <= length return start, stop def compounding(start, stop, compound): """Yield an infinite series of compounding values. Each time the generator is called, a value is produced by multiplying the previous value by the compound rate. EXAMPLE: >>> sizes = compounding(1., 10., 1.5) >>> assert next(sizes) == 1. >>> assert next(sizes) == 1 * 1.5 >>> assert next(sizes) == 1.5 * 1.5 """ def clip(value): return max(value, stop) if (start>stop) else min(value, stop) curr = float(start) while True: yield clip(curr) curr *= compound def decaying(start, stop, decay): """Yield an infinite series of linearly decaying values.""" def clip(value): return max(value, stop) if (start>stop) else min(value, stop) nr_upd = 1. while True: yield clip(start * 1./(1. + decay * nr_upd)) nr_upd += 1 def read_json(location): """Open and load JSON from file. location (Path): Path to JSON file. RETURNS (dict): Loaded JSON content. """ with location.open('r', encoding='utf8') as f: return ujson.load(f) def get_raw_input(description, default=False): """Get user input from the command line via raw_input / input. description (unicode): Text to display before prompt. default (unicode or False/None): Default value to display with prompt. RETURNS (unicode): User input. """ additional = ' (default: %s)' % default if default else '' prompt = ' %s%s: ' % (description, additional) user_input = input_(prompt) return user_input def to_bytes(getters, exclude): serialized = OrderedDict() for key, getter in getters.items(): if key not in exclude: serialized[key] = getter() return msgpack.dumps(serialized) def from_bytes(bytes_data, setters, exclude): msg = msgpack.loads(bytes_data) for key, setter in setters.items(): if key not in exclude: setter(msg[key]) return msg def to_disk(path, writers, exclude): path = ensure_path(path) if not path.exists(): path.mkdir() for key, writer in writers.items(): if key not in exclude: writer(path / key) return path def from_disk(path, readers, exclude): path = ensure_path(path) for key, reader in readers.items(): if key not in exclude: reader(path / key) return path # This stuff really belongs in thinc -- but I expect # to refactor how all this works in thinc anyway. # What a mess! def model_to_bytes(model): weights = [] queue = [model] i = 0 for layer in queue: if hasattr(layer, '_mem'): weights.append({ 'dims': normalize_string_keys(getattr(layer, '_dims', {})), 'params': []}) if hasattr(layer, 'seed'): weights[-1]['seed'] = layer.seed for (id_, name), (start, row, shape) in layer._mem._offsets.items(): if row == 1: continue param = layer._mem.get((id_, name)) if not isinstance(layer._mem.weights, numpy.ndarray): param = param.get() weights[-1]['params'].append( { 'name': name, 'offset': start, 'shape': shape, 'value': param, } ) i += 1 if hasattr(layer, '_layers'): queue.extend(layer._layers) return msgpack.dumps({'weights': weights}) def model_from_bytes(model, bytes_data): data = msgpack.loads(bytes_data) weights = data['weights'] queue = [model] i = 0 for layer in queue: if hasattr(layer, '_mem'): if 'seed' in weights[i]: layer.seed = weights[i]['seed'] for dim, value in weights[i]['dims'].items(): setattr(layer, dim, value) for param in weights[i]['params']: dest = getattr(layer, param['name']) copy_array(dest, param['value']) i += 1 if hasattr(layer, '_layers'): queue.extend(layer._layers) def print_table(data, title=None): """Print data in table format. data (dict or list of tuples): Label/value pairs. title (unicode or None): Title, will be printed above. """ if isinstance(data, dict): data = list(data.items()) tpl_row = ' {:<15}' * len(data[0]) table = '\n'.join([tpl_row.format(l, v) for l, v in data]) if title: print('\n \033[93m{}\033[0m'.format(title)) print('\n{}\n'.format(table)) def print_markdown(data, title=None): """Print data in GitHub-flavoured Markdown format for issues etc. data (dict or list of tuples): Label/value pairs. title (unicode or None): Title, will be rendered as headline 2. """ def excl_value(value): return Path(value).exists() # contains path (personal info) if isinstance(data, dict): data = list(data.items()) markdown = ["* **{}:** {}".format(l, v) for l, v in data if not excl_value(v)] if title: print("\n## {}".format(title)) print('\n{}\n'.format('\n'.join(markdown))) def prints(*texts, **kwargs): """Print formatted message (manual ANSI escape sequences to avoid dependency) *texts (unicode): Texts to print. Each argument is rendered as paragraph. **kwargs: 'title' becomes coloured headline. 'exits'=True performs sys exit. """ exits = kwargs.get('exits', None) title = kwargs.get('title', None) title = '\033[93m{}\033[0m\n'.format(_wrap(title)) if title else '' message = '\n\n'.join([_wrap(text) for text in texts]) print('\n{}{}\n'.format(title, message)) if exits is not None: sys.exit(exits) def _wrap(text, wrap_max=80, indent=4): """Wrap text at given width using textwrap module. text (unicode): Text to wrap. If it's a Path, it's converted to string. wrap_max (int): Maximum line length (indent is deducted). indent (int): Number of spaces for indentation. RETURNS (unicode): Wrapped text. """ indent = indent * ' ' wrap_width = wrap_max - len(indent) if isinstance(text, Path): text = path2str(text) return textwrap.fill(text, width=wrap_width, initial_indent=indent, subsequent_indent=indent, break_long_words=False, break_on_hyphens=False) def minify_html(html): """Perform a template-specific, rudimentary HTML minification for displaCy. Disclaimer: NOT a general-purpose solution, only removes indentation/newlines. html (unicode): Markup to minify. RETURNS (unicode): "Minified" HTML. """ return html.strip().replace(' ', '').replace('\n', '')