| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | """Miscellaneous utility classes and functions.""" |
| |
|
| | import ctypes |
| | import fnmatch |
| | import importlib |
| | import inspect |
| | import numpy as np |
| | import os |
| | import shutil |
| | import sys |
| | import types |
| | import io |
| | import pickle |
| | import re |
| | import requests |
| | import html |
| | import hashlib |
| | import glob |
| | import tempfile |
| | import urllib |
| | import urllib.request |
| | import uuid |
| |
|
| | from distutils.util import strtobool |
| | from typing import Any, List, Tuple, Union |
| |
|
| | import torch |
| |
|
| | |
| | |
| |
|
| | def calculate_adaptive_weight(recon_loss, g_loss, last_layer, disc_weight_max=1.0): |
| | recon_grads = torch.autograd.grad(recon_loss, last_layer, retain_graph=True)[0] |
| | g_grads = torch.autograd.grad(g_loss, last_layer, retain_graph=True)[0] |
| |
|
| | d_weight = torch.norm(recon_grads) / (torch.norm(g_grads) + 1e-4) |
| | d_weight = torch.clamp(d_weight, 0.0, disc_weight_max).detach() |
| | return d_weight |
| |
|
| |
|
| | class EasyDict(dict): |
| | """Convenience class that behaves like a dict but allows access with the attribute syntax.""" |
| |
|
| | def __getattr__(self, name: str) -> Any: |
| | try: |
| | return self[name] |
| | except KeyError: |
| | raise AttributeError(name) |
| |
|
| | def __setattr__(self, name: str, value: Any) -> None: |
| | self[name] = value |
| |
|
| | def __delattr__(self, name: str) -> None: |
| | del self[name] |
| |
|
| |
|
| | class Logger(object): |
| | """Redirect stderr to stdout, optionally print stdout to a file, and optionally force flushing on both stdout and the file.""" |
| |
|
| | def __init__(self, |
| | file_name: str = None, |
| | file_mode: str = "w", |
| | should_flush: bool = True): |
| | self.file = None |
| |
|
| | if file_name is not None: |
| | self.file = open(file_name, file_mode) |
| |
|
| | self.should_flush = should_flush |
| | self.stdout = sys.stdout |
| | self.stderr = sys.stderr |
| |
|
| | sys.stdout = self |
| | sys.stderr = self |
| |
|
| | def __enter__(self) -> "Logger": |
| | return self |
| |
|
| | def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any) -> None: |
| | self.close() |
| |
|
| | def write(self, text: Union[str, bytes]) -> None: |
| | """Write text to stdout (and a file) and optionally flush.""" |
| | if isinstance(text, bytes): |
| | text = text.decode() |
| | if len( |
| | text |
| | ) == 0: |
| | return |
| |
|
| | if self.file is not None: |
| | self.file.write(text) |
| |
|
| | self.stdout.write(text) |
| |
|
| | if self.should_flush: |
| | self.flush() |
| |
|
| | def flush(self) -> None: |
| | """Flush written text to both stdout and a file, if open.""" |
| | if self.file is not None: |
| | self.file.flush() |
| |
|
| | self.stdout.flush() |
| |
|
| | def close(self) -> None: |
| | """Flush, close possible files, and remove stdout/stderr mirroring.""" |
| | self.flush() |
| |
|
| | |
| | if sys.stdout is self: |
| | sys.stdout = self.stdout |
| | if sys.stderr is self: |
| | sys.stderr = self.stderr |
| |
|
| | if self.file is not None: |
| | self.file.close() |
| | self.file = None |
| |
|
| |
|
| | |
| | |
| |
|
| | _dnnlib_cache_dir = None |
| |
|
| |
|
| | def set_cache_dir(path: str) -> None: |
| | global _dnnlib_cache_dir |
| | _dnnlib_cache_dir = path |
| |
|
| |
|
| | def make_cache_dir_path(*paths: str) -> str: |
| | if _dnnlib_cache_dir is not None: |
| | return os.path.join(_dnnlib_cache_dir, *paths) |
| | if 'DNNLIB_CACHE_DIR' in os.environ: |
| | return os.path.join(os.environ['DNNLIB_CACHE_DIR'], *paths) |
| | if 'HOME' in os.environ: |
| | return os.path.join(os.environ['HOME'], '.cache', 'dnnlib', *paths) |
| | if 'USERPROFILE' in os.environ: |
| | return os.path.join(os.environ['USERPROFILE'], '.cache', 'dnnlib', |
| | *paths) |
| | return os.path.join(tempfile.gettempdir(), '.cache', 'dnnlib', *paths) |
| |
|
| |
|
| | |
| | |
| |
|
| |
|
| | def format_time(seconds: Union[int, float]) -> str: |
| | """Convert the seconds to human readable string with days, hours, minutes and seconds.""" |
| | s = int(np.rint(seconds)) |
| |
|
| | if s < 60: |
| | return "{0}s".format(s) |
| | elif s < 60 * 60: |
| | return "{0}m {1:02}s".format(s // 60, s % 60) |
| | elif s < 24 * 60 * 60: |
| | return "{0}h {1:02}m {2:02}s".format(s // (60 * 60), (s // 60) % 60, |
| | s % 60) |
| | else: |
| | return "{0}d {1:02}h {2:02}m".format(s // (24 * 60 * 60), |
| | (s // (60 * 60)) % 24, |
| | (s // 60) % 60) |
| |
|
| |
|
| | def format_time_brief(seconds: Union[int, float]) -> str: |
| | """Convert the seconds to human readable string with days, hours, minutes and seconds.""" |
| | s = int(np.rint(seconds)) |
| |
|
| | if s < 60: |
| | return "{0}s".format(s) |
| | elif s < 60 * 60: |
| | return "{0}m {1:02}s".format(s // 60, s % 60) |
| | elif s < 24 * 60 * 60: |
| | return "{0}h {1:02}m".format(s // (60 * 60), (s // 60) % 60) |
| | else: |
| | return "{0}d {1:02}h".format(s // (24 * 60 * 60), |
| | (s // (60 * 60)) % 24) |
| |
|
| |
|
| | def ask_yes_no(question: str) -> bool: |
| | """Ask the user the question until the user inputs a valid answer.""" |
| | while True: |
| | try: |
| | print("{0} [y/n]".format(question)) |
| | return strtobool(input().lower()) |
| | except ValueError: |
| | pass |
| |
|
| |
|
| | def tuple_product(t: Tuple) -> Any: |
| | """Calculate the product of the tuple elements.""" |
| | result = 1 |
| |
|
| | for v in t: |
| | result *= v |
| |
|
| | return result |
| |
|
| |
|
| | _str_to_ctype = { |
| | "uint8": ctypes.c_ubyte, |
| | "uint16": ctypes.c_uint16, |
| | "uint32": ctypes.c_uint32, |
| | "uint64": ctypes.c_uint64, |
| | "int8": ctypes.c_byte, |
| | "int16": ctypes.c_int16, |
| | "int32": ctypes.c_int32, |
| | "int64": ctypes.c_int64, |
| | "float32": ctypes.c_float, |
| | "float64": ctypes.c_double |
| | } |
| |
|
| |
|
| | def get_dtype_and_ctype(type_obj: Any) -> Tuple[np.dtype, Any]: |
| | """Given a type name string (or an object having a __name__ attribute), return matching Numpy and ctypes types that have the same size in bytes.""" |
| | type_str = None |
| |
|
| | if isinstance(type_obj, str): |
| | type_str = type_obj |
| | elif hasattr(type_obj, "__name__"): |
| | type_str = type_obj.__name__ |
| | elif hasattr(type_obj, "name"): |
| | type_str = type_obj.name |
| | else: |
| | raise RuntimeError("Cannot infer type name from input") |
| |
|
| | assert type_str in _str_to_ctype.keys() |
| |
|
| | my_dtype = np.dtype(type_str) |
| | my_ctype = _str_to_ctype[type_str] |
| |
|
| | assert my_dtype.itemsize == ctypes.sizeof(my_ctype) |
| |
|
| | return my_dtype, my_ctype |
| |
|
| |
|
| | def is_pickleable(obj: Any) -> bool: |
| | try: |
| | with io.BytesIO() as stream: |
| | pickle.dump(obj, stream) |
| | return True |
| | except: |
| | return False |
| |
|
| |
|
| | |
| | |
| |
|
| |
|
| | def get_module_from_obj_name(obj_name: str) -> Tuple[types.ModuleType, str]: |
| | """Searches for the underlying module behind the name to some python object. |
| | Returns the module and the object name (original name with module part removed).""" |
| |
|
| | |
| | obj_name = re.sub("^np.", "numpy.", obj_name) |
| | obj_name = re.sub("^tf.", "tensorflow.", obj_name) |
| |
|
| | |
| | parts = obj_name.split(".") |
| | name_pairs = [(".".join(parts[:i]), ".".join(parts[i:])) |
| | for i in range(len(parts), 0, -1)] |
| |
|
| | |
| | for module_name, local_obj_name in name_pairs: |
| | try: |
| | module = importlib.import_module( |
| | module_name) |
| | get_obj_from_module(module, |
| | local_obj_name) |
| | return module, local_obj_name |
| | except: |
| | pass |
| |
|
| | |
| | for module_name, _local_obj_name in name_pairs: |
| | try: |
| | importlib.import_module(module_name) |
| | except ImportError: |
| | if not str(sys.exc_info()[1]).startswith("No module named '" + |
| | module_name + "'"): |
| | raise |
| |
|
| | |
| | for module_name, local_obj_name in name_pairs: |
| | try: |
| | module = importlib.import_module( |
| | module_name) |
| | get_obj_from_module(module, |
| | local_obj_name) |
| | except ImportError: |
| | pass |
| |
|
| | |
| | raise ImportError(obj_name) |
| |
|
| |
|
| | def get_obj_from_module(module: types.ModuleType, obj_name: str) -> Any: |
| | """Traverses the object name and returns the last (rightmost) python object.""" |
| | if obj_name == '': |
| | return module |
| | obj = module |
| | for part in obj_name.split("."): |
| | obj = getattr(obj, part) |
| | return obj |
| |
|
| |
|
| | def get_obj_by_name(name: str) -> Any: |
| | """Finds the python object with the given name.""" |
| | module, obj_name = get_module_from_obj_name(name) |
| | return get_obj_from_module(module, obj_name) |
| |
|
| |
|
| | def call_func_by_name(*args, func_name: str = None, **kwargs) -> Any: |
| | """Finds the python object with the given name and calls it as a function.""" |
| | assert func_name is not None |
| | func_obj = get_obj_by_name(func_name) |
| | assert callable(func_obj) |
| | return func_obj(*args, **kwargs) |
| |
|
| |
|
| | def construct_class_by_name(*args, class_name: str = None, **kwargs) -> Any: |
| | """Finds the python class with the given name and constructs it with the given arguments.""" |
| | return call_func_by_name(*args, func_name=class_name, **kwargs) |
| |
|
| |
|
| | def get_module_dir_by_obj_name(obj_name: str) -> str: |
| | """Get the directory path of the module containing the given object name.""" |
| | module, _ = get_module_from_obj_name(obj_name) |
| | return os.path.dirname(inspect.getfile(module)) |
| |
|
| |
|
| | def is_top_level_function(obj: Any) -> bool: |
| | """Determine whether the given object is a top-level function, i.e., defined at module scope using 'def'.""" |
| | return callable(obj) and obj.__name__ in sys.modules[ |
| | obj.__module__].__dict__ |
| |
|
| |
|
| | def get_top_level_function_name(obj: Any) -> str: |
| | """Return the fully-qualified name of a top-level function.""" |
| | assert is_top_level_function(obj) |
| | module = obj.__module__ |
| | if module == '__main__': |
| | module = os.path.splitext( |
| | os.path.basename(sys.modules[module].__file__))[0] |
| | return module + "." + obj.__name__ |
| |
|
| |
|
| | |
| | |
| |
|
| |
|
| | def list_dir_recursively_with_ignore( |
| | dir_path: str, |
| | ignores: List[str] = None, |
| | add_base_to_relative: bool = False) -> List[Tuple[str, str]]: |
| | """List all files recursively in a given directory while ignoring given file and directory names. |
| | Returns list of tuples containing both absolute and relative paths.""" |
| | assert os.path.isdir(dir_path) |
| | base_name = os.path.basename(os.path.normpath(dir_path)) |
| |
|
| | if ignores is None: |
| | ignores = [] |
| |
|
| | result = [] |
| |
|
| | for root, dirs, files in os.walk(dir_path, topdown=True): |
| | for ignore_ in ignores: |
| | dirs_to_remove = [d for d in dirs if fnmatch.fnmatch(d, ignore_)] |
| |
|
| | |
| | for d in dirs_to_remove: |
| | dirs.remove(d) |
| |
|
| | files = [f for f in files if not fnmatch.fnmatch(f, ignore_)] |
| |
|
| | absolute_paths = [os.path.join(root, f) for f in files] |
| | relative_paths = [os.path.relpath(p, dir_path) for p in absolute_paths] |
| |
|
| | if add_base_to_relative: |
| | relative_paths = [ |
| | os.path.join(base_name, p) for p in relative_paths |
| | ] |
| |
|
| | assert len(absolute_paths) == len(relative_paths) |
| | result += zip(absolute_paths, relative_paths) |
| |
|
| | return result |
| |
|
| |
|
| | def copy_files_and_create_dirs(files: List[Tuple[str, str]]) -> None: |
| | """Takes in a list of tuples of (src, dst) paths and copies files. |
| | Will create all necessary directories.""" |
| | for file in files: |
| | target_dir_name = os.path.dirname(file[1]) |
| |
|
| | |
| | if not os.path.exists(target_dir_name): |
| | os.makedirs(target_dir_name) |
| |
|
| | shutil.copyfile(file[0], file[1]) |
| |
|
| |
|
| | |
| | |
| |
|
| |
|
| | def is_url(obj: Any, allow_file_urls: bool = False) -> bool: |
| | """Determine whether the given object is a valid URL string.""" |
| | if not isinstance(obj, str) or not "://" in obj: |
| | return False |
| | if allow_file_urls and obj.startswith('file://'): |
| | return True |
| | try: |
| | res = requests.compat.urlparse(obj) |
| | if not res.scheme or not res.netloc or not "." in res.netloc: |
| | return False |
| | res = requests.compat.urlparse(requests.compat.urljoin(obj, "/")) |
| | if not res.scheme or not res.netloc or not "." in res.netloc: |
| | return False |
| | except: |
| | return False |
| | return True |
| |
|
| |
|
| | def open_url(url: str, |
| | cache_dir: str = None, |
| | num_attempts: int = 10, |
| | verbose: bool = True, |
| | return_filename: bool = False, |
| | cache: bool = True) -> Any: |
| | """Download the given URL and return a binary-mode file object to access the data.""" |
| | assert num_attempts >= 1 |
| | assert not (return_filename and (not cache)) |
| |
|
| | |
| | if not re.match('^[a-z]+://', url): |
| | return url if return_filename else open(url, "rb") |
| |
|
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | if url.startswith('file://'): |
| | filename = urllib.parse.urlparse(url).path |
| | if re.match(r'^/[a-zA-Z]:', filename): |
| | filename = filename[1:] |
| | return filename if return_filename else open(filename, "rb") |
| |
|
| | assert is_url(url) |
| |
|
| | |
| | if cache_dir is None: |
| | cache_dir = make_cache_dir_path('downloads') |
| |
|
| | url_md5 = hashlib.md5(url.encode("utf-8")).hexdigest() |
| | if cache: |
| | cache_files = glob.glob(os.path.join(cache_dir, url_md5 + "_*")) |
| | if len(cache_files) == 1: |
| | filename = cache_files[0] |
| | return filename if return_filename else open(filename, "rb") |
| |
|
| | |
| | url_name = None |
| | url_data = None |
| | with requests.Session() as session: |
| | if verbose: |
| | print("Downloading %s ..." % url, end="", flush=True) |
| | for attempts_left in reversed(range(num_attempts)): |
| | try: |
| | with session.get(url) as res: |
| | res.raise_for_status() |
| | if len(res.content) == 0: |
| | raise IOError("No data received") |
| |
|
| | if len(res.content) < 8192: |
| | content_str = res.content.decode("utf-8") |
| | if "download_warning" in res.headers.get( |
| | "Set-Cookie", ""): |
| | links = [ |
| | html.unescape(link) |
| | for link in content_str.split('"') |
| | if "export=download" in link |
| | ] |
| | if len(links) == 1: |
| | url = requests.compat.urljoin(url, links[0]) |
| | raise IOError("Google Drive virus checker nag") |
| | if "Google Drive - Quota exceeded" in content_str: |
| | raise IOError( |
| | "Google Drive download quota exceeded -- please try again later" |
| | ) |
| |
|
| | match = re.search( |
| | r'filename="([^"]*)"', |
| | res.headers.get("Content-Disposition", "")) |
| | url_name = match[1] if match else url |
| | url_data = res.content |
| | if verbose: |
| | print(" done") |
| | break |
| | except KeyboardInterrupt: |
| | raise |
| | except: |
| | if not attempts_left: |
| | if verbose: |
| | print(" failed") |
| | raise |
| | if verbose: |
| | print(".", end="", flush=True) |
| |
|
| | |
| | if cache: |
| | safe_name = re.sub(r"[^0-9a-zA-Z-._]", "_", url_name) |
| | cache_file = os.path.join(cache_dir, url_md5 + "_" + safe_name) |
| | temp_file = os.path.join( |
| | cache_dir, |
| | "tmp_" + uuid.uuid4().hex + "_" + url_md5 + "_" + safe_name) |
| | os.makedirs(cache_dir, exist_ok=True) |
| | with open(temp_file, "wb") as f: |
| | f.write(url_data) |
| | os.replace(temp_file, cache_file) |
| | if return_filename: |
| | return cache_file |
| |
|
| | |
| | assert not return_filename |
| | return io.BytesIO(url_data) |
| |
|
| | class InfiniteSampler(torch.utils.data.Sampler): |
| |
|
| | def __init__(self, |
| | dataset, |
| | rank=0, |
| | num_replicas=1, |
| | shuffle=True, |
| | seed=0, |
| | window_size=0.5): |
| | assert len(dataset) > 0 |
| | assert num_replicas > 0 |
| | assert 0 <= rank < num_replicas |
| | assert 0 <= window_size <= 1 |
| | super().__init__(dataset) |
| | self.dataset = dataset |
| | self.rank = rank |
| | self.num_replicas = num_replicas |
| | self.shuffle = shuffle |
| | self.seed = seed |
| | self.window_size = window_size |
| |
|
| | def __iter__(self): |
| | order = np.arange(len(self.dataset)) |
| | rnd = None |
| | window = 0 |
| | if self.shuffle: |
| | rnd = np.random.RandomState(self.seed) |
| | rnd.shuffle(order) |
| | window = int(np.rint(order.size * self.window_size)) |
| |
|
| | idx = 0 |
| | while True: |
| | i = idx % order.size |
| | if idx % self.num_replicas == self.rank: |
| | yield order[i] |
| | if window >= 2: |
| | j = (i - rnd.randint(window)) % order.size |
| | order[i], order[j] = order[j], order[i] |
| | idx += 1 |
| |
|
| | def requires_grad(model, flag=True): |
| | for p in model.parameters(): |
| | p.requires_grad = flag |
| |
|