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lavis/common/annotator/uniformer/mmcv/runner/utils.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import os
+import random
+import sys
+import time
+import warnings
+from getpass import getuser
+from socket import gethostname
+
+import numpy as np
+import torch
+
+import annotator.uniformer.mmcv as mmcv
+
+
+def get_host_info():
+    """Get hostname and username.
+
+    Return empty string if exception raised, e.g. ``getpass.getuser()`` will
+    lead to error in docker container
+    """
+    host = ''
+    try:
+        host = f'{getuser()}@{gethostname()}'
+    except Exception as e:
+        warnings.warn(f'Host or user not found: {str(e)}')
+    finally:
+        return host
+
+
+def get_time_str():
+    return time.strftime('%Y%m%d_%H%M%S', time.localtime())
+
+
+def obj_from_dict(info, parent=None, default_args=None):
+    """Initialize an object from dict.
+
+    The dict must contain the key "type", which indicates the object type, it
+    can be either a string or type, such as "list" or ``list``. Remaining
+    fields are treated as the arguments for constructing the object.
+
+    Args:
+        info (dict): Object types and arguments.
+        parent (:class:`module`): Module which may containing expected object
+            classes.
+        default_args (dict, optional): Default arguments for initializing the
+            object.
+
+    Returns:
+        any type: Object built from the dict.
+    """
+    assert isinstance(info, dict) and 'type' in info
+    assert isinstance(default_args, dict) or default_args is None
+    args = info.copy()
+    obj_type = args.pop('type')
+    if mmcv.is_str(obj_type):
+        if parent is not None:
+            obj_type = getattr(parent, obj_type)
+        else:
+            obj_type = sys.modules[obj_type]
+    elif not isinstance(obj_type, type):
+        raise TypeError('type must be a str or valid type, but '
+                        f'got {type(obj_type)}')
+    if default_args is not None:
+        for name, value in default_args.items():
+            args.setdefault(name, value)
+    return obj_type(**args)
+
+
+def set_random_seed(seed, deterministic=False, use_rank_shift=False):
+    """Set random seed.
+
+    Args:
+        seed (int): Seed to be used.
+        deterministic (bool): Whether to set the deterministic option for
+            CUDNN backend, i.e., set `torch.backends.cudnn.deterministic`
+            to True and `torch.backends.cudnn.benchmark` to False.
+            Default: False.
+        rank_shift (bool): Whether to add rank number to the random seed to
+            have different random seed in different threads. Default: False.
+    """
+    if use_rank_shift:
+        rank, _ = mmcv.runner.get_dist_info()
+        seed += rank
+    random.seed(seed)
+    np.random.seed(seed)
+    torch.manual_seed(seed)
+    torch.cuda.manual_seed(seed)
+    torch.cuda.manual_seed_all(seed)
+    os.environ['PYTHONHASHSEED'] = str(seed)
+    if deterministic:
+        torch.backends.cudnn.deterministic = True
+        torch.backends.cudnn.benchmark = False

lavis/common/annotator/uniformer/mmcv/utils/__init__.py

+# flake8: noqa
+# Copyright (c) OpenMMLab. All rights reserved.
+from .config import Config, ConfigDict, DictAction
+from .misc import (check_prerequisites, concat_list, deprecated_api_warning,
+                   has_method, import_modules_from_strings, is_list_of,
+                   is_method_overridden, is_seq_of, is_str, is_tuple_of,
+                   iter_cast, list_cast, requires_executable, requires_package,
+                   slice_list, to_1tuple, to_2tuple, to_3tuple, to_4tuple,
+                   to_ntuple, tuple_cast)
+from .path import (check_file_exist, fopen, is_filepath, mkdir_or_exist,
+                   scandir, symlink)
+from .progressbar import (ProgressBar, track_iter_progress,
+                          track_parallel_progress, track_progress)
+from .testing import (assert_attrs_equal, assert_dict_contains_subset,
+                      assert_dict_has_keys, assert_is_norm_layer,
+                      assert_keys_equal, assert_params_all_zeros,
+                      check_python_script)
+from .timer import Timer, TimerError, check_time
+from .version_utils import digit_version, get_git_hash
+
+try:
+    import torch
+except ImportError:
+    __all__ = [
+        'Config', 'ConfigDict', 'DictAction', 'is_str', 'iter_cast',
+        'list_cast', 'tuple_cast', 'is_seq_of', 'is_list_of', 'is_tuple_of',
+        'slice_list', 'concat_list', 'check_prerequisites', 'requires_package',
+        'requires_executable', 'is_filepath', 'fopen', 'check_file_exist',
+        'mkdir_or_exist', 'symlink', 'scandir', 'ProgressBar',
+        'track_progress', 'track_iter_progress', 'track_parallel_progress',
+        'Timer', 'TimerError', 'check_time', 'deprecated_api_warning',
+        'digit_version', 'get_git_hash', 'import_modules_from_strings',
+        'assert_dict_contains_subset', 'assert_attrs_equal',
+        'assert_dict_has_keys', 'assert_keys_equal', 'check_python_script',
+        'to_1tuple', 'to_2tuple', 'to_3tuple', 'to_4tuple', 'to_ntuple',
+        'is_method_overridden', 'has_method'
+    ]
+else:
+    from .env import collect_env
+    from .logging import get_logger, print_log
+    from .parrots_jit import jit, skip_no_elena
+    from .parrots_wrapper import (
+        TORCH_VERSION, BuildExtension, CppExtension, CUDAExtension, DataLoader,
+        PoolDataLoader, SyncBatchNorm, _AdaptiveAvgPoolNd, _AdaptiveMaxPoolNd,
+        _AvgPoolNd, _BatchNorm, _ConvNd, _ConvTransposeMixin, _InstanceNorm,
+        _MaxPoolNd, get_build_config, is_rocm_pytorch, _get_cuda_home)
+    from .registry import Registry, build_from_cfg
+    from .trace import is_jit_tracing
+    __all__ = [
+        'Config', 'ConfigDict', 'DictAction', 'collect_env', 'get_logger',
+        'print_log', 'is_str', 'iter_cast', 'list_cast', 'tuple_cast',
+        'is_seq_of', 'is_list_of', 'is_tuple_of', 'slice_list', 'concat_list',
+        'check_prerequisites', 'requires_package', 'requires_executable',
+        'is_filepath', 'fopen', 'check_file_exist', 'mkdir_or_exist',
+        'symlink', 'scandir', 'ProgressBar', 'track_progress',
+        'track_iter_progress', 'track_parallel_progress', 'Registry',
+        'build_from_cfg', 'Timer', 'TimerError', 'check_time', 'SyncBatchNorm',
+        '_AdaptiveAvgPoolNd', '_AdaptiveMaxPoolNd', '_AvgPoolNd', '_BatchNorm',
+        '_ConvNd', '_ConvTransposeMixin', '_InstanceNorm', '_MaxPoolNd',
+        'get_build_config', 'BuildExtension', 'CppExtension', 'CUDAExtension',
+        'DataLoader', 'PoolDataLoader', 'TORCH_VERSION',
+        'deprecated_api_warning', 'digit_version', 'get_git_hash',
+        'import_modules_from_strings', 'jit', 'skip_no_elena',
+        'assert_dict_contains_subset', 'assert_attrs_equal',
+        'assert_dict_has_keys', 'assert_keys_equal', 'assert_is_norm_layer',
+        'assert_params_all_zeros', 'check_python_script',
+        'is_method_overridden', 'is_jit_tracing', 'is_rocm_pytorch',
+        '_get_cuda_home', 'has_method'
+    ]

lavis/common/annotator/uniformer/mmcv/utils/config.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import ast
+import copy
+import os
+import os.path as osp
+import platform
+import shutil
+import sys
+import tempfile
+import uuid
+import warnings
+from argparse import Action, ArgumentParser
+from collections import abc
+from importlib import import_module
+
+from addict import Dict
+from yapf.yapflib.yapf_api import FormatCode
+
+from .misc import import_modules_from_strings
+from .path import check_file_exist
+
+if platform.system() == 'Windows':
+    import regex as re
+else:
+    import re
+
+BASE_KEY = '_base_'
+DELETE_KEY = '_delete_'
+DEPRECATION_KEY = '_deprecation_'
+RESERVED_KEYS = ['filename', 'text', 'pretty_text']
+
+
+class ConfigDict(Dict):
+
+    def __missing__(self, name):
+        raise KeyError(name)
+
+    def __getattr__(self, name):
+        try:
+            value = super(ConfigDict, self).__getattr__(name)
+        except KeyError:
+            ex = AttributeError(f"'{self.__class__.__name__}' object has no "
+                                f"attribute '{name}'")
+        except Exception as e:
+            ex = e
+        else:
+            return value
+        raise ex
+
+
+def add_args(parser, cfg, prefix=''):
+    for k, v in cfg.items():
+        if isinstance(v, str):
+            parser.add_argument('--' + prefix + k)
+        elif isinstance(v, int):
+            parser.add_argument('--' + prefix + k, type=int)
+        elif isinstance(v, float):
+            parser.add_argument('--' + prefix + k, type=float)
+        elif isinstance(v, bool):
+            parser.add_argument('--' + prefix + k, action='store_true')
+        elif isinstance(v, dict):
+            add_args(parser, v, prefix + k + '.')
+        elif isinstance(v, abc.Iterable):
+            parser.add_argument('--' + prefix + k, type=type(v[0]), nargs='+')
+        else:
+            print(f'cannot parse key {prefix + k} of type {type(v)}')
+    return parser
+
+
+class Config:
+    """A facility for config and config files.
+
+    It supports common file formats as configs: python/json/yaml. The interface
+    is the same as a dict object and also allows access config values as
+    attributes.
+
+    Example:
+        >>> cfg = Config(dict(a=1, b=dict(b1=[0, 1])))
+        >>> cfg.a
+        1
+        >>> cfg.b
+        {'b1': [0, 1]}
+        >>> cfg.b.b1
+        [0, 1]
+        >>> cfg = Config.fromfile('tests/data/config/a.py')
+        >>> cfg.filename
+        "/home/kchen/projects/mmcv/tests/data/config/a.py"
+        >>> cfg.item4
+        'test'
+        >>> cfg
+        "Config [path: /home/kchen/projects/mmcv/tests/data/config/a.py]: "
+        "{'item1': [1, 2], 'item2': {'a': 0}, 'item3': True, 'item4': 'test'}"
+    """
+
+    @staticmethod
+    def _validate_py_syntax(filename):
+        with open(filename, 'r', encoding='utf-8') as f:
+            # Setting encoding explicitly to resolve coding issue on windows
+            content = f.read()
+        try:
+            ast.parse(content)
+        except SyntaxError as e:
+            raise SyntaxError('There are syntax errors in config '
+                              f'file {filename}: {e}')
+
+    @staticmethod
+    def _substitute_predefined_vars(filename, temp_config_name):
+        file_dirname = osp.dirname(filename)
+        file_basename = osp.basename(filename)
+        file_basename_no_extension = osp.splitext(file_basename)[0]
+        file_extname = osp.splitext(filename)[1]
+        support_templates = dict(
+            fileDirname=file_dirname,
+            fileBasename=file_basename,
+            fileBasenameNoExtension=file_basename_no_extension,
+            fileExtname=file_extname)
+        with open(filename, 'r', encoding='utf-8') as f:
+            # Setting encoding explicitly to resolve coding issue on windows
+            config_file = f.read()
+        for key, value in support_templates.items():
+            regexp = r'\{\{\s*' + str(key) + r'\s*\}\}'
+            value = value.replace('\\', '/')
+            config_file = re.sub(regexp, value, config_file)
+        with open(temp_config_name, 'w', encoding='utf-8') as tmp_config_file:
+            tmp_config_file.write(config_file)
+
+    @staticmethod
+    def _pre_substitute_base_vars(filename, temp_config_name):
+        """Substitute base variable placehoders to string, so that parsing
+        would work."""
+        with open(filename, 'r', encoding='utf-8') as f:
+            # Setting encoding explicitly to resolve coding issue on windows
+            config_file = f.read()
+        base_var_dict = {}
+        regexp = r'\{\{\s*' + BASE_KEY + r'\.([\w\.]+)\s*\}\}'
+        base_vars = set(re.findall(regexp, config_file))
+        for base_var in base_vars:
+            randstr = f'_{base_var}_{uuid.uuid4().hex.lower()[:6]}'
+            base_var_dict[randstr] = base_var
+            regexp = r'\{\{\s*' + BASE_KEY + r'\.' + base_var + r'\s*\}\}'
+            config_file = re.sub(regexp, f'"{randstr}"', config_file)
+        with open(temp_config_name, 'w', encoding='utf-8') as tmp_config_file:
+            tmp_config_file.write(config_file)
+        return base_var_dict
+
+    @staticmethod
+    def _substitute_base_vars(cfg, base_var_dict, base_cfg):
+        """Substitute variable strings to their actual values."""
+        cfg = copy.deepcopy(cfg)
+
+        if isinstance(cfg, dict):
+            for k, v in cfg.items():
+                if isinstance(v, str) and v in base_var_dict:
+                    new_v = base_cfg
+                    for new_k in base_var_dict[v].split('.'):
+                        new_v = new_v[new_k]
+                    cfg[k] = new_v
+                elif isinstance(v, (list, tuple, dict)):
+                    cfg[k] = Config._substitute_base_vars(
+                        v, base_var_dict, base_cfg)
+        elif isinstance(cfg, tuple):
+            cfg = tuple(
+                Config._substitute_base_vars(c, base_var_dict, base_cfg)
+                for c in cfg)
+        elif isinstance(cfg, list):
+            cfg = [
+                Config._substitute_base_vars(c, base_var_dict, base_cfg)
+                for c in cfg
+            ]
+        elif isinstance(cfg, str) and cfg in base_var_dict:
+            new_v = base_cfg
+            for new_k in base_var_dict[cfg].split('.'):
+                new_v = new_v[new_k]
+            cfg = new_v
+
+        return cfg
+
+    @staticmethod
+    def _file2dict(filename, use_predefined_variables=True):
+        filename = osp.abspath(osp.expanduser(filename))
+        check_file_exist(filename)
+        fileExtname = osp.splitext(filename)[1]
+        if fileExtname not in ['.py', '.json', '.yaml', '.yml']:
+            raise IOError('Only py/yml/yaml/json type are supported now!')
+
+        with tempfile.TemporaryDirectory() as temp_config_dir:
+            temp_config_file = tempfile.NamedTemporaryFile(
+                dir=temp_config_dir, suffix=fileExtname)
+            if platform.system() == 'Windows':
+                temp_config_file.close()
+            temp_config_name = osp.basename(temp_config_file.name)
+            # Substitute predefined variables
+            if use_predefined_variables:
+                Config._substitute_predefined_vars(filename,
+                                                   temp_config_file.name)
+            else:
+                shutil.copyfile(filename, temp_config_file.name)
+            # Substitute base variables from placeholders to strings
+            base_var_dict = Config._pre_substitute_base_vars(
+                temp_config_file.name, temp_config_file.name)
+
+            if filename.endswith('.py'):
+                temp_module_name = osp.splitext(temp_config_name)[0]
+                sys.path.insert(0, temp_config_dir)
+                Config._validate_py_syntax(filename)
+                mod = import_module(temp_module_name)
+                sys.path.pop(0)
+                cfg_dict = {
+                    name: value
+                    for name, value in mod.__dict__.items()
+                    if not name.startswith('__')
+                }
+                # delete imported module
+                del sys.modules[temp_module_name]
+            elif filename.endswith(('.yml', '.yaml', '.json')):
+                import annotator.uniformer.mmcv as mmcv
+                cfg_dict = mmcv.load(temp_config_file.name)
+            # close temp file
+            temp_config_file.close()
+
+        # check deprecation information
+        if DEPRECATION_KEY in cfg_dict:
+            deprecation_info = cfg_dict.pop(DEPRECATION_KEY)
+            warning_msg = f'The config file {filename} will be deprecated ' \
+                'in the future.'
+            if 'expected' in deprecation_info:
+                warning_msg += f' Please use {deprecation_info["expected"]} ' \
+                    'instead.'
+            if 'reference' in deprecation_info:
+                warning_msg += ' More information can be found at ' \
+                    f'{deprecation_info["reference"]}'
+            warnings.warn(warning_msg)
+
+        cfg_text = filename + '\n'
+        with open(filename, 'r', encoding='utf-8') as f:
+            # Setting encoding explicitly to resolve coding issue on windows
+            cfg_text += f.read()
+
+        if BASE_KEY in cfg_dict:
+            cfg_dir = osp.dirname(filename)
+            base_filename = cfg_dict.pop(BASE_KEY)
+            base_filename = base_filename if isinstance(
+                base_filename, list) else [base_filename]
+
+            cfg_dict_list = list()
+            cfg_text_list = list()
+            for f in base_filename:
+                _cfg_dict, _cfg_text = Config._file2dict(osp.join(cfg_dir, f))
+                cfg_dict_list.append(_cfg_dict)
+                cfg_text_list.append(_cfg_text)
+
+            base_cfg_dict = dict()
+            for c in cfg_dict_list:
+                duplicate_keys = base_cfg_dict.keys() & c.keys()
+                if len(duplicate_keys) > 0:
+                    raise KeyError('Duplicate key is not allowed among bases. '
+                                   f'Duplicate keys: {duplicate_keys}')
+                base_cfg_dict.update(c)
+
+            # Substitute base variables from strings to their actual values
+            cfg_dict = Config._substitute_base_vars(cfg_dict, base_var_dict,
+                                                    base_cfg_dict)
+
+            base_cfg_dict = Config._merge_a_into_b(cfg_dict, base_cfg_dict)
+            cfg_dict = base_cfg_dict
+
+            # merge cfg_text
+            cfg_text_list.append(cfg_text)
+            cfg_text = '\n'.join(cfg_text_list)
+
+        return cfg_dict, cfg_text
+
+    @staticmethod
+    def _merge_a_into_b(a, b, allow_list_keys=False):
+        """merge dict ``a`` into dict ``b`` (non-inplace).
+
+        Values in ``a`` will overwrite ``b``. ``b`` is copied first to avoid
+        in-place modifications.
+
+        Args:
+            a (dict): The source dict to be merged into ``b``.
+            b (dict): The origin dict to be fetch keys from ``a``.
+            allow_list_keys (bool): If True, int string keys (e.g. '0', '1')
+              are allowed in source ``a`` and will replace the element of the
+              corresponding index in b if b is a list. Default: False.
+
+        Returns:
+            dict: The modified dict of ``b`` using ``a``.
+
+        Examples:
+            # Normally merge a into b.
+            >>> Config._merge_a_into_b(
+            ...     dict(obj=dict(a=2)), dict(obj=dict(a=1)))
+            {'obj': {'a': 2}}
+
+            # Delete b first and merge a into b.
+            >>> Config._merge_a_into_b(
+            ...     dict(obj=dict(_delete_=True, a=2)), dict(obj=dict(a=1)))
+            {'obj': {'a': 2}}
+
+            # b is a list
+            >>> Config._merge_a_into_b(
+            ...     {'0': dict(a=2)}, [dict(a=1), dict(b=2)], True)
+            [{'a': 2}, {'b': 2}]
+        """
+        b = b.copy()
+        for k, v in a.items():
+            if allow_list_keys and k.isdigit() and isinstance(b, list):
+                k = int(k)
+                if len(b) <= k:
+                    raise KeyError(f'Index {k} exceeds the length of list {b}')
+                b[k] = Config._merge_a_into_b(v, b[k], allow_list_keys)
+            elif isinstance(v,
+                            dict) and k in b and not v.pop(DELETE_KEY, False):
+                allowed_types = (dict, list) if allow_list_keys else dict
+                if not isinstance(b[k], allowed_types):
+                    raise TypeError(
+                        f'{k}={v} in child config cannot inherit from base '
+                        f'because {k} is a dict in the child config but is of '
+                        f'type {type(b[k])} in base config. You may set '
+                        f'`{DELETE_KEY}=True` to ignore the base config')
+                b[k] = Config._merge_a_into_b(v, b[k], allow_list_keys)
+            else:
+                b[k] = v
+        return b
+
+    @staticmethod
+    def fromfile(filename,
+                 use_predefined_variables=True,
+                 import_custom_modules=True):
+        cfg_dict, cfg_text = Config._file2dict(filename,
+                                               use_predefined_variables)
+        if import_custom_modules and cfg_dict.get('custom_imports', None):
+            import_modules_from_strings(**cfg_dict['custom_imports'])
+        return Config(cfg_dict, cfg_text=cfg_text, filename=filename)
+
+    @staticmethod
+    def fromstring(cfg_str, file_format):
+        """Generate config from config str.
+
+        Args:
+            cfg_str (str): Config str.
+            file_format (str): Config file format corresponding to the
+               config str. Only py/yml/yaml/json type are supported now!
+
+        Returns:
+            obj:`Config`: Config obj.
+        """
+        if file_format not in ['.py', '.json', '.yaml', '.yml']:
+            raise IOError('Only py/yml/yaml/json type are supported now!')
+        if file_format != '.py' and 'dict(' in cfg_str:
+            # check if users specify a wrong suffix for python
+            warnings.warn(
+                'Please check "file_format", the file format may be .py')
+        with tempfile.NamedTemporaryFile(
+                'w', encoding='utf-8', suffix=file_format,
+                delete=False) as temp_file:
+            temp_file.write(cfg_str)
+            # on windows, previous implementation cause error
+            # see PR 1077 for details
+        cfg = Config.fromfile(temp_file.name)
+        os.remove(temp_file.name)
+        return cfg
+
+    @staticmethod
+    def auto_argparser(description=None):
+        """Generate argparser from config file automatically (experimental)"""
+        partial_parser = ArgumentParser(description=description)
+        partial_parser.add_argument('config', help='config file path')
+        cfg_file = partial_parser.parse_known_args()[0].config
+        cfg = Config.fromfile(cfg_file)
+        parser = ArgumentParser(description=description)
+        parser.add_argument('config', help='config file path')
+        add_args(parser, cfg)
+        return parser, cfg
+
+    def __init__(self, cfg_dict=None, cfg_text=None, filename=None):
+        if cfg_dict is None:
+            cfg_dict = dict()
+        elif not isinstance(cfg_dict, dict):
+            raise TypeError('cfg_dict must be a dict, but '
+                            f'got {type(cfg_dict)}')
+        for key in cfg_dict:
+            if key in RESERVED_KEYS:
+                raise KeyError(f'{key} is reserved for config file')
+
+        super(Config, self).__setattr__('_cfg_dict', ConfigDict(cfg_dict))
+        super(Config, self).__setattr__('_filename', filename)
+        if cfg_text:
+            text = cfg_text
+        elif filename:
+            with open(filename, 'r') as f:
+                text = f.read()
+        else:
+            text = ''
+        super(Config, self).__setattr__('_text', text)
+
+    @property
+    def filename(self):
+        return self._filename
+
+    @property
+    def text(self):
+        return self._text
+
+    @property
+    def pretty_text(self):
+
+        indent = 4
+
+        def _indent(s_, num_spaces):
+            s = s_.split('\n')
+            if len(s) == 1:
+                return s_
+            first = s.pop(0)
+            s = [(num_spaces * ' ') + line for line in s]
+            s = '\n'.join(s)
+            s = first + '\n' + s
+            return s
+
+        def _format_basic_types(k, v, use_mapping=False):
+            if isinstance(v, str):
+                v_str = f"'{v}'"
+            else:
+                v_str = str(v)
+
+            if use_mapping:
+                k_str = f"'{k}'" if isinstance(k, str) else str(k)
+                attr_str = f'{k_str}: {v_str}'
+            else:
+                attr_str = f'{str(k)}={v_str}'
+            attr_str = _indent(attr_str, indent)
+
+            return attr_str
+
+        def _format_list(k, v, use_mapping=False):
+            # check if all items in the list are dict
+            if all(isinstance(_, dict) for _ in v):
+                v_str = '[\n'
+                v_str += '\n'.join(
+                    f'dict({_indent(_format_dict(v_), indent)}),'
+                    for v_ in v).rstrip(',')
+                if use_mapping:
+                    k_str = f"'{k}'" if isinstance(k, str) else str(k)
+                    attr_str = f'{k_str}: {v_str}'
+                else:
+                    attr_str = f'{str(k)}={v_str}'
+                attr_str = _indent(attr_str, indent) + ']'
+            else:
+                attr_str = _format_basic_types(k, v, use_mapping)
+            return attr_str
+
+        def _contain_invalid_identifier(dict_str):
+            contain_invalid_identifier = False
+            for key_name in dict_str:
+                contain_invalid_identifier |= \
+                    (not str(key_name).isidentifier())
+            return contain_invalid_identifier
+
+        def _format_dict(input_dict, outest_level=False):
+            r = ''
+            s = []
+
+            use_mapping = _contain_invalid_identifier(input_dict)
+            if use_mapping:
+                r += '{'
+            for idx, (k, v) in enumerate(input_dict.items()):
+                is_last = idx >= len(input_dict) - 1
+                end = '' if outest_level or is_last else ','
+                if isinstance(v, dict):
+                    v_str = '\n' + _format_dict(v)
+                    if use_mapping:
+                        k_str = f"'{k}'" if isinstance(k, str) else str(k)
+                        attr_str = f'{k_str}: dict({v_str}'
+                    else:
+                        attr_str = f'{str(k)}=dict({v_str}'
+                    attr_str = _indent(attr_str, indent) + ')' + end
+                elif isinstance(v, list):
+                    attr_str = _format_list(k, v, use_mapping) + end
+                else:
+                    attr_str = _format_basic_types(k, v, use_mapping) + end
+
+                s.append(attr_str)
+            r += '\n'.join(s)
+            if use_mapping:
+                r += '}'
+            return r
+
+        cfg_dict = self._cfg_dict.to_dict()
+        text = _format_dict(cfg_dict, outest_level=True)
+        # copied from setup.cfg
+        yapf_style = dict(
+            based_on_style='pep8',
+            blank_line_before_nested_class_or_def=True,
+            split_before_expression_after_opening_paren=True)
+        text, _ = FormatCode(text, style_config=yapf_style, verify=True)
+
+        return text
+
+    def __repr__(self):
+        return f'Config (path: {self.filename}): {self._cfg_dict.__repr__()}'
+
+    def __len__(self):
+        return len(self._cfg_dict)
+
+    def __getattr__(self, name):
+        return getattr(self._cfg_dict, name)
+
+    def __getitem__(self, name):
+        return self._cfg_dict.__getitem__(name)
+
+    def __setattr__(self, name, value):
+        if isinstance(value, dict):
+            value = ConfigDict(value)
+        self._cfg_dict.__setattr__(name, value)
+
+    def __setitem__(self, name, value):
+        if isinstance(value, dict):
+            value = ConfigDict(value)
+        self._cfg_dict.__setitem__(name, value)
+
+    def __iter__(self):
+        return iter(self._cfg_dict)
+
+    def __getstate__(self):
+        return (self._cfg_dict, self._filename, self._text)
+
+    def __setstate__(self, state):
+        _cfg_dict, _filename, _text = state
+        super(Config, self).__setattr__('_cfg_dict', _cfg_dict)
+        super(Config, self).__setattr__('_filename', _filename)
+        super(Config, self).__setattr__('_text', _text)
+
+    def dump(self, file=None):
+        cfg_dict = super(Config, self).__getattribute__('_cfg_dict').to_dict()
+        if self.filename.endswith('.py'):
+            if file is None:
+                return self.pretty_text
+            else:
+                with open(file, 'w', encoding='utf-8') as f:
+                    f.write(self.pretty_text)
+        else:
+            import annotator.uniformer.mmcv as mmcv
+            if file is None:
+                file_format = self.filename.split('.')[-1]
+                return mmcv.dump(cfg_dict, file_format=file_format)
+            else:
+                mmcv.dump(cfg_dict, file)
+
+    def merge_from_dict(self, options, allow_list_keys=True):
+        """Merge list into cfg_dict.
+
+        Merge the dict parsed by MultipleKVAction into this cfg.
+
+        Examples:
+            >>> options = {'model.backbone.depth': 50,
+            ...            'model.backbone.with_cp':True}
+            >>> cfg = Config(dict(model=dict(backbone=dict(type='ResNet'))))
+            >>> cfg.merge_from_dict(options)
+            >>> cfg_dict = super(Config, self).__getattribute__('_cfg_dict')
+            >>> assert cfg_dict == dict(
+            ...     model=dict(backbone=dict(depth=50, with_cp=True)))
+
+            # Merge list element
+            >>> cfg = Config(dict(pipeline=[
+            ...     dict(type='LoadImage'), dict(type='LoadAnnotations')]))
+            >>> options = dict(pipeline={'0': dict(type='SelfLoadImage')})
+            >>> cfg.merge_from_dict(options, allow_list_keys=True)
+            >>> cfg_dict = super(Config, self).__getattribute__('_cfg_dict')
+            >>> assert cfg_dict == dict(pipeline=[
+            ...     dict(type='SelfLoadImage'), dict(type='LoadAnnotations')])
+
+        Args:
+            options (dict): dict of configs to merge from.
+            allow_list_keys (bool): If True, int string keys (e.g. '0', '1')
+              are allowed in ``options`` and will replace the element of the
+              corresponding index in the config if the config is a list.
+              Default: True.
+        """
+        option_cfg_dict = {}
+        for full_key, v in options.items():
+            d = option_cfg_dict
+            key_list = full_key.split('.')
+            for subkey in key_list[:-1]:
+                d.setdefault(subkey, ConfigDict())
+                d = d[subkey]
+            subkey = key_list[-1]
+            d[subkey] = v
+
+        cfg_dict = super(Config, self).__getattribute__('_cfg_dict')
+        super(Config, self).__setattr__(
+            '_cfg_dict',
+            Config._merge_a_into_b(
+                option_cfg_dict, cfg_dict, allow_list_keys=allow_list_keys))
+
+
+class DictAction(Action):
+    """
+    argparse action to split an argument into KEY=VALUE form
+    on the first = and append to a dictionary. List options can
+    be passed as comma separated values, i.e 'KEY=V1,V2,V3', or with explicit
+    brackets, i.e. 'KEY=[V1,V2,V3]'. It also support nested brackets to build
+    list/tuple values. e.g. 'KEY=[(V1,V2),(V3,V4)]'
+    """
+
+    @staticmethod
+    def _parse_int_float_bool(val):
+        try:
+            return int(val)
+        except ValueError:
+            pass
+        try:
+            return float(val)
+        except ValueError:
+            pass
+        if val.lower() in ['true', 'false']:
+            return True if val.lower() == 'true' else False
+        return val
+
+    @staticmethod
+    def _parse_iterable(val):
+        """Parse iterable values in the string.
+
+        All elements inside '()' or '[]' are treated as iterable values.
+
+        Args:
+            val (str): Value string.
+
+        Returns:
+            list | tuple: The expanded list or tuple from the string.
+
+        Examples:
+            >>> DictAction._parse_iterable('1,2,3')
+            [1, 2, 3]
+            >>> DictAction._parse_iterable('[a, b, c]')
+            ['a', 'b', 'c']
+            >>> DictAction._parse_iterable('[(1, 2, 3), [a, b], c]')
+            [(1, 2, 3), ['a', 'b'], 'c']
+        """
+
+        def find_next_comma(string):
+            """Find the position of next comma in the string.
+
+            If no ',' is found in the string, return the string length. All
+            chars inside '()' and '[]' are treated as one element and thus ','
+            inside these brackets are ignored.
+            """
+            assert (string.count('(') == string.count(')')) and (
+                    string.count('[') == string.count(']')), \
+                f'Imbalanced brackets exist in {string}'
+            end = len(string)
+            for idx, char in enumerate(string):
+                pre = string[:idx]
+                # The string before this ',' is balanced
+                if ((char == ',') and (pre.count('(') == pre.count(')'))
+                        and (pre.count('[') == pre.count(']'))):
+                    end = idx
+                    break
+            return end
+
+        # Strip ' and " characters and replace whitespace.
+        val = val.strip('\'\"').replace(' ', '')
+        is_tuple = False
+        if val.startswith('(') and val.endswith(')'):
+            is_tuple = True
+            val = val[1:-1]
+        elif val.startswith('[') and val.endswith(']'):
+            val = val[1:-1]
+        elif ',' not in val:
+            # val is a single value
+            return DictAction._parse_int_float_bool(val)
+
+        values = []
+        while len(val) > 0:
+            comma_idx = find_next_comma(val)
+            element = DictAction._parse_iterable(val[:comma_idx])
+            values.append(element)
+            val = val[comma_idx + 1:]
+        if is_tuple:
+            values = tuple(values)
+        return values
+
+    def __call__(self, parser, namespace, values, option_string=None):
+        options = {}
+        for kv in values:
+            key, val = kv.split('=', maxsplit=1)
+            options[key] = self._parse_iterable(val)
+        setattr(namespace, self.dest, options)

lavis/common/annotator/uniformer/mmcv/utils/env.py

+# Copyright (c) OpenMMLab. All rights reserved.
+"""This file holding some environment constant for sharing by other files."""
+
+import os.path as osp
+import subprocess
+import sys
+from collections import defaultdict
+
+import cv2
+import torch
+
+import annotator.uniformer.mmcv as mmcv
+from .parrots_wrapper import get_build_config
+
+
+def collect_env():
+    """Collect the information of the running environments.
+
+    Returns:
+        dict: The environment information. The following fields are contained.
+
+            - sys.platform: The variable of ``sys.platform``.
+            - Python: Python version.
+            - CUDA available: Bool, indicating if CUDA is available.
+            - GPU devices: Device type of each GPU.
+            - CUDA_HOME (optional): The env var ``CUDA_HOME``.
+            - NVCC (optional): NVCC version.
+            - GCC: GCC version, "n/a" if GCC is not installed.
+            - PyTorch: PyTorch version.
+            - PyTorch compiling details: The output of \
+                ``torch.__config__.show()``.
+            - TorchVision (optional): TorchVision version.
+            - OpenCV: OpenCV version.
+            - MMCV: MMCV version.
+            - MMCV Compiler: The GCC version for compiling MMCV ops.
+            - MMCV CUDA Compiler: The CUDA version for compiling MMCV ops.
+    """
+    env_info = {}
+    env_info['sys.platform'] = sys.platform
+    env_info['Python'] = sys.version.replace('\n', '')
+
+    cuda_available = torch.cuda.is_available()
+    env_info['CUDA available'] = cuda_available
+
+    if cuda_available:
+        devices = defaultdict(list)
+        for k in range(torch.cuda.device_count()):
+            devices[torch.cuda.get_device_name(k)].append(str(k))
+        for name, device_ids in devices.items():
+            env_info['GPU ' + ','.join(device_ids)] = name
+
+        from annotator.uniformer.mmcv.utils.parrots_wrapper import _get_cuda_home
+        CUDA_HOME = _get_cuda_home()
+        env_info['CUDA_HOME'] = CUDA_HOME
+
+        if CUDA_HOME is not None and osp.isdir(CUDA_HOME):
+            try:
+                nvcc = osp.join(CUDA_HOME, 'bin/nvcc')
+                nvcc = subprocess.check_output(
+                    f'"{nvcc}" -V | tail -n1', shell=True)
+                nvcc = nvcc.decode('utf-8').strip()
+            except subprocess.SubprocessError:
+                nvcc = 'Not Available'
+            env_info['NVCC'] = nvcc
+
+    try:
+        gcc = subprocess.check_output('gcc --version | head -n1', shell=True)
+        gcc = gcc.decode('utf-8').strip()
+        env_info['GCC'] = gcc
+    except subprocess.CalledProcessError:  # gcc is unavailable
+        env_info['GCC'] = 'n/a'
+
+    env_info['PyTorch'] = torch.__version__
+    env_info['PyTorch compiling details'] = get_build_config()
+
+    try:
+        import torchvision
+        env_info['TorchVision'] = torchvision.__version__
+    except ModuleNotFoundError:
+        pass
+
+    env_info['OpenCV'] = cv2.__version__
+
+    env_info['MMCV'] = mmcv.__version__
+
+    try:
+        from annotator.uniformer.mmcv.ops import get_compiler_version, get_compiling_cuda_version
+    except ModuleNotFoundError:
+        env_info['MMCV Compiler'] = 'n/a'
+        env_info['MMCV CUDA Compiler'] = 'n/a'
+    else:
+        env_info['MMCV Compiler'] = get_compiler_version()
+        env_info['MMCV CUDA Compiler'] = get_compiling_cuda_version()
+
+    return env_info

lavis/common/annotator/uniformer/mmcv/utils/ext_loader.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import importlib
+import os
+import pkgutil
+import warnings
+from collections import namedtuple
+
+import torch
+
+if torch.__version__ != 'parrots':
+
+    def load_ext(name, funcs):
+        ext = importlib.import_module('mmcv.' + name)
+        for fun in funcs:
+            assert hasattr(ext, fun), f'{fun} miss in module {name}'
+        return ext
+else:
+    from parrots import extension
+    from parrots.base import ParrotsException
+
+    has_return_value_ops = [
+        'nms',
+        'softnms',
+        'nms_match',
+        'nms_rotated',
+        'top_pool_forward',
+        'top_pool_backward',
+        'bottom_pool_forward',
+        'bottom_pool_backward',
+        'left_pool_forward',
+        'left_pool_backward',
+        'right_pool_forward',
+        'right_pool_backward',
+        'fused_bias_leakyrelu',
+        'upfirdn2d',
+        'ms_deform_attn_forward',
+        'pixel_group',
+        'contour_expand',
+    ]
+
+    def get_fake_func(name, e):
+
+        def fake_func(*args, **kwargs):
+            warnings.warn(f'{name} is not supported in parrots now')
+            raise e
+
+        return fake_func
+
+    def load_ext(name, funcs):
+        ExtModule = namedtuple('ExtModule', funcs)
+        ext_list = []
+        lib_root = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))
+        for fun in funcs:
+            try:
+                ext_fun = extension.load(fun, name, lib_dir=lib_root)
+            except ParrotsException as e:
+                if 'No element registered' not in e.message:
+                    warnings.warn(e.message)
+                ext_fun = get_fake_func(fun, e)
+                ext_list.append(ext_fun)
+            else:
+                if fun in has_return_value_ops:
+                    ext_list.append(ext_fun.op)
+                else:
+                    ext_list.append(ext_fun.op_)
+        return ExtModule(*ext_list)
+
+
+def check_ops_exist():
+    ext_loader = pkgutil.find_loader('mmcv._ext')
+    return ext_loader is not None

lavis/common/annotator/uniformer/mmcv/utils/logging.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import logging
+
+import torch.distributed as dist
+
+logger_initialized = {}
+
+
+def get_logger(name, log_file=None, log_level=logging.INFO, file_mode='w'):
+    """Initialize and get a logger by name.
+
+    If the logger has not been initialized, this method will initialize the
+    logger by adding one or two handlers, otherwise the initialized logger will
+    be directly returned. During initialization, a StreamHandler will always be
+    added. If `log_file` is specified and the process rank is 0, a FileHandler
+    will also be added.
+
+    Args:
+        name (str): Logger name.
+        log_file (str | None): The log filename. If specified, a FileHandler
+            will be added to the logger.
+        log_level (int): The logger level. Note that only the process of
+            rank 0 is affected, and other processes will set the level to
+            "Error" thus be silent most of the time.
+        file_mode (str): The file mode used in opening log file.
+            Defaults to 'w'.
+
+    Returns:
+        logging.Logger: The expected logger.
+    """
+    logger = logging.getLogger(name)
+    if name in logger_initialized:
+        return logger
+    # handle hierarchical names
+    # e.g., logger "a" is initialized, then logger "a.b" will skip the
+    # initialization since it is a child of "a".
+    for logger_name in logger_initialized:
+        if name.startswith(logger_name):
+            return logger
+
+    # handle duplicate logs to the console
+    # Starting in 1.8.0, PyTorch DDP attaches a StreamHandler <stderr> (NOTSET)
+    # to the root logger. As logger.propagate is True by default, this root
+    # level handler causes logging messages from rank>0 processes to
+    # unexpectedly show up on the console, creating much unwanted clutter.
+    # To fix this issue, we set the root logger's StreamHandler, if any, to log
+    # at the ERROR level.
+    for handler in logger.root.handlers:
+        if type(handler) is logging.StreamHandler:
+            handler.setLevel(logging.ERROR)
+
+    stream_handler = logging.StreamHandler()
+    handlers = [stream_handler]
+
+    if dist.is_available() and dist.is_initialized():
+        rank = dist.get_rank()
+    else:
+        rank = 0
+
+    # only rank 0 will add a FileHandler
+    if rank == 0 and log_file is not None:
+        # Here, the default behaviour of the official logger is 'a'. Thus, we
+        # provide an interface to change the file mode to the default
+        # behaviour.
+        file_handler = logging.FileHandler(log_file, file_mode)
+        handlers.append(file_handler)
+
+    formatter = logging.Formatter(
+        '%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+    for handler in handlers:
+        handler.setFormatter(formatter)
+        handler.setLevel(log_level)
+        logger.addHandler(handler)
+
+    if rank == 0:
+        logger.setLevel(log_level)
+    else:
+        logger.setLevel(logging.ERROR)
+
+    logger_initialized[name] = True
+
+    return logger
+
+
+def print_log(msg, logger=None, level=logging.INFO):
+    """Print a log message.
+
+    Args:
+        msg (str): The message to be logged.
+        logger (logging.Logger | str | None): The logger to be used.
+            Some special loggers are:
+            - "silent": no message will be printed.
+            - other str: the logger obtained with `get_root_logger(logger)`.
+            - None: The `print()` method will be used to print log messages.
+        level (int): Logging level. Only available when `logger` is a Logger
+            object or "root".
+    """
+    if logger is None:
+        print(msg)
+    elif isinstance(logger, logging.Logger):
+        logger.log(level, msg)
+    elif logger == 'silent':
+        pass
+    elif isinstance(logger, str):
+        _logger = get_logger(logger)
+        _logger.log(level, msg)
+    else:
+        raise TypeError(
+            'logger should be either a logging.Logger object, str, '
+            f'"silent" or None, but got {type(logger)}')

lavis/common/annotator/uniformer/mmcv/utils/misc.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import collections.abc
+import functools
+import itertools
+import subprocess
+import warnings
+from collections import abc
+from importlib import import_module
+from inspect import getfullargspec
+from itertools import repeat
+
+
+# From PyTorch internals
+def _ntuple(n):
+
+    def parse(x):
+        if isinstance(x, collections.abc.Iterable):
+            return x
+        return tuple(repeat(x, n))
+
+    return parse
+
+
+to_1tuple = _ntuple(1)
+to_2tuple = _ntuple(2)
+to_3tuple = _ntuple(3)
+to_4tuple = _ntuple(4)
+to_ntuple = _ntuple
+
+
+def is_str(x):
+    """Whether the input is an string instance.
+
+    Note: This method is deprecated since python 2 is no longer supported.
+    """
+    return isinstance(x, str)
+
+
+def import_modules_from_strings(imports, allow_failed_imports=False):
+    """Import modules from the given list of strings.
+
+    Args:
+        imports (list | str | None): The given module names to be imported.
+        allow_failed_imports (bool): If True, the failed imports will return
+            None. Otherwise, an ImportError is raise. Default: False.
+
+    Returns:
+        list[module] | module | None: The imported modules.
+
+    Examples:
+        >>> osp, sys = import_modules_from_strings(
+        ...     ['os.path', 'sys'])
+        >>> import os.path as osp_
+        >>> import sys as sys_
+        >>> assert osp == osp_
+        >>> assert sys == sys_
+    """
+    if not imports:
+        return
+    single_import = False
+    if isinstance(imports, str):
+        single_import = True
+        imports = [imports]
+    if not isinstance(imports, list):
+        raise TypeError(
+            f'custom_imports must be a list but got type {type(imports)}')
+    imported = []
+    for imp in imports:
+        if not isinstance(imp, str):
+            raise TypeError(
+                f'{imp} is of type {type(imp)} and cannot be imported.')
+        try:
+            imported_tmp = import_module(imp)
+        except ImportError:
+            if allow_failed_imports:
+                warnings.warn(f'{imp} failed to import and is ignored.',
+                              UserWarning)
+                imported_tmp = None
+            else:
+                raise ImportError
+        imported.append(imported_tmp)
+    if single_import:
+        imported = imported[0]
+    return imported
+
+
+def iter_cast(inputs, dst_type, return_type=None):
+    """Cast elements of an iterable object into some type.
+
+    Args:
+        inputs (Iterable): The input object.
+        dst_type (type): Destination type.
+        return_type (type, optional): If specified, the output object will be
+            converted to this type, otherwise an iterator.
+
+    Returns:
+        iterator or specified type: The converted object.
+    """
+    if not isinstance(inputs, abc.Iterable):
+        raise TypeError('inputs must be an iterable object')
+    if not isinstance(dst_type, type):
+        raise TypeError('"dst_type" must be a valid type')
+
+    out_iterable = map(dst_type, inputs)
+
+    if return_type is None:
+        return out_iterable
+    else:
+        return return_type(out_iterable)
+
+
+def list_cast(inputs, dst_type):
+    """Cast elements of an iterable object into a list of some type.
+
+    A partial method of :func:`iter_cast`.
+    """
+    return iter_cast(inputs, dst_type, return_type=list)
+
+
+def tuple_cast(inputs, dst_type):
+    """Cast elements of an iterable object into a tuple of some type.
+
+    A partial method of :func:`iter_cast`.
+    """
+    return iter_cast(inputs, dst_type, return_type=tuple)
+
+
+def is_seq_of(seq, expected_type, seq_type=None):
+    """Check whether it is a sequence of some type.
+
+    Args:
+        seq (Sequence): The sequence to be checked.
+        expected_type (type): Expected type of sequence items.
+        seq_type (type, optional): Expected sequence type.
+
+    Returns:
+        bool: Whether the sequence is valid.
+    """
+    if seq_type is None:
+        exp_seq_type = abc.Sequence
+    else:
+        assert isinstance(seq_type, type)
+        exp_seq_type = seq_type
+    if not isinstance(seq, exp_seq_type):
+        return False
+    for item in seq:
+        if not isinstance(item, expected_type):
+            return False
+    return True
+
+
+def is_list_of(seq, expected_type):
+    """Check whether it is a list of some type.
+
+    A partial method of :func:`is_seq_of`.
+    """
+    return is_seq_of(seq, expected_type, seq_type=list)
+
+
+def is_tuple_of(seq, expected_type):
+    """Check whether it is a tuple of some type.
+
+    A partial method of :func:`is_seq_of`.
+    """
+    return is_seq_of(seq, expected_type, seq_type=tuple)
+
+
+def slice_list(in_list, lens):
+    """Slice a list into several sub lists by a list of given length.
+
+    Args:
+        in_list (list): The list to be sliced.
+        lens(int or list): The expected length of each out list.
+
+    Returns:
+        list: A list of sliced list.
+    """
+    if isinstance(lens, int):
+        assert len(in_list) % lens == 0
+        lens = [lens] * int(len(in_list) / lens)
+    if not isinstance(lens, list):
+        raise TypeError('"indices" must be an integer or a list of integers')
+    elif sum(lens) != len(in_list):
+        raise ValueError('sum of lens and list length does not '
+                         f'match: {sum(lens)} != {len(in_list)}')
+    out_list = []
+    idx = 0
+    for i in range(len(lens)):
+        out_list.append(in_list[idx:idx + lens[i]])
+        idx += lens[i]
+    return out_list
+
+
+def concat_list(in_list):
+    """Concatenate a list of list into a single list.
+
+    Args:
+        in_list (list): The list of list to be merged.
+
+    Returns:
+        list: The concatenated flat list.
+    """
+    return list(itertools.chain(*in_list))
+
+
+def check_prerequisites(
+        prerequisites,
+        checker,
+        msg_tmpl='Prerequisites "{}" are required in method "{}" but not '
+        'found, please install them first.'):  # yapf: disable
+    """A decorator factory to check if prerequisites are satisfied.
+
+    Args:
+        prerequisites (str of list[str]): Prerequisites to be checked.
+        checker (callable): The checker method that returns True if a
+            prerequisite is meet, False otherwise.
+        msg_tmpl (str): The message template with two variables.
+
+    Returns:
+        decorator: A specific decorator.
+    """
+
+    def wrap(func):
+
+        @functools.wraps(func)
+        def wrapped_func(*args, **kwargs):
+            requirements = [prerequisites] if isinstance(
+                prerequisites, str) else prerequisites
+            missing = []
+            for item in requirements:
+                if not checker(item):
+                    missing.append(item)
+            if missing:
+                print(msg_tmpl.format(', '.join(missing), func.__name__))
+                raise RuntimeError('Prerequisites not meet.')
+            else:
+                return func(*args, **kwargs)
+
+        return wrapped_func
+
+    return wrap
+
+
+def _check_py_package(package):
+    try:
+        import_module(package)
+    except ImportError:
+        return False
+    else:
+        return True
+
+
+def _check_executable(cmd):
+    if subprocess.call(f'which {cmd}', shell=True) != 0:
+        return False
+    else:
+        return True
+
+
+def requires_package(prerequisites):
+    """A decorator to check if some python packages are installed.
+
+    Example:
+        >>> @requires_package('numpy')
+        >>> func(arg1, args):
+        >>>     return numpy.zeros(1)
+        array([0.])
+        >>> @requires_package(['numpy', 'non_package'])
+        >>> func(arg1, args):
+        >>>     return numpy.zeros(1)
+        ImportError
+    """
+    return check_prerequisites(prerequisites, checker=_check_py_package)
+
+
+def requires_executable(prerequisites):
+    """A decorator to check if some executable files are installed.
+
+    Example:
+        >>> @requires_executable('ffmpeg')
+        >>> func(arg1, args):
+        >>>     print(1)
+        1
+    """
+    return check_prerequisites(prerequisites, checker=_check_executable)
+
+
+def deprecated_api_warning(name_dict, cls_name=None):
+    """A decorator to check if some arguments are deprecate and try to replace
+    deprecate src_arg_name to dst_arg_name.
+
+    Args:
+        name_dict(dict):
+            key (str): Deprecate argument names.
+            val (str): Expected argument names.
+
+    Returns:
+        func: New function.
+    """
+
+    def api_warning_wrapper(old_func):
+
+        @functools.wraps(old_func)
+        def new_func(*args, **kwargs):
+            # get the arg spec of the decorated method
+            args_info = getfullargspec(old_func)
+            # get name of the function
+            func_name = old_func.__name__
+            if cls_name is not None:
+                func_name = f'{cls_name}.{func_name}'
+            if args:
+                arg_names = args_info.args[:len(args)]
+                for src_arg_name, dst_arg_name in name_dict.items():
+                    if src_arg_name in arg_names:
+                        warnings.warn(
+                            f'"{src_arg_name}" is deprecated in '
+                            f'`{func_name}`, please use "{dst_arg_name}" '
+                            'instead')
+                        arg_names[arg_names.index(src_arg_name)] = dst_arg_name
+            if kwargs:
+                for src_arg_name, dst_arg_name in name_dict.items():
+                    if src_arg_name in kwargs:
+
+                        assert dst_arg_name not in kwargs, (
+                            f'The expected behavior is to replace '
+                            f'the deprecated key `{src_arg_name}` to '
+                            f'new key `{dst_arg_name}`, but got them '
+                            f'in the arguments at the same time, which '
+                            f'is confusing. `{src_arg_name} will be '
+                            f'deprecated in the future, please '
+                            f'use `{dst_arg_name}` instead.')
+
+                        warnings.warn(
+                            f'"{src_arg_name}" is deprecated in '
+                            f'`{func_name}`, please use "{dst_arg_name}" '
+                            'instead')
+                        kwargs[dst_arg_name] = kwargs.pop(src_arg_name)
+
+            # apply converted arguments to the decorated method
+            output = old_func(*args, **kwargs)
+            return output
+
+        return new_func
+
+    return api_warning_wrapper
+
+
+def is_method_overridden(method, base_class, derived_class):
+    """Check if a method of base class is overridden in derived class.
+
+    Args:
+        method (str): the method name to check.
+        base_class (type): the class of the base class.
+        derived_class (type | Any): the class or instance of the derived class.
+    """
+    assert isinstance(base_class, type), \
+        "base_class doesn't accept instance, Please pass class instead."
+
+    if not isinstance(derived_class, type):
+        derived_class = derived_class.__class__
+
+    base_method = getattr(base_class, method)
+    derived_method = getattr(derived_class, method)
+    return derived_method != base_method
+
+
+def has_method(obj: object, method: str) -> bool:
+    """Check whether the object has a method.
+
+    Args:
+        method (str): The method name to check.
+        obj (object): The object to check.
+
+    Returns:
+        bool: True if the object has the method else False.
+    """
+    return hasattr(obj, method) and callable(getattr(obj, method))

lavis/common/annotator/uniformer/mmcv/utils/parrots_jit.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import os
+
+from .parrots_wrapper import TORCH_VERSION
+
+parrots_jit_option = os.getenv('PARROTS_JIT_OPTION')
+
+if TORCH_VERSION == 'parrots' and parrots_jit_option == 'ON':
+    from parrots.jit import pat as jit
+else:
+
+    def jit(func=None,
+            check_input=None,
+            full_shape=True,
+            derivate=False,
+            coderize=False,
+            optimize=False):
+
+        def wrapper(func):
+
+            def wrapper_inner(*args, **kargs):
+                return func(*args, **kargs)
+
+            return wrapper_inner
+
+        if func is None:
+            return wrapper
+        else:
+            return func
+
+
+if TORCH_VERSION == 'parrots':
+    from parrots.utils.tester import skip_no_elena
+else:
+
+    def skip_no_elena(func):
+
+        def wrapper(*args, **kargs):
+            return func(*args, **kargs)
+
+        return wrapper

lavis/common/annotator/uniformer/mmcv/utils/parrots_wrapper.py

+# Copyright (c) OpenMMLab. All rights reserved.
+from functools import partial
+
+import torch
+
+TORCH_VERSION = torch.__version__
+
+
+def is_rocm_pytorch() -> bool:
+    is_rocm = False
+    if TORCH_VERSION != 'parrots':
+        try:
+            from torch.utils.cpp_extension import ROCM_HOME
+            is_rocm = True if ((torch.version.hip is not None) and
+                               (ROCM_HOME is not None)) else False
+        except ImportError:
+            pass
+    return is_rocm
+
+
+def _get_cuda_home():
+    if TORCH_VERSION == 'parrots':
+        from parrots.utils.build_extension import CUDA_HOME
+    else:
+        if is_rocm_pytorch():
+            from torch.utils.cpp_extension import ROCM_HOME
+            CUDA_HOME = ROCM_HOME
+        else:
+            from torch.utils.cpp_extension import CUDA_HOME
+    return CUDA_HOME
+
+
+def get_build_config():
+    if TORCH_VERSION == 'parrots':
+        from parrots.config import get_build_info
+        return get_build_info()
+    else:
+        return torch.__config__.show()
+
+
+def _get_conv():
+    if TORCH_VERSION == 'parrots':
+        from parrots.nn.modules.conv import _ConvNd, _ConvTransposeMixin
+    else:
+        from torch.nn.modules.conv import _ConvNd, _ConvTransposeMixin
+    return _ConvNd, _ConvTransposeMixin
+
+
+def _get_dataloader():
+    if TORCH_VERSION == 'parrots':
+        from torch.utils.data import DataLoader, PoolDataLoader
+    else:
+        from torch.utils.data import DataLoader
+        PoolDataLoader = DataLoader
+    return DataLoader, PoolDataLoader
+
+
+def _get_extension():
+    if TORCH_VERSION == 'parrots':
+        from parrots.utils.build_extension import BuildExtension, Extension
+        CppExtension = partial(Extension, cuda=False)
+        CUDAExtension = partial(Extension, cuda=True)
+    else:
+        from torch.utils.cpp_extension import (BuildExtension, CppExtension,
+                                               CUDAExtension)
+    return BuildExtension, CppExtension, CUDAExtension
+
+
+def _get_pool():
+    if TORCH_VERSION == 'parrots':
+        from parrots.nn.modules.pool import (_AdaptiveAvgPoolNd,
+                                             _AdaptiveMaxPoolNd, _AvgPoolNd,
+                                             _MaxPoolNd)
+    else:
+        from torch.nn.modules.pooling import (_AdaptiveAvgPoolNd,
+                                              _AdaptiveMaxPoolNd, _AvgPoolNd,
+                                              _MaxPoolNd)
+    return _AdaptiveAvgPoolNd, _AdaptiveMaxPoolNd, _AvgPoolNd, _MaxPoolNd
+
+
+def _get_norm():
+    if TORCH_VERSION == 'parrots':
+        from parrots.nn.modules.batchnorm import _BatchNorm, _InstanceNorm
+        SyncBatchNorm_ = torch.nn.SyncBatchNorm2d
+    else:
+        from torch.nn.modules.instancenorm import _InstanceNorm
+        from torch.nn.modules.batchnorm import _BatchNorm
+        SyncBatchNorm_ = torch.nn.SyncBatchNorm
+    return _BatchNorm, _InstanceNorm, SyncBatchNorm_
+
+
+_ConvNd, _ConvTransposeMixin = _get_conv()
+DataLoader, PoolDataLoader = _get_dataloader()
+BuildExtension, CppExtension, CUDAExtension = _get_extension()
+_BatchNorm, _InstanceNorm, SyncBatchNorm_ = _get_norm()
+_AdaptiveAvgPoolNd, _AdaptiveMaxPoolNd, _AvgPoolNd, _MaxPoolNd = _get_pool()
+
+
+class SyncBatchNorm(SyncBatchNorm_):
+
+    def _check_input_dim(self, input):
+        if TORCH_VERSION == 'parrots':
+            if input.dim() < 2:
+                raise ValueError(
+                    f'expected at least 2D input (got {input.dim()}D input)')
+        else:
+            super()._check_input_dim(input)

lavis/common/annotator/uniformer/mmcv/utils/path.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import os
+import os.path as osp
+from pathlib import Path
+
+from .misc import is_str
+
+
+def is_filepath(x):
+    return is_str(x) or isinstance(x, Path)
+
+
+def fopen(filepath, *args, **kwargs):
+    if is_str(filepath):
+        return open(filepath, *args, **kwargs)
+    elif isinstance(filepath, Path):
+        return filepath.open(*args, **kwargs)
+    raise ValueError('`filepath` should be a string or a Path')
+
+
+def check_file_exist(filename, msg_tmpl='file "{}" does not exist'):
+    if not osp.isfile(filename):
+        raise FileNotFoundError(msg_tmpl.format(filename))
+
+
+def mkdir_or_exist(dir_name, mode=0o777):
+    if dir_name == '':
+        return
+    dir_name = osp.expanduser(dir_name)
+    os.makedirs(dir_name, mode=mode, exist_ok=True)
+
+
+def symlink(src, dst, overwrite=True, **kwargs):
+    if os.path.lexists(dst) and overwrite:
+        os.remove(dst)
+    os.symlink(src, dst, **kwargs)
+
+
+def scandir(dir_path, suffix=None, recursive=False, case_sensitive=True):
+    """Scan a directory to find the interested files.
+
+    Args:
+        dir_path (str | obj:`Path`): Path of the directory.
+        suffix (str | tuple(str), optional): File suffix that we are
+            interested in. Default: None.
+        recursive (bool, optional): If set to True, recursively scan the
+            directory. Default: False.
+        case_sensitive (bool, optional) : If set to False, ignore the case of
+            suffix. Default: True.
+
+    Returns:
+        A generator for all the interested files with relative paths.
+    """
+    if isinstance(dir_path, (str, Path)):
+        dir_path = str(dir_path)
+    else:
+        raise TypeError('"dir_path" must be a string or Path object')
+
+    if (suffix is not None) and not isinstance(suffix, (str, tuple)):
+        raise TypeError('"suffix" must be a string or tuple of strings')
+
+    if suffix is not None and not case_sensitive:
+        suffix = suffix.lower() if isinstance(suffix, str) else tuple(
+            item.lower() for item in suffix)
+
+    root = dir_path
+
+    def _scandir(dir_path, suffix, recursive, case_sensitive):
+        for entry in os.scandir(dir_path):
+            if not entry.name.startswith('.') and entry.is_file():
+                rel_path = osp.relpath(entry.path, root)
+                _rel_path = rel_path if case_sensitive else rel_path.lower()
+                if suffix is None or _rel_path.endswith(suffix):
+                    yield rel_path
+            elif recursive and os.path.isdir(entry.path):
+                # scan recursively if entry.path is a directory
+                yield from _scandir(entry.path, suffix, recursive,
+                                    case_sensitive)
+
+    return _scandir(dir_path, suffix, recursive, case_sensitive)
+
+
+def find_vcs_root(path, markers=('.git', )):
+    """Finds the root directory (including itself) of specified markers.
+
+    Args:
+        path (str): Path of directory or file.
+        markers (list[str], optional): List of file or directory names.
+
+    Returns:
+        The directory contained one of the markers or None if not found.
+    """
+    if osp.isfile(path):
+        path = osp.dirname(path)
+
+    prev, cur = None, osp.abspath(osp.expanduser(path))
+    while cur != prev:
+        if any(osp.exists(osp.join(cur, marker)) for marker in markers):
+            return cur
+        prev, cur = cur, osp.split(cur)[0]
+    return None

lavis/common/annotator/uniformer/mmcv/utils/progressbar.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import sys
+from collections.abc import Iterable
+from multiprocessing import Pool
+from shutil import get_terminal_size
+
+from .timer import Timer
+
+
+class ProgressBar:
+    """A progress bar which can print the progress."""
+
+    def __init__(self, task_num=0, bar_width=50, start=True, file=sys.stdout):
+        self.task_num = task_num
+        self.bar_width = bar_width
+        self.completed = 0
+        self.file = file
+        if start:
+            self.start()
+
+    @property
+    def terminal_width(self):
+        width, _ = get_terminal_size()
+        return width
+
+    def start(self):
+        if self.task_num > 0:
+            self.file.write(f'[{" " * self.bar_width}] 0/{self.task_num}, '
+                            'elapsed: 0s, ETA:')
+        else:
+            self.file.write('completed: 0, elapsed: 0s')
+        self.file.flush()
+        self.timer = Timer()
+
+    def update(self, num_tasks=1):
+        assert num_tasks > 0
+        self.completed += num_tasks
+        elapsed = self.timer.since_start()
+        if elapsed > 0:
+            fps = self.completed / elapsed
+        else:
+            fps = float('inf')
+        if self.task_num > 0:
+            percentage = self.completed / float(self.task_num)
+            eta = int(elapsed * (1 - percentage) / percentage + 0.5)
+            msg = f'\r[{{}}] {self.completed}/{self.task_num}, ' \
+                  f'{fps:.1f} task/s, elapsed: {int(elapsed + 0.5)}s, ' \
+                  f'ETA: {eta:5}s'
+
+            bar_width = min(self.bar_width,
+                            int(self.terminal_width - len(msg)) + 2,
+                            int(self.terminal_width * 0.6))
+            bar_width = max(2, bar_width)
+            mark_width = int(bar_width * percentage)
+            bar_chars = '>' * mark_width + ' ' * (bar_width - mark_width)
+            self.file.write(msg.format(bar_chars))
+        else:
+            self.file.write(
+                f'completed: {self.completed}, elapsed: {int(elapsed + 0.5)}s,'
+                f' {fps:.1f} tasks/s')
+        self.file.flush()
+
+
+def track_progress(func, tasks, bar_width=50, file=sys.stdout, **kwargs):
+    """Track the progress of tasks execution with a progress bar.
+
+    Tasks are done with a simple for-loop.
+
+    Args:
+        func (callable): The function to be applied to each task.
+        tasks (list or tuple[Iterable, int]): A list of tasks or
+            (tasks, total num).
+        bar_width (int): Width of progress bar.
+
+    Returns:
+        list: The task results.
+    """
+    if isinstance(tasks, tuple):
+        assert len(tasks) == 2
+        assert isinstance(tasks[0], Iterable)
+        assert isinstance(tasks[1], int)
+        task_num = tasks[1]
+        tasks = tasks[0]
+    elif isinstance(tasks, Iterable):
+        task_num = len(tasks)
+    else:
+        raise TypeError(
+            '"tasks" must be an iterable object or a (iterator, int) tuple')
+    prog_bar = ProgressBar(task_num, bar_width, file=file)
+    results = []
+    for task in tasks:
+        results.append(func(task, **kwargs))
+        prog_bar.update()
+    prog_bar.file.write('\n')
+    return results
+
+
+def init_pool(process_num, initializer=None, initargs=None):
+    if initializer is None:
+        return Pool(process_num)
+    elif initargs is None:
+        return Pool(process_num, initializer)
+    else:
+        if not isinstance(initargs, tuple):
+            raise TypeError('"initargs" must be a tuple')
+        return Pool(process_num, initializer, initargs)
+
+
+def track_parallel_progress(func,
+                            tasks,
+                            nproc,
+                            initializer=None,
+                            initargs=None,
+                            bar_width=50,
+                            chunksize=1,
+                            skip_first=False,
+                            keep_order=True,
+                            file=sys.stdout):
+    """Track the progress of parallel task execution with a progress bar.
+
+    The built-in :mod:`multiprocessing` module is used for process pools and
+    tasks are done with :func:`Pool.map` or :func:`Pool.imap_unordered`.
+
+    Args:
+        func (callable): The function to be applied to each task.
+        tasks (list or tuple[Iterable, int]): A list of tasks or
+            (tasks, total num).
+        nproc (int): Process (worker) number.
+        initializer (None or callable): Refer to :class:`multiprocessing.Pool`
+            for details.
+        initargs (None or tuple): Refer to :class:`multiprocessing.Pool` for
+            details.
+        chunksize (int): Refer to :class:`multiprocessing.Pool` for details.
+        bar_width (int): Width of progress bar.
+        skip_first (bool): Whether to skip the first sample for each worker
+            when estimating fps, since the initialization step may takes
+            longer.
+        keep_order (bool): If True, :func:`Pool.imap` is used, otherwise
+            :func:`Pool.imap_unordered` is used.
+
+    Returns:
+        list: The task results.
+    """
+    if isinstance(tasks, tuple):
+        assert len(tasks) == 2
+        assert isinstance(tasks[0], Iterable)
+        assert isinstance(tasks[1], int)
+        task_num = tasks[1]
+        tasks = tasks[0]
+    elif isinstance(tasks, Iterable):
+        task_num = len(tasks)
+    else:
+        raise TypeError(
+            '"tasks" must be an iterable object or a (iterator, int) tuple')
+    pool = init_pool(nproc, initializer, initargs)
+    start = not skip_first
+    task_num -= nproc * chunksize * int(skip_first)
+    prog_bar = ProgressBar(task_num, bar_width, start, file=file)
+    results = []
+    if keep_order:
+        gen = pool.imap(func, tasks, chunksize)
+    else:
+        gen = pool.imap_unordered(func, tasks, chunksize)
+    for result in gen:
+        results.append(result)
+        if skip_first:
+            if len(results) < nproc * chunksize:
+                continue
+            elif len(results) == nproc * chunksize:
+                prog_bar.start()
+                continue
+        prog_bar.update()
+    prog_bar.file.write('\n')
+    pool.close()
+    pool.join()
+    return results
+
+
+def track_iter_progress(tasks, bar_width=50, file=sys.stdout):
+    """Track the progress of tasks iteration or enumeration with a progress
+    bar.
+
+    Tasks are yielded with a simple for-loop.
+
+    Args:
+        tasks (list or tuple[Iterable, int]): A list of tasks or
+            (tasks, total num).
+        bar_width (int): Width of progress bar.
+
+    Yields:
+        list: The task results.
+    """
+    if isinstance(tasks, tuple):
+        assert len(tasks) == 2
+        assert isinstance(tasks[0], Iterable)
+        assert isinstance(tasks[1], int)
+        task_num = tasks[1]
+        tasks = tasks[0]
+    elif isinstance(tasks, Iterable):
+        task_num = len(tasks)
+    else:
+        raise TypeError(
+            '"tasks" must be an iterable object or a (iterator, int) tuple')
+    prog_bar = ProgressBar(task_num, bar_width, file=file)
+    for task in tasks:
+        yield task
+        prog_bar.update()
+    prog_bar.file.write('\n')

lavis/common/annotator/uniformer/mmcv/utils/registry.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import inspect
+import warnings
+from functools import partial
+
+from .misc import is_seq_of
+
+
+def build_from_cfg(cfg, registry, default_args=None):
+    """Build a module from config dict.
+
+    Args:
+        cfg (dict): Config dict. It should at least contain the key "type".
+        registry (:obj:`Registry`): The registry to search the type from.
+        default_args (dict, optional): Default initialization arguments.
+
+    Returns:
+        object: The constructed object.
+    """
+    if not isinstance(cfg, dict):
+        raise TypeError(f'cfg must be a dict, but got {type(cfg)}')
+    if 'type' not in cfg:
+        if default_args is None or 'type' not in default_args:
+            raise KeyError(
+                '`cfg` or `default_args` must contain the key "type", '
+                f'but got {cfg}\n{default_args}')
+    if not isinstance(registry, Registry):
+        raise TypeError('registry must be an mmcv.Registry object, '
+                        f'but got {type(registry)}')
+    if not (isinstance(default_args, dict) or default_args is None):
+        raise TypeError('default_args must be a dict or None, '
+                        f'but got {type(default_args)}')
+
+    args = cfg.copy()
+
+    if default_args is not None:
+        for name, value in default_args.items():
+            args.setdefault(name, value)
+
+    obj_type = args.pop('type')
+    if isinstance(obj_type, str):
+        obj_cls = registry.get(obj_type)
+        if obj_cls is None:
+            raise KeyError(
+                f'{obj_type} is not in the {registry.name} registry')
+    elif inspect.isclass(obj_type):
+        obj_cls = obj_type
+    else:
+        raise TypeError(
+            f'type must be a str or valid type, but got {type(obj_type)}')
+    try:
+        return obj_cls(**args)
+    except Exception as e:
+        # Normal TypeError does not print class name.
+        raise type(e)(f'{obj_cls.__name__}: {e}')
+
+
+class Registry:
+    """A registry to map strings to classes.
+
+    Registered object could be built from registry.
+    Example:
+        >>> MODELS = Registry('models')
+        >>> @MODELS.register_module()
+        >>> class ResNet:
+        >>>     pass
+        >>> resnet = MODELS.build(dict(type='ResNet'))
+
+    Please refer to
+    https://mmcv.readthedocs.io/en/latest/understand_mmcv/registry.html for
+    advanced usage.
+
+    Args:
+        name (str): Registry name.
+        build_func(func, optional): Build function to construct instance from
+            Registry, func:`build_from_cfg` is used if neither ``parent`` or
+            ``build_func`` is specified. If ``parent`` is specified and
+            ``build_func`` is not given,  ``build_func`` will be inherited
+            from ``parent``. Default: None.
+        parent (Registry, optional): Parent registry. The class registered in
+            children registry could be built from parent. Default: None.
+        scope (str, optional): The scope of registry. It is the key to search
+            for children registry. If not specified, scope will be the name of
+            the package where class is defined, e.g. mmdet, mmcls, mmseg.
+            Default: None.
+    """
+
+    def __init__(self, name, build_func=None, parent=None, scope=None):
+        self._name = name
+        self._module_dict = dict()
+        self._children = dict()
+        self._scope = self.infer_scope() if scope is None else scope
+
+        # self.build_func will be set with the following priority:
+        # 1. build_func
+        # 2. parent.build_func
+        # 3. build_from_cfg
+        if build_func is None:
+            if parent is not None:
+                self.build_func = parent.build_func
+            else:
+                self.build_func = build_from_cfg
+        else:
+            self.build_func = build_func
+        if parent is not None:
+            assert isinstance(parent, Registry)
+            parent._add_children(self)
+            self.parent = parent
+        else:
+            self.parent = None
+
+    def __len__(self):
+        return len(self._module_dict)
+
+    def __contains__(self, key):
+        return self.get(key) is not None
+
+    def __repr__(self):
+        format_str = self.__class__.__name__ + \
+                     f'(name={self._name}, ' \
+                     f'items={self._module_dict})'
+        return format_str
+
+    @staticmethod
+    def infer_scope():
+        """Infer the scope of registry.
+
+        The name of the package where registry is defined will be returned.
+
+        Example:
+            # in mmdet/models/backbone/resnet.py
+            >>> MODELS = Registry('models')
+            >>> @MODELS.register_module()
+            >>> class ResNet:
+            >>>     pass
+            The scope of ``ResNet`` will be ``mmdet``.
+
+
+        Returns:
+            scope (str): The inferred scope name.
+        """
+        # inspect.stack() trace where this function is called, the index-2
+        # indicates the frame where `infer_scope()` is called
+        filename = inspect.getmodule(inspect.stack()[2][0]).__name__
+        split_filename = filename.split('.')
+        return split_filename[0]
+
+    @staticmethod
+    def split_scope_key(key):
+        """Split scope and key.
+
+        The first scope will be split from key.
+
+        Examples:
+            >>> Registry.split_scope_key('mmdet.ResNet')
+            'mmdet', 'ResNet'
+            >>> Registry.split_scope_key('ResNet')
+            None, 'ResNet'
+
+        Return:
+            scope (str, None): The first scope.
+            key (str): The remaining key.
+        """
+        split_index = key.find('.')
+        if split_index != -1:
+            return key[:split_index], key[split_index + 1:]
+        else:
+            return None, key
+
+    @property
+    def name(self):
+        return self._name
+
+    @property
+    def scope(self):
+        return self._scope
+
+    @property
+    def module_dict(self):
+        return self._module_dict
+
+    @property
+    def children(self):
+        return self._children
+
+    def get(self, key):
+        """Get the registry record.
+
+        Args:
+            key (str): The class name in string format.
+
+        Returns:
+            class: The corresponding class.
+        """
+        scope, real_key = self.split_scope_key(key)
+        if scope is None or scope == self._scope:
+            # get from self
+            if real_key in self._module_dict:
+                return self._module_dict[real_key]
+        else:
+            # get from self._children
+            if scope in self._children:
+                return self._children[scope].get(real_key)
+            else:
+                # goto root
+                parent = self.parent
+                while parent.parent is not None:
+                    parent = parent.parent
+                return parent.get(key)
+
+    def build(self, *args, **kwargs):
+        return self.build_func(*args, **kwargs, registry=self)
+
+    def _add_children(self, registry):
+        """Add children for a registry.
+
+        The ``registry`` will be added as children based on its scope.
+        The parent registry could build objects from children registry.
+
+        Example:
+            >>> models = Registry('models')
+            >>> mmdet_models = Registry('models', parent=models)
+            >>> @mmdet_models.register_module()
+            >>> class ResNet:
+            >>>     pass
+            >>> resnet = models.build(dict(type='mmdet.ResNet'))
+        """
+
+        assert isinstance(registry, Registry)
+        assert registry.scope is not None
+        assert registry.scope not in self.children, \
+            f'scope {registry.scope} exists in {self.name} registry'
+        self.children[registry.scope] = registry
+
+    def _register_module(self, module_class, module_name=None, force=False):
+        if not inspect.isclass(module_class):
+            raise TypeError('module must be a class, '
+                            f'but got {type(module_class)}')
+
+        if module_name is None:
+            module_name = module_class.__name__
+        if isinstance(module_name, str):
+            module_name = [module_name]
+        for name in module_name:
+            if not force and name in self._module_dict:
+                raise KeyError(f'{name} is already registered '
+                               f'in {self.name}')
+            self._module_dict[name] = module_class
+
+    def deprecated_register_module(self, cls=None, force=False):
+        warnings.warn(
+            'The old API of register_module(module, force=False) '
+            'is deprecated and will be removed, please use the new API '
+            'register_module(name=None, force=False, module=None) instead.')
+        if cls is None:
+            return partial(self.deprecated_register_module, force=force)
+        self._register_module(cls, force=force)
+        return cls
+
+    def register_module(self, name=None, force=False, module=None):
+        """Register a module.
+
+        A record will be added to `self._module_dict`, whose key is the class
+        name or the specified name, and value is the class itself.
+        It can be used as a decorator or a normal function.
+
+        Example:
+            >>> backbones = Registry('backbone')
+            >>> @backbones.register_module()
+            >>> class ResNet:
+            >>>     pass
+
+            >>> backbones = Registry('backbone')
+            >>> @backbones.register_module(name='mnet')
+            >>> class MobileNet:
+            >>>     pass
+
+            >>> backbones = Registry('backbone')
+            >>> class ResNet:
+            >>>     pass
+            >>> backbones.register_module(ResNet)
+
+        Args:
+            name (str | None): The module name to be registered. If not
+                specified, the class name will be used.
+            force (bool, optional): Whether to override an existing class with
+                the same name. Default: False.
+            module (type): Module class to be registered.
+        """
+        if not isinstance(force, bool):
+            raise TypeError(f'force must be a boolean, but got {type(force)}')
+        # NOTE: This is a walkaround to be compatible with the old api,
+        # while it may introduce unexpected bugs.
+        if isinstance(name, type):
+            return self.deprecated_register_module(name, force=force)
+
+        # raise the error ahead of time
+        if not (name is None or isinstance(name, str) or is_seq_of(name, str)):
+            raise TypeError(
+                'name must be either of None, an instance of str or a sequence'
+                f'  of str, but got {type(name)}')
+
+        # use it as a normal method: x.register_module(module=SomeClass)
+        if module is not None:
+            self._register_module(
+                module_class=module, module_name=name, force=force)
+            return module
+
+        # use it as a decorator: @x.register_module()
+        def _register(cls):
+            self._register_module(
+                module_class=cls, module_name=name, force=force)
+            return cls
+
+        return _register

lavis/common/annotator/uniformer/mmcv/utils/testing.py

+# Copyright (c) Open-MMLab.
+import sys
+from collections.abc import Iterable
+from runpy import run_path
+from shlex import split
+from typing import Any, Dict, List
+from unittest.mock import patch
+
+
+def check_python_script(cmd):
+    """Run the python cmd script with `__main__`. The difference between
+    `os.system` is that, this function exectues code in the current process, so
+    that it can be tracked by coverage tools. Currently it supports two forms:
+
+    - ./tests/data/scripts/hello.py zz
+    - python tests/data/scripts/hello.py zz
+    """
+    args = split(cmd)
+    if args[0] == 'python':
+        args = args[1:]
+    with patch.object(sys, 'argv', args):
+        run_path(args[0], run_name='__main__')
+
+
+def _any(judge_result):
+    """Since built-in ``any`` works only when the element of iterable is not
+    iterable, implement the function."""
+    if not isinstance(judge_result, Iterable):
+        return judge_result
+
+    try:
+        for element in judge_result:
+            if _any(element):
+                return True
+    except TypeError:
+        # Maybe encounter the case: torch.tensor(True) | torch.tensor(False)
+        if judge_result:
+            return True
+    return False
+
+
+def assert_dict_contains_subset(dict_obj: Dict[Any, Any],
+                                expected_subset: Dict[Any, Any]) -> bool:
+    """Check if the dict_obj contains the expected_subset.
+
+    Args:
+        dict_obj (Dict[Any, Any]): Dict object to be checked.
+        expected_subset (Dict[Any, Any]): Subset expected to be contained in
+            dict_obj.
+
+    Returns:
+        bool: Whether the dict_obj contains the expected_subset.
+    """
+
+    for key, value in expected_subset.items():
+        if key not in dict_obj.keys() or _any(dict_obj[key] != value):
+            return False
+    return True
+
+
+def assert_attrs_equal(obj: Any, expected_attrs: Dict[str, Any]) -> bool:
+    """Check if attribute of class object is correct.
+
+    Args:
+        obj (object): Class object to be checked.
+        expected_attrs (Dict[str, Any]): Dict of the expected attrs.
+
+    Returns:
+        bool: Whether the attribute of class object is correct.
+    """
+    for attr, value in expected_attrs.items():
+        if not hasattr(obj, attr) or _any(getattr(obj, attr) != value):
+            return False
+    return True
+
+
+def assert_dict_has_keys(obj: Dict[str, Any],
+                         expected_keys: List[str]) -> bool:
+    """Check if the obj has all the expected_keys.
+
+    Args:
+        obj (Dict[str, Any]): Object to be checked.
+        expected_keys (List[str]): Keys expected to contained in the keys of
+            the obj.
+
+    Returns:
+        bool: Whether the obj has the expected keys.
+    """
+    return set(expected_keys).issubset(set(obj.keys()))
+
+
+def assert_keys_equal(result_keys: List[str], target_keys: List[str]) -> bool:
+    """Check if target_keys is equal to result_keys.
+
+    Args:
+        result_keys (List[str]): Result keys to be checked.
+        target_keys (List[str]): Target keys to be checked.
+
+    Returns:
+        bool: Whether target_keys is equal to result_keys.
+    """
+    return set(result_keys) == set(target_keys)
+
+
+def assert_is_norm_layer(module) -> bool:
+    """Check if the module is a norm layer.
+
+    Args:
+        module (nn.Module): The module to be checked.
+
+    Returns:
+        bool: Whether the module is a norm layer.
+    """
+    from .parrots_wrapper import _BatchNorm, _InstanceNorm
+    from torch.nn import GroupNorm, LayerNorm
+    norm_layer_candidates = (_BatchNorm, _InstanceNorm, GroupNorm, LayerNorm)
+    return isinstance(module, norm_layer_candidates)
+
+
+def assert_params_all_zeros(module) -> bool:
+    """Check if the parameters of the module is all zeros.
+
+    Args:
+        module (nn.Module): The module to be checked.
+
+    Returns:
+        bool: Whether the parameters of the module is all zeros.
+    """
+    weight_data = module.weight.data
+    is_weight_zero = weight_data.allclose(
+        weight_data.new_zeros(weight_data.size()))
+
+    if hasattr(module, 'bias') and module.bias is not None:
+        bias_data = module.bias.data
+        is_bias_zero = bias_data.allclose(
+            bias_data.new_zeros(bias_data.size()))
+    else:
+        is_bias_zero = True
+
+    return is_weight_zero and is_bias_zero

lavis/common/annotator/uniformer/mmcv/utils/timer.py

+# Copyright (c) OpenMMLab. All rights reserved.
+from time import time
+
+
+class TimerError(Exception):
+
+    def __init__(self, message):
+        self.message = message
+        super(TimerError, self).__init__(message)
+
+
+class Timer:
+    """A flexible Timer class.
+
+    :Example:
+
+    >>> import time
+    >>> import annotator.uniformer.mmcv as mmcv
+    >>> with mmcv.Timer():
+    >>>     # simulate a code block that will run for 1s
+    >>>     time.sleep(1)
+    1.000
+    >>> with mmcv.Timer(print_tmpl='it takes {:.1f} seconds'):
+    >>>     # simulate a code block that will run for 1s
+    >>>     time.sleep(1)
+    it takes 1.0 seconds
+    >>> timer = mmcv.Timer()
+    >>> time.sleep(0.5)
+    >>> print(timer.since_start())
+    0.500
+    >>> time.sleep(0.5)
+    >>> print(timer.since_last_check())
+    0.500
+    >>> print(timer.since_start())
+    1.000
+    """
+
+    def __init__(self, start=True, print_tmpl=None):
+        self._is_running = False
+        self.print_tmpl = print_tmpl if print_tmpl else '{:.3f}'
+        if start:
+            self.start()
+
+    @property
+    def is_running(self):
+        """bool: indicate whether the timer is running"""
+        return self._is_running
+
+    def __enter__(self):
+        self.start()
+        return self
+
+    def __exit__(self, type, value, traceback):
+        print(self.print_tmpl.format(self.since_last_check()))
+        self._is_running = False
+
+    def start(self):
+        """Start the timer."""
+        if not self._is_running:
+            self._t_start = time()
+            self._is_running = True
+        self._t_last = time()
+
+    def since_start(self):
+        """Total time since the timer is started.
+
+        Returns (float): Time in seconds.
+        """
+        if not self._is_running:
+            raise TimerError('timer is not running')
+        self._t_last = time()
+        return self._t_last - self._t_start
+
+    def since_last_check(self):
+        """Time since the last checking.
+
+        Either :func:`since_start` or :func:`since_last_check` is a checking
+        operation.
+
+        Returns (float): Time in seconds.
+        """
+        if not self._is_running:
+            raise TimerError('timer is not running')
+        dur = time() - self._t_last
+        self._t_last = time()
+        return dur
+
+
+_g_timers = {}  # global timers
+
+
+def check_time(timer_id):
+    """Add check points in a single line.
+
+    This method is suitable for running a task on a list of items. A timer will
+    be registered when the method is called for the first time.
+
+    :Example:
+
+    >>> import time
+    >>> import annotator.uniformer.mmcv as mmcv
+    >>> for i in range(1, 6):
+    >>>     # simulate a code block
+    >>>     time.sleep(i)
+    >>>     mmcv.check_time('task1')
+    2.000
+    3.000
+    4.000
+    5.000
+
+    Args:
+        timer_id (str): Timer identifier.
+    """
+    if timer_id not in _g_timers:
+        _g_timers[timer_id] = Timer()
+        return 0
+    else:
+        return _g_timers[timer_id].since_last_check()

lavis/common/annotator/uniformer/mmcv/utils/trace.py

+import warnings
+
+import torch
+
+from annotator.uniformer.mmcv.utils import digit_version
+
+
+def is_jit_tracing() -> bool:
+    if (torch.__version__ != 'parrots'
+            and digit_version(torch.__version__) >= digit_version('1.6.0')):
+        on_trace = torch.jit.is_tracing()
+        # In PyTorch 1.6, torch.jit.is_tracing has a bug.
+        # Refers to https://github.com/pytorch/pytorch/issues/42448
+        if isinstance(on_trace, bool):
+            return on_trace
+        else:
+            return torch._C._is_tracing()
+    else:
+        warnings.warn(
+            'torch.jit.is_tracing is only supported after v1.6.0. '
+            'Therefore is_tracing returns False automatically. Please '
+            'set on_trace manually if you are using trace.', UserWarning)
+        return False

lavis/common/annotator/uniformer/mmcv/utils/version_utils.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import os
+import subprocess
+import warnings
+
+from packaging.version import parse
+
+
+def digit_version(version_str: str, length: int = 4):
+    """Convert a version string into a tuple of integers.
+
+    This method is usually used for comparing two versions. For pre-release
+    versions: alpha < beta < rc.
+
+    Args:
+        version_str (str): The version string.
+        length (int): The maximum number of version levels. Default: 4.
+
+    Returns:
+        tuple[int]: The version info in digits (integers).
+    """
+    assert 'parrots' not in version_str
+    version = parse(version_str)
+    assert version.release, f'failed to parse version {version_str}'
+    release = list(version.release)
+    release = release[:length]
+    if len(release) < length:
+        release = release + [0] * (length - len(release))
+    if version.is_prerelease:
+        mapping = {'a': -3, 'b': -2, 'rc': -1}
+        val = -4
+        # version.pre can be None
+        if version.pre:
+            if version.pre[0] not in mapping:
+                warnings.warn(f'unknown prerelease version {version.pre[0]}, '
+                              'version checking may go wrong')
+            else:
+                val = mapping[version.pre[0]]
+            release.extend([val, version.pre[-1]])
+        else:
+            release.extend([val, 0])
+
+    elif version.is_postrelease:
+        release.extend([1, version.post])
+    else:
+        release.extend([0, 0])
+    return tuple(release)
+
+
+def _minimal_ext_cmd(cmd):
+    # construct minimal environment
+    env = {}
+    for k in ['SYSTEMROOT', 'PATH', 'HOME']:
+        v = os.environ.get(k)
+        if v is not None:
+            env[k] = v
+    # LANGUAGE is used on win32
+    env['LANGUAGE'] = 'C'
+    env['LANG'] = 'C'
+    env['LC_ALL'] = 'C'
+    out = subprocess.Popen(
+        cmd, stdout=subprocess.PIPE, env=env).communicate()[0]
+    return out
+
+
+def get_git_hash(fallback='unknown', digits=None):
+    """Get the git hash of the current repo.
+
+    Args:
+        fallback (str, optional): The fallback string when git hash is
+            unavailable. Defaults to 'unknown'.
+        digits (int, optional): kept digits of the hash. Defaults to None,
+            meaning all digits are kept.
+
+    Returns:
+        str: Git commit hash.
+    """
+
+    if digits is not None and not isinstance(digits, int):
+        raise TypeError('digits must be None or an integer')
+
+    try:
+        out = _minimal_ext_cmd(['git', 'rev-parse', 'HEAD'])
+        sha = out.strip().decode('ascii')
+        if digits is not None:
+            sha = sha[:digits]
+    except OSError:
+        sha = fallback
+
+    return sha

lavis/common/annotator/uniformer/mmcv/version.py

+# Copyright (c) OpenMMLab. All rights reserved.
+__version__ = '1.3.17'
+
+
+def parse_version_info(version_str: str, length: int = 4) -> tuple:
+    """Parse a version string into a tuple.
+
+    Args:
+        version_str (str): The version string.
+        length (int): The maximum number of version levels. Default: 4.
+
+    Returns:
+        tuple[int | str]: The version info, e.g., "1.3.0" is parsed into
+            (1, 3, 0, 0, 0, 0), and "2.0.0rc1" is parsed into
+            (2, 0, 0, 0, 'rc', 1) (when length is set to 4).
+    """
+    from packaging.version import parse
+    version = parse(version_str)
+    assert version.release, f'failed to parse version {version_str}'
+    release = list(version.release)
+    release = release[:length]
+    if len(release) < length:
+        release = release + [0] * (length - len(release))
+    if version.is_prerelease:
+        release.extend(list(version.pre))
+    elif version.is_postrelease:
+        release.extend(list(version.post))
+    else:
+        release.extend([0, 0])
+    return tuple(release)
+
+
+version_info = tuple(int(x) for x in __version__.split('.')[:3])
+
+__all__ = ['__version__', 'version_info', 'parse_version_info']

lavis/common/annotator/uniformer/mmcv/video/__init__.py

+# Copyright (c) OpenMMLab. All rights reserved.
+from .io import Cache, VideoReader, frames2video
+from .optflow import (dequantize_flow, flow_from_bytes, flow_warp, flowread,
+                      flowwrite, quantize_flow, sparse_flow_from_bytes)
+from .processing import concat_video, convert_video, cut_video, resize_video
+
+__all__ = [
+    'Cache', 'VideoReader', 'frames2video', 'convert_video', 'resize_video',
+    'cut_video', 'concat_video', 'flowread', 'flowwrite', 'quantize_flow',
+    'dequantize_flow', 'flow_warp', 'flow_from_bytes', 'sparse_flow_from_bytes'
+]

lavis/common/annotator/uniformer/mmcv/video/io.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import os.path as osp
+from collections import OrderedDict
+
+import cv2
+from cv2 import (CAP_PROP_FOURCC, CAP_PROP_FPS, CAP_PROP_FRAME_COUNT,
+                 CAP_PROP_FRAME_HEIGHT, CAP_PROP_FRAME_WIDTH,
+                 CAP_PROP_POS_FRAMES, VideoWriter_fourcc)
+
+from annotator.uniformer.mmcv.utils import (check_file_exist, mkdir_or_exist, scandir,
+                        track_progress)
+
+
+class Cache:
+
+    def __init__(self, capacity):
+        self._cache = OrderedDict()
+        self._capacity = int(capacity)
+        if capacity <= 0:
+            raise ValueError('capacity must be a positive integer')
+
+    @property
+    def capacity(self):
+        return self._capacity
+
+    @property
+    def size(self):
+        return len(self._cache)
+
+    def put(self, key, val):
+        if key in self._cache:
+            return
+        if len(self._cache) >= self.capacity:
+            self._cache.popitem(last=False)
+        self._cache[key] = val
+
+    def get(self, key, default=None):
+        val = self._cache[key] if key in self._cache else default
+        return val
+
+
+class VideoReader:
+    """Video class with similar usage to a list object.
+
+    This video warpper class provides convenient apis to access frames.
+    There exists an issue of OpenCV's VideoCapture class that jumping to a
+    certain frame may be inaccurate. It is fixed in this class by checking
+    the position after jumping each time.
+    Cache is used when decoding videos. So if the same frame is visited for
+    the second time, there is no need to decode again if it is stored in the
+    cache.
+
+    :Example:
+
+    >>> import annotator.uniformer.mmcv as mmcv
+    >>> v = mmcv.VideoReader('sample.mp4')
+    >>> len(v)  # get the total frame number with `len()`
+    120
+    >>> for img in v:  # v is iterable
+    >>>     mmcv.imshow(img)
+    >>> v[5]  # get the 6th frame
+    """
+
+    def __init__(self, filename, cache_capacity=10):
+        # Check whether the video path is a url
+        if not filename.startswith(('https://', 'http://')):
+            check_file_exist(filename, 'Video file not found: ' + filename)
+        self._vcap = cv2.VideoCapture(filename)
+        assert cache_capacity > 0
+        self._cache = Cache(cache_capacity)
+        self._position = 0
+        # get basic info
+        self._width = int(self._vcap.get(CAP_PROP_FRAME_WIDTH))
+        self._height = int(self._vcap.get(CAP_PROP_FRAME_HEIGHT))
+        self._fps = self._vcap.get(CAP_PROP_FPS)
+        self._frame_cnt = int(self._vcap.get(CAP_PROP_FRAME_COUNT))
+        self._fourcc = self._vcap.get(CAP_PROP_FOURCC)
+
+    @property
+    def vcap(self):
+        """:obj:`cv2.VideoCapture`: The raw VideoCapture object."""
+        return self._vcap
+
+    @property
+    def opened(self):
+        """bool: Indicate whether the video is opened."""
+        return self._vcap.isOpened()
+
+    @property
+    def width(self):
+        """int: Width of video frames."""
+        return self._width
+
+    @property
+    def height(self):
+        """int: Height of video frames."""
+        return self._height
+
+    @property
+    def resolution(self):
+        """tuple: Video resolution (width, height)."""
+        return (self._width, self._height)
+
+    @property
+    def fps(self):
+        """float: FPS of the video."""
+        return self._fps
+
+    @property
+    def frame_cnt(self):
+        """int: Total frames of the video."""
+        return self._frame_cnt
+
+    @property
+    def fourcc(self):
+        """str: "Four character code" of the video."""
+        return self._fourcc
+
+    @property
+    def position(self):
+        """int: Current cursor position, indicating frame decoded."""
+        return self._position
+
+    def _get_real_position(self):
+        return int(round(self._vcap.get(CAP_PROP_POS_FRAMES)))
+
+    def _set_real_position(self, frame_id):
+        self._vcap.set(CAP_PROP_POS_FRAMES, frame_id)
+        pos = self._get_real_position()
+        for _ in range(frame_id - pos):
+            self._vcap.read()
+        self._position = frame_id
+
+    def read(self):
+        """Read the next frame.
+
+        If the next frame have been decoded before and in the cache, then
+        return it directly, otherwise decode, cache and return it.
+
+        Returns:
+            ndarray or None: Return the frame if successful, otherwise None.
+        """
+        # pos = self._position
+        if self._cache:
+            img = self._cache.get(self._position)
+            if img is not None:
+                ret = True
+            else:
+                if self._position != self._get_real_position():
+                    self._set_real_position(self._position)
+                ret, img = self._vcap.read()
+                if ret:
+                    self._cache.put(self._position, img)
+        else:
+            ret, img = self._vcap.read()
+        if ret:
+            self._position += 1
+        return img
+
+    def get_frame(self, frame_id):
+        """Get frame by index.
+
+        Args:
+            frame_id (int): Index of the expected frame, 0-based.
+
+        Returns:
+            ndarray or None: Return the frame if successful, otherwise None.
+        """
+        if frame_id < 0 or frame_id >= self._frame_cnt:
+            raise IndexError(
+                f'"frame_id" must be between 0 and {self._frame_cnt - 1}')
+        if frame_id == self._position:
+            return self.read()
+        if self._cache:
+            img = self._cache.get(frame_id)
+            if img is not None:
+                self._position = frame_id + 1
+                return img
+        self._set_real_position(frame_id)
+        ret, img = self._vcap.read()
+        if ret:
+            if self._cache:
+                self._cache.put(self._position, img)
+            self._position += 1
+        return img
+
+    def current_frame(self):
+        """Get the current frame (frame that is just visited).
+
+        Returns:
+            ndarray or None: If the video is fresh, return None, otherwise
+                return the frame.
+        """
+        if self._position == 0:
+            return None
+        return self._cache.get(self._position - 1)
+
+    def cvt2frames(self,
+                   frame_dir,
+                   file_start=0,
+                   filename_tmpl='{:06d}.jpg',
+                   start=0,
+                   max_num=0,
+                   show_progress=True):
+        """Convert a video to frame images.
+
+        Args:
+            frame_dir (str): Output directory to store all the frame images.
+            file_start (int): Filenames will start from the specified number.
+            filename_tmpl (str): Filename template with the index as the
+                placeholder.
+            start (int): The starting frame index.
+            max_num (int): Maximum number of frames to be written.
+            show_progress (bool): Whether to show a progress bar.
+        """
+        mkdir_or_exist(frame_dir)
+        if max_num == 0:
+            task_num = self.frame_cnt - start
+        else:
+            task_num = min(self.frame_cnt - start, max_num)
+        if task_num <= 0:
+            raise ValueError('start must be less than total frame number')
+        if start > 0:
+            self._set_real_position(start)
+
+        def write_frame(file_idx):
+            img = self.read()
+            if img is None:
+                return
+            filename = osp.join(frame_dir, filename_tmpl.format(file_idx))
+            cv2.imwrite(filename, img)
+
+        if show_progress:
+            track_progress(write_frame, range(file_start,
+                                              file_start + task_num))
+        else:
+            for i in range(task_num):
+                write_frame(file_start + i)
+
+    def __len__(self):
+        return self.frame_cnt
+
+    def __getitem__(self, index):
+        if isinstance(index, slice):
+            return [
+                self.get_frame(i)
+                for i in range(*index.indices(self.frame_cnt))
+            ]
+        # support negative indexing
+        if index < 0:
+            index += self.frame_cnt
+            if index < 0:
+                raise IndexError('index out of range')
+        return self.get_frame(index)
+
+    def __iter__(self):
+        self._set_real_position(0)
+        return self
+
+    def __next__(self):
+        img = self.read()
+        if img is not None:
+            return img
+        else:
+            raise StopIteration
+
+    next = __next__
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, exc_type, exc_value, traceback):
+        self._vcap.release()
+
+
+def frames2video(frame_dir,
+                 video_file,
+                 fps=30,
+                 fourcc='XVID',
+                 filename_tmpl='{:06d}.jpg',
+                 start=0,
+                 end=0,
+                 show_progress=True):
+    """Read the frame images from a directory and join them as a video.
+
+    Args:
+        frame_dir (str): The directory containing video frames.
+        video_file (str): Output filename.
+        fps (float): FPS of the output video.
+        fourcc (str): Fourcc of the output video, this should be compatible
+            with the output file type.
+        filename_tmpl (str): Filename template with the index as the variable.
+        start (int): Starting frame index.
+        end (int): Ending frame index.
+        show_progress (bool): Whether to show a progress bar.
+    """
+    if end == 0:
+        ext = filename_tmpl.split('.')[-1]
+        end = len([name for name in scandir(frame_dir, ext)])
+    first_file = osp.join(frame_dir, filename_tmpl.format(start))
+    check_file_exist(first_file, 'The start frame not found: ' + first_file)
+    img = cv2.imread(first_file)
+    height, width = img.shape[:2]
+    resolution = (width, height)
+    vwriter = cv2.VideoWriter(video_file, VideoWriter_fourcc(*fourcc), fps,
+                              resolution)
+
+    def write_frame(file_idx):
+        filename = osp.join(frame_dir, filename_tmpl.format(file_idx))
+        img = cv2.imread(filename)
+        vwriter.write(img)
+
+    if show_progress:
+        track_progress(write_frame, range(start, end))
+    else:
+        for i in range(start, end):
+            write_frame(i)
+    vwriter.release()

lavis/common/annotator/uniformer/mmcv/video/optflow.py

+# Copyright (c) OpenMMLab. All rights reserved.
+import warnings
+
+import cv2
+import numpy as np
+
+from annotator.uniformer.mmcv.arraymisc import dequantize, quantize
+from annotator.uniformer.mmcv.image import imread, imwrite
+from annotator.uniformer.mmcv.utils import is_str
+
+
+def flowread(flow_or_path, quantize=False, concat_axis=0, *args, **kwargs):
+    """Read an optical flow map.
+
+    Args:
+        flow_or_path (ndarray or str): A flow map or filepath.
+        quantize (bool): whether to read quantized pair, if set to True,
+            remaining args will be passed to :func:`dequantize_flow`.
+        concat_axis (int): The axis that dx and dy are concatenated,
+            can be either 0 or 1. Ignored if quantize is False.
+
+    Returns:
+        ndarray: Optical flow represented as a (h, w, 2) numpy array
+    """
+    if isinstance(flow_or_path, np.ndarray):
+        if (flow_or_path.ndim != 3) or (flow_or_path.shape[-1] != 2):
+            raise ValueError(f'Invalid flow with shape {flow_or_path.shape}')
+        return flow_or_path
+    elif not is_str(flow_or_path):
+        raise TypeError(f'"flow_or_path" must be a filename or numpy array, '
+                        f'not {type(flow_or_path)}')
+
+    if not quantize:
+        with open(flow_or_path, 'rb') as f:
+            try:
+                header = f.read(4).decode('utf-8')
+            except Exception:
+                raise IOError(f'Invalid flow file: {flow_or_path}')
+            else:
+                if header != 'PIEH':
+                    raise IOError(f'Invalid flow file: {flow_or_path}, '
+                                  'header does not contain PIEH')
+
+            w = np.fromfile(f, np.int32, 1).squeeze()
+            h = np.fromfile(f, np.int32, 1).squeeze()
+            flow = np.fromfile(f, np.float32, w * h * 2).reshape((h, w, 2))
+    else:
+        assert concat_axis in [0, 1]
+        cat_flow = imread(flow_or_path, flag='unchanged')
+        if cat_flow.ndim != 2:
+            raise IOError(
+                f'{flow_or_path} is not a valid quantized flow file, '
+                f'its dimension is {cat_flow.ndim}.')
+        assert cat_flow.shape[concat_axis] % 2 == 0
+        dx, dy = np.split(cat_flow, 2, axis=concat_axis)
+        flow = dequantize_flow(dx, dy, *args, **kwargs)
+
+    return flow.astype(np.float32)
+
+
+def flowwrite(flow, filename, quantize=False, concat_axis=0, *args, **kwargs):
+    """Write optical flow to file.
+
+    If the flow is not quantized, it will be saved as a .flo file losslessly,
+    otherwise a jpeg image which is lossy but of much smaller size. (dx and dy
+    will be concatenated horizontally into a single image if quantize is True.)
+
+    Args:
+        flow (ndarray): (h, w, 2) array of optical flow.
+        filename (str): Output filepath.
+        quantize (bool): Whether to quantize the flow and save it to 2 jpeg
+            images. If set to True, remaining args will be passed to
+            :func:`quantize_flow`.
+        concat_axis (int): The axis that dx and dy are concatenated,
+            can be either 0 or 1. Ignored if quantize is False.
+    """
+    if not quantize:
+        with open(filename, 'wb') as f:
+            f.write('PIEH'.encode('utf-8'))
+            np.array([flow.shape[1], flow.shape[0]], dtype=np.int32).tofile(f)
+            flow = flow.astype(np.float32)
+            flow.tofile(f)
+            f.flush()
+    else:
+        assert concat_axis in [0, 1]
+        dx, dy = quantize_flow(flow, *args, **kwargs)
+        dxdy = np.concatenate((dx, dy), axis=concat_axis)
+        imwrite(dxdy, filename)
+
+
+def quantize_flow(flow, max_val=0.02, norm=True):
+    """Quantize flow to [0, 255].
+
+    After this step, the size of flow will be much smaller, and can be
+    dumped as jpeg images.
+
+    Args:
+        flow (ndarray): (h, w, 2) array of optical flow.
+        max_val (float): Maximum value of flow, values beyond
+                        [-max_val, max_val] will be truncated.
+        norm (bool): Whether to divide flow values by image width/height.
+
+    Returns:
+        tuple[ndarray]: Quantized dx and dy.
+    """
+    h, w, _ = flow.shape
+    dx = flow[..., 0]
+    dy = flow[..., 1]
+    if norm:
+        dx = dx / w  # avoid inplace operations
+        dy = dy / h
+    # use 255 levels instead of 256 to make sure 0 is 0 after dequantization.
+    flow_comps = [
+        quantize(d, -max_val, max_val, 255, np.uint8) for d in [dx, dy]
+    ]
+    return tuple(flow_comps)
+
+
+def dequantize_flow(dx, dy, max_val=0.02, denorm=True):
+    """Recover from quantized flow.
+
+    Args:
+        dx (ndarray): Quantized dx.
+        dy (ndarray): Quantized dy.
+        max_val (float): Maximum value used when quantizing.
+        denorm (bool): Whether to multiply flow values with width/height.
+
+    Returns:
+        ndarray: Dequantized flow.
+    """
+    assert dx.shape == dy.shape
+    assert dx.ndim == 2 or (dx.ndim == 3 and dx.shape[-1] == 1)
+
+    dx, dy = [dequantize(d, -max_val, max_val, 255) for d in [dx, dy]]
+
+    if denorm:
+        dx *= dx.shape[1]
+        dy *= dx.shape[0]
+    flow = np.dstack((dx, dy))
+    return flow
+
+
+def flow_warp(img, flow, filling_value=0, interpolate_mode='nearest'):
+    """Use flow to warp img.
+
+    Args:
+        img (ndarray, float or uint8): Image to be warped.
+        flow (ndarray, float): Optical Flow.
+        filling_value (int): The missing pixels will be set with filling_value.
+        interpolate_mode (str): bilinear -> Bilinear Interpolation;
+                                nearest -> Nearest Neighbor.
+
+    Returns:
+        ndarray: Warped image with the same shape of img
+    """
+    warnings.warn('This function is just for prototyping and cannot '
+                  'guarantee the computational efficiency.')
+    assert flow.ndim == 3, 'Flow must be in 3D arrays.'
+    height = flow.shape[0]
+    width = flow.shape[1]
+    channels = img.shape[2]
+
+    output = np.ones(
+        (height, width, channels), dtype=img.dtype) * filling_value
+
+    grid = np.indices((height, width)).swapaxes(0, 1).swapaxes(1, 2)
+    dx = grid[:, :, 0] + flow[:, :, 1]
+    dy = grid[:, :, 1] + flow[:, :, 0]
+    sx = np.floor(dx).astype(int)
+    sy = np.floor(dy).astype(int)
+    valid = (sx >= 0) & (sx < height - 1) & (sy >= 0) & (sy < width - 1)
+
+    if interpolate_mode == 'nearest':
+        output[valid, :] = img[dx[valid].round().astype(int),
+                               dy[valid].round().astype(int), :]
+    elif interpolate_mode == 'bilinear':
+        # dirty walkround for integer positions
+        eps_ = 1e-6
+        dx, dy = dx + eps_, dy + eps_
+        left_top_ = img[np.floor(dx[valid]).astype(int),
+                        np.floor(dy[valid]).astype(int), :] * (
+                            np.ceil(dx[valid]) - dx[valid])[:, None] * (
+                                np.ceil(dy[valid]) - dy[valid])[:, None]
+        left_down_ = img[np.ceil(dx[valid]).astype(int),
+                         np.floor(dy[valid]).astype(int), :] * (
+                             dx[valid] - np.floor(dx[valid]))[:, None] * (
+                                 np.ceil(dy[valid]) - dy[valid])[:, None]
+        right_top_ = img[np.floor(dx[valid]).astype(int),
+                         np.ceil(dy[valid]).astype(int), :] * (
+                             np.ceil(dx[valid]) - dx[valid])[:, None] * (
+                                 dy[valid] - np.floor(dy[valid]))[:, None]
+        right_down_ = img[np.ceil(dx[valid]).astype(int),
+                          np.ceil(dy[valid]).astype(int), :] * (
+                              dx[valid] - np.floor(dx[valid]))[:, None] * (
+                                  dy[valid] - np.floor(dy[valid]))[:, None]
+        output[valid, :] = left_top_ + left_down_ + right_top_ + right_down_
+    else:
+        raise NotImplementedError(
+            'We only support interpolation modes of nearest and bilinear, '
+            f'but got {interpolate_mode}.')
+    return output.astype(img.dtype)
+
+
+def flow_from_bytes(content):
+    """Read dense optical flow from bytes.
+
+    .. note::
+        This load optical flow function works for FlyingChairs, FlyingThings3D,
+        Sintel, FlyingChairsOcc datasets, but cannot load the data from
+        ChairsSDHom.
+
+    Args:
+        content (bytes): Optical flow bytes got from files or other streams.
+
+    Returns:
+        ndarray: Loaded optical flow with the shape (H, W, 2).
+    """
+
+    # header in first 4 bytes
+    header = content[:4]
+    if header.decode('utf-8') != 'PIEH':
+        raise Exception('Flow file header does not contain PIEH')
+    # width in second 4 bytes
+    width = np.frombuffer(content[4:], np.int32, 1).squeeze()
+    # height in third 4 bytes
+    height = np.frombuffer(content[8:], np.int32, 1).squeeze()
+    # after first 12 bytes, all bytes are flow
+    flow = np.frombuffer(content[12:], np.float32, width * height * 2).reshape(
+        (height, width, 2))
+
+    return flow
+
+
+def sparse_flow_from_bytes(content):
+    """Read the optical flow in KITTI datasets from bytes.
+
+    This function is modified from RAFT load the `KITTI datasets
+    <https://github.com/princeton-vl/RAFT/blob/224320502d66c356d88e6c712f38129e60661e80/core/utils/frame_utils.py#L102>`_.
+
+    Args:
+        content (bytes): Optical flow bytes got from files or other streams.
+
+    Returns:
+        Tuple(ndarray, ndarray): Loaded optical flow with the shape (H, W, 2)
+            and flow valid mask with the shape (H, W).
+    """  # nopa
+
+    content = np.frombuffer(content, np.uint8)
+    flow = cv2.imdecode(content, cv2.IMREAD_ANYDEPTH | cv2.IMREAD_COLOR)
+    flow = flow[:, :, ::-1].astype(np.float32)
+    # flow shape (H, W, 2) valid shape (H, W)
+    flow, valid = flow[:, :, :2], flow[:, :, 2]
+    flow = (flow - 2**15) / 64.0
+    return flow, valid