# Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import contextlib import importlib.util import inspect import logging import numpy as np import os import random import re import shutil import sys import tempfile import unittest from distutils.util import strtobool from io import StringIO from packaging import version from pathlib import Path from typing import Iterator, Union from unittest import mock from unittest.case import SkipTest try: import torch _torch_available = True except: _torch_available = False def is_torch_available(): return _torch_available def parse_flag_from_env(key, default=False): try: value = os.environ[key] except KeyError: # KEY isn't set, default to `default`. _value = default else: # KEY is set, convert it to True or False. try: _value = strtobool(value) except ValueError: # More values are supported, but let's keep the message simple. raise ValueError(f"If set, {key} must be yes or no.") return _value def parse_int_from_env(key, default=None): try: value = os.environ[key] except KeyError: _value = default else: try: _value = int(value) except ValueError: raise ValueError(f"If set, {key} must be a int.") return _value def require_torch(test_case): """ Decorator marking a test that requires PyTorch. These tests are skipped when PyTorch isn't installed. """ if not is_torch_available(): return unittest.skip("test requires PyTorch")(test_case) else: return test_case def require_torch_multi_gpu(test_case): """ Decorator marking a test that requires a multi-GPU setup (in PyTorch). These tests are skipped on a machine without multiple GPUs. To run *only* the multi_gpu tests, assuming all test names contain multi_gpu: $ pytest -sv ./tests -k "multi_gpu" """ if not is_torch_available(): return unittest.skip("test requires PyTorch")(test_case) import torch if torch.cuda.device_count() < 2: return unittest.skip("test requires multiple GPUs")(test_case) else: return test_case def require_torch_non_multi_gpu(test_case): """ Decorator marking a test that requires 0 or 1 GPU setup (in PyTorch). """ if not is_torch_available(): return unittest.skip("test requires PyTorch")(test_case) import torch if torch.cuda.device_count() > 1: return unittest.skip("test requires 0 or 1 GPU")(test_case) else: return test_case def require_torch_up_to_2_gpus(test_case): """ Decorator marking a test that requires 0 or 1 or 2 GPU setup (in PyTorch). """ if not is_torch_available(): return unittest.skip("test requires PyTorch")(test_case) import torch if torch.cuda.device_count() > 2: return unittest.skip("test requires 0 or 1 or 2 GPUs")(test_case) else: return test_case def require_torch_tpu(test_case): """ Decorator marking a test that requires a TPU (in PyTorch). """ if not is_torch_tpu_available(): return unittest.skip("test requires PyTorch TPU") else: return test_case if is_torch_available(): # Set env var CUDA_VISIBLE_DEVICES="" to force cpu-mode import torch torch_device = "cuda" if torch.cuda.is_available() else "cpu" else: torch_device = None def require_torch_gpu(test_case): """Decorator marking a test that requires CUDA and PyTorch.""" if torch_device != "cuda": return unittest.skip("test requires CUDA")(test_case) else: return test_case def require_datasets(test_case): """Decorator marking a test that requires datasets.""" if not is_datasets_available(): return unittest.skip("test requires `datasets`")(test_case) else: return test_case def is_deepspeed_available(): return importlib.util.find_spec("deepspeed") is not None def require_deepspeed(test_case): """ Decorator marking a test that requires deepspeed """ if not is_deepspeed_available(): return unittest.skip("test requires deepspeed")(test_case) else: return test_case def is_bnb_available(): return importlib.util.find_spec("bitsandbytes") is not None def require_bnb(test_case): """ Decorator marking a test that requires bitsandbytes """ if not is_bnb_available(): return unittest.skip("test requires bitsandbytes from https://github.com/facebookresearch/bitsandbytes")(test_case) else: return test_case def require_bnb_non_decorator(): """ Non-Decorator function that would skip a test if bitsandbytes is missing """ if not is_bnb_available(): raise SkipTest("Test requires bitsandbytes from https://github.com/facebookresearch/bitsandbytes") def set_seed(seed: int=42): """ Helper function for reproducible behavior to set the seed in ``random``, ``numpy``, ``torch`` Args: seed (:obj:`int`): The seed to set. """ random.seed(seed) np.random.seed(seed) if is_torch_available(): torch.manual_seed(seed) torch.cuda.manual_seed_all(seed) # ^^ safe to call this function even if cuda is not available def get_gpu_count(): """ Return the number of available gpus (regardless of whether torch or tf is used) """ if is_torch_available(): import torch return torch.cuda.device_count() elif is_tf_available(): import tensorflow as tf return len(tf.config.list_physical_devices("GPU")) else: return 0 def torch_assert_equal(actual, expected, **kwargs): # assert_close was added around pt-1.9, it does better checks - e.g will check dimensions match if hasattr(torch.testing, "assert_close"): return torch.testing.assert_close(actual, expected, rtol=0.0, atol=0.0, **kwargs) else: return torch.allclose(actual, expected, rtol=0.0, atol=0.0) def torch_assert_close(actual, expected, **kwargs): # assert_close was added around pt-1.9, it does better checks - e.g will check dimensions match if hasattr(torch.testing, "assert_close"): return torch.testing.assert_close(actual, expected, **kwargs) else: kwargs.pop("msg", None) # doesn't have msg arg return torch.allclose(actual, expected, **kwargs) def is_torch_bf16_available(): # from https://github.com/huggingface/transformers/blob/26eb566e43148c80d0ea098c76c3d128c0281c16/src/transformers/file_utils.py#L301 if is_torch_available(): import torch if not torch.cuda.is_available() or torch.version.cuda is None: return False if torch.cuda.get_device_properties(torch.cuda.current_device()).major < 8: return False if int(torch.version.cuda.split(".")[0]) < 11: return False if not version.parse(torch.__version__) >= version.parse("1.09"): return False return True else: return False def require_torch_bf16(test_case): """Decorator marking a test that requires CUDA hardware supporting bf16 and PyTorch >= 1.9.""" if not is_torch_bf16_available(): return unittest.skip("test requires CUDA hardware supporting bf16 and PyTorch >= 1.9")(test_case) else: return test_case def get_tests_dir(append_path=None): """ Args: append_path: optional path to append to the tests dir path Return: The full path to the `tests` dir, so that the tests can be invoked from anywhere. Optionally `append_path` is joined after the `tests` dir the former is provided. """ # this function caller's __file__ caller__file__ = inspect.stack()[1][1] tests_dir = os.path.abspath(os.path.dirname(caller__file__)) if append_path: return os.path.join(tests_dir, append_path) else: return tests_dir # # Helper functions for dealing with testing text outputs # The original code came from: # https://github.com/fastai/fastai/blob/master/tests/utils/text.py # When any function contains print() calls that get overwritten, like progress bars, # a special care needs to be applied, since under pytest -s captured output (capsys # or contextlib.redirect_stdout) contains any temporary printed strings, followed by # \r's. This helper function ensures that the buffer will contain the same output # with and without -s in pytest, by turning: # foo bar\r tar mar\r final message # into: # final message # it can handle a single string or a multiline buffer def apply_print_resets(buf): return re.sub(r"^.*\r", "", buf, 0, re.M) def assert_screenout(out, what): out_pr = apply_print_resets(out).lower() match_str = out_pr.find(what.lower()) assert match_str != -1, f"expecting to find {what} in output: f{out_pr}" class CaptureStd: """ Context manager to capture: - stdout: replay it, clean it up and make it available via ``obj.out`` - stderr: replay it and make it available via ``obj.err`` init arguments: - out - capture stdout:`` True``/``False``, default ``True`` - err - capture stdout: ``True``/``False``, default ``True`` - replay - whether to replay or not: ``True``/``False``, default ``True``. By default each captured stream gets replayed back on context's exit, so that one can see what the test was doing. If this is a not wanted behavior and the captured data shouldn't be replayed, pass ``replay=False`` to disable this feature. Examples:: # to capture stdout only with auto-replay with CaptureStdout() as cs: print("Secret message") assert "message" in cs.out # to capture stderr only with auto-replay import sys with CaptureStderr() as cs: print("Warning: ", file=sys.stderr) assert "Warning" in cs.err # to capture both streams with auto-replay with CaptureStd() as cs: print("Secret message") print("Warning: ", file=sys.stderr) assert "message" in cs.out assert "Warning" in cs.err # to capture just one of the streams, and not the other, with auto-replay with CaptureStd(err=False) as cs: print("Secret message") assert "message" in cs.out # but best use the stream-specific subclasses # to capture without auto-replay with CaptureStd(replay=False) as cs: print("Secret message") assert "message" in cs.out """ def __init__(self, out=True, err=True, replay=True): self.replay = replay if out: self.out_buf = StringIO() self.out = "error: CaptureStd context is unfinished yet, called too early" else: self.out_buf = None self.out = "not capturing stdout" if err: self.err_buf = StringIO() self.err = "error: CaptureStd context is unfinished yet, called too early" else: self.err_buf = None self.err = "not capturing stderr" def __enter__(self): if self.out_buf: self.out_old = sys.stdout sys.stdout = self.out_buf if self.err_buf: self.err_old = sys.stderr sys.stderr = self.err_buf return self def __exit__(self, *exc): if self.out_buf: sys.stdout = self.out_old captured = self.out_buf.getvalue() if self.replay: sys.stdout.write(captured) self.out = apply_print_resets(captured) if self.err_buf: sys.stderr = self.err_old captured = self.err_buf.getvalue() if self.replay: sys.stderr.write(captured) self.err = captured def __repr__(self): msg = "" if self.out_buf: msg += f"stdout: {self.out}\n" if self.err_buf: msg += f"stderr: {self.err}\n" return msg # in tests it's the best to capture only the stream that's wanted, otherwise # it's easy to miss things, so unless you need to capture both streams, use the # subclasses below (less typing). Or alternatively, configure `CaptureStd` to # disable the stream you don't need to test. class CaptureStdout(CaptureStd): """Same as CaptureStd but captures only stdout""" def __init__(self, replay=True): super().__init__(err=False, replay=replay) class CaptureStderr(CaptureStd): """Same as CaptureStd but captures only stderr""" def __init__(self, replay=True): super().__init__(out=False, replay=replay) class CaptureLogger: """ Context manager to capture `logging` streams Args: - logger: 'logging` logger object Results: The captured output is available via `self.out` Example:: >>> from transformers import logging >>> from transformers.testing_utils import CaptureLogger >>> msg = "Testing 1, 2, 3" >>> logging.set_verbosity_info() >>> logger = logging.get_logger("transformers.models.bart.tokenization_bart") >>> with CaptureLogger(logger) as cl: ... logger.info(msg) >>> assert cl.out, msg+"\n" """ def __init__(self, logger): self.logger = logger self.io = StringIO() self.sh = logging.StreamHandler(self.io) self.out = "" def __enter__(self): self.logger.addHandler(self.sh) return self def __exit__(self, *exc): self.logger.removeHandler(self.sh) self.out = self.io.getvalue() def __repr__(self): return f"captured: {self.out}\n" @contextlib.contextmanager # adapted from https://stackoverflow.com/a/64789046/9201239 def ExtendSysPath(path: Union[str, os.PathLike]) -> Iterator[None]: """ Temporary add given path to `sys.path`. Usage :: with ExtendSysPath('/path/to/dir'): mymodule = importlib.import_module('mymodule') """ path = os.fspath(path) try: sys.path.insert(0, path) yield finally: sys.path.remove(path) class TestCasePlus(unittest.TestCase): """ This class extends `unittest.TestCase` with additional features. Feature 1: A set of fully resolved important file and dir path accessors. In tests often we need to know where things are relative to the current test file, and it's not trivial since the test could be invoked from more than one directory or could reside in sub-directories with different depths. This class solves this problem by sorting out all the basic paths and provides easy accessors to them: * ``pathlib`` objects (all fully resolved): - ``test_file_path`` - the current test file path (=``__file__``) - ``test_file_dir`` - the directory containing the current test file - ``tests_dir`` - the directory of the ``tests`` test suite - ``data_dir`` - the directory of the ``tests/data`` test suite - ``repo_root_dir`` - the directory of the repository - ``src_dir`` - the directory of ``src`` (i.e. where the ``transformers`` sub-dir resides) * stringified paths---same as above but these return paths as strings, rather than ``pathlib`` objects: - ``test_file_path_str`` - ``test_file_dir_str`` - ``tests_dir_str`` - ``data_dir_str`` - ``repo_root_dir_str`` - ``src_dir_str`` Feature 2: Flexible auto-removable temporary dirs which are guaranteed to get removed at the end of test. 1. Create a unique temporary dir: :: def test_whatever(self): tmp_dir = self.get_auto_remove_tmp_dir() ``tmp_dir`` will contain the path to the created temporary dir. It will be automatically removed at the end of the test. 2. Create a temporary dir of my choice, ensure it's empty before the test starts and don't empty it after the test. :: def test_whatever(self): tmp_dir = self.get_auto_remove_tmp_dir("./xxx") This is useful for debug when you want to monitor a specific directory and want to make sure the previous tests didn't leave any data in there. 3. You can override the first two options by directly overriding the ``before`` and ``after`` args, leading to the following behavior: ``before=True``: the temporary dir will always be cleared at the beginning of the test. ``before=False``: if the temporary dir already existed, any existing files will remain there. ``after=True``: the temporary dir will always be deleted at the end of the test. ``after=False``: the temporary dir will always be left intact at the end of the test. Note 1: In order to run the equivalent of ``rm -r`` safely, only subdirs of the project repository checkout are allowed if an explicit ``tmp_dir`` is used, so that by mistake no ``/tmp`` or similar important part of the filesystem will get nuked. i.e. please always pass paths that start with ``./`` Note 2: Each test can register multiple temporary dirs and they all will get auto-removed, unless requested otherwise. Feature 3: Get a copy of the ``os.environ`` object that sets up ``PYTHONPATH`` specific to the current test suite. This is useful for invoking external programs from the test suite - e.g. distributed training. :: def test_whatever(self): env = self.get_env() """ def setUp(self): # get_auto_remove_tmp_dir feature: self.teardown_tmp_dirs = [] # figure out the resolved paths for repo_root, tests, etc. self._test_file_path = inspect.getfile(self.__class__) path = Path(self._test_file_path).resolve() self._test_file_dir = path.parents[0] for up in [1, 2, 3]: tmp_dir = path.parents[up] if (tmp_dir / "megatron").is_dir() and (tmp_dir / "tests").is_dir(): break if tmp_dir: self._repo_root_dir = tmp_dir else: raise ValueError(f"can't figure out the root of the repo from {self._test_file_path}") self._tests_dir = self._repo_root_dir / "tests" self._data_dir = self._repo_root_dir / "tests" / "data" self._src_dir = self._repo_root_dir # megatron doesn't use "src/" prefix in the repo @property def test_file_path(self): return self._test_file_path @property def test_file_path_str(self): return str(self._test_file_path) @property def test_file_dir(self): return self._test_file_dir @property def test_file_dir_str(self): return str(self._test_file_dir) @property def tests_dir(self): return self._tests_dir @property def tests_dir_str(self): return str(self._tests_dir) @property def data_dir(self): return self._data_dir @property def data_dir_str(self): return str(self._data_dir) @property def repo_root_dir(self): return self._repo_root_dir @property def repo_root_dir_str(self): return str(self._repo_root_dir) @property def src_dir(self): return self._src_dir @property def src_dir_str(self): return str(self._src_dir) def get_env(self): """ Return a copy of the ``os.environ`` object that sets up ``PYTHONPATH`` correctly. This is useful for invoking external programs from the test suite - e.g. distributed training. It always inserts ``.`` first, then ``./tests`` depending on the test suite type and finally the preset ``PYTHONPATH`` if any (all full resolved paths). """ env = os.environ.copy() paths = [self.src_dir_str] paths.append(self.tests_dir_str) paths.append(env.get("PYTHONPATH", "")) env["PYTHONPATH"] = ":".join(paths) return env def get_auto_remove_tmp_dir(self, tmp_dir=None, before=None, after=None): """ Args: tmp_dir (:obj:`string`, `optional`): if :obj:`None`: - a unique temporary path will be created - sets ``before=True`` if ``before`` is :obj:`None` - sets ``after=True`` if ``after`` is :obj:`None` else: - :obj:`tmp_dir` will be created - sets ``before=True`` if ``before`` is :obj:`None` - sets ``after=False`` if ``after`` is :obj:`None` before (:obj:`bool`, `optional`): If :obj:`True` and the :obj:`tmp_dir` already exists, make sure to empty it right away if :obj:`False` and the :obj:`tmp_dir` already exists, any existing files will remain there. after (:obj:`bool`, `optional`): If :obj:`True`, delete the :obj:`tmp_dir` at the end of the test if :obj:`False`, leave the :obj:`tmp_dir` and its contents intact at the end of the test. Returns: tmp_dir(:obj:`string`): either the same value as passed via `tmp_dir` or the path to the auto-selected tmp dir """ if tmp_dir is not None: # defining the most likely desired behavior for when a custom path is provided. # this most likely indicates the debug mode where we want an easily locatable dir that: # 1. gets cleared out before the test (if it already exists) # 2. is left intact after the test if before is None: before = True if after is None: after = False # using provided path path = Path(tmp_dir).resolve() # to avoid nuking parts of the filesystem, only relative paths are allowed if not tmp_dir.startswith("./"): raise ValueError( f"`tmp_dir` can only be a relative path, i.e. `./some/path`, but received `{tmp_dir}`" ) # ensure the dir is empty to start with if before is True and path.exists(): shutil.rmtree(tmp_dir, ignore_errors=True) path.mkdir(parents=True, exist_ok=True) else: # defining the most likely desired behavior for when a unique tmp path is auto generated # (not a debug mode), here we require a unique tmp dir that: # 1. is empty before the test (it will be empty in this situation anyway) # 2. gets fully removed after the test if before is None: before = True if after is None: after = True # using unique tmp dir (always empty, regardless of `before`) tmp_dir = tempfile.mkdtemp() if after is True: # register for deletion self.teardown_tmp_dirs.append(tmp_dir) return tmp_dir def tearDown(self): # get_auto_remove_tmp_dir feature: remove registered temp dirs for path in self.teardown_tmp_dirs: shutil.rmtree(path, ignore_errors=True) self.teardown_tmp_dirs = [] def mockenv(**kwargs): """ this is a convenience wrapper, that allows this :: @mockenv(RUN_SLOW=True, USE_TF=False) def test_something(): run_slow = os.getenv("RUN_SLOW", False) use_tf = os.getenv("USE_TF", False) """ return mock.patch.dict(os.environ, kwargs) # from https://stackoverflow.com/a/34333710/9201239 @contextlib.contextmanager def mockenv_context(*remove, **update): """ Temporarily updates the ``os.environ`` dictionary in-place. Similar to mockenv The ``os.environ`` dictionary is updated in-place so that the modification is sure to work in all situations. Args: remove: Environment variables to remove. update: Dictionary of environment variables and values to add/update. """ env = os.environ update = update or {} remove = remove or [] # List of environment variables being updated or removed. stomped = (set(update.keys()) | set(remove)) & set(env.keys()) # Environment variables and values to restore on exit. update_after = {k: env[k] for k in stomped} # Environment variables and values to remove on exit. remove_after = frozenset(k for k in update if k not in env) try: env.update(update) [env.pop(k, None) for k in remove] yield finally: env.update(update_after) [env.pop(k) for k in remove_after] # --- distributed testing functions --- # # adapted from https://stackoverflow.com/a/59041913/9201239 import asyncio # noqa class _RunOutput: def __init__(self, returncode, stdout, stderr): self.returncode = returncode self.stdout = stdout self.stderr = stderr async def _read_stream(stream, callback): while True: line = await stream.readline() if line: callback(line) else: break async def _stream_subprocess(cmd, env=None, stdin=None, timeout=None, quiet=False, echo=False) -> _RunOutput: if echo: print("\nRunning: ", " ".join(cmd)) p = await asyncio.create_subprocess_exec( cmd[0], *cmd[1:], stdin=stdin, stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE, env=env, ) # note: there is a warning for a possible deadlock when using `wait` with huge amounts of data in the pipe # https://docs.python.org/3/library/asyncio-subprocess.html#asyncio.asyncio.subprocess.Process.wait # # If it starts hanging, will need to switch to the following code. The problem is that no data # will be seen until it's done and if it hangs for example there will be no debug info. # out, err = await p.communicate() # return _RunOutput(p.returncode, out, err) out = [] err = [] def tee(line, sink, pipe, label=""): line = line.decode("utf-8").rstrip() sink.append(line) if not quiet: print(label, line, file=pipe) # XXX: the timeout doesn't seem to make any difference here await asyncio.wait( [ _read_stream(p.stdout, lambda l: tee(l, out, sys.stdout, label="stdout:")), _read_stream(p.stderr, lambda l: tee(l, err, sys.stderr, label="stderr:")), ], timeout=timeout, ) return _RunOutput(await p.wait(), out, err) def execute_subprocess_async(cmd, env=None, stdin=None, timeout=180, quiet=False, echo=True) -> _RunOutput: loop = asyncio.get_event_loop() result = loop.run_until_complete( _stream_subprocess(cmd, env=env, stdin=stdin, timeout=timeout, quiet=quiet, echo=echo) ) cmd_str = " ".join(cmd) if result.returncode > 0: stderr = "\n".join(result.stderr) raise RuntimeError( f"'{cmd_str}' failed with returncode {result.returncode}\n\n" f"The combined stderr from workers follows:\n{stderr}" ) # check that the subprocess actually did run and produced some output, should the test rely on # the remote side to do the testing if not result.stdout and not result.stderr: raise RuntimeError(f"'{cmd_str}' produced no output.") return result # --- Misc utils --- # def flatten_arguments(args): """ Converts dictionary argument to a list. Note: we add "IGNORED" at the beginning as this value is ignored by the argparser Example: {"arg1": "value1", "arg2": "value2"} -> ["IGNORED", "arg1", "value1", "arg2", "value2"] """ return ["IGNORED"] + [item for key_value in args.items() for item in key_value if item != ""]