pytorch/caffe2/python/test_util.py

## @package test_util
# Module caffe2.python.test_util




import numpy as np
from caffe2.python import core, workspace

import os
import pathlib
import shutil
import tempfile
import unittest
from typing import Any, Callable, Tuple, Type
from types import TracebackType


def rand_array(*dims):
    # np.random.rand() returns float instead of 0-dim array, that's why need to
    # do some tricks
    return np.array(np.random.rand(*dims) - 0.5).astype(np.float32)


def randBlob(name, type, *dims, **kwargs):
    offset = kwargs['offset'] if 'offset' in kwargs else 0.0
    workspace.FeedBlob(name, np.random.rand(*dims).astype(type) + offset)


def randBlobFloat32(name, *dims, **kwargs):
    randBlob(name, np.float32, *dims, **kwargs)


def randBlobsFloat32(names, *dims, **kwargs):
    for name in names:
        randBlobFloat32(name, *dims, **kwargs)


def numOps(net):
    return len(net.Proto().op)


def str_compare(a, b, encoding="utf8"):
    if isinstance(a, bytes):
        a = a.decode(encoding)
    if isinstance(b, bytes):
        b = b.decode(encoding)
    return a == b


def get_default_test_flags():
    return [
        'caffe2',
        '--caffe2_log_level=0',
        '--caffe2_cpu_allocator_do_zero_fill=0',
        '--caffe2_cpu_allocator_do_junk_fill=1',
    ]


def caffe2_flaky(test_method):
    # This decorator is used to mark a test method as flaky.
    # This is used in conjunction with the environment variable
    # CAFFE2_RUN_FLAKY_TESTS that specifies "flaky tests" mode
    # If flaky tests mode are on, only flaky tests are run
    # If flaky tests mode are off, only non-flaky tests are run
    # NOTE: the decorator should be applied as the top-level decorator
    # in a test method.
    test_method.__caffe2_flaky__ = True
    return test_method


def is_flaky_test_mode():
    return os.getenv('CAFFE2_RUN_FLAKY_TESTS', '0') == '1'


class TestCase(unittest.TestCase):
    @classmethod
    def setUpClass(cls):
        workspace.GlobalInit(get_default_test_flags())
        # clear the default engines settings to separate out its
        # affect from the ops tests
        core.SetEnginePref({}, {})

    def setUp(self):
        # Skip tests based on whether we're in flaky test mode and
        # the test is decorated as a flaky test.
        test_method = getattr(self, self._testMethodName)
        is_flaky_test = getattr(test_method, "__caffe2_flaky__", False)
        if (is_flaky_test_mode() and not is_flaky_test):
            raise unittest.SkipTest("Non-flaky tests are skipped in flaky test mode")
        elif (not is_flaky_test_mode() and is_flaky_test):
            raise unittest.SkipTest("Flaky tests are skipped in regular test mode")

        self.ws = workspace.C.Workspace()
        workspace.ResetWorkspace()

    def tearDown(self):
        workspace.ResetWorkspace()

    def make_tempdir(self) -> pathlib.Path:
        tmp_folder = pathlib.Path(tempfile.mkdtemp(prefix="caffe2_test."))
        self.addCleanup(self._remove_tempdir, tmp_folder)
        return tmp_folder

    def _remove_tempdir(self, path: pathlib.Path) -> None:
        def _onerror(
            fn: Callable[..., Any],
            path: str,
            exc_info: Tuple[Type[BaseException], BaseException, TracebackType],
        ) -> None:
            # Ignore FileNotFoundError, but re-raise anything else
            if not isinstance(exc_info[1], FileNotFoundError):
                raise exc_info[1].with_traceback(exc_info[2])

        shutil.rmtree(str(path), onerror=_onerror)