Python tempfile.gettempdir方法代码示例

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def download_workflow(url):
    """Download workflow at ``url`` to a local temporary file.

    :param url: URL to .alfredworkflow file in GitHub repo
    :returns: path to downloaded file

    """
    filename = url.split('/')[-1]

    if (not filename.endswith('.alfredworkflow') and
            not filename.endswith('.alfred3workflow')):
        raise ValueError('attachment not a workflow: {0}'.format(filename))

    local_path = os.path.join(tempfile.gettempdir(), filename)

    wf().logger.debug(
        'downloading updated workflow from `%s` to `%s` ...', url, local_path)

    response = web.get(url)

    with open(local_path, 'wb') as output:
        output.write(response.content)

    return local_path 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def maybe_download_mnist_file(file_name, datadir=None, force=False):
    try:
        from urllib.parse import urljoin
        from urllib.request import urlretrieve
    except ImportError:
        from urlparse import urljoin
        from urllib import urlretrieve

    if not datadir:
        datadir = tempfile.gettempdir()
    dest_file = os.path.join(datadir, file_name)

    if force or not os.path.isfile(file_name):
        url = urljoin('http://yann.lecun.com/exdb/mnist/', file_name)
        urlretrieve(url, dest_file)
    return dest_file 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def __init__(self, label="DefaultValues", logfile=None, verbose=False, debug=False):
        super(DefaultValues, self).__init__(label=label, logfile=logfile, verbose=verbose, debug=debug)
        self._validator = Validator(logfile=logfile, verbose=verbose, debug=debug)
        pipeline_dir = os.path.dirname(self._validator.get_full_path(os.path.dirname(scripts.__file__)))

        self._DEFAULT_seed = random.randint(0, 2147483640)
        self._DEFAULT_tmp_dir = tempfile.gettempdir()
        self._DEFAULT_directory_pipeline = pipeline_dir

        original_wd = os.getcwd()
        os.chdir(pipeline_dir)
        file_path_config = os.path.join(pipeline_dir, "default_config.ini")
        if self._validator.validate_file(file_path_config, silent=True):
            self._from_config(file_path_config)
        else:
            self._from_hardcoded(pipeline_dir)
        os.chdir(original_wd) 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def default_ccache_dir() -> str:
    """:return: ccache directory for the current platform"""
    # Share ccache across containers
    if 'CCACHE_DIR' in os.environ:
        ccache_dir = os.path.realpath(os.environ['CCACHE_DIR'])
        try:
            os.makedirs(ccache_dir, exist_ok=True)
            return ccache_dir
        except PermissionError:
            logging.info('Unable to make dirs at %s, falling back to local temp dir', ccache_dir)
    # In osx tmpdir is not mountable by default
    import platform
    if platform.system() == 'Darwin':
        ccache_dir = "/tmp/_mxnet_ccache"
        os.makedirs(ccache_dir, exist_ok=True)
        return ccache_dir
    return os.path.join(tempfile.gettempdir(), "ci_ccache") 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def sendImageWithUrl(self, to_, url):
        """Send a image with given image url

        :param url: image url to send
        """
        path = '%s/pythonLine-%1.data' % (tempfile.gettempdir(), randint(0, 9))


        r = requests.get(url, stream=True)
        if r.status_code == 200:
            with open(path, 'w') as f:
                shutil.copyfileobj(r.raw, f)
        else:
            raise Exception('Download image failure.')

        try:
            self.sendImage(to_, path)
        except Exception as e:
            raise e 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def build(path,inConsole=False,addWeb=False):
    params=[path,"--noupx","--onefile"]

    if not inConsole:
        params.append( "--noconsole")
    
    web=os.path.join( os.path.dirname(path), "web" )
    if addWeb and os.path.isdir(web):
        sep = (os.name == 'nt') and ";" or ":"
        params.append("--add-data=%s%sweb" % (web,sep))

    temp=os.path.join(tempfile.gettempdir(),".build")
    params.append( "--workpath" )
    params.append( temp )

    params.append( "--distpath" )
    params.append( os.path.dirname(path) )

    print( "PYINSTALLER:",params )
    pyi.run( params ) 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def _tar_and_copy(src_dir, target_dir):
  """Tar and gzip src_dir and copy to GCS target_dir."""
  src_dir = src_dir.rstrip("/")
  target_dir = target_dir.rstrip("/")
  tmp_dir = tempfile.gettempdir().rstrip("/")
  src_base = os.path.basename(src_dir)
  cloud.shell_run(
      "tar -zcf {tmp_dir}/{src_base}.tar.gz -C {src_dir} .",
      src_dir=src_dir,
      src_base=src_base,
      tmp_dir=tmp_dir)
  final_destination = "%s/%s.tar.gz" % (target_dir, src_base)
  cloud.shell_run(
      ("gsutil cp {tmp_dir}/{src_base}.tar.gz "
       "{final_destination}"),
      tmp_dir=tmp_dir,
      src_base=src_base,
      final_destination=final_destination)
  return final_destination 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def tar_and_copy_usr_dir(usr_dir, train_dir):
  """Package, tar, and copy usr_dir to GCS train_dir."""
  tf.logging.info("Tarring and pushing t2t_usr_dir.")
  usr_dir = os.path.abspath(os.path.expanduser(usr_dir))
  # Copy usr dir to a temp location
  top_dir = os.path.join(tempfile.gettempdir(), "t2t_usr_container")
  tmp_usr_dir = os.path.join(top_dir, usr_dir_lib.INTERNAL_USR_DIR_PACKAGE)
  shutil.rmtree(top_dir, ignore_errors=True)
  shutil.copytree(usr_dir, tmp_usr_dir)
  # Insert setup.py if one does not exist
  top_setup_fname = os.path.join(top_dir, "setup.py")
  setup_file_str = get_setup_file(
      name="DummyUsrDirPackage",
      packages=get_requirements(usr_dir)
  )
  with tf.gfile.Open(top_setup_fname, "w") as f:
    f.write(setup_file_str)
  usr_tar = _tar_and_copy(top_dir, train_dir)
  return usr_tar 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def configure(dir=None, format_strs=None):
    if dir is None:
        dir = os.getenv('OPENAI_LOGDIR')
    if dir is None:
        dir = osp.join(tempfile.gettempdir(),
            datetime.datetime.now().strftime("openai-%Y-%m-%d-%H-%M-%S-%f"))
    assert isinstance(dir, str)
    os.makedirs(dir, exist_ok=True)

    if format_strs is None:
        strs = os.getenv('OPENAI_LOG_FORMAT')
        format_strs = strs.split(',') if strs else LOG_OUTPUT_FORMATS
    output_formats = [make_output_format(f, dir) for f in format_strs]

    Logger.CURRENT = Logger(dir=dir, output_formats=output_formats)
    log('Logging to %s'%dir) 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def test_toolchain_standard_not_implemented(self):
        spec = Spec()

        with self.assertRaises(NotImplementedError):
            self.toolchain(spec)

        with self.assertRaises(NotImplementedError):
            self.toolchain.assemble(spec)

        with self.assertRaises(NotImplementedError):
            self.toolchain.link(spec)

        # Check that the build_dir is set on the spec based on tempfile
        self.assertTrue(spec['build_dir'].startswith(
            realpath(tempfile.gettempdir())))
        # Also that it got deleted properly.
        self.assertFalse(exists(spec['build_dir'])) 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def configure(dir=None, format_strs=None):
    if dir is None:
        dir = os.getenv('OPENAI_LOGDIR')
    if dir is None:
        dir = osp.join(tempfile.gettempdir(),
            datetime.datetime.now().strftime("openai-%Y-%m-%d-%H-%M-%S-%f"))
    assert isinstance(dir, str)
    os.makedirs(dir, exist_ok=True)

    log_suffix = ''
    from mpi4py import MPI
    rank = MPI.COMM_WORLD.Get_rank()
    if rank > 0:
        log_suffix = "-rank%03i" % rank

    if format_strs is None:
        if rank == 0:
            format_strs = os.getenv('OPENAI_LOG_FORMAT', 'stdout,log,csv').split(',')
        else:
            format_strs = os.getenv('OPENAI_LOG_FORMAT_MPI', 'log').split(',')
    format_strs = filter(None, format_strs)
    output_formats = [make_output_format(f, dir, log_suffix) for f in format_strs]

    Logger.CURRENT = Logger(dir=dir, output_formats=output_formats)
    log('Logging to %s'%dir) 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def __init__(
            self,
            seed=0,
            episode_len=None,
            no_images=None
    ):
        from tensorflow.examples.tutorials.mnist import input_data
        # we could use temporary directory for this with a context manager and 
        # TemporaryDirecotry, but then each test that uses mnist would re-download the data
        # this way the data is not cleaned up, but we only download it once per machine
        mnist_path = osp.join(tempfile.gettempdir(), 'MNIST_data')
        with filelock.FileLock(mnist_path + '.lock'):
           self.mnist = input_data.read_data_sets(mnist_path)

        self.np_random = np.random.RandomState()
        self.np_random.seed(seed)

        self.observation_space = Box(low=0.0, high=1.0, shape=(28,28,1))
        self.action_space = Discrete(10)
        self.episode_len = episode_len
        self.time = 0
        self.no_images = no_images

        self.train_mode()
        self.reset() 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def main():
    # Get data files for the model.
    data_paths, [deploy_file, model_file, mean_proto] = common.find_sample_data(description="Runs an MNIST network using a Caffe model file", subfolder="mnist", find_files=["mnist.prototxt", "mnist.caffemodel", "mnist_mean.binaryproto"])

    # Cache the engine in a temporary directory.
    engine_path = os.path.join(tempfile.gettempdir(), "mnist.engine")
    with get_engine(deploy_file, model_file, engine_path) as engine, engine.create_execution_context() as context:
        # Build an engine, allocate buffers and create a stream.
        # For more information on buffer allocation, refer to the introductory samples.
        inputs, outputs, bindings, stream = common.allocate_buffers(engine)
        mean = retrieve_mean(mean_proto)
        # For more information on performing inference, refer to the introductory samples.
        inputs[0].host, case_num = load_normalized_test_case(data_paths, mean)
        # The common.do_inference function will return a list of outputs - we only have one in this case.
        [output] = common.do_inference(context, bindings=bindings, inputs=inputs, outputs=outputs, stream=stream)
        pred = np.argmax(output)
        print("Test Case: " + str(case_num))
        print("Prediction: " + str(pred))

    # After the engine is destroyed, we destroy the plugin. This function is exposed through the binding code in plugin/pyFullyConnected.cpp.
    fc_factory.destroy_plugin() 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def test_task_embed(self):
        inputs, outputs = get_model(
            token_num=20,
            embed_dim=12,
            head_num=3,
            transformer_num=2,
            use_task_embed=True,
            task_num=10,
            training=False,
            dropout_rate=0.0,
        )
        model = keras.models.Model(inputs, outputs)
        model_path = os.path.join(tempfile.gettempdir(), 'keras_bert_%f.h5' % np.random.random())
        model.save(model_path)
        model = keras.models.load_model(
            model_path,
            custom_objects=get_custom_objects(),
        )
        model.summary(line_length=200) 

# 需要导入模块: import tempfile [as 别名]
# 或者: from tempfile import gettempdir [as 别名]
def retrieve_download(dl):
    """Saves a download to a temporary file and returns path.

    .. versionadded: 1.37

    Args:
        url (unicode): URL to .alfredworkflow file in GitHub repo

    Returns:
        unicode: path to downloaded file

    """
    if not match_workflow(dl.filename):
        raise ValueError('attachment not a workflow: ' + dl.filename)

    path = os.path.join(tempfile.gettempdir(), dl.filename)
    wf().logger.debug('downloading update from '
                      '%r to %r ...', dl.url, path)

    r = web.get(dl.url)
    r.raise_for_status()

    r.save_to_path(path)

    return path