gurudesh/pytracebugs huggingface dataset:
# Buggy code
def __init__(
    self,
    tokenizer,
    max_seq_len,
    data_dir,
    label_list=None,
    metric=None,
    train_filename="train.txt",
    dev_filename="dev.txt",
    test_filename="test.txt",
    dev_split=0.0,
    delimiter="\t",
    **kwargs,
):
    # Custom processor attributes
    self.delimiter = delimiter

    super(NERProcessor, self).__init__(
        tokenizer=tokenizer,
        max_seq_len=max_seq_len,
        train_filename=train_filename,
        dev_filename=dev_filename,
        test_filename=test_filename,
        dev_split=dev_split,
        data_dir=data_dir,
        tasks={},
    )

    if metric and label_list:
        self.add_task("ner", metric, label_list)


# Traceback (KeyError)
10/17/2019 20:16:51 - INFO - pytorch_transformers.modeling_utils -   load
ing weights file https://s3.amazonaws.com/models.huggingface.co/bert/bert
-base-cased-pytorch_model.bin from cache at /root/.cache/torch/pytorch_tr
ansformers/35d8b9d36faaf46728a0192d82bf7d00137490cd6074e8500778afed552a67
e5.3fadbea36527ae472139fe84cddaa65454d7429f12d543d80bfc3ad70de55ac2
10/17/2019 20:16:54 - WARNING - farm.modeling.language_model -   Could no
t automatically detect from language model name what language it is.
We guess it's an *ENGLISH* model ...
If not: Init the language model by supplying the 'language' param.
Example: Bert.load('my_mysterious_model_name', language='de')
10/17/2019 20:16:58 - INFO - farm.modeling.optimization -   Number of opt
imization steps: 12220
Traceback (most recent call last):
File "run_all_experiments.py", line 36, in <module>
main()
File "run_all_experiments.py", line 33, in main
run_experiment(experiment)
File "/home/user/farm/experiment.py", line 147, in run_experiment
model = trainer.train(model)
File "/home/user/farm/train.py", line 129, in train
model.connect_heads_with_processor(self.data_silo.processor.tasks)
File "/home/user/farm/modeling/adaptive_model.py", line 233, in connect
_heads_with_processor
head.label_tensor_name = tasks[head.task_name]["label_tensor_name"]
KeyError: 'question_answering'

# Fixed code
def __init__(
    self,
    tokenizer,
    max_seq_len,
    data_dir,
    label_list=None,
    metric=None,
    train_filename="train.txt",
    dev_filename="dev.txt",
    test_filename="test.txt",
    dev_split=0.0,
    delimiter="\t",
    **kwargs,
):
    # Custom processor attributes
    self.delimiter = delimiter

    super(NERProcessor, self).__init__(
        tokenizer=tokenizer,
        max_seq_len=max_seq_len,
        train_filename=train_filename,
        dev_filename=dev_filename,
        test_filename=test_filename,
        dev_split=dev_split,
        data_dir=data_dir,
        tasks={},
    )

    if metric and label_list:
        self.add_task("ner", metric, label_list)
    else:
        logger.info(
            "Initialized processor without tasks. Supply `metric` and `label_list` to the constructor for "
            "using the default task or add a custom task later via processor.add_task()"
        )
# Buggy code
def __init__(
    self, processor, batch_size, distributed=False, multiprocessing_chunk_size=100
):
    """
    :param processor: A dataset specific Processor object which will turn input (file or dict) into a Pytorch Dataset.
    :type processor: Processor
    :param batch_size: The size of batch that should be returned by the DataLoaders.
    :type batch_size: int
    :param distributed: Set to True if the program is running in a distributed setting.
    :type distributed: bool

    """
    self.distributed = distributed
    self.processor = processor
    self.data = {}
    self.batch_size = batch_size
    self.class_weights = None
    self.multiprocessing_chunk_size = multiprocessing_chunk_size
    self.max_processes = 128
    self._load_data()


# Traceback (AssertionError)
10/11/2019 17:12:47 - INFO - farm.data_handler.data_silo -   Loading dev set as a slice of train set
Traceback (most recent call last):
File ".../train.py", line 436, in <module>
augmentation=True)
File ".../train.py", line 348, in continue_finetuning
data_silo = DataSilo(processor=processor, batch_size=batch_size, multiprocessing_chunk_size=2000)
File "/.../farm/data_handler/data_silo.py", line 49, in __init__
self._load_data()
File ".../farm/data_handler/data_silo.py", line 104, in _load_data
self._create_dev_from_train()
File ".../farm/data_handler/data_silo.py", line 175, in _create_dev_from_train
train_dataset, dev_dataset = self.random_split_ConcatDataset(self.data["train"], lengths=[n_train, n_dev])
File ".../farm/data_handler/data_silo.py", line 200, in random_split_ConcatDataset
train = ConcatDataset(ds.datasets[:idx_dataset])
File ".../torch/utils/data/dataset.py", line 68, in __init__
assert len(datasets) > 0, 'datasets should not be an empty iterable'
AssertionError: datasets should not be an empty iterable

# Fixed code
def __init__(self, processor, batch_size, distributed=False):
    """
    :param processor: A dataset specific Processor object which will turn input (file or dict) into a Pytorch Dataset.
    :type processor: Processor
    :param batch_size: The size of batch that should be returned by the DataLoaders.
    :type batch_size: int
    :param distributed: Set to True if the program is running in a distributed setting.
    :type distributed: bool

    """
    self.distributed = distributed
    self.processor = processor
    self.data = {}
    self.batch_size = batch_size
    self.class_weights = None
    self.max_processes = 128
    self._load_data()
# Buggy code
def _create_dev_from_train(self):
    # TODO checks to ensure dev is loaded the right way
    n_dev = int(self.processor.dev_split * len(self.data["train"]))
    n_train = len(self.data["train"]) - n_dev

    # Todo: Seed
    # if(isinstance(self.data["train"], Dataset)):
    #     train_dataset, dev_dataset = random_split(self.data["train"], [n_train, n_dev])
    # else:
    train_dataset, dev_dataset = self.random_split_ConcatDataset(
        self.data["train"], lengths=[n_train, n_dev]
    )
    self.data["train"] = train_dataset
    if len(dev_dataset) > 0:
        self.data["dev"] = dev_dataset
    else:
        logger.warning(
            "No dev set created. Maybe adjust the dev_split parameter or the multiprocessing chunk size"
        )

    logger.info(
        f"Took {len(dev_dataset)} samples out of train set to create dev set (dev split is roughly {self.processor.dev_split})"
    )


# Traceback (AssertionError)
10/11/2019 17:12:47 - INFO - farm.data_handler.data_silo -   Loading dev set as a slice of train set
Traceback (most recent call last):
File ".../train.py", line 436, in <module>
augmentation=True)
File ".../train.py", line 348, in continue_finetuning
data_silo = DataSilo(processor=processor, batch_size=batch_size, multiprocessing_chunk_size=2000)
File "/.../farm/data_handler/data_silo.py", line 49, in __init__
self._load_data()
File ".../farm/data_handler/data_silo.py", line 104, in _load_data
self._create_dev_from_train()
File ".../farm/data_handler/data_silo.py", line 175, in _create_dev_from_train
train_dataset, dev_dataset = self.random_split_ConcatDataset(self.data["train"], lengths=[n_train, n_dev])
File ".../farm/data_handler/data_silo.py", line 200, in random_split_ConcatDataset
train = ConcatDataset(ds.datasets[:idx_dataset])
File ".../torch/utils/data/dataset.py", line 68, in __init__
assert len(datasets) > 0, 'datasets should not be an empty iterable'
AssertionError: datasets should not be an empty iterable

# Fixed code
def _create_dev_from_train(self):
    n_dev = int(self.processor.dev_split * len(self.data["train"]))
    n_train = len(self.data["train"]) - n_dev

    train_dataset, dev_dataset = self.random_split_ConcatDataset(
        self.data["train"], lengths=[n_train, n_dev]
    )
    self.data["train"] = train_dataset
    if len(dev_dataset) > 0:
        self.data["dev"] = dev_dataset
    else:
        logger.warning("No dev set created. Please adjust the dev_split parameter.")

    logger.info(
        f"Took {len(dev_dataset)} samples out of train set to create dev set (dev split is roughly {self.processor.dev_split})"
    )
# Buggy code
def random_split_ConcatDataset(self, ds, lengths):
    """
    Roughly split a Concatdataset into non-overlapping new datasets of given lengths.
    Samples inside Concatdataset should already be shuffled

    Arguments:
        ds (Dataset): Dataset to be split
        lengths (sequence): lengths of splits to be produced
    """
    if sum(lengths) != len(ds):
        raise ValueError(
            "Sum of input lengths does not equal the length of the input dataset!"
        )

    idx_dataset = np.where(np.array(ds.cumulative_sizes) > lengths[0])[0][0]

    train = ConcatDataset(ds.datasets[:idx_dataset])
    test = ConcatDataset(ds.datasets[idx_dataset:])
    return train, test


# Traceback (AssertionError)
10/11/2019 17:12:47 - INFO - farm.data_handler.data_silo -   Loading dev set as a slice of train set
Traceback (most recent call last):
File ".../train.py", line 436, in <module>
augmentation=True)
File ".../train.py", line 348, in continue_finetuning
data_silo = DataSilo(processor=processor, batch_size=batch_size, multiprocessing_chunk_size=2000)
File "/.../farm/data_handler/data_silo.py", line 49, in __init__
self._load_data()
File ".../farm/data_handler/data_silo.py", line 104, in _load_data
self._create_dev_from_train()
File ".../farm/data_handler/data_silo.py", line 175, in _create_dev_from_train
train_dataset, dev_dataset = self.random_split_ConcatDataset(self.data["train"], lengths=[n_train, n_dev])
File ".../farm/data_handler/data_silo.py", line 200, in random_split_ConcatDataset
train = ConcatDataset(ds.datasets[:idx_dataset])
File ".../torch/utils/data/dataset.py", line 68, in __init__
assert len(datasets) > 0, 'datasets should not be an empty iterable'
AssertionError: datasets should not be an empty iterable

# Fixed code
def random_split_ConcatDataset(self, ds, lengths):
    """
    Roughly split a Concatdataset into non-overlapping new datasets of given lengths.
    Samples inside Concatdataset should already be shuffled

    Arguments:
        ds (Dataset): Dataset to be split
        lengths (sequence): lengths of splits to be produced
    """
    if sum(lengths) != len(ds):
        raise ValueError(
            "Sum of input lengths does not equal the length of the input dataset!"
        )

    idx_dataset = np.where(np.array(ds.cumulative_sizes) > lengths[0])[0][0]
    assert idx_dataset >= 1, (
        "Dev_split ratio is too large, there is no data in train set. "
        f"Please lower dev_split = {self.processor.dev_split}"
    )

    train = ConcatDataset(ds.datasets[:idx_dataset])
    test = ConcatDataset(ds.datasets[idx_dataset:])
    return train, test
# Buggy code
def _dict_to_samples(self, dictionary, all_dicts=None):
    doc = dictionary["doc"]
    samples = []
    for idx in range(len(doc) - 1):
        text_a, text_b, is_next_label = get_sentence_pair(doc, all_dicts, idx)
        sample_in_clear_text = {
            "text_a": text_a,
            "text_b": text_b,
            "nextsentence_label": is_next_label,
        }
        tokenized = {}
        tokenized["text_a"] = tokenize_with_metadata(
            text_a, self.tokenizer, self.max_seq_len
        )
        tokenized["text_b"] = tokenize_with_metadata(
            text_b, self.tokenizer, self.max_seq_len
        )
        samples.append(
            Sample(id=None, clear_text=sample_in_clear_text, tokenized=tokenized)
        )
    return samples


# Traceback (AssertionError)
10/11/2019 17:12:47 - INFO - farm.data_handler.data_silo -   Loading dev set as a slice of train set
Traceback (most recent call last):
File ".../train.py", line 436, in <module>
augmentation=True)
File ".../train.py", line 348, in continue_finetuning
data_silo = DataSilo(processor=processor, batch_size=batch_size, multiprocessing_chunk_size=2000)
File "/.../farm/data_handler/data_silo.py", line 49, in __init__
self._load_data()
File ".../farm/data_handler/data_silo.py", line 104, in _load_data
self._create_dev_from_train()
File ".../farm/data_handler/data_silo.py", line 175, in _create_dev_from_train
train_dataset, dev_dataset = self.random_split_ConcatDataset(self.data["train"], lengths=[n_train, n_dev])
File ".../farm/data_handler/data_silo.py", line 200, in random_split_ConcatDataset
train = ConcatDataset(ds.datasets[:idx_dataset])
File ".../torch/utils/data/dataset.py", line 68, in __init__
assert len(datasets) > 0, 'datasets should not be an empty iterable'
AssertionError: datasets should not be an empty iterable

# Fixed code
def _dict_to_samples(self, dictionary, all_dicts=None):
    assert len(all_dicts) > 1, (
        "Need at least 2 documents to sample random sentences from"
    )
    doc = dictionary["doc"]
    samples = []
    for idx in range(len(doc) - 1):
        text_a, text_b, is_next_label = get_sentence_pair(doc, all_dicts, idx)
        sample_in_clear_text = {
            "text_a": text_a,
            "text_b": text_b,
            "nextsentence_label": is_next_label,
        }
        tokenized = {}
        tokenized["text_a"] = tokenize_with_metadata(
            text_a, self.tokenizer, self.max_seq_len
        )
        tokenized["text_b"] = tokenize_with_metadata(
            text_b, self.tokenizer, self.max_seq_len
        )
        samples.append(
            Sample(id=None, clear_text=sample_in_clear_text, tokenized=tokenized)
        )
    return samples
# Buggy code
def success(res):
    msg = None
    if isinstance(res, types.Accept):
        custom = {"x_cb_node_id": self._router_factory._node_id}
        welcome(
            res.realm,
            res.authid,
            res.authrole,
            res.authmethod,
            res.authprovider,
            res.authextra,
            custom,
        )

    elif isinstance(res, types.Deny):
        msg = message.Abort(res.reason, res.message)

    else:
        pass

    if msg:
        self._transport.send(msg)


# Traceback (builtins.KeyError)
Unhandled error in Deferred:
Traceback (most recent call last):
File "/usr/local/lib/python3.6/dist-packages/autobahn/wamp/protocol.py", line 888, in onMessage
txaio.resolve(on_reply, msg.args[0])
File "/usr/local/lib/python3.6/dist-packages/txaio/tx.py", line 468, in resolve
future.callback(result)
File "/usr/local/lib/python3.6/dist-packages/twisted/internet/defer.py", line 460, in callback
self._startRunCallbacks(result)
File "/usr/local/lib/python3.6/dist-packages/twisted/internet/defer.py", line 568, in _startRunCallbacks
self._runCallbacks()
--- <exception caught here> ---
File "/usr/local/lib/python3.6/dist-packages/twisted/internet/defer.py", line 654, in _runCallbacks
current.result = callback(current.result, *args, **kw)
File "/usr/local/lib/python3.6/dist-packages/crossbar/router/dealer.py", line 441, in on_authorize_success
self._session_to_registrations[session].add(registration)
builtins.KeyError: <crossbar.router.session.RouterSession object at 0x7f653abfaef0>

# Fixed code
def success(res):
    msg = None
    # it is possible this session has disconnected
    # while authentication was taking place
    if self._transport is None:
        self.log.info(
            "Client session disconnected during authentication",
        )
        return

    if isinstance(res, types.Accept):
        custom = {"x_cb_node_id": self._router_factory._node_id}
        welcome(
            res.realm,
            res.authid,
            res.authrole,
            res.authmethod,
            res.authprovider,
            res.authextra,
            custom,
        )

    elif isinstance(res, types.Deny):
        msg = message.Abort(res.reason, res.message)

    else:
        pass

    if msg:
        self._transport.send(msg)
# Buggy code
def get_default_cwd():
    """Determine a reasonable default cwd"""
    cwd = os.getcwd()
    if not os.path.exists(cwd) or not os.path.isdir(cwd):
        try:
            cwd = pwd.getpwuid(os.getuid())[5]
        except KeyError:
            cwd = "/"

    return cwd


# Traceback (FileNotFoundError)
Traceback (most recent call last):
File "/usr/local/bin/terminator", line 87, in <module>
dbus_service = ipc.DBusService()
File "/usr/local/lib/python3.7/dist-packages/terminatorlib/ipc.py", line 42, in __init__
self.prepare_attributes()
File "/usr/local/lib/python3.7/dist-packages/terminatorlib/ipc.py", line 56, in prepare_attributes
"Couldn't get DBus name %s: Name exists" % BUS_NAME)
dbus.exceptions.DBusException: Couldn't get DBus name net.tenshu.Terminator21a9d5db22c73a993ff0b42f64b396873: Name exists

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/usr/local/bin/terminator", line 108, in <module>
ipc.new_window_cmdline(optionslist)
File "/usr/local/lib/python3.7/dist-packages/terminatorlib/ipc.py", line 194, in _exec
func(proxy, *args, **argd)
File "/usr/local/lib/python3.7/dist-packages/terminatorlib/ipc.py", line 200, in new_window_cmdline
session.new_window_cmdline(options)
File "/usr/lib/python3/dist-packages/dbus/proxies.py", line 72, in __call__
return self._proxy_method(*args, **keywords)
File "/usr/lib/python3/dist-packages/dbus/proxies.py", line 147, in __call__
**keywords)
File "/usr/lib/python3/dist-packages/dbus/connection.py", line 653, in call_blocking
message, timeout)
dbus.exceptions.DBusException: org.freedesktop.DBus.Python.FileNotFoundError: Traceback (most recent call last):
File "/usr/lib/python3/dist-packages/dbus/service.py", line 711, in _message_cb
retval = candidate_method(self, *args, **keywords)
File "/usr/lib/python3/dist-packages/terminatorlib/ipc.py", line 71, in new_window_cmdline
self.terminator.create_layout(oldopts.layout)
File "/usr/lib/python3/dist-packages/terminatorlib/terminator.py", line 310, in create_layout
window, terminal = self.new_window()
File "/usr/lib/python3/dist-packages/terminatorlib/terminator.py", line 233, in new_window
terminal = maker.make('Terminal')
File "/usr/lib/python3/dist-packages/terminatorlib/factory.py", line 93, in make
output = func(**kwargs)
File "/usr/lib/python3/dist-packages/terminatorlib/factory.py", line 105, in make_terminal
return(terminal.Terminal())
File "/usr/lib/python3/dist-packages/terminatorlib/terminal.py", line 141, in __init__
self.cwd = get_default_cwd()
File "/usr/lib/python3/dist-packages/terminatorlib/cwd.py", line 28, in get_default_cwd
cwd = os.getcwd()
FileNotFoundError:

# Fixed code
def get_default_cwd():
    """Determine a reasonable default cwd"""
    try:
        cwd = os.getcwd()
    except (FileNotFoundError, OSError):
        err("unable to set current working directory, does not exist")
        cwd = "/"

    return cwd
# Buggy code
def _add_regex(self, name, re):
    reg = Vte.Regex.new_for_match(re, len(re), self.regex_flags)
    self.matches[name] = self.vte.match_add_regex(reg, 0)
    self.vte.match_set_cursor_name(self.matches[name], "pointer")


# Traceback (AttributeError)
$ terminator
Traceback (most recent call last):
File "/usr/bin/terminator", line 122, in <module>
TERMINATOR.create_layout(OPTIONS.layout)
File "/usr/share/terminator/terminatorlib/terminator.py", line 311, in create_layout
window, terminal = self.new_window()
File "/usr/share/terminator/terminatorlib/terminator.py", line 234, in new_window
terminal = maker.make('Terminal')
File "/usr/share/terminator/terminatorlib/factory.py", line 94, in make
output = func(**kwargs)
File "/usr/share/terminator/terminatorlib/factory.py", line 106, in make_terminal
return(terminal.Terminal())
File "/usr/share/terminator/terminatorlib/terminal.py", line 147, in __init__
self.update_url_matches()
File "/usr/share/terminator/terminatorlib/terminal.py", line 273, in update_url_matches
reg = Vte.Regex.new_for_match(re, len(re), self.regex_flags)
File "/usr/lib/python2.7/dist-packages/gi/module.py", line 139, in __getattr__
self.__name__, name))
AttributeError: 'gi.repository.Vte' object has no attribute 'Regex'

# Fixed code
def _add_regex(self, name, re):
    if REGEX_MODERN:
        reg = Vte.Regex.new_for_match(re, len(re), self.regex_flags)
        self.matches[name] = self.vte.match_add_regex(reg, 0)
    else:
        reg = GLib.Regex.new(re, self.regex_flags, 0)
        self.matches[name] = self.vte.match_add_gregex(reg, 0)
    self.vte.match_set_cursor_name(self.matches[name], "pointer")
# Buggy code
def _peekkey_ss3(offset):
    global _cbuf
    if len(_cbuf) <= offset:
        return Key(kc.TYPE_UNICODE, "O", kc.MOD_ALT)
    cmd = _cbuf[offset]
    if cmd < 0x40 or cmd >= 0x80:
        return
    _cbuf = _cbuf[numb:]  # XXX: numb is not defined

    if chr(cmd) in _csi_ss3s:
        return Key(*_csi_ss3s[chr(cmd)])

    if chr(cmd) in _csi_ss3kp:
        t, c, a = _csi_ss3kp[chr(cmd)]
        if CONVERTKP and a:  # XXX: CONVERTKP is not defined
            return Key(kc.TYPE_UNICODE, a)
        else:
            return Key(t, c)


# Traceback (NameError)
Traceback (most recent call last):
File "foo.py", line 907, in <module>
inp = sys.stdin.readline().strip().decode('utf-8')
File "/lib/python2.7/site-packages/pwnlib/term/readline.py", line 412, in readline
return readline(size)
File "/lib/python2.7/site-packages/pwnlib/term/readline.py", line 376, in readline
keymap.handle_input()
File "/lib/python2.7/site-packages/pwnlib/term/keymap.py", line 20, in handle_input
self.send(key.get())
File "/lib/python2.7/site-packages/pwnlib/term/key.py", line 164, in get
k = _peek()
File "/lib/python2.7/site-packages/pwnlib/term/key.py", line 159, in _peek
return _peek_ti() or _peek_csi() or _peek_simple()
File "/lib/python2.7/site-packages/pwnlib/term/key.py", line 393, in _peek_csi
return _peekkey_ss3(2)
File "/lib/python2.7/site-packages/pwnlib/term/key.py", line 372, in _peekkey_ss3
_cbuf = _cbuf[numb:] # XXX: numb is not defined
NameError: global name 'numb' is not defined

# Fixed code
def _peekkey_ss3(offset):
    global _cbuf
    if len(_cbuf) <= offset:
        return Key(kc.TYPE_UNICODE, "O", kc.MOD_ALT)
    cmd = _cbuf[offset]
    if cmd < 0x40 or cmd >= 0x80:
        return
    _cbuf = _cbuf[offset:]

    if chr(cmd) in _csi_ss3s:
        return Key(*_csi_ss3s[chr(cmd)])

    if chr(cmd) in _csi_ss3kp:
        t, c, a = _csi_ss3kp[chr(cmd)]
        if FLAG_CONVERTKP and a:
            return Key(kc.TYPE_UNICODE, a)
        else:
            return Key(t, c)
# Buggy code
def __getattr__(self, desc):
    ds = desc.replace("gray", "bright_black").split("_")
    init = ""
    while ds:
        d = ds[0]
        try:
            init += self._attributes[d]
            ds.pop(0)
        except KeyError:
            break

    def c():
        bright = 0
        c = ds.pop(0)
        if c == "bright":
            c = ds.pop(0)
            if self.has_bright:
                bright = 8
        return self._colors[c] + bright

    if ds:
        if ds[0] == "on":
            ds.pop(0)
            init += self._bg_color(c())
        else:
            init += self._fg_color(c())
            if len(ds):
                assert ds.pop(0) == "on"
                init += self._bg_color(c())
    return self._decorator(desc, init)


# Traceback (KeyError)
import pwnlib
pwnlib.term.text.__lol__
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "pwnlib/term/text.py", line 99, in __getattr__
init += self._fg_color(c())
File "pwnlib/term/text.py", line 93, in c
return self._colors[c] + bright
KeyError: ''

# Fixed code
def __getattr__(self, desc):
    try:
        ds = desc.replace("gray", "bright_black").split("_")
        init = ""
        while ds:
            d = ds[0]
            try:
                init += self._attributes[d]
                ds.pop(0)
            except KeyError:
                break

        def c():
            bright = 0
            c = ds.pop(0)
            if c == "bright":
                c = ds.pop(0)
                if self.has_bright:
                    bright = 8
            return self._colors[c] + bright

        if ds:
            if ds[0] == "on":
                ds.pop(0)
                init += self._bg_color(c())
            else:
                init += self._fg_color(c())
                if len(ds):
                    assert ds.pop(0) == "on"
                    init += self._bg_color(c())
        return self._decorator(desc, init)
    except (IndexError, KeyError):
        raise AttributeError("'module' object has no attribute %r" % desc)
# Buggy code
def show_result(self, data, result, **kwargs):
    if self.with_mask:
        ms_bbox_result, ms_segm_result = result
        if isinstance(ms_bbox_result, dict):
            result = (ms_bbox_result["ensemble"], ms_segm_result["ensemble"])
    else:
        if isinstance(result, dict):
            result = result["ensemble"]
    super(CascadeRCNN, self).show_result(data, result, **kwargs)


# Traceback (IndexError)
Traceback (most recent call last):
File "demo/image_demo.py", line 26, in <module>
main()
File "demo/image_demo.py", line 22, in main
show_result_pyplot(model, args.img, result, score_thr=args.score_thr)
File "/root/mmdetection-master/mmdet/apis/inference.py", line 146, in show_result_pyplot
img = model.show_result(img, result, score_thr=score_thr, show=False)
File "/root/mmdetection-master/mmdet/models/detectors/base.py", line 211, in show_result
mask = maskUtils.decode(segms[i]).astype(np.bool)
File "/root/anaconda3/lib/python3.7/site-packages/pycocotools-2.0-py3.7-linux-x86_64.egg/pycocotools/mask.py", line 91, in decode
return _mask.decode([rleObjs])[:,:,0]
File "pycocotools/_mask.pyx", line 146, in pycocotools._mask.decode
File "pycocotools/_mask.pyx", line 128, in pycocotools._mask._frString
IndexError: only integers, slices (`:`), ellipsis (`...`), numpy.newaxis (`None`) and integer or boolean arrays are valid indices

# Fixed code
def show_result(self, data, result, **kwargs):
    if self.with_mask:
        ms_bbox_result, ms_segm_result = result
        if isinstance(ms_bbox_result, dict):
            result = (ms_bbox_result["ensemble"], ms_segm_result["ensemble"])
    else:
        if isinstance(result, dict):
            result = result["ensemble"]
    return super(CascadeRCNN, self).show_result(data, result, **kwargs)
# Buggy code
def parseBamPEFDistributionFile(self, f):
    d = dict()
    lastsample = []
    for line in f["f"].splitlines():
        cols = line.rstrip().split("\t")
        if cols[0] == "#bamPEFragmentSize":
            continue
        elif cols[0] == "Size":
            continue
        else:
            s_name = self.clean_s_name(cols[2].rstrip().split("/")[-1], f["root"])
            if s_name != lastsample:
                d[s_name] = dict()
                lastsample = s_name
            d[s_name].update({int(cols[0]): int(cols[1])})

    return d


# Traceback (ValueError)
Module deeptools raised an exception: Traceback (most recent call last):
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/bin/multiqc", line 440, in multiqc
output = mod()
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/lib/python3.6/site-packages/multiqc/modules/deeptools/deeptools.py", line 75, in __init__
n['plotProfile'] = self.parse_plotProfile()
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/lib/python3.6/site-packages/multiqc/modules/deeptools/plotProfile.py", line 36, in parse_plotProfile
{'from': converted_bin_labels[bin_labels.index('TES')], 'to': converted_bin_labels[-1], 'color': '#f7cfcf'},
ValueError: 'TES' is not in list

# Fixed code
def parseBamPEFDistributionFile(self, f):
    d = dict()
    lastsample = []
    for line in f["f"].splitlines():
        cols = line.rstrip().split("\t")
        if cols[0] == "#bamPEFragmentSize":
            continue
        elif cols[0] == "Size":
            continue
        else:
            s_name = self.clean_s_name(cols[2].rstrip().split("/")[-1], f["root"])
            if s_name != lastsample:
                d[s_name] = dict()
                lastsample = s_name
            d[s_name].update({self._int(cols[0]): self._int(cols[1])})

    return d
# Buggy code
def parseBamPEFile(self, f):
    d = {}
    headers = None
    for line in f["f"].splitlines():
        cols = line.rstrip().split("\t")
        if headers is None:
            headers = cols
        else:
            s_name = None
            for idx, h in enumerate(headers):
                if idx == 0:
                    s_name = self.clean_s_name(cols[0], f["root"])
                    if s_name in d:
                        log.debug("Replacing duplicate sample {}.".format(s_name))
                    d[s_name] = OrderedDict()
                else:
                    if idx < 19 and cols[1] == "0":
                        # Don't store fragment metrics for SE datasets, they're just 0.
                        continue
                    try:
                        # Most values are ac
                        d[s_name][h] = int(cols[idx])
                    except ValueError:
                        d[s_name][h] = float(cols[idx])

    return d


# Traceback (ValueError)
Module deeptools raised an exception: Traceback (most recent call last):
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/bin/multiqc", line 440, in multiqc
output = mod()
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/lib/python3.6/site-packages/multiqc/modules/deeptools/deeptools.py", line 75, in __init__
n['plotProfile'] = self.parse_plotProfile()
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/lib/python3.6/site-packages/multiqc/modules/deeptools/plotProfile.py", line 36, in parse_plotProfile
{'from': converted_bin_labels[bin_labels.index('TES')], 'to': converted_bin_labels[-1], 'color': '#f7cfcf'},
ValueError: 'TES' is not in list

# Fixed code
def parseBamPEFile(self, f):
    d = {}
    headers = None
    for line in f["f"].splitlines():
        cols = line.rstrip().split("\t")
        if headers is None:
            headers = cols
        else:
            s_name = None
            for idx, h in enumerate(headers):
                if idx == 0:
                    s_name = self.clean_s_name(cols[0], f["root"])
                    if s_name in d:
                        log.debug("Replacing duplicate sample {}.".format(s_name))
                    d[s_name] = OrderedDict()
                else:
                    if idx < 19 and cols[1] == "0":
                        # Don't store fragment metrics for SE datasets, they're just 0.
                        continue
                    try:
                        # Most values are ac
                        d[s_name][h] = self._int(cols[idx])
                    except ValueError:
                        d[s_name][h] = float(cols[idx])

    return d
# Buggy code
def parsePlotEnrichment(self, f):
    d = {}
    firstLine = True
    for line in f["f"].splitlines():
        if firstLine:
            firstLine = False
            continue
        cols = line.strip().split("\t")

        if len(cols) != 5:
            log.warning(
                "{} was initially flagged as the output from plotEnrichment, but that seems to not be the case. Skipping...".format(
                    f["fn"]
                )
            )
            return dict()

        s_name = self.clean_s_name(cols[0], f["root"])
        if s_name not in d:
            d[s_name] = dict()
        cols[1] = str(cols[1])
        if cols[1] in d[s_name]:
            log.warning(
                "Replacing duplicate sample:featureType {}:{}.".format(s_name, cols[1])
            )
        d[s_name][cols[1]] = dict()

        try:
            d[s_name][cols[1]]["percent"] = float(cols[2])
            d[s_name][cols[1]]["count"] = int(cols[3])
        except:
            log.warning(
                "{} was initially flagged as the output from plotEnrichment, but that seems to not be the case. Skipping...".format(
                    f["fn"]
                )
            )
            return dict()
    return d


# Traceback (ValueError)
Module deeptools raised an exception: Traceback (most recent call last):
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/bin/multiqc", line 440, in multiqc
output = mod()
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/lib/python3.6/site-packages/multiqc/modules/deeptools/deeptools.py", line 75, in __init__
n['plotProfile'] = self.parse_plotProfile()
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/lib/python3.6/site-packages/multiqc/modules/deeptools/plotProfile.py", line 36, in parse_plotProfile
{'from': converted_bin_labels[bin_labels.index('TES')], 'to': converted_bin_labels[-1], 'color': '#f7cfcf'},
ValueError: 'TES' is not in list

# Fixed code
def parsePlotEnrichment(self, f):
    d = {}
    firstLine = True
    for line in f["f"].splitlines():
        if firstLine:
            firstLine = False
            continue
        cols = line.strip().split("\t")

        if len(cols) != 5:
            log.warning(
                "{} was initially flagged as the output from plotEnrichment, but that seems to not be the case. Skipping...".format(
                    f["fn"]
                )
            )
            return dict()

        s_name = self.clean_s_name(cols[0], f["root"])
        if s_name not in d:
            d[s_name] = dict()
        cols[1] = str(cols[1])
        if cols[1] in d[s_name]:
            log.warning(
                "Replacing duplicate sample:featureType {}:{}.".format(s_name, cols[1])
            )
        d[s_name][cols[1]] = dict()

        try:
            d[s_name][cols[1]]["percent"] = float(cols[2])
            d[s_name][cols[1]]["count"] = self._int(cols[3])
        except:
            log.warning(
                "{} was initially flagged as the output from plotEnrichment, but that seems to not be the case. Skipping...".format(
                    f["fn"]
                )
            )
            return dict()
    return d
# Buggy code
def parsePlotFingerprintOutRawCounts(self, f):
    d = dict()
    samples = []
    firstLine = True
    for line in f["f"].splitlines():
        cols = line.strip().split("\t")
        if cols[0] == "#plotFingerprint --outRawCounts":
            continue

        if firstLine:
            for c in cols:
                c = str(c).strip("'")
                s_name = self.clean_s_name(c, f["root"])
                d[s_name] = []
                samples.append(s_name)
            firstLine = False
            continue

        for idx, c in enumerate(cols):
            d[samples[idx]].append(int(c))

    # Switch to numpy, get the normalized cumsum
    x = np.linspace(
        0, len(d[samples[0]]) - 1, endpoint=True, num=100, dtype=int
    )  # The indices into the vectors that we'll actually return for plotting
    xp = np.arange(len(d[samples[0]]) + 1) / float(len(d[samples[0]]) + 1)
    for k, v in d.items():
        v = np.array(v)
        v = np.sort(v)
        cs = np.cumsum(v)
        cs = cs / float(cs[-1])
        # Convert for plotting
        v2 = dict()
        v2[0.0] = 0.0
        for _ in x:
            v2[xp[_]] = cs[_]
        d[k] = v2
    return d


# Traceback (ValueError)
Module deeptools raised an exception: Traceback (most recent call last):
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/bin/multiqc", line 440, in multiqc
output = mod()
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/lib/python3.6/site-packages/multiqc/modules/deeptools/deeptools.py", line 75, in __init__
n['plotProfile'] = self.parse_plotProfile()
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/lib/python3.6/site-packages/multiqc/modules/deeptools/plotProfile.py", line 36, in parse_plotProfile
{'from': converted_bin_labels[bin_labels.index('TES')], 'to': converted_bin_labels[-1], 'color': '#f7cfcf'},
ValueError: 'TES' is not in list

# Fixed code
def parsePlotFingerprintOutRawCounts(self, f):
    d = dict()
    samples = []
    firstLine = True
    for line in f["f"].splitlines():
        cols = line.strip().split("\t")
        if cols[0] == "#plotFingerprint --outRawCounts":
            continue

        if firstLine:
            for c in cols:
                c = str(c).strip("'")
                s_name = self.clean_s_name(c, f["root"])
                d[s_name] = []
                samples.append(s_name)
            firstLine = False
            continue

        for idx, c in enumerate(cols):
            d[samples[idx]].append(self._int(c))

    # Switch to numpy, get the normalized cumsum
    x = np.linspace(
        0, len(d[samples[0]]) - 1, endpoint=True, num=100, dtype=int
    )  # The indices into the vectors that we'll actually return for plotting
    xp = np.arange(len(d[samples[0]]) + 1) / float(len(d[samples[0]]) + 1)
    for k, v in d.items():
        v = np.array(v)
        v = np.sort(v)
        cs = np.cumsum(v)
        cs = cs / float(cs[-1])
        # Convert for plotting
        v2 = dict()
        v2[0.0] = 0.0
        for _ in x:
            v2[xp[_]] = cs[_]
        d[k] = v2
    return d
# Buggy code
def parsePlotPCAData(self, f):
    d = dict()
    samples = []
    for line in f["f"].splitlines():
        cols = line.strip().split("\t")
        if cols[0] == "#plotPCA --outFileNameData":
            continue
        elif cols[0] == "Component":
            for c in cols[1 : (len(cols) - 1)]:
                c = str(c).strip("'")
                s_name = self.clean_s_name(c, f["root"])
                d[s_name] = {}
                samples.append(s_name)
        else:
            idx = 0
            compo = cols[0]
            for c in cols[1 : (len(cols) - 1)]:
                d[samples[idx]][int(compo)] = float(c)
                idx += 1
    return d


# Traceback (ValueError)
Module deeptools raised an exception: Traceback (most recent call last):
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/bin/multiqc", line 440, in multiqc
output = mod()
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/lib/python3.6/site-packages/multiqc/modules/deeptools/deeptools.py", line 75, in __init__
n['plotProfile'] = self.parse_plotProfile()
File "/sandbox/users/foucal-a/miniconda3/envs/deeptools/lib/python3.6/site-packages/multiqc/modules/deeptools/plotProfile.py", line 36, in parse_plotProfile
{'from': converted_bin_labels[bin_labels.index('TES')], 'to': converted_bin_labels[-1], 'color': '#f7cfcf'},
ValueError: 'TES' is not in list

# Fixed code
def parsePlotPCAData(self, f):
    d = dict()
    samples = []
    for line in f["f"].splitlines():
        cols = line.strip().split("\t")
        if cols[0] == "#plotPCA --outFileNameData":
            continue
        elif cols[0] == "Component":
            for c in cols[1 : (len(cols) - 1)]:
                c = str(c).strip("'")
                s_name = self.clean_s_name(c, f["root"])
                d[s_name] = {}
                samples.append(s_name)
        else:
            idx = 0
            compo = cols[0]
            for c in cols[1 : (len(cols) - 1)]:
                d[samples[idx]][self._int(compo)] = float(c)
                idx += 1
    return d
# Buggy code
def describe_log_groups(self, limit, log_group_name_prefix, next_token):
    if log_group_name_prefix is None:
        log_group_name_prefix = ""
    if next_token is None:
        next_token = 0

    groups = [
        group.to_describe_dict()
        for name, group in self.groups.items()
        if name.startswith(log_group_name_prefix)
    ]
    groups = sorted(groups, key=lambda x: x["creationTime"], reverse=True)
    groups_page = groups[next_token : next_token + limit]

    next_token += limit
    if next_token >= len(groups):
        next_token = None

    return groups_page, next_token


# Traceback (botocore.exceptions.ParamValidationError)
Traceback (most recent call last):
File "foo.py", line 13, in <module>
client.describe_log_groups(nextToken=result['nextToken'])
File "/home/ubuntu/.venvs/moto-test-case/lib/python3.8/site-packages/botocore/client.py", line 357, in _api_call
return self._make_api_call(operation_name, kwargs)
File "/home/ubuntu/.venvs/moto-test-case/lib/python3.8/site-packages/botocore/client.py", line 648, in _make_api_call
request_dict = self._convert_to_request_dict(
File "/home/ubuntu/.venvs/moto-test-case/lib/python3.8/site-packages/botocore/client.py", line 696, in _convert_to_request_dict
request_dict = self._serializer.serialize_to_request(
File "/home/ubuntu/.venvs/moto-test-case/lib/python3.8/site-packages/botocore/validate.py", line 297, in serialize_to_request
raise ParamValidationError(report=report.generate_report())
botocore.exceptions.ParamValidationError: Parameter validation failed:
Invalid type for parameter nextToken, value: 50, type: <class 'int'>, valid types: <class 'str'>

# Fixed code
def describe_log_groups(self, limit, log_group_name_prefix, next_token):
    if log_group_name_prefix is None:
        log_group_name_prefix = ""

    groups = [
        group.to_describe_dict()
        for name, group in self.groups.items()
        if name.startswith(log_group_name_prefix)
    ]
    groups = sorted(groups, key=lambda x: x["logGroupName"])

    index_start = 0
    if next_token:
        try:
            index_start = (
                next(
                    index
                    for (index, d) in enumerate(groups)
                    if d["logGroupName"] == next_token
                )
                + 1
            )
        except StopIteration:
            index_start = 0
            # AWS returns an empty list if it receives an invalid token.
            groups = []

    index_end = index_start + limit
    if index_end > len(groups):
        index_end = len(groups)

    groups_page = groups[index_start:index_end]

    next_token = None
    if groups_page and index_end < len(groups):
        next_token = groups_page[-1]["logGroupName"]

    return groups_page, next_token
# Buggy code
def describe_log_groups(self):
    log_group_name_prefix = self._get_param("logGroupNamePrefix")
    next_token = self._get_param("nextToken")
    limit = self._get_param("limit", 50)
    assert limit <= 50
    groups, next_token = self.logs_backend.describe_log_groups(
        limit, log_group_name_prefix, next_token
    )
    return json.dumps({"logGroups": groups, "nextToken": next_token})


# Traceback (botocore.exceptions.ParamValidationError)
Traceback (most recent call last):
File "foo.py", line 13, in <module>
client.describe_log_groups(nextToken=result['nextToken'])
File "/home/ubuntu/.venvs/moto-test-case/lib/python3.8/site-packages/botocore/client.py", line 357, in _api_call
return self._make_api_call(operation_name, kwargs)
File "/home/ubuntu/.venvs/moto-test-case/lib/python3.8/site-packages/botocore/client.py", line 648, in _make_api_call
request_dict = self._convert_to_request_dict(
File "/home/ubuntu/.venvs/moto-test-case/lib/python3.8/site-packages/botocore/client.py", line 696, in _convert_to_request_dict
request_dict = self._serializer.serialize_to_request(
File "/home/ubuntu/.venvs/moto-test-case/lib/python3.8/site-packages/botocore/validate.py", line 297, in serialize_to_request
raise ParamValidationError(report=report.generate_report())
botocore.exceptions.ParamValidationError: Parameter validation failed:
Invalid type for parameter nextToken, value: 50, type: <class 'int'>, valid types: <class 'str'>

# Fixed code
def describe_log_groups(self):
    log_group_name_prefix = self._get_param("logGroupNamePrefix")
    next_token = self._get_param("nextToken")
    limit = self._get_param("limit", 50)
    assert limit <= 50
    groups, next_token = self.logs_backend.describe_log_groups(
        limit, log_group_name_prefix, next_token
    )
    result = {"logGroups": groups}
    if next_token:
        result["nextToken"] = next_token
    return json.dumps(result)
# Buggy code
def value(self, new_value):
    self._value_buffer.seek(0)
    self._value_buffer.truncate()

    # Hack for working around moto's own unit tests; this probably won't
    # actually get hit in normal use.
    if isinstance(new_value, six.text_type):
        new_value = new_value.encode(DEFAULT_TEXT_ENCODING)
    self._value_buffer.write(new_value)


# Traceback (botocore.exceptions.ClientError)
Traceback (most recent call last):
File "/Users/myuser/projects/project/web/pdf_file_downloader.py", line 16, in download
self.s3.download_file(self.bucket_name, self.file_name, self.local_path())
File "/Users/myuser/Library/Caches/pypoetry/virtualenvs/project-X5XCMv3p-py3.6/lib/python3.6/site-packages/boto3/s3/inject.py", line 172, in download_file
extra_args=ExtraArgs, callback=Callback)
File "/Users/myuser/Library/Caches/pypoetry/virtualenvs/project-X5XCMv3p-py3.6/lib/python3.6/site-packages/boto3/s3/transfer.py", line 307, in download_file
future.result()
File "/Users/myuser/Library/Caches/pypoetry/virtualenvs/project-X5XCMv3p-py3.6/lib/python3.6/site-packages/s3transfer/futures.py", line 106, in result
return self._coordinator.result()
File "/Users/myuser/Library/Caches/pypoetry/virtualenvs/project-X5XCMv3p-py3.6/lib/python3.6/site-packages/s3transfer/futures.py", line 265, in result
raise self._exception
File "/Users/myuser/Library/Caches/pypoetry/virtualenvs/project-X5XCMv3p-py3.6/lib/python3.6/site-packages/s3transfer/tasks.py", line 126, in __call__
return self._execute_main(kwargs)
File "/Users/myuser/Library/Caches/pypoetry/virtualenvs/project-X5XCMv3p-py3.6/lib/python3.6/site-packages/s3transfer/tasks.py", line 150, in _execute_main
return_value = self._main(**kwargs)
File "/Users/myuser/Library/Caches/pypoetry/virtualenvs/project-X5XCMv3p-py3.6/lib/python3.6/site-packages/s3transfer/download.py", line 512, in _main
Bucket=bucket, Key=key, **extra_args)
File "/Users/myuser/Library/Caches/pypoetry/virtualenvs/project-X5XCMv3p-py3.6/lib/python3.6/site-packages/botocore/client.py", line 316, in _api_call
return self._make_api_call(operation_name, kwargs)
File "/Users/myuser/Library/Caches/pypoetry/virtualenvs/project-X5XCMv3p-py3.6/lib/python3.6/site-packages/botocore/client.py", line 626, in _make_api_call
raise error_class(parsed_response, operation_name)
botocore.exceptions.ClientError: An error occurred (416) when calling the GetObject operation: Requested Range Not Satisfiable

# Fixed code
def value(self, new_value):
    self._value_buffer.seek(0)
    self._value_buffer.truncate()

    # Hack for working around moto's own unit tests; this probably won't
    # actually get hit in normal use.
    if isinstance(new_value, six.text_type):
        new_value = new_value.encode(DEFAULT_TEXT_ENCODING)
    self._value_buffer.write(new_value)
    self.contentsize = len(new_value)