MonoshiTonmoy/Code_Statement_Prediction_Dataset huggingface dataset:
Project Name: OxfordHED+sunbear
Language: Python
Statement Type: Assignment

Source Code:
def _get_idx(ndim, dim, s, defidx=None):
    defidx = slice(None, None, None) if defidx is None else defidx
    idx = [defidx] * ndim
    idx[dim] = s
    return tuple(idx)

_get_idx(ndim=1, dim=0, s=slice(1, 2, None), defidx=None)

Selected Statement: idx = [defidx] * ndim

Function Input:
ndim: 1
dim: 0
s: slice(1, 2, None)
defidx: None

Variable Values Before Statement:
ndim: 1

Value After Statement Execution: [slice(None, None, None)]

Variable States During Runtime (line, value):
ndim: 1
1
dim: 1
0
s: 1
slice(1, 2, None)
defidx: 1
None
2
slice(None, None, None)
idx: 3
[slice(None, None, None)]
4
[slice(1, 2, None)]
Project Name: activeloopai+deeplake
Language: Python
Statement Type: Assignment

Source Code:
def get_reporting_config() -> Dict[str, Any]:
    """Get an existing reporting config"""
    reporting_config: Dict[str, Any] = {"consent": False}
    try:
        if not os.path.exists(REPORTING_CONFIG_FILE_PATH):
            client_id = str(uuid.uuid4())
            reporting_config["client_id"] = client_id
            reporting_config = save_reporting_config(True, client_id)
        else:
            with open(REPORTING_CONFIG_FILE_PATH, "r") as ifp:
                reporting_config = json.load(ifp)

        # The following changes do NOT mutate the reporting_config.json file on the file system, but
        # they provide a means to report the username as the client_id (if the username is available)
        # while tracking the existing client_id as a machine_id.
        reporting_config["machine_id"] = reporting_config["client_id"]

        if (
            reporting_config.get("username") is not None
            and reporting_config["client_id"] != reporting_config["username"]
        ):
            reporting_config["client_id"] = reporting_config["username"]

    except Exception:
        # Not being able to load reporting consent should not get in the user's way. We will just
        # return the default reporting_config object in which consent is set to False.
        pass
    return reporting_config

get_reporting_config()

Selected Statement: reporting_config["machine_id"] = reporting_config["client_id"]

Function Input:

Variable Values Before Statement:
reporting_config: client_id: 8728ad25-a15b-4b67-91db-a3a3878aba24
consent: yes

Value After Statement Execution: client_id: 8728ad25-a15b-4b67-91db-a3a3878aba24
consent: yes
machine_id: 8728ad25-a15b-4b67-91db-a3a3878aba24

Variable States During Runtime (line, value):
reporting_config: 3
consent: no
11
client_id: 8728ad25-a15b-4b67-91db-a3a3878aba24
consent: yes
16
client_id: 8728ad25-a15b-4b67-91db-a3a3878aba24
consent: yes
machine_id: 8728ad25-a15b-4b67-91db-a3a3878aba24
ifp: 10
<_io.TextIOWrapper name='/home/jinjun/.activeloop/reporting_config.json' mode='r' encoding='UTF-8'>
Project Name: activeloopai+deeplake
Language: Python
Statement Type: Assignment

Source Code:
def _validate_htype_overwrites(htype: str, htype_overwrite: dict):
    """Raises errors if ``htype_overwrite`` has invalid keys or was missing required values."""

    defaults = HTYPE_CONFIGURATIONS[htype]

    for key, value in htype_overwrite.items():
        if key not in defaults:
            raise TensorMetaInvalidHtypeOverwriteKey(htype, key, list(defaults.keys()))

        if isinstance(value, str) and value == UNSPECIFIED:
            if defaults[key] == REQUIRE_USER_SPECIFICATION:
                raise TensorMetaMissingRequiredValue(htype, key)

    sc = htype_overwrite["sample_compression"]
    cc = htype_overwrite["chunk_compression"]
    compr = sc if cc in (None, UNSPECIFIED) else cc
    actual_htype = f"link[{htype}]" if htype_overwrite["is_link"] else htype
    if htype.startswith("image") and sc == UNSPECIFIED and cc == UNSPECIFIED:
        raise TensorMetaMissingRequiredValue(
            actual_htype, ["chunk_compression", "sample_compression"]  # type: ignore
        )
    if htype in ("audio", "video", "point_cloud", "mesh", "nifti"):
        if cc not in (UNSPECIFIED, None):
            raise UnsupportedCompressionError("Chunk compression", htype=htype)
        elif sc == UNSPECIFIED:
            raise TensorMetaMissingRequiredValue(
                actual_htype, "sample_compression"  # type: ignore
            )
    supported_compressions = HTYPE_SUPPORTED_COMPRESSIONS.get(htype)
    if (
        compr
        and compr != UNSPECIFIED
        and supported_compressions
        and compr not in supported_compressions
    ):
        raise UnsupportedCompressionError(compr, htype=htype)

_validate_htype_overwrites(htype='generic', htype_overwrite={'sample_compression': 'unspecified', 'chunk_compression': 'unspecified', 'dtype': 'unspecified', 'hidden': False, 'tiling_threshold': None, 'max_chunk_size': 2000000, 'is_sequence': False, 'is_link': False, 'verify': True})

Selected Statement: sc = htype_overwrite["sample_compression"]

Function Input:
htype: 'generic'
htype_overwrite: sample_compression: unspecified
chunk_compression: unspecified
dtype: unspecified
hidden: no
max_chunk_size: 2000000
is_sequence: no
is_link: no
verify: yes

Variable Values Before Statement:
htype_overwrite: sample_compression: unspecified
chunk_compression: unspecified
dtype: unspecified
hidden: no
max_chunk_size: 2000000
is_sequence: no
is_link: no
verify: yes

Value After Statement Execution: 'unspecified'

Variable States During Runtime (line, value):
htype: 1
'generic'
htype_overwrite: 1
sample_compression: unspecified
chunk_compression: unspecified
dtype: unspecified
hidden: no
max_chunk_size: 2000000
is_sequence: no
is_link: no
verify: yes
defaults: 4
is_sequence: no
is_link: no
hidden: no
verify: no
key: 6
'sample_compression'
6
'chunk_compression'
6
'dtype'
6
'hidden'
6
'tiling_threshold'
6
'max_chunk_size'
6
'is_sequence'
6
'is_link'
6
'verify'
value: 6
'unspecified'
6
False
6
None
6
2000000
6
False
6
True
sc: 14
'unspecified'
cc: 15
'unspecified'
compr: 16
'unspecified'
actual_htype: 17
'generic'
supported_compressions: 29
None
Project Name: activeloopai+deeplake
Language: Python
Statement Type: Assignment

Source Code:
def _format_values(htype: str, htype_overwrite: dict):
    """Replaces values in `htype_overwrite` with consistent types/formats."""

    dtype = htype_overwrite["dtype"]
    if dtype is not None:
        if htype in ("json", "list", "tag", "intrinsics"):
            if getattr(dtype, "__module__", None) == "typing":
                htype_overwrite["dtype"] = str(dtype)
        else:
            htype_overwrite["dtype"] = np.dtype(htype_overwrite["dtype"]).name

    for key, value in COMPRESSION_ALIASES.items():
        if htype_overwrite.get("sample_compression") == key:
            htype_overwrite["sample_compression"] = value
        if htype_overwrite.get("chunk_compression") == key:
            htype_overwrite["chunk_compression"] = value

_format_values(htype='generic', htype_overwrite={'sample_compression': None, 'chunk_compression': None, 'dtype': None, 'hidden': False, 'tiling_threshold': None, 'max_chunk_size': 2000000, 'is_sequence': False, 'is_link': False, 'verify': True})

Selected Statement: dtype = htype_overwrite["dtype"]

Function Input:
htype: 'generic'
htype_overwrite: hidden: no
max_chunk_size: 2000000
is_sequence: no
is_link: no
verify: yes

Variable Values Before Statement:
htype_overwrite: hidden: no
max_chunk_size: 2000000
is_sequence: no
is_link: no
verify: yes

Value After Statement Execution: None

Variable States During Runtime (line, value):
htype: 1
'generic'
htype_overwrite: 1
hidden: no
max_chunk_size: 2000000
is_sequence: no
is_link: no
verify: yes
dtype: 4
None
key: 12
'jpg'
12
'tif'
12
'jp2'
value: 12
'jpeg'
12
'tiff'
12
'jpeg2000'
Project Name: activeloopai+deeplake
Language: Python
Statement Type: Assignment

Source Code:
def serialize_chunkids(version: str, arr: np.ndarray) -> memoryview:
    """Serializes chunk ID encoders into a single byte stream. This is how the encoders will be written to the storage provider.

    Args:
        version: (str) Version of deeplake library.
        arr: (np.ndarray) Encoded chunk ids from a `ChunkIdEncoder` instance.

    Returns:
        Serialized chunk ids as memoryview.
    """
    len_version = len(version)
    write_dtype = version_compare(version, "2.7.6") >= 0
    flatbuff = bytearray(1 + int(write_dtype) + len_version + arr.nbytes)

    # Write version
    len_version = len(version)
    flatbuff[0] = len_version
    flatbuff[1 : 1 + len_version] = version.encode("ascii")
    offset = 1 + len_version

    # write encoder dtype
    if write_dtype:
        dtype = arr.dtype
        num_bytes = int(dtype.itemsize)
        flatbuff[offset] = num_bytes
        offset += 1

    # Write ids
    flatbuff[offset : offset + arr.nbytes] = arr.tobytes()
    offset += arr.nbytes
    return memoryview(flatbuff)

serialize_chunkids(version='3.8.18', arr=array([], shape=(0, 2), dtype=uint64))

Selected Statement: offset = 1 + len_version

Function Input:
version: '3.8.18'
arr: array([], shape=(0, 2), dtype=uint64)

Variable Values Before Statement:
len_version: 6

Value After Statement Execution: 7

Variable States During Runtime (line, value):
version: 1
'3.8.18'
arr: 1
array([], shape=(0, 2), dtype=uint64)
len_version: 11
6
write_dtype: 12
True
flatbuff: 13
bytearray(b'\x00\x00\x00\x00\x00\x00\x00\x00')
17
bytearray(b'\x06\x00\x00\x00\x00\x00\x00\x00')
18
bytearray(b'\x063.8.18\x00')
25
bytearray(b'\x063.8.18\x08')
offset: 19
7
26
8
dtype: 23
dtype('uint64')
num_bytes: 24
8
Project Name: dbcli+mycli
Language: Python
Statement Type: Assignment

Source Code:
def parse_special_command(sql):
    command, _, arg = sql.partition(' ')
    verbose = '+' in command
    command = command.strip().replace('+', '')
    return (command, verbose, arg.strip())

parse_special_command(sql='\\. ')

Selected Statement: verbose = '+' in command

Function Input:
sql: '\\. '

Variable Values Before Statement:
command: '\\.'

Value After Statement Execution: False

Variable States During Runtime (line, value):
sql: 1
'\\. '
command: 2
'\\.'
_: 2
' '
arg: 2
''
verbose: 3
False
Project Name: dbcli+mycli
Language: Python
Statement Type: Assignment

Source Code:
def strip_matching_quotes(s):
    """Remove matching, surrounding quotes from a string.

    This is the same logic that ConfigObj uses when parsing config
    values.

    """
    if (isinstance(s, basestring) and len(s) >= 2 and
            s[0] == s[-1] and s[0] in ('"', "'")):
        s = s[1:-1]
    return s

strip_matching_quotes(s='"May the force be with you."')

Selected Statement: s = s[1:-1]

Function Input:
s: '"May the force be with you."'

Variable Values Before Statement:
s: '"May the force be with you."'

Value After Statement Execution: 'May the force be with you.'

Variable States During Runtime (line, value):
s: 1
'"May the force be with you."'
10
'May the force be with you.'
Project Name: zauberzeug+nicegui
Language: Python
Statement Type: Assignment

Source Code:
def glob_absolute_paths(file: Union[str, Path]) -> List[Path]:
            path = Path(file)
            if not path.is_absolute():
                path = base / path
            return sorted(path.parent.glob(path.name), key=lambda p: p.stem)

glob_absolute_paths(file='aggrid.js', base=PosixPath('/local/rcs/jinjun/code/pytrace-collector/logs/self_collected/tried/zauberzeug+nicegui/zauberzeug+nicegui/nicegui/elements'))

Selected Statement: path = base / path

Function Input:
file: 'aggrid.js'
base: PosixPath('/local/rcs/jinjun/code/pytrace-collector/logs/self_collected/tried/zauberzeug+nicegui/zauberzeug+nicegui/nicegui/elements')

Variable Values Before Statement:
base: PosixPath('/local/rcs/jinjun/code/pytrace-collector/logs/self_collected/tried/zauberzeug+nicegui/zauberzeug+nicegui/nicegui/elements')
path: PosixPath('aggrid.js')

Value After Statement Execution: PosixPath('/local/rcs/jinjun/code/pytrace-collector/logs/self_collected/tried/zauberzeug+nicegui/zauberzeug+nicegui/nicegui/elements/aggrid.js')

Variable States During Runtime (line, value):
file: 1
'aggrid.js'
base: 1
PosixPath('/local/rcs/jinjun/code/pytrace-collector/logs/self_collected/tried/zauberzeug+nicegui/zauberzeug+nicegui/nicegui/elements')
path: 2
PosixPath('aggrid.js')
4
PosixPath('/local/rcs/jinjun/code/pytrace-collector/logs/self_collected/tried/zauberzeug+nicegui/zauberzeug+nicegui/nicegui/elements/aggrid.js')
Project Name: sensepost+objection
Language: Python
Statement Type: Assignment

Source Code:
def show_android_class_methods(args: list = None) -> None:
    """
        Shows the methods available on an Android class.

        :param args:
        :return:
    """

    if len(clean_argument_flags(args)) <= 0:
        click.secho('Usage: android hooking list class_methods <class name>', bold=True)
        return

    class_name = args[0]

    api = state_connection.get_api()
    methods = api.android_hooking_get_class_methods(class_name)

    # print the enumerated classes
    for class_name in sorted(methods):
        click.secho(class_name)

    click.secho('\nFound {0} method(s)'.format(len(methods)), bold=True)

show_android_class_methods(args=['com.foo.bar'])

Selected Statement: class_name = args[0]

Function Input:
args: com.foo.bar

Variable Values Before Statement:
args: com.foo.bar

Value After Statement Execution: 'com.foo.bar'

Variable States During Runtime (line, value):
args: 1
com.foo.bar
class_name: 13
'com.foo.bar'
19
'bar'
19
'baz'
19
'foo'
api: 15
<MagicMock name='get_api()' id='140041905108928'>
methods: 16
foo, bar, baz
Project Name: sensepost+objection
Language: Python
Statement Type: Assignment

Source Code:
def show_ios_class_methods(args: list) -> None:
    """
        Displays the methods available in a class.

        :param args:
        :return:
    """

    if len(clean_argument_flags(args)) <= 0:
        click.secho('Usage: ios hooking list class_methods <class name> (--include-parents)', bold=True)
        return

    classname = args[0]

    api = state_connection.get_api()
    methods = api.ios_hooking_get_class_methods(classname, _should_include_parent_methods(args))

    if len(methods) > 0:

        # dump the methods to screen
        for method in methods:
            click.secho(method)

        click.secho('\nFound {0} methods'.format(len(methods)), bold=True)

    else:
        click.secho('No class / methods found')

show_ios_class_methods(args=['TEKeychainManager'])

Selected Statement: classname = args[0]

Function Input:
args: TEKeychainManager

Variable Values Before Statement:
args: TEKeychainManager

Value After Statement Execution: 'TEKeychainManager'

Variable States During Runtime (line, value):
args: 1
TEKeychainManager
classname: 13
'TEKeychainManager'
api: 15
<MagicMock name='get_api()' id='140041837197248'>
methods: 16
foo, bar
method: 21
'foo'
21
'bar'
Project Name: sensepost+objection
Language: Python
Statement Type: Assignment

Source Code:
def cat(args: list = None) -> None:
    """
        Parses a plist on an iOS device and echoes it in a more human
        readable way.

        :param args:
        :return:
    """

    if len(args) <= 0:
        click.secho('Usage: ios plist cat <remote_plist>', bold=True)
        return

    plist = args[0]

    if not os.path.isabs(plist):
        pwd = filemanager.pwd()
        plist = device_state.platform.path_separator.join([pwd, plist])

    api = state_connection.get_api()
    plist_data = api.ios_plist_read(plist)

    click.secho(plist_data, bold=True)

cat(args=['/foo'])

Selected Statement: plist = args[0]

Function Input:
args: /foo

Variable Values Before Statement:
args: /foo

Value After Statement Execution: '/foo'

Variable States During Runtime (line, value):
args: 1
/foo
plist: 14
'/foo'
api: 20
<MagicMock name='get_api()' id='140041837108288'>
plist_data: 21
'foo'
Project Name: sensepost+objection
Language: Python
Statement Type: Assignment

Source Code:
def rm(args: list) -> None:
    """
        Remove a file from the remote filesystem.

        :param args:
        :return:
    """

    if len(args) < 1:
        click.secho('Usage: rm <target remote file>', bold=True)
        return

    target = args[0]

    if not os.path.isabs(target):
        target = device_state.platform.path_separator.join([pwd(), target])

    if not click.confirm('Really delete {0} ?'.format(target)):
        click.secho('Not deleting {0}'.format(target), dim=True)
        return

    if device_state.platform == Ios:
        _rm_ios(target)

    if device_state.platform == Android:
        _rm_android(target)

rm(args='/poo')

Selected Statement: target = args[0]

Function Input:
args: '/poo'

Variable Values Before Statement:
args: '/poo'

Value After Statement Execution: '/'

Variable States During Runtime (line, value):
args: 1
'/poo'
target: 13
'/'
Project Name: sensepost+objection
Language: Python
Statement Type: Assignment

Source Code:
def dump_from_base(args: list) -> None:
    """
        Dump memory from a base address for a specific size to file

        :param args:
        :return:
    """

    if len(clean_argument_flags(args)) < 3:
        click.secho('Usage: memory dump from_base <base_address> <size_to_dump> <local_destination>', bold=True)
        return

    # the destination file to write the dump to
    base_address = args[0]
    memory_size = args[1]
    destination = args[2]

    # Check for file override
    if os.path.exists(destination):
        click.secho('Destination file {dest} already exists'.format(dest=destination), fg='yellow', bold=True)
        if not click.confirm('Override?'):
            return

    click.secho('Dumping {0} from {1} to {2}'.format(sizeof_fmt(int(memory_size)), base_address, destination),
                fg='green', dim=True)

    api = state_connection.get_api()

    # iirc, if you don't cast the return type to a bytearray it uses the sizeof(int) per cell, which is massive
    dump = bytearray()
    chunks = _get_chunks(int(base_address, 16), int(memory_size), BLOCK_SIZE)
    for chunk in chunks:
        dump.extend(bytearray(api.memory_dump(chunk[0], chunk[1])))

    # append the results to the destination file
    with open(destination, 'wb') as f:
        f.write(dump)

    click.secho('Memory dumped to file: {0}'.format(destination), fg='green')

dump_from_base(args=['0x00008000', '200', '/foo'])

Selected Statement: base_address = args[0]

Function Input:
args: 0x00008000, 200, /foo

Variable Values Before Statement:
args: 0x00008000, 200, /foo

Value After Statement Execution: '0x00008000'

Variable States During Runtime (line, value):
args: 1
0x00008000, 200, /foo
base_address: 14
'0x00008000'
memory_size: 15
'200'
destination: 16
'/foo'
api: 27
<MagicMock name='get_api()' id='140041905169216'>
dump: 30
bytearray(b'')
33
bytearray(b'\x00')
chunks: 31
[(32768, 200)]
chunk: 32
(32768, 200)
f: 36
<MagicMock name='open().__enter__()' id='140041907062336'>
Project Name: sensepost+objection
Language: Python
Statement Type: Assignment

Source Code:
def ios_screenshot(args: list = None) -> None:
    """
        Take an iOS screenshot.

        :param args:
        :return:
    """

    if len(args) <= 0:
        click.secho('Usage: ios ui screenshot <local png destination>', bold=True)
        return

    destination = args[0]

    if not destination.endswith('.png'):
        destination = destination + '.png'

    api = state_connection.get_api()
    png = api.ios_ui_screenshot()

    with open(destination, 'wb') as f:
        f.write(png)

    click.secho('Screenshot saved to: {0}'.format(destination), fg='green')

ios_screenshot(args=['foo'])

Selected Statement: destination = args[0]

Function Input:
args: foo

Variable Values Before Statement:
args: foo

Value After Statement Execution: 'foo'

Variable States During Runtime (line, value):
args: 1
foo
destination: 13
'foo'
16
'foo.png'
api: 18
<MagicMock name='get_api()' id='140041828273504'>
png: 19
b'\x00'
f: 21
<MagicMock name='open().__enter__()' id='140041828431664'>
Project Name: darknessomi+musicbox
Language: Python
Statement Type: Assignment

Source Code:
def rsa(text, pubkey, modulus):
    text = text[::-1]
    rs = pow(int(binascii.hexlify(text), 16), int(pubkey, 16), int(modulus, 16))
    return format(rs, "x").zfill(256)

rsa(text=b'8f0f5370d2e586d8', pubkey='010001', modulus='00e0b509f6259df8642dbc35662901477df22677ec152b5ff68ace615bb7b725152b3ab17a876aea8a5aa76d2e417629ec4ee341f56135fccf695280104e0312ecbda92557c93870114af6c9d05c4f7f0c3685b7a46bee255932575cce10b424d813cfe4875d3e82047b97ddef52741d546b8e289dc6935b3ece0462db0a22b8e7')

Selected Statement: text = text[::-1]

Function Input:
text: b'8f0f5370d2e586d8'
pubkey: '010001'
modulus: '00e0b509f6259df8642dbc35662901477df22677ec152b5ff68ace615bb7b725152b3ab17a876aea8a5aa76d2e417629ec4ee341f56135fccf695280104e0312ecbda92557c93870114af6c9d05c4f7f0c3685b7a46bee255932575cce10b424d813cfe4875d3e82047b97ddef52741d546b8e289dc6935b3ece0462db0a22b8e7'

Variable Values Before Statement:
text: b'8f0f5370d2e586d8'

Value After Statement Execution: b'8d685e2d0735f0f8'

Variable States During Runtime (line, value):
text: 1
b'8f0f5370d2e586d8'
2
b'8d685e2d0735f0f8'
pubkey: 1
'010001'
modulus: 1
'00e0b509f6259df8642dbc35662901477df22677ec152b5ff68ace615bb7b725152b3ab17a876aea8a5aa76d2e417629ec4ee341f56135fccf695280104e0312ecbda92557c93870114af6c9d05c4f7f0c3685b7a46bee255932575cce10b424d813cfe4875d3e82047b97ddef52741d546b8e289dc6935b3ece0462db0a22b8e7'
rs: 3
41289025236364532763659893484694654271957746525301846225496173810914971221673940219469794803075175772641409601769538690249948382654879184221263545282891541468281379611086448019401240456345998524768441427254251530526498242614378789439179129682525095499524622736788988351523341804681052326293260583730641212123
Project Name: Lightning-AI+lit-gpt
Language: Python
Statement Type: Assignment

Source Code:
def sample(logits: torch.Tensor, temperature: float = 1.0, top_k: Optional[int] = None) -> torch.Tensor:
    logits = logits[0, -1]
    # optionally crop the logits to only the top k options
    if top_k is not None:
        v, i = torch.topk(logits, min(top_k, logits.size(-1)))
        # do not use `torch.where` as in nanogpt because it will repeat top-k collisions
        logits = torch.full_like(logits, float("-inf")).scatter_(-1, i, v)
    # optionally scale the logits and sample from a probability distribution
    if temperature > 0.0:
        probs = torch.nn.functional.softmax(logits / temperature, dim=-1)
        return multinomial_num_samples_1(probs)
    return torch.argmax(logits, dim=-1, keepdim=True)

sample(logits=tensor([[[ 0.2595,  0.0058,  0.6498, -0.5155,  0.0366, -0.2944,  0.0555,          -0.4013],         [ 0.5342, -0.9790, -0.0861,  0.2530,  0.1378, -0.4913,  0.1915,          -0.3248],         [ 0.5289, -0.3149,  0.4052,  0.2107, -0.8788, -0.9871,  0.6539,          -0.2213]]], device='cuda:0'), temperature=0.8, top_k=None)

Selected Statement: logits = logits[0, -1]

Function Input:
logits: tensor([[[ 0.2595,  0.0058,  0.6498, -0.5155,  0.0366, -0.2944,  0.0555,          -0.4013],         [ 0.5342, -0.9790, -0.0861,  0.2530,  0.1378, -0.4913,  0.1915,          -0.3248],         [ 0.5289, -0.3149,  0.4052,  0.2107, -0.8788, -0.9871,  0.6539,          -0.2213]]], device='cuda:0')
temperature: 0.8
top_k: None

Variable Values Before Statement:
logits: tensor([[[ 0.2595,  0.0058,  0.6498, -0.5155,  0.0366, -0.2944,  0.0555,          -0.4013],         [ 0.5342, -0.9790, -0.0861,  0.2530,  0.1378, -0.4913,  0.1915,          -0.3248],         [ 0.5289, -0.3149,  0.4052,  0.2107, -0.8788, -0.9871,  0.6539,          -0.2213]]], device='cuda:0')

Value After Statement Execution: tensor([ 0.5289, -0.3149,  0.4052,  0.2107, -0.8788, -0.9871,  0.6539, -0.2213],       device

Variable States During Runtime (line, value):
logits: 1
tensor([[[ 0.2595,  0.0058,  0.6498, -0.5155,  0.0366, -0.2944,  0.0555,          -0.4013],         [ 0.5342, -0.9790, -0.0861,  0.2530,  0.1378, -0.4913,  0.1915,          -0.3248],         [ 0.5289, -0.3149,  0.4052,  0.2107, -0.8788, -0.9871,  0.6539,          -0.2213]]], device='cuda:0')
2
tensor([ 0.5289, -0.3149,  0.4052,  0.2107, -0.8788, -0.9871,  0.6539, -0.2213],       device='cuda:0')
temperature: 1
0.8
top_k: 1
None
probs: 10
tensor([0.2101, 0.0732, 0.1800, 0.1411, 0.0362, 0.0316, 0.2456, 0.0823],       device='cuda:0')