code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
import torc... | 13 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_t... | 13 | 1 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __magic_name__ ( __UpperCAmelCase = "AAPL" ) -> str:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
__SCREAMI... | 13 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"asapp/sew-tiny-100k": "https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json",
# See a... | 13 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
... | 13 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase = 1 , __UpperCAmelCase = 1000 ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 1
__SCREAMING_SNAKE_CASE = 0
for divide_by_number in range(__UpperCAm... | 13 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = len(__UpperCAmelCase )
__SCREAMING_SNAKE_CASE = len(matrix[0] )
__SCREAMING_SNAKE_CASE ... | 13 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_available():
import... | 13 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
__SCREAMING_SNAKE_CASE = f"""Input value of [number={number}] must be an integer... | 13 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __magic_name__ ( __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
def wrapper(*__UpperCAmel... | 13 | 1 |
'''simple docstring'''
import numpy
# List of input, output pairs
a = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
a = (((515, 22, 13), 555), ((61, 35, 49), 150))
a = [2, 4, 1, 5]
a = len(train_d... | 13 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
a = "__DUMMY_TRANSFORMERS_USER__"
a = "Dummy User"
a = "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"
... | 13 | 1 |
'''simple docstring'''
from math import pi, sqrt, tan
def __magic_name__ ( __UpperCAmelCase ) -> float:
'''simple docstring'''
if side_length < 0:
raise ValueError("""surface_area_cube() only accepts non-negative values""" )
return 6 * side_length**2
... | 13 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a = logging.get_logger(__name__)
a = {
"ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}
class __a ( ... | 13 | 1 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def __magic_name__ ( __UpperCAmelCase = 1500000 ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = defaultdict(__UpperCAmelCase )
__SCREAMING_SNAKE_CASE ... | 13 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class __a ( nn.Module ):
__UpperCamelCase : int
__UpperCamelCase : jnp.dtype = jnp.floataa
def UpperCAmelCase__ ( self : List[Any] ):
'''simple docstring'''
__SC... | 13 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> float:
'''simple docstring'''
_validate_point(__UpperCAmelCase )
_validate_point(__UpperCAmelCase )
if len(__UpperCAmelCase ) != len(__UpperCAmelCase ... | 13 |
'''simple docstring'''
import sys
from collections import defaultdict
class __a :
def __init__( self : Dict ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = []
def UpperCAmelCase__ ( self : List[Any] ,lowerCamelCase : ... | 13 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from tr... | 13 |
'''simple docstring'''
import os
import string
import sys
a = 1 << 8
a = {
"tab": ord("\t"),
"newline": ord("\r"),
"esc": 27,
"up": 65 + ARROW_KEY_FLAG,
"down": 66 + ARROW_KEY_FLAG,
"right": 67 + ARROW_KEY_FLAG,
"left": 68 + ARROW_KEY_FLAG,
"mod_int": 91... | 13 | 1 |
'''simple docstring'''
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
a = logging.get_logger(__name__)
a = OrderedDict(
[
... | 13 |
'''simple docstring'''
from __future__ import annotations
import bisect
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
'''simple docstring'''
if hi < 0:
__SCREAMING_SNAKE_CAS... | 13 | 1 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stabl... | 13 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
a = logging.get_logger(__name__)
class __a ( _snake_case ):
__UpperCamelCase : int... | 13 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils im... | 13 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a = {"configuration_sew": ["SEW_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvail... | 13 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
if num < 0:
return False
__SCREAMING_SNAKE_CASE = num
__SCREAMING_SNAKE_CASE = 0
while num > 0:
__SCREAMING_SNAKE_... | 13 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __magic_name__ ( __UpperCAmelCase = "AAPL" ) -> str:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
__SCREAMI... | 13 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a = {
"configuration_electra": ["ELECTRA_PRETRAINED_CONFIG_ARCH... | 13 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
if num < 0:
return False
__SCREAMING_SNAKE_CASE = num
__SCREAMING_SNAKE_CASE = 0
while num > 0:
__SCREAMING_SNAKE_... | 13 | 1 |
'''simple docstring'''
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MOD... | 13 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
a = list[list[float | int]]
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> Matrix:
'''simple docstring'''
__SCREAMING_SNAKE_CASE ... | 13 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"pro... | 13 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available... | 13 | 1 |
'''simple docstring'''
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
a = re.compile(r"^(?P<major>\d+)" r"\.(?P<minor>\d+)" r"\.(?P<patch>\d+)$")
@total_ordering
@dataclass
class __a :
... | 13 |
'''simple docstring'''
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be check... | 13 | 1 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def __magic_name__ ( __UpperCAmelCase ) -> datetime:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = year % 19
__SCREAMING_SNAKE_CASE = year % 4
__S... | 13 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequen... | 13 | 1 |
'''simple docstring'''
from __future__ import annotations
a = 10
def __magic_name__ ( __UpperCAmelCase ) -> list[int]:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 1
__SCREAMING_SNAKE_CASE = max(__UpperCAmelCase... | 13 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAv... | 13 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a = {
"configuration_convbert": ["CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvBertCo... | 13 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = BeautifulSoup(requests.get(__UpperCAmelCase , params... | 13 | 1 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class __a ( nn.Module ):
__UpperCamelCase : int
__UpperCamelCase : jnp.dtype = jnp.floataa
def UpperCAmelCase__ ( self : List[Any] ):
'''simple docstring'''
__SC... | 13 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"camembert-base": "https://huggingface.co/ca... | 13 | 1 |
'''simple docstring'''
a = {}
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not failed any othe... | 13 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_t... | 13 | 1 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def __magic_name__ ( __UpperCAmelCase ) -> List[str]:
'''simple docstring'''
... | 13 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"asapp/sew-tiny-100k": "https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json",
# See a... | 13 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin,... | 13 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase = 1 , __UpperCAmelCase = 1000 ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 1
__SCREAMING_SNAKE_CASE = 0
for divide_by_number in range(__UpperCAm... | 13 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
a = logging.get_logger(__name... | 13 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_available():
import... | 13 | 1 |
'''simple docstring'''
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase=7 ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE ... | 13 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __magic_name__ ( __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
def wrapper(*__UpperCAmel... | 13 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImag... | 13 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
a = "__DUMMY_TRANSFORMERS_USER__"
a = "Dummy User"
a = "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"
... | 13 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class __a ( _snake_case ):
__UpperCamelCase :... | 13 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a = logging.get_logger(__name__)
a = {
"ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}
class __a ( ... | 13 | 1 |
'''simple docstring'''
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@data... | 13 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class __a ( nn.Module ):
__UpperCamelCase : int
__UpperCamelCase : jnp.dtype = jnp.floataa
def UpperCAmelCase__ ( self : List[Any] ):
'''simple docstring'''
__SC... | 13 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
fr... | 13 |
'''simple docstring'''
import sys
from collections import defaultdict
class __a :
def __init__( self : Dict ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = []
def UpperCAmelCase__ ( self : List[Any] ,lowerCamelCase : ... | 13 | 1 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_... | 13 |
'''simple docstring'''
import os
import string
import sys
a = 1 << 8
a = {
"tab": ord("\t"),
"newline": ord("\r"),
"esc": 27,
"up": 65 + ARROW_KEY_FLAG,
"down": 66 + ARROW_KEY_FLAG,
"right": 67 + ARROW_KEY_FLAG,
"left": 68 + ARROW_KEY_FLAG,
"mod_int": 91... | 13 | 1 |
'''simple docstring'''
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def __magic_name__ ... | 13 |
'''simple docstring'''
from __future__ import annotations
import bisect
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
'''simple docstring'''
if hi < 0:
__SCREAMING_SNAKE_CAS... | 13 | 1 |
'''simple docstring'''
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("""socket.socket""" )
@patch("""builtins.open""" )
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> List[str]:
'''simple docstring''... | 13 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
a = logging.get_logger(__name__)
class __a ( _snake_case ):
__UpperCamelCase : int... | 13 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
a = logging.get_logger(__name__) # pylint: disable=invalid-name
class __a ( _snake_case ):... | 13 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a = {"configuration_sew": ["SEW_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvail... | 13 | 1 |
'''simple docstring'''
import re
def __magic_name__ ( __UpperCAmelCase ) -> str:
'''simple docstring'''
if len(re.findall("""[ATCG]""" , __UpperCAmelCase ) ) != len(__UpperCAmelCase ):
raise ValueError("""Invalid Strand""" )
retur... | 13 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __magic_name__ ( __UpperCAmelCase = "AAPL" ) -> str:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
__SCREAMI... | 13 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __a ( metaclass=_snake_case ):
__UpperCamelCase : List[str] = ['torch', 'torchsde']
def __init__( self : Optional[Any] ,*lowerCamelCase : Optional[int] ,**lowerCamelCase : Option... | 13 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
if num < 0:
return False
__SCREAMING_SNAKE_CASE = num
__SCREAMING_SNAKE_CASE = 0
while num > 0:
__SCREAMING_SNAKE_... | 13 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
... | 13 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
a = list[list[float | int]]
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> Matrix:
'''simple docstring'''
__SCREAMING_SNAKE_CASE ... | 13 | 1 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
a = "__DUMMY_TRANSFORMERS_USER__"
a = "Dummy User"
a = "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"
... | 13 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available... | 13 | 1 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a = get_tests_dir("fixtures/test_sentencepiece_with_by... | 13 |
'''simple docstring'''
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be check... | 13 | 1 |
'''simple docstring'''
import torch
def __magic_name__ ( ) -> Dict:
'''simple docstring'''
if torch.cuda.is_available():
__SCREAMING_SNAKE_CASE = torch.cuda.device_count()
else:
__SCREAMING_SNAKE_CASE = 0
print(f"""Su... | 13 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequen... | 13 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def __magic_name__ ( __Upp... | 13 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAv... | 13 | 1 |
'''simple docstring'''
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_module... | 13 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = BeautifulSoup(requests.get(__UpperCAmelCase , params... | 13 | 1 |
'''simple docstring'''
import math
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even num... | 13 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"camembert-base": "https://huggingface.co/ca... | 13 | 1 |
'''simple docstring'''
import argparse
a = "docs/source/_static/js/custom.js"
def __magic_name__ ( __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
with open(__UpperCAmelCase , encoding="""utf-8""" , newline="""\n""" ) as f:
_... | 13 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_t... | 13 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase = 1 , __UpperCAmelCase = 1000 ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 1
__SCREAMING_SNAKE_CASE = 0
for divide_by_number in range(__UpperCAm... | 13 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"asapp/sew-tiny-100k": "https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json",
# See a... | 13 | 1 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class... | 13 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase = 1 , __UpperCAmelCase = 1000 ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 1
__SCREAMING_SNAKE_CASE = 0
for divide_by_number in range(__UpperCAm... | 13 | 1 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = FileLock(str(tmpdir / """foo.lock""" ... | 13 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_available():
import... | 13 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __a ( metaclass=_snake_case ):
__UpperCamelCase : Tuple = ['note_seq']
def __init__( self : Optional[Any] ,*lowerCamelCase : Tuple ,**lowerCamelCase : Any ):
'''simple ... | 13 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __magic_name__ ( __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
def wrapper(*__UpperCAmel... | 13 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProces... | 13 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
a = "__DUMMY_TRANSFORMERS_USER__"
a = "Dummy User"
a = "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"
... | 13 | 1 |
'''simple docstring'''
a = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.60_9344,
"knot": 1.852,
}
a = {
"km/h": 1.0,
"m/s": 0.2_7777_7778,
"mph": 0.6_2137_1192,
"knot": 0.5_3995_6803,
}
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCa... | 13 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a = logging.get_logger(__name__)
a = {
"ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}
class __a ( ... | 13 | 1 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
a = logging.g... | 13 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class __a ( nn.Module ):
__UpperCamelCase : int
__UpperCamelCase : jnp.dtype = jnp.floataa
def UpperCAmelCase__ ( self : List[Any] ):
'''simple docstring'''
__SC... | 13 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
requir... | 13 |
'''simple docstring'''
import sys
from collections import defaultdict
class __a :
def __init__( self : Dict ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = []
def UpperCAmelCase__ ( self : List[Any] ,lowerCamelCase : ... | 13 | 1 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_gr... | 13 |
'''simple docstring'''
import os
import string
import sys
a = 1 << 8
a = {
"tab": ord("\t"),
"newline": ord("\r"),
"esc": 27,
"up": 65 + ARROW_KEY_FLAG,
"down": 66 + ARROW_KEY_FLAG,
"right": 67 + ARROW_KEY_FLAG,
"left": 68 + ARROW_KEY_FLAG,
"mod_int": 91... | 13 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
a = {"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_available():
raise Optional... | 13 |
'''simple docstring'''
from __future__ import annotations
import bisect
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
'''simple docstring'''
if hi < 0:
__SCREAMING_SNAKE_CAS... | 13 | 1 |
'''simple docstring'''
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_R... | 13 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
a = logging.get_logger(__name__)
class __a ( _snake_case ):
__UpperCamelCase : int... | 13 | 1 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 13 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a = {"configuration_sew": ["SEW_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvail... | 13 | 1 |
'''simple docstring'''
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
a = [
"word_embeddings_layern... | 13 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __magic_name__ ( __UpperCAmelCase = "AAPL" ) -> str:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
__SCREAMI... | 13 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
if index == number_of_items:
return 0
__SCREAMING_SNAKE_CASE ... | 13 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
if num < 0:
return False
__SCREAMING_SNAKE_CASE = num
__SCREAMING_SNAKE_CASE = 0
while num > 0:
__SCREAMING_SNAKE_... | 13 | 1 |
'''simple docstring'''
# Imports
import numpy as np
class __a :
def __init__( self : Dict ,lowerCamelCase : Optional[Any]=None ,lowerCamelCase : Dict=None ,lowerCamelCase : Optional[int]=None ,lowerCamelCase : Tuple=None ,lowerCamelCase : int=None ... | 13 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
a = list[list[float | int]]
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> Matrix:
'''simple docstring'''
__SCREAMING_SNAKE_CASE ... | 13 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a = {"configuration_sew": ["SEW_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvail... | 13 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available... | 13 | 1 |
'''simple docstring'''
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
a = logging.get_logger(__name__)
a = {name: getattr(transformers, name + "Fast") for name in SLOW... | 13 |
'''simple docstring'''
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be check... | 13 | 1 |
'''simple docstring'''
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
a = "src/transformers"
a = "docs/sour... | 13 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequen... | 13 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"camembert-base": "https://huggingface.co/ca... | 13 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAv... | 13 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from... | 13 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = BeautifulSoup(requests.get(__UpperCAmelCase , params... | 13 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .... | 13 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"camembert-base": "https://huggingface.co/ca... | 13 | 1 |
'''simple docstring'''
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase=1024 , __UpperCAm... | 13 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_t... | 13 | 1 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase=False ) -> Dict:
'''simple docstring'''
__SCREAMING_SNAKE_CASE ... | 13 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"asapp/sew-tiny-100k": "https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json",
# See a... | 13 | 1 |
'''simple docstring'''
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
... | 13 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase = 1 , __UpperCAmelCase = 1000 ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 1
__SCREAMING_SNAKE_CASE = 0
for divide_by_number in range(__UpperCAm... | 13 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
a = (3, 9, -11, 0, 7, 5, 1, -1)
a = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class __a :
__UpperCamelCase : int
__UpperCamelCase : Nod... | 13 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_available():
import... | 13 | 1 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
a = logging.get_logger(__name__)
class __a ( _snake_case ):
__UpperCamelCase : int... | 13 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __magic_name__ ( __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
def wrapper(*__UpperCAmel... | 13 | 1 |
'''simple docstring'''
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def __m... | 13 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
a = "__DUMMY_TRANSFORMERS_USER__"
a = "Dummy User"
a = "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"
... | 13 | 1 |
'''simple docstring'''
from collections import defaultdict
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 1
__SCREAMING_SNAKE_CASE = True
for v in tree[start]:
if v not ... | 13 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a = logging.get_logger(__name__)
a = {
"ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}
class __a ( ... | 13 | 1 |
'''simple docstring'''
def __magic_name__ ( ) -> int:
'''simple docstring'''
return 1
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def ... | 13 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class __a ( nn.Module ):
__UpperCamelCase : int
__UpperCamelCase : jnp.dtype = jnp.floataa
def UpperCAmelCase__ ( self : List[Any] ):
'''simple docstring'''
__SC... | 13 | 1 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Neste... | 13 |
'''simple docstring'''
import sys
from collections import defaultdict
class __a :
def __init__( self : Dict ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = []
def UpperCAmelCase__ ( self : List[Any] ,lowerCamelCase : ... | 13 | 1 |
'''simple docstring'''
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
a = logging.get_logger(__name__) # pylint: disable=invalid-name
def __magic_na... | 13 |
'''simple docstring'''
import os
import string
import sys
a = 1 << 8
a = {
"tab": ord("\t"),
"newline": ord("\r"),
"esc": 27,
"up": 65 + ARROW_KEY_FLAG,
"down": 66 + ARROW_KEY_FLAG,
"right": 67 + ARROW_KEY_FLAG,
"left": 68 + ARROW_KEY_FLAG,
"mod_int": 91... | 13 | 1 |
'''simple docstring'''
a = [
"DownloadConfig",
"DownloadManager",
"DownloadMode",
"StreamingDownloadManager",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager
... | 13 |
'''simple docstring'''
from __future__ import annotations
import bisect
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
'''simple docstring'''
if hi < 0:
__SCREAMING_SNAKE_CAS... | 13 | 1 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def __magic_name__ ( __UpperCAmelCase ) -> float:
'''simple docstring'''
if num <= 0:
raise ValueError("""math domain error""" )
return quad(__UpperCAmelCase ... | 13 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
a = logging.get_logger(__name__)
class __a ( _snake_case ):
__UpperCamelCase : int... | 13 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
return "\n".join(
f"""{number} * {i} = {number * i}""" for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__"... | 13 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a = {"configuration_sew": ["SEW_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvail... | 13 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transforme... | 13 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __magic_name__ ( __UpperCAmelCase = "AAPL" ) -> str:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
__SCREAMI... | 13 | 1 |
'''simple docstring'''
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax... | 13 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
if num < 0:
return False
__SCREAMING_SNAKE_CASE = num
__SCREAMING_SNAKE_CASE = 0
while num > 0:
__SCREAMING_SNAKE_... | 13 | 1 |
'''simple docstring'''
import os
import string
import sys
a = 1 << 8
a = {
"tab": ord("\t"),
"newline": ord("\r"),
"esc": 27,
"up": 65 + ARROW_KEY_FLAG,
"down": 66 + ARROW_KEY_FLAG,
"right": 67 + ARROW_KEY_FLAG,
"left": 68 + ARROW_KEY_FLAG,
"mod_int": 91... | 13 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
a = list[list[float | int]]
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> Matrix:
'''simple docstring'''
__SCREAMING_SNAKE_CASE ... | 13 | 1 |
'''simple docstring'''
from ....utils import logging
a = logging.get_logger(__name__)
class __a ( _snake_case ):
def __init__( self : Tuple ,lowerCamelCase : List[str] ,lowerCamelCase : Optional[int]=None ,lowerCamelCase : Optional[Any]=2048 ):... | 13 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available... | 13 | 1 |
'''simple docstring'''
from __future__ import annotations
import bisect
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
'''simple docstring'''
if hi < 0:
__SCREAMING_SNAKE_CAS... | 13 |
'''simple docstring'''
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be check... | 13 | 1 |
'''simple docstring'''
import argparse
import os
import re
a = "src/diffusers"
# Pattern that looks at the indentation in a line.
a = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
a = re.compile(r"^\s*\"([^\"]+)\":")
# Pattern that match... | 13 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequen... | 13 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> str:
'''simple docstring'''
return "".join(chr(ord(__UpperCAmelCase ) - 32 ) if """a""" <= char <= """z""" else char for char in word )
if __name__ == "__main__":
from doctest impo... | 13 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAv... | 13 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
fr... | 13 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = BeautifulSoup(requests.get(__UpperCAmelCase , params... | 13 | 1 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
a = TypeVar("KT")
a = TypeVar("VT")
class __a ( Generic[KT, VT] ):
def __init__( self : Any ,lowerCamelCase : KT | str = "root" ... | 13 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"camembert-base": "https://huggingface.co/ca... | 13 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase = False ) -> float:
'''simple docstring'''
if not arr:
return 0
__SCREAMING_SNAKE_CASE = 0 if allow_empty_subarrays... | 13 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_t... | 13 | 1 |
'''simple docstring'''
import sys
a = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"668966489504452445231617318... | 13 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
"asapp/sew-tiny-100k": "https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json",
# See a... | 13 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
a = get_tests_dir("fixtures/test_sent... | 13 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase = 1 , __UpperCAmelCase = 1000 ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 1
__SCREAMING_SNAKE_CASE = 0
for divide_by_number in range(__UpperCAm... | 13 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> float:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = u
for i in range(1 , __UpperCAmelCase ):... | 13 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_available():
import... | 13 | 1 |
'''simple docstring'''
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
a = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
a = [ord(letter) for letter in string.ascii_lowercase]
a ... | 13 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __magic_name__ ( __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
def wrapper(*__UpperCAmel... | 13 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFo... | 13 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
a = "__DUMMY_TRANSFORMERS_USER__"
a = "Dummy User"
a = "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"
... | 13 | 1 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accele... | 13 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a = logging.get_logger(__name__)
a = {
"ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}
class __a ( ... | 13 | 1 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available... | 13 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class __a ( nn.Module ):
__UpperCamelCase : int
__UpperCamelCase : jnp.dtype = jnp.floataa
def UpperCAmelCase__ ( self : List[Any] ):
'''simple docstring'''
__SC... | 13 | 1 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = len(__UpperCAmelCase )
__SCREAMING_SNAKE_CASE = len(__UpperCAmelCase )
... | 13 |
'''simple docstring'''
import sys
from collections import defaultdict
class __a :
def __init__( self : Dict ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = []
def UpperCAmelCase__ ( self : List[Any] ,lowerCamelCase : ... | 13 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
a = ... | 13 |
'''simple docstring'''
import os
import string
import sys
a = 1 << 8
a = {
"tab": ord("\t"),
"newline": ord("\r"),
"esc": 27,
"up": 65 + ARROW_KEY_FLAG,
"down": 66 + ARROW_KEY_FLAG,
"right": 67 + ARROW_KEY_FLAG,
"left": 68 + ARROW_KEY_FLAG,
"mod_int": 91... | 13 | 1 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 13 |
'''simple docstring'''
from __future__ import annotations
import bisect
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 , __UpperCAmelCase = -1 ) -> int:
'''simple docstring'''
if hi < 0:
__SCREAMING_SNAKE_CAS... | 13 | 1 |
'''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def __magic_name__ ( __UpperCAmelCase ) -> Optional[Any]:
'''simple docstring'''
for param in module.parameters():
__SCREAMING_SNAKE_CASE = Fal... | 13 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
a = logging.get_logger(__name__)
class __a ( _snake_case ):
__UpperCamelCase : int... | 13 | 1 |
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