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 |
|---|---|---|---|---|
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pipe... | 675 |
from typing import Dict, Optional
import numpy as np
import datasets
lowerCAmelCase = """
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For binary (two classes) or multi-class seg... | 675 | 1 |
from math import pi
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> float:
'''simple docstring'''
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 675 |
lowerCAmelCase = 256
# Modulus to hash a string
lowerCAmelCase = 1_000_003
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> bool:
'''simple docstring'''
__UpperCAmelCase : List[str] = len(lowercase_ )
__UpperC... | 675 | 1 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
lowerCAmelCase = Lock()
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ , lowercase_ , lowercase_ , lowercase_... | 675 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> list:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = int(lowercase_ )
if n_element < 1:
__UpperCAmelCase : str = ValueError('''a should be a positive number''' )
... | 675 | 1 |
def __SCREAMING_SNAKE_CASE ( lowercase_ = 50000000 ) -> int:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = set()
__UpperCAmelCase : int = int((limit - 24) ** (1 / 2) )
__UpperCAmelCase : List[Any] = set(... | 675 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""google/realm-cc-news-pretrained-embedder""": (
"""https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/conf... | 675 | 1 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_tok... | 675 |
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
... | 675 | 1 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_proce... | 675 |
def __SCREAMING_SNAKE_CASE ( ) -> list[list[int]]:
'''simple docstring'''
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
lowerCAmelCase = generate_large_matrix()
lowerCAmelCase = (
[[4, 3, 2, -1], [3, 2,... | 675 | 1 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = OrderedDict(
[
... | 675 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
lowerCAmelCase = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
lowerCAmelCase = _LazyModule(__name__, globals()["""__file... | 675 | 1 |
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
lowerCAmelCase ... | 675 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 675 | 1 |
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
lowerCAmelCase = logging.get_logger(__name__)
def __SCREAMING_... | 700 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""bert-base-uncased""": """https://huggingface... | 675 | 0 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_uti... | 701 |
from random import shuffle
import tensorflow as tf
from numpy import array
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = int(lowercase_ )
assert noofclust... | 675 | 0 |
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase = False
lowerCAmelCase = True
lowerCAmelCase = False
if __name__ == "__main__":
lowerCAmelCase = ... | 702 |
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> int:
'''simple docstring'''
if not nums:
return 0
__UpperCAmelCase : int = nums[0]
__UpperCAmelCase : Optional[Any] = 0
for num in... | 675 | 0 |
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_available():
from tran... | 703 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class lowerCamelCase ( unittest.TestCase ):
@require_torch
def A(... | 675 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase = {'''configuration_xlnet''': ['''XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP''... | 704 |
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCamelCase (... | 675 | 0 |
import os
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = len(grid[0] )
__UpperCAmelCase : List[str] = len(_A )
__UpperCAmelCase : Tuple = 0
... | 705 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSa... | 675 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...utils... | 706 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
lowerCAmelCase = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def __SCREAMING_SNAKE_CASE ( lowercase_ = "mumbai" ) -> Generator[tuple[str, ... | 675 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAv... | 707 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_acceler... | 675 | 0 |
import argparse
import os
# New Code #
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 accelerate import Ac... | 708 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
lowerCAmelCase = """sshleifer/bart-tiny-random"""
lowerCAme... | 675 | 0 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> int:
'''simple docstring'''
if len(__lowerCAmelCase ) != len(__lowerCAmelCase ):
raise ValueError('''String lengths must match!''' )
__UpperCAmelCase : ... | 709 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json""",
... | 675 | 0 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( ) -> Tuple:
'''simple docstring'''
__UpperCAmelCase : str = 0
for i in range(1 , 1001 ):
total += i**i
return str(lowerCamelCase__ )[-10:]
if __name__ == "__main__":
... | 710 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,
... | 675 | 0 |
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> Union[str, Any]:
'''simple docstring'''
return [ord(_lowerCAmelCase ) - 96 for elem in plain]
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> List[str]:
'''simple docst... | 711 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class lowerCamelCase :
_lowerCAmelCase : Optional[Union[str, Path]] = None
_lowerCAmelCase : bool = False
_lowerCAmelCase : bool = False
_low... | 675 | 0 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def __SCREAMING_SNAKE_CASE ( lowercase_ = "isbn/0140328726" ) -> dict:
'''simple docstring'''
__UpperCAmelCase : Optional[int] = olid.strip().strip(''... | 712 |
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
__UpperCAmelCase : Dict = str(bin(lowercase_ ) )[2:] # ... | 675 | 0 |
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
lowerCAmelCase = logging.get_logger(__name__)
cla... | 713 |
from string import ascii_uppercase
lowerCAmelCase = {char: i for i, char in enumerate(ascii_uppercase)}
lowerCAmelCase = dict(enumerate(ascii_uppercase))
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
... | 675 | 0 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from ... | 714 |
from typing import Dict, Optional
import numpy as np
import datasets
lowerCAmelCase = """
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For binary (two classes) or multi-class seg... | 675 | 0 |
import os
import sys
lowerCAmelCase = os.path.join(os.path.dirname(__file__), """src""")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSequenceClassification,
... | 715 |
lowerCAmelCase = 256
# Modulus to hash a string
lowerCAmelCase = 1_000_003
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> bool:
'''simple docstring'''
__UpperCAmelCase : List[str] = len(lowercase_ )
__UpperC... | 675 | 0 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
lowerCAmelCase = logging.get_logger(__name__)
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> str:
'''... | 716 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> list:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = int(lowercase_ )
if n_element < 1:
__UpperCAmelCase : str = ValueError('''a should be a positive number''' )
... | 675 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/git-base/resolve/main/config.jso... | 717 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""google/realm-cc-news-pretrained-embedder""": (
"""https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/conf... | 675 | 0 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ , lowercase_ , ) -> list[float]:
'''simple docstring'''
__UpperCAm... | 718 |
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
... | 675 | 0 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , **lowercase_ ) -> str:
'''simple docstring'''
__UpperCAmelCase : List[str] = AutoConfig.from_pretrai... | 719 |
def __SCREAMING_SNAKE_CASE ( ) -> list[list[int]]:
'''simple docstring'''
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
lowerCAmelCase = generate_large_matrix()
lowerCAmelCase = (
[[4, 3, 2, -1], [3, 2,... | 675 | 0 |
from __future__ import annotations
lowerCAmelCase = """#"""
class lowerCamelCase :
def __init__( self):
__UpperCAmelCase : List[str] = {}
def A( self , lowercase__):
__UpperCAmelCase : Tuple = self._trie
for char... | 720 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
lowerCAmelCase = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
lowerCAmelCase = _LazyModule(__name__, globals()["""__file... | 675 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@requ... | 721 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 675 | 0 |
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ = 0 , lowercase_ = 0 ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : Tuple = right or len(snake_case__ ) - 1
if left > right:
return -1
... | 700 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""bert-base-uncased""": """https://huggingface... | 675 | 0 |
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
lowerCAmelCase = logging.get_logger(__name__)
def __SCREAMING_SN... | 701 |
from random import shuffle
import tensorflow as tf
from numpy import array
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = int(lowercase_ )
assert noofclust... | 675 | 0 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerFast
from ... | 702 |
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> int:
'''simple docstring'''
if not nums:
return 0
__UpperCAmelCase : int = nums[0]
__UpperCAmelCase : Optional[Any] = 0
for num in... | 675 | 0 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCamelCase ( UpperCamelCase_ ):
def __init__( self , lowercase__ , lowercase__ = None ... | 703 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class lowerCamelCase ( unittest.TestCase ):
@require_torch
def A(... | 675 | 0 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_... | 704 |
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCamelCase (... | 675 | 0 |
def __SCREAMING_SNAKE_CASE ( ) -> int:
'''simple docstring'''
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> Union[str, Any]:
'''simple docstring'''
__Upper... | 705 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSa... | 675 | 0 |
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)... | 706 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
lowerCAmelCase = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def __SCREAMING_SNAKE_CASE ( lowercase_ = "mumbai" ) -> Generator[tuple[str, ... | 675 | 0 |
from __future__ import annotations
from typing import Any
class lowerCamelCase :
def __init__( self , lowercase__ = 6):
__UpperCAmelCase : Optional[int] = None
__UpperCAmelCase : str = None
self.create_linked_list(__lowerCAmelCase)
... | 707 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_acceler... | 675 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"vinvino02/glpn-kitti": "https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json",
# See all GLPN models at https://huggingfa... | 708 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
lowerCAmelCase = """sshleifer/bart-tiny-random"""
lowerCAme... | 675 | 0 |
'''simple docstring'''
import sys
lowerCAmelCase = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557'''
... | 709 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json""",
... | 675 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class lowerCamelCase :
def __init__( self , lowercase__ = None):
if components is None:
__UpperCAmelC... | 710 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,
... | 675 | 0 |
print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
| 711 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class lowerCamelCase :
_lowerCAmelCase : Optional[Union[str, Path]] = None
_lowerCAmelCase : bool = False
_lowerCAmelCase : bool = False
_low... | 675 | 0 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ = "cpu" , lowercase_ = None ) -> Dict:
'''simple docstring'''
__UpperCAmelCase : str = torch.load(_lowercase , ... | 712 |
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
__UpperCAmelCase : Dict = str(bin(lowercase_ ) )[2:] # ... | 675 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise OptionalDependencyNotAvailab... | 713 |
from string import ascii_uppercase
lowerCAmelCase = {char: i for i, char in enumerate(ascii_uppercase)}
lowerCAmelCase = dict(enumerate(ascii_uppercase))
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
... | 675 | 0 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Path
from urllib.... | 714 |
from typing import Dict, Optional
import numpy as np
import datasets
lowerCAmelCase = """
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For binary (two classes) or multi-class seg... | 675 | 0 |
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ ) -> Dict:
'''simple docstring'''
__UpperCAmelCase : List[str... | 715 |
lowerCAmelCase = 256
# Modulus to hash a string
lowerCAmelCase = 1_000_003
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> bool:
'''simple docstring'''
__UpperCAmelCase : List[str] = len(lowercase_ )
__UpperC... | 675 | 0 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowerCAmelCase = logging.get_logger(__name__)
class lowerCamelCase ( __snake_case ):
def __init__( self , *lowercase__ , **lowercase__):
warnings.war... | 716 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> list:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = int(lowercase_ )
if n_element < 1:
__UpperCAmelCase : str = ValueError('''a should be a positive number''' )
... | 675 | 0 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> List[Any]:
'''simple docstring'''
if any(not isinstance(lowercase_ , lowercase_ ) or x < 0 for x in sequence ):
raise TypeError('''Sequence must be list of non-negative integers''' )
for _ in range... | 717 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""google/realm-cc-news-pretrained-embedder""": (
"""https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/conf... | 675 | 0 |
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> List[Any]:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = len(__lowerCAmelCase )
print('''The following activities are selected:''' )
# The first activity is always s... | 718 |
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
... | 675 | 0 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ ) -> Dict:
'''s... | 719 |
def __SCREAMING_SNAKE_CASE ( ) -> list[list[int]]:
'''simple docstring'''
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
lowerCAmelCase = generate_large_matrix()
lowerCAmelCase = (
[[4, 3, 2, -1], [3, 2,... | 675 | 0 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
fro... | 720 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
lowerCAmelCase = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
lowerCAmelCase = _LazyModule(__name__, globals()["""__file... | 675 | 0 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common import ConfigTester
fr... | 721 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 675 | 0 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import GenerationTes... | 700 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""bert-base-uncased""": """https://huggingface... | 675 | 0 |
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> bool:
'''simple docstring'''
return len(set(_SCREAMING_SNAKE_CASE ) ) == len(_SCREAMING_SNAKE_CASE )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 701 |
from random import shuffle
import tensorflow as tf
from numpy import array
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = int(lowercase_ )
assert noofclust... | 675 | 0 |
def __SCREAMING_SNAKE_CASE ( lowercase_ = 50 ) -> Optional[Any]:
'''simple docstring'''
__UpperCAmelCase : List[str] = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
f... | 702 |
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> int:
'''simple docstring'''
if not nums:
return 0
__UpperCAmelCase : int = nums[0]
__UpperCAmelCase : Optional[Any] = 0
for num in... | 675 | 0 |
import argparse
import datetime
import io
import itertools
import json
import math
import os
import platform
import re
import shlex
import subprocess
import sys
from pathlib import Path
from statistics import fmean
import pandas as pd
import torch
from tqdm import tqdm
import transformers
lowerCAmelCase = ... | 703 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class lowerCamelCase ( unittest.TestCase ):
@require_torch
def A(... | 675 | 0 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import HeunDiscreteScheduler
from .... | 704 |
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCamelCase (... | 675 | 0 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowerCamelCase ( unittest.TestCase ):
def A( self):
__UpperCAmelCase : int ... | 705 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSa... | 675 | 0 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_config... | 706 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
lowerCAmelCase = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def __SCREAMING_SNAKE_CASE ( lowercase_ = "mumbai" ) -> Generator[tuple[str, ... | 675 | 0 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> int:
'''simple docstring'''
if not isinstance(lowercase_ , lowercase_ ):
__UpperCAmelCase : List[str] = f"Input value of [number={number}] must be an integer"
raise TypeError(lowerc... | 707 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_acceler... | 675 | 0 |
import argparse
lowerCAmelCase = """docs/source/_static/js/custom.js"""
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> Dict:
'''simple docstring'''
with open(__UpperCamelCase , encoding='''utf-8''' , newline='''\n''' ) as f:
__Uppe... | 708 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
lowerCAmelCase = """sshleifer/bart-tiny-random"""
lowerCAme... | 675 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
lowerCAmelCase = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP""",... | 709 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json""",
... | 675 | 0 |
'''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 i... | 710 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,
... | 675 | 0 |
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_E... | 711 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class lowerCamelCase :
_lowerCAmelCase : Optional[Union[str, Path]] = None
_lowerCAmelCase : bool = False
_lowerCAmelCase : bool = False
_low... | 675 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {"""vocab_file""": """spm_... | 712 |
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
__UpperCAmelCase : Dict = str(bin(lowercase_ ) )[2:] # ... | 675 | 0 |
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def __SCREAMING_SNAKE_CASE ( lowercas... | 713 |
from string import ascii_uppercase
lowerCAmelCase = {char: i for i, char in enumerate(ascii_uppercase)}
lowerCAmelCase = dict(enumerate(ascii_uppercase))
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
... | 675 | 0 |
from datetime import datetime as dt
import os
from github import Github
lowerCAmelCase = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""feature request""",
"""new model""",
"""wip""",
]
def __SCREAMING_SNAKE_CASE ( ) -> ... | 714 |
from typing import Dict, Optional
import numpy as np
import datasets
lowerCAmelCase = """
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For binary (two classes) or multi-class seg... | 675 | 0 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ ) -> List[str]:
'''simple docstring'''
__UpperCAmelCase : Optional[int] = {
'''en''': ... | 715 |
lowerCAmelCase = 256
# Modulus to hash a string
lowerCAmelCase = 1_000_003
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> bool:
'''simple docstring'''
__UpperCAmelCase : List[str] = len(lowercase_ )
__UpperC... | 675 | 0 |
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
lowerCAmelCase = logging.getLogger(__name__)
if __name__ == "__main__":
lowe... | 716 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> list:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = int(lowercase_ )
if n_element < 1:
__UpperCAmelCase : str = ValueError('''a should be a positive number''' )
... | 675 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky.text_encoder import ... | 717 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""google/realm-cc-news-pretrained-embedder""": (
"""https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/conf... | 675 | 0 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCAmelCase = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
"""attn""": """attention.self""",
"""se... | 718 |
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
... | 675 | 0 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
lowerCAmelCase = logging.get_logger(__name__)
class lowerCamelCase ( __snake_case ):
def __init__( self , *lowercase__ , **lowercase__):
warnings.w... | 719 |
def __SCREAMING_SNAKE_CASE ( ) -> list[list[int]]:
'''simple docstring'''
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
lowerCAmelCase = generate_large_matrix()
lowerCAmelCase = (
[[4, 3, 2, -1], [3, 2,... | 675 | 0 |
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResampling,
get_image_s... | 720 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
lowerCAmelCase = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
lowerCAmelCase = _LazyModule(__name__, globals()["""__file... | 675 | 0 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
fro... | 721 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 675 | 0 |
import os
from datetime import datetime as dt
from github import Github
lowerCAmelCase = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
]
def __SCREAMING_SN... | 700 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""bert-base-uncased""": """https://huggingface... | 675 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.set_verbosity_info()
lowerCAmel... | 701 |
from random import shuffle
import tensorflow as tf
from numpy import array
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = int(lowercase_ )
assert noofclust... | 675 | 0 |
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
lowerCAmelCase = {
"""facebook/maskformer-swin-base-ade""": (
"""https... | 702 |
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> int:
'''simple docstring'''
if not nums:
return 0
__UpperCAmelCase : int = nums[0]
__UpperCAmelCase : Optional[Any] = 0
for num in... | 675 | 0 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_... | 703 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class lowerCamelCase ( unittest.TestCase ):
@require_torch
def A(... | 675 | 0 |
import random
class lowerCamelCase :
@staticmethod
def A( lowercase__):
__UpperCAmelCase : Dict = [ord(lowercase__) for i in text]
__UpperCAmelCase : Optional[int] = []
__UpperCAmelCase : List[str] = []
for i in plain:
... | 704 |
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCamelCase (... | 675 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowerCAmelCase = {
"""configuration_gpt_neox_japanese""": ["""GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXJapaneseConfig"""],
"""tokeniz... | 705 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSa... | 675 | 0 |
from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import AttentionProcessor, AttnProcessor
from .modeling... | 706 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
lowerCAmelCase = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def __SCREAMING_SNAKE_CASE ( lowercase_ = "mumbai" ) -> Generator[tuple[str, ... | 675 | 0 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
lowerCAmelCase = """\
"""
lowerCAmelCase = """
Perplexity (PPL) is one of the most common metrics for evaluating l... | 707 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_acceler... | 675 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""YituTech/conv-bert-base""": """https://huggi... | 708 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
lowerCAmelCase = """sshleifer/bart-tiny-random"""
lowerCAme... | 675 | 0 |
'''simple docstring'''
import inspect
import re
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_config_docstrings.py
lowerCAmelCase = 'src/transformers'
# This... | 709 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json""",
... | 675 | 0 |
'''simple docstring'''
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ ) -> List[str]:
'''simple docstring'''
__UpperCAmelCase : int = list(range(len(A_ ) ) )
__UpperCAmelC... | 710 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,
... | 675 | 0 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> int:
'''simple docstring'''
if not isinstance(lowercase_ , lowercase_ ):
raise ValueError('''multiplicative_persistence() only accepts integral values''' )
if num < 0:
raise ValueError('''multiplicative_persistence() does ... | 711 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class lowerCamelCase :
_lowerCAmelCase : Optional[Union[str, Path]] = None
_lowerCAmelCase : bool = False
_lowerCAmelCase : bool = False
_low... | 675 | 0 |
lowerCAmelCase = {
"""km/h""": 1.0,
"""m/s""": 3.6,
"""mph""": 1.60_93_44,
"""knot""": 1.8_52,
}
lowerCAmelCase = {
"""km/h""": 1.0,
"""m/s""": 0.2_77_77_77_78,
"""mph""": 0.6_21_37_11_92,
"""knot""": 0.5_39_95_68_03,
}
def __SCREAMING_SNAKE_CASE ... | 712 |
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
__UpperCAmelCase : Dict = str(bin(lowercase_ ) )[2:] # ... | 675 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json""",
"""microsoft/markuplm-la... | 713 |
from string import ascii_uppercase
lowerCAmelCase = {char: i for i, char in enumerate(ascii_uppercase)}
lowerCAmelCase = dict(enumerate(ascii_uppercase))
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
... | 675 | 0 |
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():
from PIL import Image
from ..image_utils import... | 714 |
from typing import Dict, Optional
import numpy as np
import datasets
lowerCAmelCase = """
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For binary (two classes) or multi-class seg... | 675 | 0 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowerCAmelCase = version.parse(version.parse(torch.__version__).base_version) < version.parse("""1.11""")
def __SCREAMING_SNAKE_CASE ... | 715 |
lowerCAmelCase = 256
# Modulus to hash a string
lowerCAmelCase = 1_000_003
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> bool:
'''simple docstring'''
__UpperCAmelCase : List[str] = len(lowercase_ )
__UpperC... | 675 | 0 |
class lowerCamelCase :
def __init__( self):
__UpperCAmelCase : Optional[Any] = {}
def A( self):
print(self.vertex)
for i in self.vertex:
print(lowercase_ , ''' -> ''' , ''' -> '''.join([str(lowercase_) for j in self.vert... | 716 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> list:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = int(lowercase_ )
if n_element < 1:
__UpperCAmelCase : str = ValueError('''a should be a positive number''' )
... | 675 | 0 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax
if is_tor... | 717 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""google/realm-cc-news-pretrained-embedder""": (
"""https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/conf... | 675 | 0 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> List[Any]:
'''simple docstring'''
if not head:
return True
# split the list to two parts
__UpperCAmelCase : str = head.next, head
while fast and fast.next:
__UpperCAmelCas... | 718 |
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
'''simple docstring'''
... | 675 | 0 |
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get_up_block
@dataclass
cla... | 719 |
def __SCREAMING_SNAKE_CASE ( ) -> list[list[int]]:
'''simple docstring'''
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
lowerCAmelCase = generate_large_matrix()
lowerCAmelCase = (
[[4, 3, 2, -1], [3, 2,... | 675 | 0 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class lowerCamelCase ( __lowerCamelCa... | 720 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
lowerCAmelCase = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
lowerCAmelCase = _LazyModule(__name__, globals()["""__file... | 675 | 0 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
lowerCAmelCase = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
author={Yonghui Wu a... | 721 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 675 | 0 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...feat... | 700 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
"""bert-base-uncased""": """https://huggingface... | 675 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowerCAmelCase = {
"""configuration_ernie""": ["""ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ErnieConfig""", """ErnieOnnxConfig"""],
}
try:
if not i... | 701 |
from random import shuffle
import tensorflow as tf
from numpy import array
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = int(lowercase_ )
assert noofclust... | 675 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils impor... | 702 |
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> int:
'''simple docstring'''
if not nums:
return 0
__UpperCAmelCase : int = nums[0]
__UpperCAmelCase : Optional[Any] = 0
for num in... | 675 | 0 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
lowerCAmelCase = logging.get_logger(__name__)
lower... | 703 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class lowerCamelCase ( unittest.TestCase ):
@require_torch
def A(... | 675 | 0 |
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