code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : int = {
'microsoft/markuplm-base': 'https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json',
'microsoft/markup... | 352 |
def lowerCAmelCase_ (lowerCAmelCase__: int , lowerCAmelCase__: float , lowerCAmelCase__: float ):
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def lowerCAmelCase_ (lowerCAmelCase__: f... | 82 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : int = logging.get_logger(__name__)
a : int = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'tiiuae/falcon-7b': 'https://huggingfac... | 353 |
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
@dataclass... | 82 | 0 |
import argparse
import os
import re
import zipfile
import torch
from transformers import AutoTokenizer, GPTaConfig
def lowerCAmelCase_ (lowerCAmelCase__: Optional[Any] , lowerCAmelCase__: str , lowerCAmelCase__: Optional[int]=0 ):
""... | 354 |
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available... | 82 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
a : List[Any] = logging.get_logger(__name__)
a : List[Any] = {
'microsoft/... | 355 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_... | 82 | 0 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subpr... | 356 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
a : Optional[int] = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.self',
'se... | 82 | 0 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
... | 357 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
a : List[str] = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
... | 82 | 0 |
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowerCAmelCase_ (lowerCAmelCase__: List[str] ):
"""simple... | 358 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
a : Dict = datasets.logging.get_logger(__name__)
a : Any = '\\n@InProceedings{moosavi2019minimum,\n ... | 82 | 0 |
import pprint
import requests
a : str = """https://zenquotes.io/api"""
def lowerCAmelCase_ ():
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowerCAmelCase_ ():
... | 359 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin... | 82 | 0 |
from math import ceil, sqrt
def lowerCAmelCase_ (lowerCAmelCase__: int = 1_0_0_0_0_0_0 ):
"""simple docstring"""
UpperCAmelCase_: Union[str, Any] = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**... | 360 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : Optional[Any] = {
'facebook/encodec_24khz': 'https://huggingface.co/facebo... | 82 | 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
f... | 361 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigT... | 82 | 0 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
a : List[str] = logging... | 362 |
from __future__ import annotations
def lowerCAmelCase_ (lowerCAmelCase__: list[float] ):
"""simple docstring"""
UpperCAmelCase_: Union[str, Any] = 0.00
UpperCAmelCase_: List[str] = 0
for resistor in resistors:
... | 82 | 0 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
a : Union[str, Any] = False
class _a ( unittest.TestCase ):
d... | 363 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
a : str ... | 82 | 0 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class _a ... | 364 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
a : Tuple = {'tokenization_tapex': ['TapexTokenizer']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
a : List[Any] = _LazyModule(__name__, globals()['_... | 82 | 0 |
def lowerCAmelCase_ (lowerCAmelCase__: int ):
"""simple docstring"""
if n == 1 or not isinstance(__a , __a ):
return 0
elif n == 2:
return 1
else:
UpperCAmelCase_: Any = [0, 1]
for i in range(2 , n +... | 365 |
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_to... | 82 | 0 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
... | 366 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
a : List[... | 82 | 0 |
import itertools
import string
from collections.abc import Generator, Iterable
def lowerCAmelCase_ (lowerCAmelCase__: Iterable[str] , lowerCAmelCase__: int ):
"""simple docstring"""
UpperCAmelCase_: List[str] = iter(a... | 367 |
from __future__ import annotations
def lowerCAmelCase_ (lowerCAmelCase__: list[int | float] , lowerCAmelCase__: int , lowerCAmelCase__: int ):
"""simple docstring"""
if len(lowerCAmelCase__ ) == 0:
raise ValueError("""fin... | 82 | 0 |
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 .tokenization_big_bi... | 368 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
a : Optional[Any] = logging.get_logger(__na... | 82 | 0 |
"""simple docstring"""
def lowerCAmelCase_ (lowerCAmelCase__: Dict ):
"""simple docstring"""
UpperCAmelCase_: List[str] = [0] * len(a__ )
for i in range(1 , len(a__ ) ):
# use last results for better perform... | 369 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
f... | 82 | 0 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
a : str = logging.get_logger(__name__)
def lowerCAmelCase_ (lowerCAmelCase__: Optional[Any]=Non... | 370 |
from collections import defaultdict
class _a :
def __init__(self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_ ) -> List[str]:
UpperCAmelCase_: Optional[int] = total # total no of tasks (N)
# DP table will have a dimension of (2^M)*N
... | 82 | 0 |
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require_torchaudi... | 371 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _a ( unittest.TestCase , _lowerCAmelCase ):
def __snake_case (self ) -> Optional[int]:
UpperCAmelCase_: Optional[int] = l... | 82 | 0 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def lowerCAmelCase_ (lowerCAmelCase__: Tuple ):
"""simple docstring"""
monkeypatch.setattr("""datasets.utils.deprecation_utils._emitted_deprecation_warnings"""... | 350 |
a : Tuple = 'Tobias Carryer'
from time import time
class _a :
def __init__(self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_=int(time() ) ) -> List[Any]: # noqa: B008
UpperCAmelCase_: List[str]... | 82 | 0 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_conf... | 351 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoMo... | 82 | 0 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import ... | 352 |
def lowerCAmelCase_ (lowerCAmelCase__: int , lowerCAmelCase__: float , lowerCAmelCase__: float ):
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def lowerCAmelCase_ (lowerCAmelCase__: f... | 82 | 0 |
def lowerCAmelCase_ ():
"""simple docstring"""
UpperCAmelCase_: Optional[int] = [3_1, 2_8, 3_1, 3_0, 3_1, 3_0, 3_1, 3_1, 3_0, 3_1, 3_0, 3_1]
UpperCAmelCase_: int = 6
UpperCAmelCase_: Dict = 1
UpperCAmelCase_: ... | 353 |
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
@dataclass... | 82 | 0 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
a : int = datasets.utils.log... | 354 |
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available... | 82 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
loggi... | 355 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_... | 82 | 0 |
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : str = logging.get_logger(__name__)
a : Union[str, Any] =... | 356 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
a : Optional[int] = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.self',
'se... | 82 | 0 |
from math import ceil, sqrt
def lowerCAmelCase_ (lowerCAmelCase__: int = 1_0_0_0_0_0_0 ):
"""simple docstring"""
UpperCAmelCase_: int = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:... | 357 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
a : List[str] = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
... | 82 | 0 |
def lowerCAmelCase_ (lowerCAmelCase__: Tuple = 1_0_0 ):
"""simple docstring"""
UpperCAmelCase_: Optional[int] = (n * (n + 1) // 2) ** 2
UpperCAmelCase_: Optional[int] = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name... | 358 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
a : Dict = datasets.logging.get_logger(__name__)
a : Any = '\\n@InProceedings{moosavi2019minimum,\n ... | 82 | 0 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def ... | 359 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin... | 82 | 0 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from .... | 360 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : Optional[Any] = {
'facebook/encodec_24khz': 'https://huggingface.co/facebo... | 82 | 0 |
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"""kwargs, expected""" , [
({"""num_shards""": 0, """max_num_jobs""": 1}, []),
({"""num_shards""": 1_0, """max_num_job... | 361 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigT... | 82 | 0 |
from ...processing_utils import ProcessorMixin
class _a ( __snake_case ):
A = 'SpeechT5FeatureExtractor'
A = 'SpeechT5Tokenizer'
def __init__(self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_ ) -> int:
super().__init__(SCREAMING... | 362 |
from __future__ import annotations
def lowerCAmelCase_ (lowerCAmelCase__: list[float] ):
"""simple docstring"""
UpperCAmelCase_: Union[str, Any] = 0.00
UpperCAmelCase_: List[str] = 0
for resistor in resistors:
... | 82 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a : str = {
'configuration_xlm_robe... | 363 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
a : str ... | 82 | 0 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class _a :
def __init__(self, SCREAMING_SNAKE_CASE_ ) -> Any:
UpperCAmelCase_: Any = data
UpperCAmelCase_: Tuple = [0X67_45_23_01, 0Xef_cd_ab_89, 0X9... | 364 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
a : Tuple = {'tokenization_tapex': ['TapexTokenizer']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
a : List[Any] = _LazyModule(__name__, globals()['_... | 82 | 0 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.utils ... | 365 |
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_to... | 82 | 0 |
"""simple docstring"""
def lowerCAmelCase_ (lowerCAmelCase__: int = 5_0 ):
"""simple docstring"""
UpperCAmelCase_: Optional[Any] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3... | 366 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
a : List[... | 82 | 0 |
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class _a ( UpperCamelCase__ ):
A = DistilB... | 367 |
from __future__ import annotations
def lowerCAmelCase_ (lowerCAmelCase__: list[int | float] , lowerCAmelCase__: int , lowerCAmelCase__: int ):
"""simple docstring"""
if len(lowerCAmelCase__ ) == 0:
raise ValueError("""fin... | 82 | 0 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnx... | 368 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
a : Optional[Any] = logging.get_logger(__na... | 82 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _a ... | 369 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
f... | 82 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : List[Any] = {
'facebook/xmod-base':... | 370 |
from collections import defaultdict
class _a :
def __init__(self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_ ) -> List[str]:
UpperCAmelCase_: Optional[int] = total # total no of tasks (N)
# DP table will have a dimension of (2^M)*N
... | 82 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class _a ( _a ):
def __init__(self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_ ) -> Optional[Any]:
UpperCAmelCase_: List[str] = params
UpperCAmelCase... | 371 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _a ( unittest.TestCase , _lowerCAmelCase ):
def __snake_case (self ) -> Optional[int]:
UpperCAmelCase_: Optional[int] = l... | 82 | 0 |
import json
import pathlib
import unittest
import numpy as np
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 ImageProcessingSavingTestMixin, prepare_image_in... | 350 |
a : Tuple = 'Tobias Carryer'
from time import time
class _a :
def __init__(self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_=int(time() ) ) -> List[Any]: # noqa: B008
UpperCAmelCase_: List[str]... | 82 | 0 |
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
@require_sente... | 351 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoMo... | 82 | 0 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Tok... | 352 |
def lowerCAmelCase_ (lowerCAmelCase__: int , lowerCAmelCase__: float , lowerCAmelCase__: float ):
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def lowerCAmelCase_ (lowerCAmelCase__: f... | 82 | 0 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_onnx_av... | 353 |
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
@dataclass... | 82 | 0 |
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp_space_opt... | 354 |
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available... | 82 | 0 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data impor... | 355 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_... | 82 | 0 |
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if not is_tf_ava... | 356 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
a : Optional[int] = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.self',
'se... | 82 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless ... | 357 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
a : List[str] = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
... | 82 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : Dict = {
'roberta-base': 'https://huggingface.co/roberta-b... | 358 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
a : Dict = datasets.logging.get_logger(__name__)
a : Any = '\\n@InProceedings{moosavi2019minimum,\n ... | 82 | 0 |
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 ... | 359 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin... | 82 | 0 |
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image
from ... | 360 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : Optional[Any] = {
'facebook/encodec_24khz': 'https://huggingface.co/facebo... | 82 | 0 |
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool
class _a ( __lowercase ):
A = '''openai/whisper-base'''
A = (
'''This is a tool that transcribes an audio into text. It takes a... | 361 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigT... | 82 | 0 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision... | 362 |
from __future__ import annotations
def lowerCAmelCase_ (lowerCAmelCase__: list[float] ):
"""simple docstring"""
UpperCAmelCase_: Union[str, Any] = 0.00
UpperCAmelCase_: List[str] = 0
for resistor in resistors:
... | 82 | 0 |
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class _a ( _A ):
def __lt__(self, SCREAMING_SNAKE_CASE_ ) -> Dict:
return self[-1] < other[-1]
def __eq__(self... | 363 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
a : str ... | 82 | 0 |
def lowerCAmelCase_ (lowerCAmelCase__: Optional[int] ):
"""simple docstring"""
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def lowerCAmelCase_ (lowerCAmelCase__: str ):
"""simple docstring"""
UpperCAmelCase_: Any ... | 364 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
a : Tuple = {'tokenization_tapex': ['TapexTokenizer']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
a : List[Any] = _LazyModule(__name__, globals()['_... | 82 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
... | 365 |
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_to... | 82 | 0 |
"""simple docstring"""
def lowerCAmelCase_ ():
"""simple docstring"""
return [list(range(1_0_0_0 - i , -1_0_0_0 - i , -1 ) ) for i in range(1_0_0_0 )]
a : Dict = generate_large_matrix()
a : str = (
[[... | 366 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
a : List[... | 82 | 0 |
from __future__ import annotations
def lowerCAmelCase_ (lowerCAmelCase__: list , lowerCAmelCase__: int | None = None , lowerCAmelCase__: int | None = None ):
"""simple docstring"""
if start is None:
UpperCAmelCa... | 367 |
from __future__ import annotations
def lowerCAmelCase_ (lowerCAmelCase__: list[int | float] , lowerCAmelCase__: int , lowerCAmelCase__: int ):
"""simple docstring"""
if len(lowerCAmelCase__ ) == 0:
raise ValueError("""fin... | 82 | 0 |
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 impor... | 368 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
a : Optional[Any] = logging.get_logger(__na... | 82 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common ... | 369 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
f... | 82 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : Optional[Any] = {
'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/config.json',
# See all XGLM models at http... | 370 |
from collections import defaultdict
class _a :
def __init__(self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_ ) -> List[str]:
UpperCAmelCase_: Optional[int] = total # total no of tasks (N)
# DP table will have a dimension of (2^M)*N
... | 82 | 0 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _a ( _lowerCAmelCase ):
A = ''''''
A = (
None # protocol passed in prefix to the url. ex... | 371 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _a ( unittest.TestCase , _lowerCAmelCase ):
def __snake_case (self ) -> Optional[int]:
UpperCAmelCase_: Optional[int] = l... | 82 | 0 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
a : Union[str, Any] = "\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n au... | 350 |
a : Tuple = 'Tobias Carryer'
from time import time
class _a :
def __init__(self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_=int(time() ) ) -> List[Any]: # noqa: B008
UpperCAmelCase_: List[str]... | 82 | 0 |
def lowerCAmelCase_ (lowerCAmelCase__: str ):
"""simple docstring"""
UpperCAmelCase_: List[str] = hex_num.strip()
if not hex_num:
raise ValueError("""No value was passed to the function""" )
UpperCAmelCase_: Optional[int] ... | 351 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoMo... | 82 | 0 |
def lowerCAmelCase_ (lowerCAmelCase__: int = 6_0_0_8_5_1_4_7_5_1_4_3 ):
"""simple docstring"""
try:
UpperCAmelCase_: List[str] = int(UpperCamelCase__ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or... | 352 |
def lowerCAmelCase_ (lowerCAmelCase__: int , lowerCAmelCase__: float , lowerCAmelCase__: float ):
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def lowerCAmelCase_ (lowerCAmelCase__: f... | 82 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.tokenizatio... | 353 |
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
@dataclass... | 82 | 0 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
a : ... | 354 |
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available... | 82 | 0 |
import os
from datetime import datetime as dt
from github import Github
a : Dict = [
"good first issue",
"feature request",
"wip",
]
def lowerCAmelCase_ ():
"""simple docstring"""
UpperCAmelCase_: int = ... | 355 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_... | 82 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenize... | 356 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
a : Optional[int] = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.self',
'se... | 82 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker... | 357 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
a : List[str] = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
... | 82 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from transforme... | 358 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
a : Dict = datasets.logging.get_logger(__name__)
a : Any = '\\n@InProceedings{moosavi2019minimum,\n ... | 82 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a : Tuple = {'configuration_unispeech': ['UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP', 'UniSpeechConfig']}... | 359 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin... | 82 | 0 |
def lowerCAmelCase_ (lowerCAmelCase__: int = 4_0_0_0_0_0_0 ):
"""simple docstring"""
UpperCAmelCase_: Optional[int] = [0, 1]
UpperCAmelCase_: List[str] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
i... | 360 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : Optional[Any] = {
'facebook/encodec_24khz': 'https://huggingface.co/facebo... | 82 | 0 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase_ (lowerCAmelCase__: Tuple , lowerCAmelCase__: Opti... | 361 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigT... | 82 | 0 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from trans... | 362 |
from __future__ import annotations
def lowerCAmelCase_ (lowerCAmelCase__: list[float] ):
"""simple docstring"""
UpperCAmelCase_: Union[str, Any] = 0.00
UpperCAmelCase_: List[str] = 0
for resistor in resistors:
... | 82 | 0 |
from __future__ import annotations
from typing import Any
def lowerCAmelCase_ (lowerCAmelCase__: list ):
"""simple docstring"""
if not postfix_notation:
return 0
UpperCAmelCase_: Dict = {"+", "-", "*", "/"}
UpperCAmelC... | 363 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
a : str ... | 82 | 0 |
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spectrogram_diffusion import... | 364 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
a : Tuple = {'tokenization_tapex': ['TapexTokenizer']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
a : List[Any] = _LazyModule(__name__, globals()['_... | 82 | 0 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def lowerCAmelCase_ (lowerCAmel... | 365 |
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_to... | 82 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_avai... | 366 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
a : List[... | 82 | 0 |
from __future__ import annotations
from collections.abc import Generator
def lowerCAmelCase_ ():
"""simple docstring"""
UpperCAmelCase_: dict[int, int] = {}
UpperCAmelCase_: List[Any] = 2
while True:
... | 367 |
from __future__ import annotations
def lowerCAmelCase_ (lowerCAmelCase__: list[int | float] , lowerCAmelCase__: int , lowerCAmelCase__: int ):
"""simple docstring"""
if len(lowerCAmelCase__ ) == 0:
raise ValueError("""fin... | 82 | 0 |
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
a : List[str] = logging.get_logger(__name__)
class _a ( __a ):
A = CLIPCon... | 368 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
a : Optional[Any] = logging.get_logger(__na... | 82 | 0 |
"""simple docstring"""
import numpy as np
def lowerCAmelCase_ (lowerCAmelCase__: Union[str, Any] , lowerCAmelCase__: Optional[Any] , lowerCAmelCase__: Tuple , lowerCAmelCase__: Union[str, Any] , lowerCAmelCase__: str ):
... | 369 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
f... | 82 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a : Optional[Any] = {
'configuration_groupvit': [
'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'GroupViTConfig',
'GroupViTOnnx... | 370 |
from collections import defaultdict
class _a :
def __init__(self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_ ) -> List[str]:
UpperCAmelCase_: Optional[int] = total # total no of tasks (N)
# DP table will have a dimension of (2^M)*N
... | 82 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer, TFAutoModelForSeq... | 371 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _a ( unittest.TestCase , _lowerCAmelCase ):
def __snake_case (self ) -> Optional[int]:
UpperCAmelCase_: Optional[int] = l... | 82 | 0 |
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,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PND... | 350 |
a : Tuple = 'Tobias Carryer'
from time import time
class _a :
def __init__(self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_=int(time() ) ) -> List[Any]: # noqa: B008
UpperCAmelCase_: List[str]... | 82 | 0 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrF... | 351 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoMo... | 82 | 0 |
from __future__ import annotations
from collections.abc import Generator
def lowerCAmelCase_ ():
"""simple docstring"""
UpperCAmelCase_: Any = {}
UpperCAmelCase_: Union[str, Any] = 2
while True:
UpperCAmelCase_: ... | 352 |
def lowerCAmelCase_ (lowerCAmelCase__: int , lowerCAmelCase__: float , lowerCAmelCase__: float ):
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def lowerCAmelCase_ (lowerCAmelCase__: f... | 82 | 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
a : List[str] = logging.... | 353 |
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
@dataclass... | 82 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_ME... | 354 |
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available... | 82 | 0 |
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,
... | 355 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_... | 82 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
a : Union[str, Any] = logging.get_logger(__name__)
... | 356 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
a : Optional[int] = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.self',
'se... | 82 | 0 |
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Union[str, Any] = logging.get_logger(__name__)
a : str =... | 357 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
a : List[str] = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
... | 82 | 0 |
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
a :... | 358 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
a : Dict = datasets.logging.get_logger(__name__)
a : Any = '\\n@InProceedings{moosavi2019minimum,\n ... | 82 | 0 |
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class _a :
A = 42
A = None
A = None
a : int = namedtuple('CoinsDistribResult', 'm... | 359 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin... | 82 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
a : Union[str, Any] = {
"configuration_gpt_bigcode": ["GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTBigCodeConfig"],
}
try:
if not is_tor... | 360 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : Optional[Any] = {
'facebook/encodec_24khz': 'https://huggingface.co/facebo... | 82 | 0 |
from manim import *
class _a ( _lowerCAmelCase ):
def __snake_case (self ) -> str:
UpperCAmelCase_: Tuple = Rectangle(height=0.5, width=0.5 )
UpperCAmelCase_: str = Rectangle(height=0.4_6, width=0.4_6 ).set_str... | 361 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigT... | 82 | 0 |
import socket
def lowerCAmelCase_ ():
"""simple docstring"""
UpperCAmelCase_: Dict = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
UpperCAmelCase_: Optional[int] = socket.gethostname()
UpperCAmelCase_: ... | 362 |
from __future__ import annotations
def lowerCAmelCase_ (lowerCAmelCase__: list[float] ):
"""simple docstring"""
UpperCAmelCase_: Union[str, Any] = 0.00
UpperCAmelCase_: List[str] = 0
for resistor in resistors:
... | 82 | 0 |
import unittest
from transformers import LiltConfig, 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 ModelTest... | 363 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
a : str ... | 82 | 0 |
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