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 |
|---|---|---|---|---|
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
from ...tokenizatio... | 709 | import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class lowerCAmelCase_ ( __lowercase ):
UpperCAmelCase = (... | 71 | 0 |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPipeline,
UNetaD... | 710 | import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCAmelCase_ :
@property
def UpperCamelCase_ ( self : ... | 71 | 0 |
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...test_tokenization_common import... | 711 | def _snake_case ( __snake_case ):
if not isinstance(__snake_case , __snake_case ):
raise TypeError('''Input value must be an \'int\' type''' )
_UpperCamelCase = 0
while number:
position += 1
number >>= 1
return position
if __name__ == "__main_... | 71 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import Bit... | 712 | import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVec... | 71 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {
"configuration_x_clip": [
"XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"XCLIPConfig",
"XCLIPTextConfig",
"XCLIPVisionConfig",
],
... | 713 | from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ... | 71 | 0 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from trans... | 714 | def _snake_case ( __snake_case , __snake_case , __snake_case , __snake_case ):
# Return True if there is node that has not iterated.
_UpperCamelCase = [False] * len(__snake_case )
_UpperCamelCase = []
queue.append(__snake_case )
_UpperCamelCase = ... | 71 | 0 |
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def _snake_case ( __snake_case , __snake_case , __snake_case ):
_UpperCamelCase = 1.5
_UpperCam... | 715 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCAmelCase = {"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechConfig"]}
try:
if not is_to... | 71 | 0 |
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from transformers.utils import WEIGHTS... | 716 | import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils im... | 71 | 0 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
RequestCounter,
... | 717 | def _snake_case ( __snake_case , __snake_case , __snake_case ):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(__snake_case , n - 1 , __snake_case ) * a) % mod
else:
_UpperCamelCase = binary_exponentiation(__s... | 71 | 0 |
def _snake_case ( __snake_case , __snake_case ):
return abs(__snake_case ) if a == 0 else greatest_common_divisor(b % a , __snake_case )
def _snake_case ( __snake_case , __snake_case ):
while y: # --> when y=0 then loop will terminate and return x as final GCD.
... | 718 | from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def _snake_case ( __snake_case , __snake_case , __snake_case = 1 / sqrt(2 ) ):
_UpperCamelCase = tau * frequency / samplerate
_UpperCamelCase = sin(__snake_case )
_UpperCamelCase ... | 71 | 0 |
from __future__ import annotations
def _snake_case ( __snake_case , __snake_case ):
_UpperCamelCase , _UpperCamelCase = position
_UpperCamelCase = [
(y + 1, x + 2),
(y - 1, x + 2),
(y + 1, x - 2),
(y - 1, x - 2),
(y + 2... | 719 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json",
# See all GPTNeoX models at https://huggingface.c... | 71 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json",
# See all AltCLIP model... | 720 | from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=__lowercase ):
UpperCAmelCase = ["keras_nlp"]
def __init__( self : Any , *_A : Dict , **_A : List[str] ):
requires_backends(self , ['''keras_nlp'... | 71 | 0 |
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
AutoencoderKL,
DDIMSch... | 721 | from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutputWithP... | 71 | 0 |
'''simple docstring'''
def _snake_case ( __snake_case = 4000000 ):
_UpperCamelCase = [0, 1]
_UpperCamelCase = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
_UpperCamelCase = 0
... | 700 | from sklearn.metrics import mean_squared_error
import datasets
_lowerCAmelCase = "\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P... | 71 | 0 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 701 | import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_lowerCAmelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the reference code that wi... | 71 | 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"],
"tokenization_gpt_neox_japan... | 702 | from __future__ import annotations
import math
class lowerCAmelCase_ :
def __init__( self : int , _A : int ):
_UpperCamelCase = size
# approximate the overall size of segment tree with given value
_UpperCamelCase = [0 for i in r... | 71 | 0 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, rando... | 703 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {
"configuration_jukebox": [
"JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
"JukeboxConfig",
"JukeboxPriorConfig",
"JukeboxVQVAEConfig",
],
... | 71 | 0 |
from math import factorial
def _snake_case ( __snake_case , __snake_case ):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError('''Please enter positive in... | 704 | import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
f... | 71 | 0 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
f... | 705 | import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowerCAmelCase_ ( enum.Enum ):
U... | 71 | 0 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
import ... | 706 | 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
@require_to... | 71 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import I... | 707 | import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM,
AutoTokenizer,
... | 71 | 0 |
from __future__ import annotations
from typing import Generic, TypeVar
_lowerCAmelCase = TypeVar("T")
class lowerCAmelCase_ ( Generic[T] ):
def __init__( self : Any , _A : T ):
_UpperCamelCase = data
_UpperCamelCase ... | 708 | from __future__ import annotations
import typing
from collections import Counter
def _snake_case ( __snake_case ):
_UpperCamelCase = Counter()
for base in range(1 , max_perimeter + 1 ):
for perpendicular in range(__snake_case , max_perimeter + 1 ):
_Uppe... | 71 | 0 |
_lowerCAmelCase = {
"joule": 1.0,
"kilojoule": 1_000,
"megajoule": 1_000_000,
"gigajoule": 1_000_000_000,
"wattsecond": 1.0,
"watthour": 3_600,
"kilowatthour": 3_600_000,
"newtonmeter": 1.0,
"calorie_nutr": 4_186.8,
"kilocalorie_nutr": 4_186_800.00,
"electronvolt": 1.602... | 709 | import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class lowerCAmelCase_ ( __lowercase ):
UpperCAmelCase = (... | 71 | 0 |
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=__lowercase ):
UpperCAmelCase = ["keras_nlp"]
def __init__( self : Any , *_A : Dict , **_A : List[str] ):
requires_backends(self , ['''keras_nlp'... | 710 | import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCAmelCase_ :
@property
def UpperCamelCase_ ( self : ... | 71 | 0 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModel... | 711 | def _snake_case ( __snake_case ):
if not isinstance(__snake_case , __snake_case ):
raise TypeError('''Input value must be an \'int\' type''' )
_UpperCamelCase = 0
while number:
position += 1
number >>= 1
return position
if __name__ == "__main_... | 71 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase_ ( __lowercase ):
UpperCAmelCase ... | 712 | import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVec... | 71 | 0 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCAmelCase_ :
@property
def UpperCamelCase_ ( ... | 713 | from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ... | 71 | 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 (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
from .... | 714 | def _snake_case ( __snake_case , __snake_case , __snake_case , __snake_case ):
# Return True if there is node that has not iterated.
_UpperCamelCase = [False] * len(__snake_case )
_UpperCamelCase = []
queue.append(__snake_case )
_UpperCamelCase = ... | 71 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase_ ( __lowercase ):
@staticmethod
@abstractmethod
def UpperCamelCase_ ( _A : ArgumentParser ):
raise NotImplementedError()
@abstractmethod
... | 715 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCAmelCase = {"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechConfig"]}
try:
if not is_to... | 71 | 0 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
@require_torch
@require... | 716 | import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils im... | 71 | 0 |
import argparse
import os
import re
_lowerCAmelCase = "src/diffusers"
# Pattern that looks at the indentation in a line.
_lowerCAmelCase = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCAmelCase = re.compile(r"^\s*\"([^\"]+)\":")
# Pattern that matches `_impo... | 717 | def _snake_case ( __snake_case , __snake_case , __snake_case ):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(__snake_case , n - 1 , __snake_case ) * a) % mod
else:
_UpperCamelCase = binary_exponentiation(__s... | 71 | 0 |
def _snake_case ( __snake_case ):
_UpperCamelCase , _UpperCamelCase = [], []
while len(__snake_case ) > 1:
_UpperCamelCase , _UpperCamelCase = min(__snake_case ), max(__snake_case )
start.append(__snake_case )
end.append(__snake_case )
... | 718 | from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def _snake_case ( __snake_case , __snake_case , __snake_case = 1 / sqrt(2 ) ):
_UpperCamelCase = tau * frequency / samplerate
_UpperCamelCase = sin(__snake_case )
_UpperCamelCase ... | 71 | 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 AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER, get_... | 719 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json",
# See all GPTNeoX models at https://huggingface.c... | 71 | 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
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = "▁"
_lowerC... | 720 | from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=__lowercase ):
UpperCAmelCase = ["keras_nlp"]
def __init__( self : Any , *_A : Dict , **_A : List[str] ):
requires_backends(self , ['''keras_nlp'... | 71 | 0 |
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 ImageProcessingSavin... | 721 | from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutputWithP... | 71 | 0 |
'''simple docstring'''
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _snake_case ( __snake_case , __snake_case , __snake_case , __snake_case=1024 ):
_UpperCamelCase , _UpperCamelCase = [], ... | 700 | from sklearn.metrics import mean_squared_error
import datasets
_lowerCAmelCase = "\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P... | 71 | 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,
logging,
)
logging.s... | 701 | import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_lowerCAmelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the reference code that wi... | 71 | 0 |
import re
def _snake_case ( __snake_case ):
_UpperCamelCase = re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__snake_case , __snake_case ):
return match.string == phone
return False
if __name__ == "__main__":
print(indian_phone_valida... | 702 | from __future__ import annotations
import math
class lowerCAmelCase_ :
def __init__( self : int , _A : int ):
_UpperCamelCase = size
# approximate the overall size of segment tree with given value
_UpperCamelCase = [0 for i in r... | 71 | 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-large": "https://huggingface.... | 703 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {
"configuration_jukebox": [
"JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
"JukeboxConfig",
"JukeboxPriorConfig",
"JukeboxVQVAEConfig",
],
... | 71 | 0 |
from math import sqrt
def _snake_case ( __snake_case = 1000000 ):
_UpperCamelCase = 0
_UpperCamelCase = 0
_UpperCamelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , 2 * max_cuboid_size + 1 ):
... | 704 | import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
f... | 71 | 0 |
from collections import namedtuple
import requests
from lxml import html # type: ignore
_lowerCAmelCase = namedtuple("covid_data", "cases deaths recovered")
def _snake_case ( __snake_case = "https://www.worldometers.info/coronavirus/" ):
_UpperCamelCase = '''//div[@class = "maincounter-numb... | 705 | import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowerCAmelCase_ ( enum.Enum ):
U... | 71 | 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
@require_to... | 706 | 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
@require_to... | 71 | 0 |
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import Te... | 707 | import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM,
AutoTokenizer,
... | 71 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, l... | 708 | from __future__ import annotations
import typing
from collections import Counter
def _snake_case ( __snake_case ):
_UpperCamelCase = Counter()
for base in range(1 , max_perimeter + 1 ):
for perpendicular in range(__snake_case , max_perimeter + 1 ):
_Uppe... | 71 | 0 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_lowerCAmelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the reference code that wi... | 709 | import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class lowerCAmelCase_ ( __lowercase ):
UpperCAmelCase = (... | 71 | 0 |
def _snake_case ( __snake_case , __snake_case , __snake_case , __snake_case ):
# Return True if there is node that has not iterated.
_UpperCamelCase = [False] * len(__snake_case )
_UpperCamelCase = []
queue.append(__snake_case )
_UpperCamelCase = ... | 710 | import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCAmelCase_ :
@property
def UpperCamelCase_ ( self : ... | 71 | 0 |
def _snake_case ( __snake_case = 10 ):
if not isinstance(__snake_case , __snake_case ) or n < 0:
raise ValueError('''Invalid input''' )
_UpperCamelCase = 10**n
_UpperCamelCase = 28433 * (pow(2 , 7830457 , __snake_case )) + 1
return str(number % m... | 711 | def _snake_case ( __snake_case ):
if not isinstance(__snake_case , __snake_case ):
raise TypeError('''Input value must be an \'int\' type''' )
_UpperCamelCase = 0
while number:
position += 1
number >>= 1
return position
if __name__ == "__main_... | 71 | 0 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbeddi... | 712 | import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVec... | 71 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
_lowerCAmelCase = {"tokenization_byt5": ["ByT5Tokenizer"]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
_lowerCAmelCase = _LazyModule(__name__, globals()["__file__"], _import_... | 713 | from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ... | 71 | 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 Accel... | 714 | def _snake_case ( __snake_case , __snake_case , __snake_case , __snake_case ):
# Return True if there is node that has not iterated.
_UpperCamelCase = [False] * len(__snake_case )
_UpperCamelCase = []
queue.append(__snake_case )
_UpperCamelCase = ... | 71 | 0 |
def _snake_case ( __snake_case ):
if not isinstance(__snake_case , __snake_case ):
raise TypeError('''Input value must be an \'int\' type''' )
_UpperCamelCase = 0
while number:
position += 1
number >>= 1
return position
if __name__ == "__main_... | 715 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCAmelCase = {"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechConfig"]}
try:
if not is_to... | 71 | 0 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def _snake_case ( __snake_case ):
_UpperCamelCase = ... | 716 | import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils im... | 71 | 0 |
# Copyright 2021 The HuggingFace 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 required by applicabl... | 717 | def _snake_case ( __snake_case , __snake_case , __snake_case ):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(__snake_case , n - 1 , __snake_case ) * a) % mod
else:
_UpperCamelCase = binary_exponentiation(__s... | 71 | 0 |
def _snake_case ( __snake_case , __snake_case , __snake_case ):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(__snake_case ) )
def _snake_case ( __snake_case , __snake_case , __snake_case , __snak... | 718 | from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def _snake_case ( __snake_case , __snake_case , __snake_case = 1 / sqrt(2 ) ):
_UpperCamelCase = tau * frequency / samplerate
_UpperCamelCase = sin(__snake_case )
_UpperCamelCase ... | 71 | 0 |
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
_lowerCAmelCase = HUGGINGFACE_HUB_CACHE
_lowerCAmelCase = "config.json"
_lowerCAmelCase = "diffusion_pytorch_model.bin"
_lowerCAmelCase = "diffusion_flax_model.msgpack"
_lowerCAmelCase = "model.... | 719 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json",
# See all GPTNeoX models at https://huggingface.c... | 71 | 0 |
from __future__ import annotations
import math
def _snake_case ( __snake_case ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
... | 720 | from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=__lowercase ):
UpperCAmelCase = ["keras_nlp"]
def __init__( self : Any , *_A : Dict , **_A : List[str] ):
requires_backends(self , ['''keras_nlp'... | 71 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"google/pix2struct-textcaps-base": (
"https://huggingface.co/google/pix2struct-textcaps-base/resolve/main... | 721 | from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutputWithP... | 71 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase = {"configuration_plbart": ["PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP", "PLB... | 700 | from sklearn.metrics import mean_squared_error
import datasets
_lowerCAmelCase = "\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Grisel, O. and Blondel, M. and Prettenhofer, P... | 71 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {
"configuration_jukebox": [
"JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
"JukeboxConfig",
"JukeboxPriorConfig",
"JukeboxVQVAEConfig",
... | 701 | import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_lowerCAmelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the reference code that wi... | 71 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def _snake_case ( __snake_case , __snake_case=1000 ):
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
_UpperCamelCase = n - 1
_UpperCamelCase = 0
while d % 2... | 702 | from __future__ import annotations
import math
class lowerCAmelCase_ :
def __init__( self : int , _A : int ):
_UpperCamelCase = size
# approximate the overall size of segment tree with given value
_UpperCamelCase = [0 for i in r... | 71 | 0 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import ... | 703 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {
"configuration_jukebox": [
"JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
"JukeboxConfig",
"JukeboxPriorConfig",
"JukeboxVQVAEConfig",
],
... | 71 | 0 |
from __future__ import annotations
class lowerCAmelCase_ :
def __init__( self : Optional[Any] , _A : str , _A : str ):
_UpperCamelCase , _UpperCamelCase = text, pattern
_UpperCamelCase , _UpperCamelCase = len(_A ), le... | 704 | import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
f... | 71 | 0 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ... | 705 | import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowerCAmelCase_ ( enum.Enum ):
U... | 71 | 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": "spiece.model"}
_lowerC... | 706 | 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
@require_to... | 71 | 0 |
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property
from ...test_tokeni... | 707 | import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM,
AutoTokenizer,
... | 71 | 0 |
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked befor... | 708 | from __future__ import annotations
import typing
from collections import Counter
def _snake_case ( __snake_case ):
_UpperCamelCase = Counter()
for base in range(1 , max_perimeter + 1 ):
for perpendicular in range(__snake_case , max_perimeter + 1 ):
_Uppe... | 71 | 0 |
import re
def _snake_case ( __snake_case ):
if len(re.findall('''[ATCG]''' , __snake_case ) ) != len(__snake_case ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '''TAGC''' ) )
if __name__ == "__main__":
import doctest
... | 709 | import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class lowerCAmelCase_ ( __lowercase ):
UpperCAmelCase = (... | 71 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {"configuration_mmbt": ["MMBTConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pas... | 710 | import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCAmelCase_ :
@property
def UpperCamelCase_ ( self : ... | 71 | 0 |
def _snake_case ( __snake_case , __snake_case = False ):
if not isinstance(__snake_case , __snake_case ):
_UpperCamelCase = f"""Expected string as input, found {type(__snake_case )}"""
raise ValueError(__snake_case )
if not isinstance(__snake_case , __... | 711 | def _snake_case ( __snake_case ):
if not isinstance(__snake_case , __snake_case ):
raise TypeError('''Input value must be an \'int\' type''' )
_UpperCamelCase = 0
while number:
position += 1
number >>= 1
return position
if __name__ == "__main_... | 71 | 0 |
def _snake_case ( __snake_case ):
def merge(__snake_case , __snake_case ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
... | 712 | import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVec... | 71 | 0 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
_lowerCAmelCase = "\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2... | 713 | from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ... | 71 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json",
# See all GPTNeoX models at https://huggingface.c... | 714 | def _snake_case ( __snake_case , __snake_case , __snake_case , __snake_case ):
# Return True if there is node that has not iterated.
_UpperCamelCase = [False] * len(__snake_case )
_UpperCamelCase = []
queue.append(__snake_case )
_UpperCamelCase = ... | 71 | 0 |
# Copyright 2023 The HuggingFace 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 required by applicabl... | 715 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCAmelCase = {"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechConfig"]}
try:
if not is_to... | 71 | 0 |
from collections.abc import Callable
class lowerCAmelCase_ :
def __init__( self : Optional[int] , _A : Callable | None = None ):
# Stores actual heap items.
_UpperCamelCase = []
# Stores indexes of each item for supporting updates and d... | 716 | import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils im... | 71 | 0 |
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_modeling_common imp... | 717 | def _snake_case ( __snake_case , __snake_case , __snake_case ):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(__snake_case , n - 1 , __snake_case ) * a) % mod
else:
_UpperCamelCase = binary_exponentiation(__s... | 71 | 0 |
import math
def _snake_case ( __snake_case = 100 ):
_UpperCamelCase = sum(i * i for i in range(1 , n + 1 ) )
_UpperCamelCase = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return square_of_sum - sum_of_squares
if __name__ == "__main__":
print(f'{solution... | 718 | from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def _snake_case ( __snake_case , __snake_case , __snake_case = 1 / sqrt(2 ) ):
_UpperCamelCase = tau * frequency / samplerate
_UpperCamelCase = sin(__snake_case )
_UpperCamelCase ... | 71 | 0 |
def _snake_case ( __snake_case , __snake_case , __snake_case , __snake_case , __snake_case , __snake_case ):
if index == r:
for j in range(__snake_case ):
print(data[j] , end=''' ''' )
print(''' ''' )
return
... | 719 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json",
# See all GPTNeoX models at https://huggingface.c... | 71 | 0 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOutput
from tran... | 720 | from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=__lowercase ):
UpperCAmelCase = ["keras_nlp"]
def __init__( self : Any , *_A : Dict , **_A : List[str] ):
requires_backends(self , ['''keras_nlp'... | 71 | 0 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentParser, TrainingArguments
fr... | 721 | from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutputWithP... | 71 | 0 |
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_flax_available():
i... | 72 |
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttention, ImageClassifierOutp... | 72 | 1 |
__SCREAMING_SNAKE_CASE : Optional[Any] ={
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''': '''flax>... | 72 |
from numpy import exp, pi, sqrt
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = 0.0 ,lowerCAmelCase__ = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 72 | 1 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassif... | 72 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class A_ :
_A :int
_A :int
class A_ :
def __init__( self : List[str] , snake_case__ : int ... | 72 | 1 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__SCREAMING_SNAKE_CASE : List[str] =logging.get_logger(__name__)
__SCREAMI... | 72 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : str =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : str ={
'''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2vec-a... | 72 | 1 |
__SCREAMING_SNAKE_CASE : List[Any] ='''ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'''
def UpperCamelCase__ ( lowerCAmelCase__ ):
# Make sure the supplied data is a bytes-like object
if not isinstance(lowerCAmelCase__ ,lowerCAmelCase__ ):
... | 72 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = [
"""decoder.version""",
"""decoder.output_projection.weight""",
"""_float... | 72 | 1 |
import copy
import re
class A_ :
_A :Optional[int] = '''hp'''
_A :Union[str, Any] = {}
_A :List[Any] = None
@classmethod
def SCREAMING_SNAKE_CASE__ ( cls : Optional[Any] , snake_case__ : Optional... | 72 |
from __future__ import annotations
import bisect
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ = 0 ,lowerCAmelCase__ = -1 ):
if hi < 0:
lowercase = len(lowerCAmelCase__ )
while lo < hi:
lowercase = lo + (hi - lo) //... | 72 | 1 |
from ....utils import logging
__SCREAMING_SNAKE_CASE : List[str] =logging.get_logger(__name__)
class A_ ( __a ):
def __init__( self : List[Any] , snake_case__ : str , snake_case__ : Union[str, Any]=None , snake_case... | 72 |
# 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 UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmel... | 72 | 1 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__SCREAMING_SNAKE_CASE : str =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Dict ={
'''nielsr/canine-s''': 2_048,
}
# U... | 72 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A_ ( __a ):
_A ... | 72 | 1 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
__SCREAMING_SNAKE_CASE : Tuple =version.parse(importlib_metadata.version('''nltk'''))
if NLTK_VERSION >= version.Version('''3.6.4'''):
from nltk import wo... | 72 |
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 ...f... | 72 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Tuple ={
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ... | 72 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
... | 72 | 1 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
__SCREAMING_SNAKE_CASE : Dict =logging.getLogger(__name__)
@dataclass
class A_ ( __a ):
_A :Optional... | 72 |
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
__SCREAMING_SNAKE_CASE : List[Any] ='''.'''
if __name__ == "__main__":
__SCREAMING_SNAKE_CASE : List[str] =os.... | 72 | 1 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils import R... | 72 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Tuple ={
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ... | 72 | 1 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPMSche... | 72 |
import argparse
import os
import re
import packaging.version
__SCREAMING_SNAKE_CASE : Optional[int] ='''examples/'''
__SCREAMING_SNAKE_CASE : Any ={
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")... | 72 | 1 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" ,[
["""full:README.md""", """dataset_infos.json"""],
["""empty:README.md""", """dataset_infos.json"""... | 72 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Union[str, Any] =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Tuple ={
'''google/pix2struct-textcaps-b... | 72 | 1 |
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ):
if principal <= 0:
raise Exception("""Principal borrowed must be > 0""" )
if rate_per_annum < 0:
raise Exception("""Rate of interest must be >= 0""" )
if years_to_repay <= 0 or not isi... | 72 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils import R... | 72 | 1 |
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ):
return abs(lowerCAmelCase__ ) if a == 0 else greatest_common_divisor(b % a ,lowerCAmelCase__ )
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ):
while y: # --> when y=0 then loop will terminate... | 72 |
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,
FEATUR... | 72 | 1 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class A_ ( __a , __a ):
@register_to_config
d... | 72 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" ,[
["""full:README.md""", """dataset_infos.json"""],
["""empty:README.md""", """dataset_infos.json"""... | 72 | 1 |
# 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 required b... | 72 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = args.pruning_method
lowercase = args.threshold
lowercase = args.model_na... | 72 | 1 |
from numpy import exp, pi, sqrt
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = 0.0 ,lowerCAmelCase__ = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 72 |
# using dfs for finding eulerian path traversal
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__=None ):
lowercase = (path or []) + [u]
for v in graph[u]:
if visited_edge[u][v] is False:
lowercase , l... | 72 | 1 |
from __future__ import annotations
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = 0.00
lowercase = 0
for resistor in resistors:
if resistor <= 0:
lowercase = f"""Resistor at index {index} has a negative or zero value!"""
rais... | 72 |
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
f... | 72 | 1 |
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class A_ :
_A :List[str]
_A :Optional[str] = None
# Automaticall... | 72 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class A_ :
def __init__( self : List[str] , snake_case__ : Union[str, Any] ):
lowercase = data
lowercase = [0X6_7_4_5_2_3_0_1, 0Xe_f_c_d_a_b... | 72 | 1 |
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