code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...... | 573 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase = logging.getLogger(__name__)
class lowercase__ ( A ):
'''simple docstring'''
_UpperCAmelCase = '''maske... | 573 | 1 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Tokenize... | 701 | """simple docstring"""
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class snake_case__ :
_snake_case : torch.Tensor # [batch_size x 3]
_snake_case : torch.Tensor # [batch_size x 3]
_snake_case : torch.Tensor # [batch_size... | 67 | 0 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
__magic_name__ : Tuple = 0
while len(UpperCamelCase__ ) > 1:
__magic_name__ : List[Any] = 0
# Con... | 436 |
'''simple docstring'''
class UpperCAmelCase :
def __init__( self : List[str] , __snake_case : str ) -> Union[str, Any]:
_lowerCAmelCase = val
_lowerCAmelCase = None
_lowerCAmelCase ... | 207 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
__lowerCAmelCase : Any = {
'''microsoft/wavlm-base''': '''https://huggingface.co/microsoft/wavlm-base/resolve... | 716 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_c... | 662 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Dict = logging.get_logger(__name__)
__lowerCAmelCase : str = {
"facebook/wav2vec2-base-960h": "https://huggingface.co/... | 644 | """simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCAmelCase : Optional[int] = None
try:
import msvcrt
except ImportError:
__lowerCAmelCase : List[Any] = None
try:
import fcntl
except Impor... | 644 | 1 |
import math
def lowercase_ ( A__ , A__ ) -> float:
"""simple docstring"""
return math.pow(A__ , 2 ) - a
def lowercase_ ( A__ ) -> float:
"""simple docstring"""
return 2 * x
def lowercase_ ( A__ ) -> float... | 294 |
_A = 0 # The first color of the flag.
_A = 1 # The second color of the flag.
_A = 2 # The third color of the flag.
_A = (red, white, blue)
def lowercase_ ( A__ ) -> list:
"""simple docstring"""
if not sequence:
... | 294 | 1 |
'''simple docstring'''
def a__ ( _SCREAMING_SNAKE_CASE : int ) -> int:
"""simple docstring"""
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
raise TypeError("Input value must be an 'int' type" )
UpperCAmelCase_ : Union[str,... | 71 | '''simple docstring'''
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def _lowercase ( lowerCamelCase__ ) -> int:
"""simple docstring"""
return DownloadCommand(args.model , args.cache_dir , args.force , ... | 168 | 0 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : str =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Any ={
'''facebook/encodec_24khz''': ''... | 715 |
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 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, D... | 413 |
class _snake_case :
def __init__( self : Optional[int], __lowercase : int ):
lowercase__ = size
lowercase__ = [0] * size
lowercase__ = [0] * size
@staticmethod
def A__ ( __lowercase : ... | 413 | 1 |
'''simple docstring'''
def _lowerCAmelCase (_lowercase , _lowercase ):
"""simple docstring"""
a__ = len(__UpperCamelCase )
a__ = len(__UpperCamelCase )
a__ = (
first_str_length if first_str_length > second_str_length else secon... | 708 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase_ : Optional[int] = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_... | 394 | 0 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
a = logging.get_logger(__name__)
a = {'''vocab_file''': '''vocab.txt'''... | 7 | '''simple docstring'''
_lowerCAmelCase :Union[str, Any] = {
"""meter""": """m""",
"""kilometer""": """km""",
"""megametre""": """Mm""",
"""gigametre""": """Gm""",
"""terametre""": """Tm""",
"""petametre""": """Pm""",
"""exametre""": """Em""",
"""zettametre""":... | 251 | 0 |
def __lowerCamelCase ( A__ : float , A__ : float ) -> float:
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 * mass * abs(A__ ) * abs(A__ )
if __name__ == "__main__":
import doctest
doctest.testmod(verbose=True)
... | 704 |
import argparse
snake_case__ : Dict = 'docs/source/_static/js/custom.js'
def __lowerCamelCase ( A__ : List[str] ) -> int:
with open(A__ , encoding="""utf-8""" , newline="""\n""" ) as f:
lowerCamelCase_ : List[Any] = f.readlines()
lowerCamelCase_ ... | 171 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor,... | 532 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"facebook/s2t-wav2vec2-large-en-de": (
"https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolv... | 532 | 1 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class UpperCAmelCase__ ( unittest.TestCase ):
"""simp... | 715 |
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modelin... | 472 | 0 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def lowerCamelCase__ ( A_ , A_ ):
# For applying gaussian function for each element in matrix.
UpperCAmelCase_ = math.sqrt(__UpperCamelCase )
UpperCAmelCase_ = 1 / (sigma... | 660 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def UpperCAmelCase_ ( ):
SCREAMING_SNAKE_CASE__ =ArgumentParser("""Diffusers CLI tool""", usage="""diffusers-cli <command> [<args>]""" )
SCREAMING_SNAKE_CASE__ =parser.add_subparsers(help="... | 151 | 0 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_snake_case : List[str] = {
'facebook/mask2former-swin-small-coco-instance': (
'https://huggingface.co/... | 214 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def _A ( __snake_case :int ) -> Optional[int]:
"""simple docstring"""
if (
(cp >= 0x4E_00 and cp <= 0x9F_FF)
or (cp >= 0x34_0... | 214 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase_ = {
'''configuration_efficientformer''': [
'''EFFICIENTFORMER_PRET... | 95 |
"""simple docstring"""
def __A ( a_ :Tuple , a_ :Union[str, Any] , a_ :int=False) -> List[str]:
if isinstance(a_ , a_) and isinstance(a_ , a_):
__a : List[str] = len(set_a.intersection(a_))
if alternative... | 52 | 0 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import ... | 721 |
"""simple docstring"""
import os
import unittest
from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTest... | 109 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
a_ :List[str] = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'SwiftFormerOnnxConfig',
... | 35 |
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenizati... | 146 | 0 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__lowerCamelCase : Tuple = pytest.mark.integration
@pytest.m... | 721 |
def A__ ( _a : Optional[Any] , _a : Tuple , _a : List[str]=False ):
'''simple docstring'''
if isinstance(_a , _a ) and isinstance(_a , _a ):
snake_case__ : int =len(set_a.intersection(_a ) )
if alternative_union:
snake_case__ : int ... | 448 | 0 |
def lowerCamelCase_ ( lowerCamelCase__ ):
if not isinstance(lowerCamelCase__ , lowerCamelCase__ ):
lowerCamelCase_ = F'Input value of [number={number}] must be an integer'
raise TypeError(lowerCamelCase__ )
if number < 1:
lowerCame... | 463 |
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 im... | 463 | 1 |
'''simple docstring'''
from __future__ import annotations
__lowerCAmelCase = [-1_0, -5, 0, 5, 5.1, 1_1, 1_3, 2_1, 3, 4, -2_1, -1_0, -5, -1, 0]
__lowerCAmelCase = [-5, 0, 5, 5.1, 1_1, 1_3, 2_1, -1, 4, -1, -1_0, -5, -1, 0, -1]
def UpperCAmelCase_ (__a : list[float] ):
... | 708 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
__lowerCAm... | 319 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cache... | 42 |
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def UpperCAmelCase_ ( _A , _A , _A , _A , _A = None , _A = None , _A = None , ):
'''simple docstring'''
... | 493 | 0 |
_a: List[Any] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_0000)]
def __lowerCAmelCase ( A ):
UpperCAmelCase_ = 0
while number:
# Increased Speed Slightly by checking every 5 digits together.
sum_of_digits_squared += DIGITS_SQUARED[number % 100000]... | 268 |
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTes... | 268 | 1 |
'''simple docstring'''
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()
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCa... | 229 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transfo... | 2 | 0 |
"""simple docstring"""
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from dat... | 549 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils ... | 549 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load... | 69 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase__ : Optional[int] =0B1011_0011_1110_1100_1001_0000_0111_... | 101 | 0 |
'''simple docstring'''
import operator as op
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : Union[str, Any] = []
_snake_case : Dict = lambda lowerCAmelCase_ , lowerCAmelCase_ : int(x / y ) # noqa: E731 integer divisio... | 703 |
'''simple docstring'''
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_t... | 47 | 0 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE = 1000 ) -> int:
SCREAMING_SNAKE_CASE_ : Union[str, Any] = 3
SCREAMING_SNAKE_CASE_ : Optional[Any] = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
return resu... | 345 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataL... | 345 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class UpperCamelCa... | 317 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Optional[int] = {
"""configuration_timesformer""": ["""TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Timesforme... | 317 | 1 |
'''simple docstring'''
__magic_name__ : Tuple = """Alexander Joslin"""
import operator as op
from .stack import Stack
def snake_case_ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
_snake_case = {'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 672 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.co... | 638 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase_ : List[Any] = {
"""configuration_efficientformer""": [
... | 204 | '''simple docstring'''
import sys
from collections import defaultdict
class SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Tuple ) ->Optional[int]:
'''simple docstring'''
_UpperCame... | 204 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'facebook/wav2vec2-base-960h': 'https://huggingface.co/facebook/wav2vec2-base-960h/resolv... | 592 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
def a (self : Union[str, Any] ):
"""simple docstring... | 592 | 1 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
def _UpperCamelCase (a__ :int , ... | 548 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _UpperCamelCase (a__ :str , a__ :complex , a__ :str = "x" , a__ :float = 10**-10 , a__ :int = 1 , ):
"""simple docstring"""
UpperCamelCase__ = sym... | 548 | 1 |
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class A_ ( unittest.TestCase ):
... | 303 |
def __a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
'''simple docstring'''
__UpperCAmelCase = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def __a ( SC... | 303 | 1 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
UpperCAmelCase_ : Union[str, Any] = version.parse(version.parse(torch.__version__).base_version) < version.parse('''1.11''')
def SCREAMIN... | 716 |
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 FlaxTimestepEmbedding,... | 590 | 0 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
lowerCAmelCase_ = '''__DUMMY_TRANSFORMERS_USER__'''
lowerCAmelCase_ = '''Dummy User'''
lowerCAmelCase_ = '''hf_hZEmn... | 60 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaagf, RegNetYaaa... | 631 | 0 |
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
__UpperCAmelCase : Union[str, Any] = "scheduler_config.json"
class _snake_case ( _A ):... | 700 |
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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
ImageInput,
... | 57 | 0 |
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ... | 70 |
def _SCREAMING_SNAKE_CASE ( lowercase : str , lowercase : str ):
'''simple docstring'''
if len(lowercase ) != len(lowercase ):
raise ValueError('String lengths must match!' )
lowerCamelCase_ = 0
for chara, cha... | 70 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCAmelCase__ : str, UpperCAmelCase__ : int ) ->list:
A__ : Dict = word.split()
def justify(UpperCAmelCase__ : list, UpperCAmelCase__ : int, UpperCAmelCase__ : ... | 498 |
"""simple docstring"""
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _lowerCAmelCase ( UpperCAmelCase__ : List[str] ) ->str:
A__ : Tu... | 498 | 1 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_specific_par... | 105 |
import os
import sys
import unittest
UpperCamelCase__ : Optional[Any] = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dumm... | 105 | 1 |
"""simple docstring"""
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation... | 701 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowerCAmelCase : str = logging.get_logger(__name__)
__lowerCA... | 21 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transformers.testing_utils import DUMM... | 175 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
"""t5-small""": """https://huggingface.co/t5-small/resolve/main/config.json""",
"""... | 175 | 1 |
from math import sqrt
def A_ ( snake_case : Tuple = 1000000 ) -> List[Any]:
'''simple docstring'''
__UpperCamelCase = 0
__UpperCamelCase = 0
__UpperCamelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
... | 714 |
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForImageClassification,
MobileViTVaForSe... | 451 | 0 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
__snake_case :int ={
'config': [
'EXTERNAL_DATA_FORMAT_SIZE_LIMIT',
'OnnxConfig',
'OnnxConfigWithPast',
'OnnxSeq2SeqConfigWithPast',
'PatchingSpec',
],
'convert': ['export', 'validate... | 106 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCAmelCase__ ( _lowerCamelCase ):
def __init__( self : int , __UpperCamelCase : Callable... | 106 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : str , _snake_case : list[str] ) -> int:
'''simple docstring'''
_A = ''
for word_or_phrase in separated:
if not isinstance(snake_case__ , sna... | 700 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/de... | 505 | 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 transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.set_... | 20 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a nice... | 20 | 1 |
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,
TFBaseModelOutput... | 701 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Dict = logging.get_logger(__name__)
UpperCamelCase__ : Optional[int] = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
... | 685 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( a_: float, a_: float, a_: float, a_: float, a_: float, ):
_UpperCAmelCase : Any = [redshift, radiation_density, matter_density, dark_energy]
if any(p < 0 for p in parameters ):
raise ValueError("All input paramet... | 494 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json',
}
class A__ ... | 494 | 1 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PAC... | 241 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
__A =logging.get_logger(__name__)
__A ={name: getattr(transformers, name + "Fast") for name in SLOW_TO_FAST_CONVE... | 241 | 1 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_available, ... | 511 |
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
lowerCAmelCase : Optional[int] = argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for Transfer Learned'... | 511 | 1 |
"""simple docstring"""
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 ImageProce... | 492 |
"""simple docstring"""
from pathlib import Path
import fire
def _snake_case ( lowercase__ , lowercase__ , lowercase__ ):
_lowerCamelCase : int = Path(lowercase__ )
_lowerCamelCase : List[Any] = Path(lowercase__ )
... | 492 | 1 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_SCREAMING_SNAKE_CASE : List[str] = logging.get_logger(__name__)
# TODO: upload to AWS
_SCREAMING_SNAKE_CASE : Any = {
"yjernite/retribert-base-uncased": (
"http... | 400 |
'''simple docstring'''
import os
import pytest
from attr import dataclass
_SCREAMING_SNAKE_CASE : Dict = "us-east-1" # defaults region
@dataclass
class _snake_case :
lowerCAmelCase_ : str
lowerCAmelCase_ : Tuple = "arn:aws:iam::558105141721:role/sagemaker_execut... | 400 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ : List[str] ... | 716 |
'''simple docstring'''
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 (
SegformerConfig,
SegformerForImageClassification,
SegformerFo... | 233 | 0 |
'''simple docstring'''
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
UpperCamelCase : str = [
... | 50 |
'''simple docstring'''
def A__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 50 | 1 |
"""simple docstring"""
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 ( lowerCAmelCase__ ):
SCREAM... | 718 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def SCREAMING_SNAKE_CASE_ ( )-> int:
_lowerCamelCase = {
'repo_name': ['test_repo1', 'test_repo2', 'test_repo3'... | 222 | 0 |
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermarker
from diffusers.utils.testin... | 74 |
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
cached_file,
get_fi... | 579 | 0 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version(">=", FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed.checkpoint.default_planner ... | 345 |
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class _lowerCamelCase (lowerCamelCase ):
... | 345 | 1 |
__lowerCamelCase : int = tuple[float, float, float]
__lowerCamelCase : int = tuple[float, float, float]
def _snake_case ( lowerCAmelCase : Pointad , lowerCAmelCase : Pointad ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any =... | 216 | from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _snake_case ( lowerCAmelCase : str , lowerCAmelCase : complex , lowerCAmelCase : str = "x" , lowerCAmelCase : float = 1_0**-1_0 , lowerCAmelCase : int = 1 , ):
"""simple do... | 216 | 1 |
'''simple docstring'''
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
UpperCAmelCase_ : Optional[Any] = datasets.utils.logging.get_logger(__name__)
class a ( folder_based_builder.Folder... | 700 |
'''simple docstring'''
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def UpperCAmelCase_ ( A , A = True , A = math.inf , A = -math.inf , A = math.inf , A = -math.inf , A = False , A = 1_0_0 , A = 0.01 , A = 1 , ):
'''simple docst... | 424 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer
... | 651 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.utils i... | 665 | 0 |
"""simple docstring"""
def UpperCamelCase_ ( SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_ ):
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
SCREAMING_SNAKE_CASE = str(bin(SCREAMING_SNAKE_CASE_ ) )[2:] # remove the le... | 406 |
"""simple docstring"""
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text impo... | 406 | 1 |
def _lowerCamelCase ( SCREAMING_SNAKE_CASE = 1000 ):
'''simple docstring'''
A_ = -1
A_ = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
A_ = (n * n -... | 203 |
from PIL import Image
def lowerCamelCase__ ( __A :Image ):
"""simple docstring"""
__snake_case , __snake_case = image.size
__snake_case = 0
__snake_case = image.load()
for i in range(__A ):
... | 268 | 0 |
from math import factorial, radians
def A__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = 18 , SCREAMING_SNAKE_CASE__ = 10) -> float:
__snake_case: Union[str, Any] = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Converting from de... | 707 |
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def A__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__) ... | 155 | 0 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class _a :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase=0.2 , _UpperC... | 23 |
# 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
#
# Unl... | 606 | 0 |
'''simple docstring'''
import math
def lowerCamelCase_ ( SCREAMING_SNAKE_CASE__ : int ) -> bool:
UpperCAmelCase_ : Optional[int] = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(SCREAMING_SNAKE_CASE__ )
... | 644 |
'''simple docstring'''
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 ...te... | 644 | 1 |
def lowerCAmelCase__(__snake_case ,__snake_case ) -> str:
'''simple docstring'''
lowerCamelCase__ = len(__snake_case )
lowerCamelCase__ = len(__snake_case )
lowerCamelCase__ = (
first_str_length if first_str_length > sec... | 481 |
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''': 10, '''max_num_jobs''': 1}, [range(10 ... | 481 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ : Union[str, Any] = logging.get_logger(__name__)
UpperCamelCase_ : Any = {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class __l... | 702 |
"""simple docstring"""
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from tra... | 482 | 0 |
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler... | 2 |
from torch import nn
class __lowerCAmelCase ( nn.Module ):
"""simple docstring"""
def __init__( self : Optional[int] , _snake_case : List[Any] , _snake_case : Tuple ):
super().__init__()
__lower... | 509 | 0 |
"""simple docstring"""
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,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
res... | 22 |
"""simple docstring"""
def _snake_case ( snake_case__ : list , snake_case__ : list , snake_case__ : int ):
A = len(snake_case__ )
A = [[0] * n for i in range(snake_case__ )]
for i in range(snake_case__ ):
A = y_points[i]
for i... | 22 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__lowerCAmelCase : List[Any] ={"""processing_wav2vec2_with_lm""": ["""Wav2Vec2ProcessorWithLM"""]}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
els... | 359 | """simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
__lowerCAmelCase : int =pd.read_csv("""sample_data... | 359 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {'vocab_file': 'sentencepie... | 701 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError('To use the rich extension, install rich with `pip install rich`')
| 515 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ={
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
... | 617 |
'''simple docstring'''
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_availa... | 399 | 0 |
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def snake_case ( UpperCAmelCase : List[Any] ):
A = [
'encoder.version',
'decoder.version',
'model.encoder.version',
... | 721 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class UpperCamelCase ( unittest.TestCase ):
"""simple docstring"""
snake_case = JukeboxTokenizer
snake_case = {
"artist": "Zac Brown Band",
"genres": "Coun... | 110 | 0 |
"""simple docstring"""
def A_ ( __lowercase ):
if num <= 0:
raise ValueError('Input must be a positive integer' )
UpperCamelCase_ : List[str] =[True] * (num + 1)
UpperCamelCase_ : Dict =2
while p * p <= num:
if primes[p]:
for i in range(p * p , num + 1 , lo... | 357 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""google/pix2struct-textcaps-base""": (
"""https://huggingface.co/google/pix2struct-textcaps-base/reso... | 377 | 0 |
import os
from datetime import datetime as dt
from github import Github
_A = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
]
def lowercase_ ... | 703 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
im... | 294 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
DiffusionPipeline,
UnCLIP... | 62 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase : Tuple ={
"""configuration_mobilenet_v2""": [
"""MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""MobileNetV2Config""",
"... | 113 | 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 applica... | 673 |
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,
DDIMS... | 673 | 1 |
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs("""hub/hopper-medium-v2/unet/hor32""", exist_ok=True)
os.makedirs("""hub/hopper-medium-v2/unet/hor128""", exist_ok=True)
os.makedirs("""hub/hopper-medium-v2/value_function""", exist_ok=True)
def __lowerCAmelCase ( A )... | 162 |
'''simple docstring'''
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGe... | 689 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase__ = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}
try:
... | 639 |
import qiskit
def A ( _UpperCAmelCase : int , _UpperCAmelCase : int ) -> qiskit.result.counts.Counts:
'''simple docstring'''
_UpperCAmelCase = qiskit.Aer.get_backend('aer_simulator' )
# Create a Quantum Circuit acting on the q regis... | 639 | 1 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class __snake_case (_a ):
lowerCAmelCase__ = ""
lowerCAmelCase__ = (
None # protocol passed in prefix to the url. ex... | 429 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=_a )
class __snake_case (_a ):
lowerCAmelCase__ = field(default="audio-classification" , metad... | 429 | 1 |
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoM... | 73 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase__ ( __lowerCamelCase ):
"""simple docstring"""
__UpperCAmelCase : Dict = '''ClapFeatureExtractor'''
__UpperCAmelCase : ... | 73 | 1 |
from copy import deepcopy
class lowercase_ :
'''simple docstring'''
def __init__( self : int , __UpperCAmelCase : list[int] | None = None , __UpperCAmelCase : int | None = None ) ->Any:
"""simple docstring"""
... | 117 |
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __magic_name__ (snake_case_ ):
'''simple docstring'''
__lowercase : List[str] = ['image_processor', 'tokenizer']
__lowercase :... | 33 | 0 |
'''simple docstring'''
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase ):
if discount_rate < 0:
raise ValueError("Discount rate cannot be negative" )
if not cash_flows:
raise ValueError("Cash flows list cannot be empty" )
_UpperCAmelCase : Optional[int] ... | 719 |
'''simple docstring'''
import os
def __lowerCAmelCase ():
_UpperCAmelCase : List[Any] = os.path.join(os.path.dirname(__lowerCAmelCase ) , "num.txt" )
with open(__lowerCAmelCase ) as file_hand:
return str(sum(int(__lowerCAmelCase ) for line in file_hand... | 40 | 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""... | 569 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate... | 569 | 1 |
'''simple docstring'''
import sys
__snake_case = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557'''
'''6689... | 709 |
'''simple docstring'''
class lowercase :
"""simple docstring"""
def __init__( self , UpperCamelCase_ = "" , UpperCamelCase_ = False ):
'''simple docstring'''
UpperCamelCase__ :dict[str, RadixNode] = {}
# A node will be a leaf if the tree ... | 280 | 0 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import torch.... | 27 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
a_ ... | 296 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( a_: Any ):
_UpperCAmelCase : Optional[int] = len(a_ )
for i in range(length - 1 ):
_UpperCAmelCase : List[str] = i
for k in range(i + 1, a_ ):
if collection[k] < c... | 709 | '''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
... | 257 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ : str = {
'''configuration_git''': ['''GIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GitConfig''', '''GitVisionConfig'''],
... | 255 |
"""simple docstring"""
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
UpperCAmelCase_ : Any = logging.get_logger(__name__)
... | 255 | 1 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
lowercase =loggin... | 721 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
lowercase =[int(0.5 * n * (n + 1)) for n in range(1, 101)]
def lowerCamelCase__ ( ):
'''simple docstring'''
_UpperCAmelCase : int =os.path.dirname(os.path.realpath(__low... | 331 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchm... | 123 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
lowercase__ :Optional[i... | 522 | 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_available() a... | 365 |
import numpy as np
from PIL import Image
def _UpperCamelCase ( UpperCamelCase_ : np.ndarray , UpperCamelCase_ : int , UpperCamelCase_ : int ) -> np.ndarray:
"""simple docstring"""
lowerCAmelCase__ = np.array(UpperCamel... | 365 | 1 |
'''simple docstring'''
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
... | 585 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCAmelCase = {
'configuration_wav2vec2': ['WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Wav2Vec2Co... | 585 | 1 |
"""simple docstring"""
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self , snake_case_ = "" , snake_case_ = False ) -> None:
# Mapping from the first character of the prefix of the node
__lowerCAmelC... | 573 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requi... | 573 | 1 |
"""simple docstring"""
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark... | 174 |
"""simple docstring"""
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {name: getattr(transformers,... | 174 | 1 |
'''simple docstring'''
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... | 708 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def __UpperCAmelCase ( A : np.ndarray ) -> np.ndarray:
UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ : int = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
re... | 216 | 0 |
'''simple docstring'''
def __snake_case ( lowercase : Optional[Any] ):
snake_case_ = len(lowercase )
snake_case_ = sum(lowercase )
snake_case_ = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1 , n + 1 ):
snake_... | 508 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_te... | 508 | 1 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
UpperCAmelCase__ : str = pytest.mark.integration
@pytest.mark.parametr... | 446 |
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
UpperCAmelCase__ : Optional[Any] = False
UpperCAmelCase__ : Union[str, Any] = True
UpperCAmelCase__ : int = ... | 446 | 1 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class A_ ( __UpperCamelCase ):
'''simple docstring'''
def __init__( self: int , a: List[str] , a: Optional[Any] , a: int ):
__l... | 669 |
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()
lowerCAmelCase__: Any = logging.get_logger(__name__)
lowerCAmelCase__: U... | 345 | 0 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
c... | 702 |
'''simple docstring'''
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
Dis... | 233 | 0 |
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