code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
lowerCamelCase__ = True
except I... | 524 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified... | 661 | 0 |
def SCREAMING_SNAKE_CASE ( __UpperCamelCase : int , __UpperCamelCase : int ) -> int:
UpperCAmelCase_ = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
UpperCAmelCase_ = n - k
# Calculate C(n,k)
for i in... | 144 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Optional[Any] = {str(digit): digit**5 for digit in range(1_0)}
def lowerCAmelCase_( lowercase_ : int ) -> int:
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(lowercase_ ) )
def lowerCAmelCase_( ) ... | 661 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowerCAmelCase = {
'''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''... | 466 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__SCREAMING_SNAKE_CASE : str = tuple[int, int]
class lowerCamelCase_:
'''simple docstring'''
def __init__( self , lowerCamelCase__ , lowerCamelCase__... | 661 | 0 |
_lowercase = 9.80_665
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ = g):
if fluid_density <= 0:
raise ValueError("Impossible fluid density")
if volume < 0:
raise ValueError("Impossible Object volume")
if gravity <= 0:
... | 659 |
"""simple docstring"""
from __future__ import annotations
from math import ceil, floor, sqrt
def lowerCAmelCase_( lowercase_ : int = 2_00_00_00 ) -> int:
_lowerCamelCase = [0]
_lowerCamelCase = 42
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ... | 661 | 0 |
"""simple docstring"""
lowerCAmelCase : dict[tuple[int, int, int], int] = {}
def a__ ( snake_case__ , snake_case__ , snake_case__ ) -> int:
# if we are absent twice, or late 3 consecutive days,
# no further prize strings are possible
if late == 3... | 543 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
__SCREAMING_SNAKE_CASE : List[Any] = logging.get_logger(__name__)
class lowerCamelCase_( A__ ):
'''simple docstring'''
def __init__( self , ... | 661 | 0 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
A__: str = 2_9979_2458
# Symbols
A__: Union[str, Any] = symbols('''ct x y z''')
def lowerCAmelCase_ ( A_):
if velocity > c:
raise ValueError("Speed mu... | 380 |
"""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_distilbert import DistilBertTokenizer
__SCREAMING_SNAKE_CASE : int = logging.... | 661 | 0 |
def lowerCAmelCase ( UpperCAmelCase = 1, UpperCAmelCase = 1000 ) ->int:
"""simple docstring"""
__magic_name__ : Tuple = 1
__magic_name__ : Tuple = 0
for divide_by_number in range(lowercase_, digit + 1 ... | 154 |
"""simple docstring"""
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
__SCREAMING_SNAKE_CASE : str = 2_9_9_7_9_2_4_5_8
# Symbols
__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_... | 661 | 0 |
from __future__ import annotations
lowercase_: Dict = 1.6_021e-19 # units = C
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
"""simple docstring"""
if (conductivity, electron_conc, mobility).count(0) != 1:
raise Valu... | 648 |
"""simple docstring"""
from __future__ import annotations
__SCREAMING_SNAKE_CASE : Dict = 1.6_0_2_1e-1_9 # units = C
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : float , ) -> tuple[str, float]:
if (conductivity, electron_con... | 661 | 0 |
def lowerCamelCase ( UpperCamelCase : list[int] , UpperCamelCase : list[int] ) -> tuple[float, float]:
# Check if the input is valid
if not len(lowercase_ ) == len(lowercase_ ) == 3:
raise ValueError('Please enter a valid equation.' )
if equationa[... | 544 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
... | 661 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
snake_case_ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
sn... | 507 |
"""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.conversational i... | 661 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
'''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/config.json''',
# See all XGLM models at http... | 699 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_prop... | 661 | 0 |
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def _lowerCamelCase( __snake_case ) -> Optional[int]:
return x + 2
class UpperCamelCase ( unittest.TestCase ):
def UpperCamelCase_ ( se... | 524 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int = 10 ) -> str:
if not isinstance(lowercase_ , lowercase_ ) or n < 0:
raise ValueError('''Invalid input''' )
_lowerCamelCase = 10**n
_lowerCamelCase = 2_84_33 * (pow(2 , 7_83_04_57 ,... | 661 | 0 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoIm... | 144 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE : Optional[int] = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHI... | 661 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( __A : int , __A : list ):
_enforce_args(lowercase_ , lowercase_ )
if n == 0:
return 0
a_ : List[str] = float('''-inf''' )
for i in range(1 , n + 1 ):
a_ : Any ... | 466 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : str , lowercase_ : str ) -> float:
def get_matched_characters(lowercase_ : str , lowercase_ : str ) -> str:
_lowerCamelCase = []
_lowerCamelCase = min(len(_stra ) , len(_st... | 661 | 0 |
from pathlib import Path
import numpy as np
from PIL import Image
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ : Optional[Any] = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2_989 * r + 0.5_870 * g + 0.1_140 * b
def ... | 659 |
"""simple docstring"""
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
... | 661 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase : List[str] = {}
try:
if not is_sentencepiece_availabl... | 543 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__SCREAMING_SNAKE_CASE : Optional[int] = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translatio... | 661 | 0 |
from typing import Any
def lowerCAmelCase_ ( A_):
if not input_list:
return []
UpperCamelCase__: List[Any] = [input_list.count(lowercase_) for value in input_list]
UpperCamelCase__: int = max(lowercase_) # Gets the maximum count in the input list.
... | 380 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Union[str, Any] = {
'''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRE... | 661 | 0 |
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
lowercase_ = logging.get_logger(__name__)
class A__ ( A__ ):
def __init__( self , *lowerCamelCase , **lowerCamelCase ) -> i... | 154 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Any = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''... | 661 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_: Dict = {
'''configuration_table_transformer''': [
'''TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TableTransformerConfig''',
... | 648 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastap... | 661 | 0 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 544 |
"""simple docstring"""
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def lo... | 661 | 0 |
'''simple docstring'''
from __future__ import annotations
def __lowercase (_SCREAMING_SNAKE_CASE :int | str ):
SCREAMING_SNAKE_CASE : Optional[Any] = str(lowercase_ )
return n == n[::-1]
def __lowercase (_SCREAMING_SNAKE_CASE :int = 1_00_00_00 ):
SC... | 507 |
"""simple docstring"""
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTest... | 661 | 0 |
from statistics import mean
import numpy as np
def __UpperCamelCase (lowerCAmelCase : list, lowerCAmelCase : list, lowerCAmelCase : list, lowerCAmelCase : int ) -> list:
A = 0
# Number of processes finished
A = 0
# Displays the f... | 699 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_availa... | 661 | 0 |
def _lowerCamelCase( __snake_case ) -> None:
__snake_case = generate_pascal_triangle(lowercase_ )
for row_idx in range(lowercase_ ):
# Print left spaces
for _ in range(num_rows - row_idx - 1 ):
print(end=" " )
# Print row values
for col_idx in range(ro... | 524 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified... | 661 | 0 |
import sys
def SCREAMING_SNAKE_CASE ( __UpperCamelCase : Union[str, Any] ) -> Optional[Any]:
UpperCAmelCase_ = len(lowercase_ )
UpperCAmelCase_ = [[0 for x in range(lowercase_ )] for x in range(lowercase_ )]
UpperCAmelCase_ = [[0 for x in ra... | 144 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Optional[Any] = {str(digit): digit**5 for digit in range(1_0)}
def lowerCAmelCase_( lowercase_ : int ) -> int:
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(lowercase_ ) )
def lowerCAmelCase_( ) ... | 661 | 0 |
'''simple docstring'''
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
__lowerCAmelCase = (
'''This m... | 466 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__SCREAMING_SNAKE_CASE : str = tuple[int, int]
class lowerCamelCase_:
'''simple docstring'''
def __init__( self , lowerCamelCase__ , lowerCamelCase__... | 661 | 0 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerca... | 659 |
"""simple docstring"""
from __future__ import annotations
from math import ceil, floor, sqrt
def lowerCAmelCase_( lowercase_ : int = 2_00_00_00 ) -> int:
_lowerCamelCase = [0]
_lowerCamelCase = 42
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ... | 661 | 0 |
"""simple docstring"""
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 __magic_name__ ( A__ ):
... | 543 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
__SCREAMING_SNAKE_CASE : List[Any] = logging.get_logger(__name__)
class lowerCamelCase_( A__ ):
'''simple docstring'''
def __init__( self , ... | 661 | 0 |
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
A__: Optional[int] = False
class _a ( unittest.TestCase):
... | 380 |
"""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_distilbert import DistilBertTokenizer
__SCREAMING_SNAKE_CASE : int = logging.... | 661 | 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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_ver... | 154 |
"""simple docstring"""
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
__SCREAMING_SNAKE_CASE : str = 2_9_9_7_9_2_4_5_8
# Symbols
__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_... | 661 | 0 |
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.conversational import Con... | 648 |
"""simple docstring"""
from __future__ import annotations
__SCREAMING_SNAKE_CASE : Dict = 1.6_0_2_1e-1_9 # units = C
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : float , ) -> tuple[str, float]:
if (conductivity, electron_con... | 661 | 0 |
from __future__ import annotations
A = 1_0
def lowerCamelCase ( UpperCamelCase : list[int] ) -> list[int]:
_lowerCamelCase = 1
_lowerCamelCase = max(lowercase_ )
while placement <= max_digit:
# declare and initialize empty buckets
_lowerCamelC... | 544 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
... | 661 | 0 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def __lowercase (_SCREAMING_SNAK... | 507 |
"""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.conversational i... | 661 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json''... | 699 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_prop... | 661 | 0 |
def _lowerCamelCase( __snake_case ) -> int:
if not isinstance(lowercase_ , lowercase_ ) or number < 0:
raise ValueError("Input must be a non-negative integer" )
__snake_case = 0
while number:
# This way we arrive at next set bit (next 1) instead of looping
# thro... | 524 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int = 10 ) -> str:
if not isinstance(lowercase_ , lowercase_ ) or n < 0:
raise ValueError('''Invalid input''' )
_lowerCamelCase = 10**n
_lowerCamelCase = 2_84_33 * (pow(2 , 7_83_04_57 ,... | 661 | 0 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_... | 144 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE : Optional[int] = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHI... | 661 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( __A : int ):
assert isinstance(lowercase_ , lowercase_ ), f'The input value of [n={number}] is not an integer'
if number == 1:
return 2
elif number < 1:
a_ : int = f'The input value of... | 466 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : str , lowercase_ : str ) -> float:
def get_matched_characters(lowercase_ : str , lowercase_ : str ) -> str:
_lowerCamelCase = []
_lowerCamelCase = min(len(_stra ) , len(_st... | 661 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggin... | 659 |
"""simple docstring"""
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
... | 661 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : List[str] = {
'''configuration_clap''': [
'''CLAP_PRETRAINED_MODEL_ARCHIVE_LIST''',
'''ClapAudioConfig''',
'... | 543 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__SCREAMING_SNAKE_CASE : Optional[int] = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translatio... | 661 | 0 |
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__: Optional[int] = logging.get_logger(__name__)
A__: Optional[int] = {
... | 380 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Union[str, Any] = {
'''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRE... | 661 | 0 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...t... | 154 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Any = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''... | 661 | 0 |
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
from... | 648 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastap... | 661 | 0 |
import math
def lowerCamelCase ( UpperCamelCase : int ) -> str:
_lowerCamelCase = 0
_lowerCamelCase = 0
while num > 0:
_lowerCamelCase = num % 8
_lowerCamelCase = octal + (remainder * math.floor(math.pow(10 , lowercase_ ) ))
... | 544 |
"""simple docstring"""
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def lo... | 661 | 0 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/r... | 507 |
"""simple docstring"""
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTest... | 661 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
)
if is_flax_available(... | 699 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_availa... | 661 | 0 |
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastapi.routing import APIRoute
f... | 524 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified... | 661 | 0 |
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE ( __UpperCamelCase : int , __UpperCamelCase : int , __UpperCamelCase : bool , __UpperCamelCase : list[int] , __UpperCamelCase : float ) -> int:
if depth < 0:
rai... | 144 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Optional[Any] = {str(digit): digit**5 for digit in range(1_0)}
def lowerCAmelCase_( lowercase_ : int ) -> int:
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(lowercase_ ) )
def lowerCAmelCase_( ) ... | 661 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE ( metaclass=A__ ):
snake_case__ = ['torch', 'transformers', 'onnx']
def __init__( self : Any , *__SCREAMING_SNAKE_CASE ... | 466 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__SCREAMING_SNAKE_CASE : str = tuple[int, int]
class lowerCamelCase_:
'''simple docstring'''
def __init__( self , lowerCamelCase__ , lowerCamelCase__... | 661 | 0 |
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 __snake_case ( A__ ):
"... | 659 |
"""simple docstring"""
from __future__ import annotations
from math import ceil, floor, sqrt
def lowerCAmelCase_( lowercase_ : int = 2_00_00_00 ) -> int:
_lowerCamelCase = [0]
_lowerCamelCase = 42
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ... | 661 | 0 |
"""simple docstring"""
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
lowerCAmelCase : List[Any] = WebClient(token=os.environ["""CI_SLACK_BOT_TOKEN"""])
def ... | 543 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
__SCREAMING_SNAKE_CASE : List[Any] = logging.get_logger(__name__)
class lowerCamelCase_( A__ ):
'''simple docstring'''
def __init__( self , ... | 661 | 0 |
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
A__: Any = logging.get_logger(__name__)
def lowerCAmelCase_ ( A_ ... | 380 |
"""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_distilbert import DistilBertTokenizer
__SCREAMING_SNAKE_CASE : int = logging.... | 661 | 0 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def lowerCAmelCase ( UpperCAmelCase ) ->Union[str, Any]:... | 154 |
"""simple docstring"""
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
__SCREAMING_SNAKE_CASE : str = 2_9_9_7_9_2_4_5_8
# Symbols
__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_... | 661 | 0 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowercase ( UpperCAmelCase_):
... | 648 |
"""simple docstring"""
from __future__ import annotations
__SCREAMING_SNAKE_CASE : Dict = 1.6_0_2_1e-1_9 # units = C
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : float , ) -> tuple[str, float]:
if (conductivity, electron_con... | 661 | 0 |
from __future__ import annotations
A = '''Muhammad Umer Farooq'''
A = '''MIT'''
A = '''1.0.0'''
A = '''Muhammad Umer Farooq'''
A = '''contact@muhammadumerfarooq.me'''
A = '''Alpha'''
import re
from html.parser import HTMLParser
from urllib import parse
import re... | 544 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
... | 661 | 0 |
'''simple docstring'''
import functools
from typing import Any
def __lowercase (_SCREAMING_SNAKE_CASE :str , _SCREAMING_SNAKE_CASE :list[str] ):
# Validation
if not isinstance(lowercase_ , lowercase_ ) or len(lowercase_ ) == 0:
raise ValueError('''t... | 507 |
"""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.conversational i... | 661 | 0 |
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
_UpperCAmelCase = TypeVar("T")
class _UpperCAmelCase ( Generic[T] ):
'''simple docstring'''
def __init__( self : int , UpperCamelCase__ : st... | 699 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_prop... | 661 | 0 |
import collections
import importlib.util
import os
import re
from pathlib import Path
lowerCamelCase__ = '''src/transformers'''
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(r'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ ... | 524 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int = 10 ) -> str:
if not isinstance(lowercase_ , lowercase_ ) or n < 0:
raise ValueError('''Invalid input''' )
_lowerCamelCase = 10**n
_lowerCamelCase = 2_84_33 * (pow(2 , 7_83_04_57 ,... | 661 | 0 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import... | 144 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE : Optional[int] = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHI... | 661 | 0 |
'''simple docstring'''
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 SCREAMING_SNAKE_CASE :
... | 466 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : str , lowercase_ : str ) -> float:
def get_matched_characters(lowercase_ : str , lowercase_ : str ) -> str:
_lowerCamelCase = []
_lowerCamelCase = min(len(_stra ) , len(_st... | 661 | 0 |
from collections.abc import Sequence
def UpperCamelCase ( snake_case__ , snake_case__):
return sum(c * (x**i) for i, c in enumerate(lowercase_))
def UpperCamelCase ( snake_case__ , snake_case__):
lowerCAmelCase_ : Tuple = 0.0
for coeff in reversed(lowerc... | 659 |
"""simple docstring"""
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
... | 661 | 0 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_a... | 543 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__SCREAMING_SNAKE_CASE : Optional[int] = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translatio... | 661 | 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 transforme... | 380 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Union[str, Any] = {
'''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRE... | 661 | 0 |
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase_ = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
parser.add_argument('''--dpm''', a... | 154 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Any = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''... | 661 | 0 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_atten... | 648 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastap... | 661 | 0 |
def lowerCamelCase ( UpperCamelCase : Dict ) -> str:
_lowerCamelCase = [0] * len(lowercase_ )
_lowerCamelCase = []
_lowerCamelCase = []
_lowerCamelCase = 0
for values in graph.values():
for i in values:
indegree[i] += 1
for i in ... | 544 |
"""simple docstring"""
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def lo... | 661 | 0 |
'''simple docstring'''
import argparse
import json
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
f... | 507 |
"""simple docstring"""
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTest... | 661 | 0 |
_UpperCAmelCase = '''0.21.0'''
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
... | 699 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_availa... | 661 | 0 |
def _lowerCamelCase( __snake_case , __snake_case ) -> float:
if mass < 0:
raise ValueError("The mass of a body cannot be negative" )
return 0.5 * mass * abs(lowercase_ ) * abs(lowercase_ )
if __name__ == "__main__":
import doctest
doctest.testmod(verbose=True)
| 524 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified... | 661 | 0 |
from ...processing_utils import ProcessorMixin
class a ( A__ ):
'''simple docstring'''
lowerCAmelCase : List[Any] = ['image_processor', 'feature_extractor']
lowerCAmelCase : str = 'TvltImageProcessor'
lowerCAmelCase ... | 144 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Optional[Any] = {str(digit): digit**5 for digit in range(1_0)}
def lowerCAmelCase_( lowercase_ : int ) -> int:
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(lowercase_ ) )
def lowerCAmelCase_( ) ... | 661 | 0 |
'''simple docstring'''
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... | 466 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__SCREAMING_SNAKE_CASE : str = tuple[int, int]
class lowerCamelCase_:
'''simple docstring'''
def __init__( self , lowerCamelCase__ , lowerCamelCase__... | 661 | 0 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE_GEN... | 659 |
"""simple docstring"""
from __future__ import annotations
from math import ceil, floor, sqrt
def lowerCAmelCase_( lowercase_ : int = 2_00_00_00 ) -> int:
_lowerCamelCase = [0]
_lowerCamelCase = 42
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ... | 661 | 0 |
"""simple docstring"""
lowerCAmelCase : Optional[Any] = {str(digit): digit**5 for digit in range(10)}
def a__ ( snake_case__ ) -> int:
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(lowercase_ ) )
def a__ ( ) -> int:
ret... | 543 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
__SCREAMING_SNAKE_CASE : List[Any] = logging.get_logger(__name__)
class lowerCamelCase_( A__ ):
'''simple docstring'''
def __init__( self , ... | 661 | 0 |
def lowerCAmelCase_ ( A_):
if p < 2:
raise ValueError("p should not be less than 2!")
elif p == 2:
return True
UpperCamelCase__: List[str] = 4
UpperCamelCase__: List[Any] = (1 << p) - 1
for _ in range(p - 2):
UpperCamelCase__:... | 380 |
"""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_distilbert import DistilBertTokenizer
__SCREAMING_SNAKE_CASE : int = logging.... | 661 | 0 |
def lowerCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase = 0, UpperCAmelCase = 0 ) ->int:
"""simple docstring"""
__magic_name__ : str = right or len(lowercase_ ) - 1
if left > right:
return -1
... | 154 |
"""simple docstring"""
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
__SCREAMING_SNAKE_CASE : str = 2_9_9_7_9_2_4_5_8
# Symbols
__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_... | 661 | 0 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase_: Optional[int] = logging.get_logger(__name__)
class lowercase__ (A__ ):
"""simple docstring"""
def __init__( self : Optional[Any]... | 648 |
"""simple docstring"""
from __future__ import annotations
__SCREAMING_SNAKE_CASE : Dict = 1.6_0_2_1e-1_9 # units = C
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : float , ) -> tuple[str, float]:
if (conductivity, electron_con... | 661 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A = {
'''configuration_pix2struct''': [
'''PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Pix2StructConfig''',
'''Pix2StructTextConfi... | 544 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
... | 661 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
snake_case_ = list[list[float | int]]
def __lowercase (_SCREAMING_SNAKE_CASE :Matrix , _SCREAMING_SNAKE_CASE :Matrix ):
SCREAMING_SNAKE_CASE : List[str] = len(lowerca... | 507 |
"""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.conversational i... | 661 | 0 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import TEXT_GUIDED_IMAGE... | 699 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_prop... | 661 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/ma... | 524 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : int = 10 ) -> str:
if not isinstance(lowercase_ , lowercase_ ) or n < 0:
raise ValueError('''Invalid input''' )
_lowerCamelCase = 10**n
_lowerCamelCase = 2_84_33 * (pow(2 , 7_83_04_57 ,... | 661 | 0 |
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
f... | 144 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE : Optional[int] = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHI... | 661 | 0 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
requi... | 466 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : str , lowercase_ : str ) -> float:
def get_matched_characters(lowercase_ : str , lowercase_ : str ) -> str:
_lowerCamelCase = []
_lowerCamelCase = min(len(_stra ) , len(_st... | 661 | 0 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def __UpperCamelCase ( _lowerCAmelCase ) -> Tuple:
"""simple docstring"""
A : List[str] =... | 662 |
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STA... | 662 | 1 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def __UpperCamelCase ( _lowerCAmelCase = True , *_lowerCAmelCase , **_lowerCAmelCase ) -> str:
"""simple docstring"""
if not is_tqd... | 662 |
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
def __init__( self, lowerCamelCase__ ):
# we need a list not a string, so do something to change the type
A : List[Any] = arr.split(""",""" )
def _lowerCAmelCase ( self ):
... | 662 | 1 |
import random
def __UpperCamelCase ( _lowerCAmelCase ) -> bool:
"""simple docstring"""
A : Tuple = num - 1
A : List[str] = 0
while s % 2 == 0:
A : Tuple = s // 2
t += 1
for _ in range(5 ):
A : List[... | 662 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
SCREAMING_SNAKE_CASE_:List[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_:List[Any] = {
"""google/bit-50""": ... | 662 | 1 |
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,
MobileViTVaFo... | 662 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTeste... | 662 | 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 by ... | 662 |
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,
)
fr... | 662 | 1 |
import os
import numpy
import onnx
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> Union[str, Any]:
"""simple docstring"""
A : int = a.name
A : Optional[int] = b.name
A : Tuple = """"""
A : List[Any] = """"""
... | 662 |
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 BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILImageResamplin... | 662 | 1 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from ... | 662 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
SCREAMING_SNAKE_CASE_:Optional[int] = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
def __init__( self, *... | 662 | 1 |
SCREAMING_SNAKE_CASE_:Tuple = 256
# Modulus to hash a string
SCREAMING_SNAKE_CASE_:Any = 1_000_003
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
"""simple docstring"""
A : Optional[int] = len(_lowerCAmelCase )
A : Opti... | 662 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
... | 662 | 1 |
from __future__ import annotations
SCREAMING_SNAKE_CASE_:Tuple = """#"""
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
def __init__( self ):
A : dict = {}
def _lowerCAmelCase ( self, lowerCamelCase__ ):
A : List[A... | 662 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
SCREAMING_SNAKE_CASE_:int = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
SCREAMING_SNAKE_CASE_:Dict = _LazyModule(__name__, global... | 662 | 1 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTeste... | 662 |
def __UpperCamelCase ( _lowerCAmelCase = 1000 ) -> int:
"""simple docstring"""
A , A : str = 1, 1
A : List[Any] = []
for i in range(1 , n + 1 ):
A : Optional[int] = prev_numerator + 2 * prev_denominator
A : Any =... | 662 | 1 |
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE_:List[str] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_:List[Any] = {
"""vocab_file""": """vocab.json""",
"""token... | 662 |
import re
def __UpperCamelCase ( _lowerCAmelCase ) -> str:
"""simple docstring"""
if len(re.findall("""[ATCG]""" , _lowerCAmelCase ) ) != len(_lowerCAmelCase ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans(""... | 662 | 1 |
from math import factorial, pi
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase = 30 ) -> float:
"""simple docstring"""
if not isinstance(_lowerCAmelCase , (int, float) ):
raise ValueError("""maclaurin_sin() requires either an int or float for theta"... | 662 |
from __future__ import annotations
SCREAMING_SNAKE_CASE_:Tuple = """#"""
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
def __init__( self ):
A : dict = {}
def _lowerCAmelCase ( self, lowerCamelCase__ ):
A : List[A... | 662 | 1 |
from __future__ import annotations
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
"""simple docstring"""
if len(_lowerCAmelCase ) == 0:
return False
A : Union[str, Any] = len(_lowerCAmelCase ) // 2
if a_list[midpoint... | 662 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .dataclasses import Bn... | 662 | 1 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfig,
ViTHybri... | 662 |
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_tf import PTtoTFCommand
fro... | 662 | 1 |
def __UpperCamelCase ( _lowerCAmelCase ) -> list:
"""simple docstring"""
for i in range(len(_lowerCAmelCase ) - 1 , 0 , -1 ):
A : Any = False
for j in range(_lowerCAmelCase , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
... | 662 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_:int = {
"""configuration_blenderbot""": [
"""BLENDERBOT_PRETRAINED_... | 662 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
SCREAMING_SNAKE_CASE_:str = 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 refer... | 662 |
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> list[int]:
"""simple docstring"""
A : Optional[int] = int(_lowerCAmelCase )
# Initialize Result
A : int = []
# Traverse through all denomination
for denomination in reversed(... | 662 | 1 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE_:Optional[int] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_:Dict = [
["""attention""", """attn"... | 662 |
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny vocab first, and then a tiny model - so the outcome is truly tiny -
# all files ~60KB. As compared to ... | 662 | 1 |
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Opti... | 662 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__v... | 662 | 1 |
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
__lowerCamelCase : Optional[Any] = ["sentencepiece"]
def __init__( self, *lowerCamelCase__, **lowerCamelCase... | 662 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTokenizer, BlipImageProce... | 662 | 1 |
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
SCREAMING_SNAKE_CASE_:List[str] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_:List[Any] = {... | 662 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@s... | 662 | 1 |
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