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 |
|---|---|---|---|---|
"""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 PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ = logging.get_logger... | 645 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 0 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
_a: List[Any] = {
"""n_samples""": 64,
"""horizon""": 32,
"""num_inference_steps""": 20,
"""n_guide_steps""": 2, # can set to 0 for faster sampling, does not use value network
"""s... | 162 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 0 |
import math
def A__ ( snake_case_ : Optional[Any] , snake_case_ : Dict ):
if (
not isinstance(lowercase_ , (int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError('''power_factor must be a valid float value between -1 and 1.''' ... | 64 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 0 |
class __magic_name__ :
def __init__( self ) -> Tuple:
'''simple docstring'''
__a =0
__a =0
__a ={}
def __magic_name__ ( self , __snake_case ) -> List[Any]:
'''simple docstr... | 242 |
"""simple docstring"""
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_... | 624 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@require_torc... | 302 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 0 |
'''simple docstring'''
def UpperCAmelCase ( lowerCamelCase_ :Optional[int] ):
'''simple docstring'''
if number > 0:
raise ValueError("""input must be a negative integer""" )
snake_case_ : int = len(bin(lowercase_ )[3:] )
snake_case_ : Tuple = ... | 334 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
loggin... | 343 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmel... | 351 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 0 |
'''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,
Musi... | 8 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 0 |
from ...processing_utils import ProcessorMixin
class a__ ( _UpperCamelCase ):
A__ : Optional[int] = "SpeechT5FeatureExtractor"
A__ : str = "SpeechT5Tokenizer"
def __init__( self , UpperCAmelCase , UpperCAmelCase ) -> Op... | 559 |
"""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
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 0 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils ... | 99 |
"""simple docstring"""
import collections
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__ = re.compile(R"^_i... | 624 | 0 |
"""simple docstring"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
lowerCAmelCase__ = numpy.array([0, 0])
lowerCAmelCase__ = numpy.array([0.5, 0.8660254])
lowerCAmelCase__ = numpy.array([1, 0])
l... | 645 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
from diffusers.util... | 162 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.util... | 624 | 0 |
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def A__ ( snake_case_ : Any , snake_case_ : str , snake_case_ : Tuple , snake_case_ : Union[str, Any]=5 ):
assert masked_input.count('''<mask>''' ) == 1
SCREAMING_SNAKE_CAS... | 64 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 0 |
from math import isqrt
def UpperCamelCase_( _snake_case : Union[str, Any] ):
"""simple docstring"""
__a =[True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase... | 242 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 0 |
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
lowercase : Tuple = logging.get_logger(__name__)
... | 302 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 0 |
'''simple docstring'''
def UpperCAmelCase ( lowerCamelCase_ :Tuple ): # noqa: E741
'''simple docstring'''
snake_case_ : List[Any] = len(lowercase_ )
snake_case_ : str = 0
snake_case_ : List[Any] = [0] * n
snake_case_ : Any ... | 334 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 0 |
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ) -> List[Any]:
'''simple docstring'''
lowerCAmelCase : List[Any] = len(lowercase_ )
for i in range(length - 1 ):
lowerCAmelCase : str = i
for k in range(i + 1, lo... | 343 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 0 |
def a_ (__A , __A ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError("both inputs must be positive integers" )
__a : List[Any] = str(bin(lowercase_ ) )
binary_number += "0" * shift_am... | 351 |
"""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,
MusicgenForConditionalGenerat... | 624 | 0 |
'''simple docstring'''
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
... | 8 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 0 |
def lowerCAmelCase( __lowerCamelCase ):
__a = min(lowercase_ ) # min() finds the minimum value
__a = max(lowercase_ ) # max() finds the maximum value
__a = max_val - min_val + 1 # size is difference of max and min values plus one
# list of pigeonhole... | 559 |
"""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,
... | 624 | 0 |
import argparse
from collections import defaultdict
import yaml
SCREAMING_SNAKE_CASE = 'docs/source/en/_toctree.yml'
def a (lowerCAmelCase__ ):
__a = defaultdict(lowercase_ )
__a = []
__a = []
for doc in doc_list:
if "local" in doc:
... | 99 |
"""simple docstring"""
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 624 | 0 |
"""simple docstring"""
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class SCREAMING_SNAKE_CASE__ ( _UpperCamelCase ):
"""simple docstring"""
a : str ="EncodecFeatureExtractor"
... | 645 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 0 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch... | 162 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 0 |
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():
import torch... | 64 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 0 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def UpperCamelCase_( _snake_case : str ):
"""simple docstring"""
__a =[
"decoder.version",
"decode... | 242 |
"""simple docstring"""
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_... | 624 | 0 |
def A_ ( A__ , A__ , A__ ) -> int:
def update_area_of_max_square(A__ , A__ ) -> int:
# BASE CASE
if row >= rows or col >= cols:
return 0
a__ : Tuple = update_area_of_max_square(lowe... | 302 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 0 |
'''simple docstring'''
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
__A : List[Any] = [
# (stable-diffusion, HF Diffusers)
('time_embed.0.weight', 'time_embed... | 334 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 0 |
import argparse
import datetime
import io
import itertools
import json
import math
import os
import platform
import re
import shlex
import subprocess
import sys
from pathlib import Path
from statistics import fmean
import pandas as pd
import torch
from tqdm import tqdm
import transformers
__A : Optional[Any] ... | 343 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 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
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''g... | 351 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 0 |
'''simple docstring'''
import math
def _lowerCAmelCase ( __snake_case : int ) -> bool:
assert isinstance(lowercase_ , lowercase_ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
#... | 8 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 0 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_as... | 559 |
"""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
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 0 |
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def a (lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
__a = TaConfig.from_json_file(lowercase_... | 99 |
"""simple docstring"""
import collections
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__ = re.compile(R"^_i... | 624 | 0 |
"""simple docstring"""
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 ... | 645 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 0 |
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
_a: Tuple = get_logger(... | 162 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.util... | 624 | 0 |
import os
from pathlib import Path
def A__ ( snake_case_ : Optional[Any] , snake_case_ : Optional[int] , snake_case_ : str , snake_case_ : Optional[Any] ):
SCREAMING_SNAKE_CASE__: Union[str, Any]= {
"en": "Machine learning is great, isn't it?",
... | 64 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 0 |
def UpperCamelCase_( _snake_case : Optional[int] , _snake_case : Tuple ):
"""simple docstring"""
return int(input_a == input_a == 0 )
def UpperCamelCase_( ):
"""simple docstring"""
print('Truth Table of NOR Gate:' ... | 242 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 0 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( _UpperCamelCase ):
"""simple d... | 302 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 0 |
'''simple docstring'''
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
__A ... | 334 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : List[Any] = {
'''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json''',
# See all GLPN models at https://huggingf... | 343 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 0 |
from __future__ import annotations
from typing import Any
class snake_case_ :
"""simple docstring"""
def __init__(self: List[Any] , __UpperCAmelCase: int , __UpperCAmelCase: int , __UpperCAmelCase: float = 0 ) -> None:
'''simpl... | 351 |
"""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,
MusicgenForConditionalGenerat... | 624 | 0 |
'''simple docstring'''
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqd... | 8 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 0 |
import re
def lowerCAmelCase( __lowerCamelCase ):
__a = re.compile(
r'^(?:0|94|\+94|0{2}94)' r'7(0|1|2|4|5|6|7|8)' r'(-| |)' r'\d{7}$' )
return bool(re.search(lowercase_ , lowercase_ ) )
if __name__ == "__main__":
lowerCamelCase_ : Union[str, Any] ... | 559 |
"""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,
... | 624 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE = {'configuration_yolos': ['YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YolosConfig', 'YolosOnnxConfig']}
try:
if not is_vision_a... | 99 |
"""simple docstring"""
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 624 | 0 |
"""simple docstring"""
def a__ ( SCREAMING_SNAKE_CASE : Union[str, Any] = 1_0 ):
'''simple docstring'''
if not isinstance(lowercase_ , lowercase_ ) or n < 0:
raise ValueError("Invalid input" )
lowerCAmelCase : Union[str, Any] = 1_0*... | 645 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 0 |
def __lowerCAmelCase ( A ):
UpperCAmelCase_ = int(lowercase_ )
if decimal in (0, 1): # Exit cases for the recursion
return str(lowercase_ )
UpperCAmelCase_ = divmod(lowercase_ , 2 )
return binary_recursive(lowercase_ ) + str(lowercase_ )
... | 162 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 0 |
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp_space_optuna,
default_hp_... | 64 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 0 |
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
_lowerCAmelCase : str = "<<<<<<< This should probably be modified because it mentions: "
_lowerCAmelC... | 242 |
"""simple docstring"""
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_... | 624 | 0 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def A_ ( A__ ) -> List[str]:
if "model" in orig_key:
a__ : Any = orig_key.replace('model.' , '' )
if "norm1" in orig_key:
a__ : ... | 302 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 0 |
'''simple docstring'''
def UpperCAmelCase ( lowerCamelCase_ :Tuple = 50 ):
'''simple docstring'''
snake_case_ : List[Any] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_st... | 334 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 0 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constant_schedule_wit... | 343 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 0 |
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 351 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : Dict = 1_00_00_00 ) -> int:
__A : Optional[int] = set(range(3 , lowercase_ , 2 ) )
primes.add(2 )
for p in range(3 , lowercase_ , 2 ):
... | 8 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 0 |
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
requi... | 559 |
"""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
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 0 |
SCREAMING_SNAKE_CASE = [
9_9_9,
8_0_0,
7_9_9,
6_0_0,
5_9_9,
5_0_0,
4_0_0,
3_9_9,
3_7_7,
3_5_5,
3_3_3,
3_1_1,
2_8_8,
2_6_6,
2_4_4,
2_2_2,
2_0_0,
1_9_9,
1_7_7,
1_5_5,
1_3_3,
1_1_1,
8_8,... | 99 |
"""simple docstring"""
import collections
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__ = re.compile(R"^_i... | 624 | 0 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
lowerCAmelCase__ = (720, 1_280) # Height, Width
lowerCAmelCase__ = (0.4, 0.6) # if height or width lower than this scale, drop it.
lowerCAmelCas... | 645 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 0 |
import cmath
import math
def __lowerCAmelCase ( A , A , A , A ):
UpperCAmelCase_ = math.radians(lowercase_ )
UpperCAmelCase_ = math.radians(lowercase_ )
# Convert voltage and current to rectangular form
UpperCAmelCase_ = ... | 162 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.util... | 624 | 0 |
from __future__ import annotations
import math
from collections.abc import Callable
def A__ ( snake_case_ : Union[str, Any] , snake_case_ : str , snake_case_ : int , snake_case_ : Tuple = 100 , ):
SCREAMING_SNAKE_CASE__: Any= x_start
SCREAMING... | 64 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 0 |
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils import ConfigMixin, register_to_config
from diffusers.schedulers.scheduling_utils import SchedulerMixin
from diffusers.utils import BaseOutput, ... | 242 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 0 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def A_ ( A__ , A__ , A__ , A_... | 302 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 0 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__A : List[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... | 334 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 0 |
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool
class __A ( _UpperCamelCase ):
lowerCAmelCase_ : Union[str, Any] = "philschmid/bart-large-cnn-samsum"
lowerCAmelCase_ : Union[str, Any] = (
"This is a tool that summa... | 343 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 0 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceClassification,
... | 351 |
"""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,
MusicgenForConditionalGenerat... | 624 | 0 |
'''simple docstring'''
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import ... | 8 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 0 |
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
DPR_CONTEX... | 559 |
"""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,
... | 624 | 0 |
def a (lowerCAmelCase__ ):
if number < 0:
raise ValueError("""number must not be negative""" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 99 |
"""simple docstring"""
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 624 | 0 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCAmelCase__ = False
try:
low... | 645 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 0 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class __UpperCamelCase ( _UpperCamelCase ):
SCREAMING_SNAKE_CASE__ = CustomTokenizer
pass | 162 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 0 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
lowercase_ : Any = ... | 64 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 0 |
def UpperCamelCase_( _snake_case : Tuple ):
"""simple docstring"""
__a =abs(lowercase_ )
__a =0
while n > 0:
res += n % 10
n //= 10
return res
def UpperCamelCase_( _snake_case : List[str] ):
"""... | 242 |
"""simple docstring"""
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_... | 624 | 0 |
from math import factorial
def A_ ( A__ , A__ ) -> int:
if n < k or k < 0:
raise ValueError('Please enter positive integers for n and k where n >= k' )
return factorial(lowercase_ ) // (factorial(lowercase_ ) * factorial(n - k ))... | 302 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Any = logging.get_logger(__name__)
__A : Optional[Any] = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'tiiuae/falcon-7b... | 334 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 0 |
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase, _UpperCAmelCase ) -> float:
'''simple docstring'''
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modulus' )
return (bulk_modul... | 343 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 0 |
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''': '''sen... | 351 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 0 |
'''simple docstring'''
import argparse
import os
from accelerate.test_utils import execute_subprocess_async
def _lowerCAmelCase ( __snake_case : List[str]=None ) -> int:
if subparsers is not None:
__A : List[Any] = subparsers.add_... | 8 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 0 |
import argparse
import os
import re
import packaging.version
lowerCamelCase_ : int = """examples/"""
lowerCamelCase_ : Any = {
"""examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""... | 559 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'google/vivit-b-16x2-kinetics400': (
'https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/... | 99 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ = re.compile(R"^_i... | 624 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
fr... | 645 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 0 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils impor... | 162 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.util... | 624 | 0 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
lowercase_ : Any = HfArgumentParser(InitializationArguments)
lowercase_ : Optional[int] = parser.parse_args()
# Load codeparrot tokenizer t... | 64 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 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 : List[str] = pytest.mark.integration
@pytest.ma... | 242 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 0 |
def A_ ( A__ = "The quick brown fox jumps over the lazy dog" , ) -> bool:
a__ : Optional[int] = set()
# Replace all the whitespace in our sentence
a__ : List[str] = input_str.replace(' ' , '' )
for alpha in input_str:
... | 302 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 0 |
'''simple docstring'''
from math import factorial
__A : List[Any] = {str(digit): factorial(digit) for digit in range(10)}
def UpperCAmelCase ( lowerCamelCase_ :int ):
'''simple docstring'''
if not isinstance(lowercase_ , lowercase_ ):
raise TypeError("""Paramete... | 334 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 0 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
__A : Dict = logging.getLogger(__name__)
class __A :
def __init__( self : str ):
lowerCAme... | 343 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 0 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, Pat... | 351 |
"""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,
MusicgenForConditionalGenerat... | 624 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : int = logging.get_logger(__name__)
lowercase__ : Dict = {
'''microsoft/git-... | 8 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 0 |
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditionalGeneration, Bar... | 559 |
"""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,
... | 624 | 0 |
import re
from filelock import FileLock
try:
import nltk
SCREAMING_SNAKE_CASE = True
except (ImportError, ModuleNotFoundError):
SCREAMING_SNAKE_CASE = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('punkt', quiet=True)
... | 99 |
"""simple docstring"""
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 624 | 0 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
lowerCAmelCase__ = True
except (ImportError, ModuleNotFoundError):
lowerCAmelCase__ = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', quiet... | 645 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a: Optional[Any] = logging.get_logger(__name__)
_a: Dict = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class __UpperCamelCase ( _UpperCamelCase ):
SCREAMIN... | 162 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 0 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowercase_ : List[str] = {'UserAgent': UserAgent().random}
def A__ ( snake_case_ : str ):
SCREAMING_SNAKE_CASE__: List[Any]= script.contents[0]
SC... | 64 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 0 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def UpperCamelCase_( _snake_case : Any ):
"""simple docstring"""
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
... | 242 |
"""simple docstring"""
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_... | 624 | 0 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common... | 302 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 0 |
'''simple docstring'''
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils i... | 334 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 0 |
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
__A : Optional[int] = True
except Imp... | 343 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = '''▁'''
Uppe... | 351 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 0 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def _lowerCAmelCase ( __snake_case : List[str] ) -> Any:
if (
(cp >= 0x4_e_0_0 and cp <= 0x9_f_f_f)
... | 8 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 0 |
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowerCAmelCase( __lowerCamelCase = 8 ):
__a = ascii_letters + digits + punctuation
return "".join(secrets.choice(lowercase_ ) for _ in range(lowercase_... | 559 |
"""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
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 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 Ac... | 99 |
"""simple docstring"""
import collections
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__ = re.compile(R"^_i... | 624 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 645 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 0 |
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