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 functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface... | 101 |
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 torc... | 87 | 0 |
"""simple docstring"""
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
__mag... | 102 |
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
_lowerCamelCase : Dict = 6_378_137.0
_lowerCamelCase : Union[str, Any] = 6_356_752.314_245
_lowerCamelCase : List[Any] = 6378137
def SCREAMING_SNAKE_CASE ... | 87 | 0 |
"""simple docstring"""
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
s... | 103 |
import heapq
import sys
import numpy as np
_lowerCamelCase : Any = tuple[int, int]
class UpperCamelCase_ :
'''simple docstring'''
def __init__( self : Any) ->str:
'''simple docstring'''
A__ = []
A__ = ... | 87 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
UpperCamelCase = """\
"""
UpperCamelCase = """
Perplexity (PPL... | 104 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 87 | 0 |
from math import pow
def __UpperCAmelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int , lowerCamelCase_ : int , lowerCamelCase_ : int , lowerCamelCase_ : int , ) -> tuple[int, int]:
"""simple docstring"""
if ... | 105 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCamelCase : int = logging.get_logger("""transformers.models.speecht5""")
def SCREAMING_SNAKE_CASE ( lowercase_ , ... | 87 | 0 |
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
fro... | 106 |
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 ModelTest... | 87 | 0 |
'''simple docstring'''
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_UpperCAmelCase : Any = 10
def _SCREAMING_SNAKE_CASE ( __snake_case : i... | 107 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
_lowerCamelCase : int = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE ( lowercase_ , low... | 87 | 0 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils... | 108 |
class UpperCamelCase_ : # Public class to implement a graph
'''simple docstring'''
def __init__( self : str , UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : list[list[bool]]) ->None:
'''simple docstring'''... | 87 | 0 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgume... | 109 |
from __future__ import annotations
import requests
_lowerCamelCase : str = set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories c... | 87 | 0 |
"""simple docstring"""
import warnings
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 ( lowercase ... | 110 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class UpperCamelCase_ ( unittest.TestCase ):
'''simple docstring'''
UpperCAmelCase__ = JukeboxTokenizer
UpperCAmelCase__ = {
'''artist''': '''Z... | 87 | 0 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, 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... | 400 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : str = logging.get_logger(__name__)
_lowerCamelCase : List[str] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class UpperCamelCase... | 87 | 0 |
'''simple docstring'''
def lowercase__( _UpperCamelCase : Tuple )-> Union[str, Any]:
"""simple docstring"""
_UpperCamelCase = len(lowercase_ )
while cur > 1:
# Find the maximum number in arr
_UpperCamelCase = arr.index(max(arr[0:cur] )... | 138 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def SCREAMING_SNAKE_CASE ( ) -> None:
"""simple docstring"""
assert or_gate(0 , 0 ) == 0
... | 87 | 0 |
__magic_name__: Optional[int] = {
"""Pillow""": """Pillow""",
"""accelerate""": """accelerate>=0.11.0""",
"""compel""": """compel==0.1.8""",
"""black""": """black~=23.1""",
"""datasets""": """datasets""",
"""filelock""": """filelock""",
"""flax""": """flax>=0.4.1""",
""... | 324 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import torch.nn as nn
from ... | 87 | 0 |
import string
def a__ ( __UpperCamelCase ):
SCREAMING_SNAKE_CASE_ = ""
for i in sequence:
SCREAMING_SNAKE_CASE_ = ord(lowercase_ )
if 6_5 <= extract <= 9_0:
output += chr(1_5_5 - extract )
elif 9_7 <= extract <= 1_2_2:
... | 140 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
_lowerCamelCase : str = 299792458
# Symbols
_lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase : int = symbols("""ct x y z""")
def... | 87 | 0 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def A_ ( snake_case__ ) -> Any:
_UpperCamelCase :List[str] = args.pruning_method
_UpperCamelCase :Union[str... | 355 |
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
A__ = []
def generate(lowercase_ , lowercase_ ):
if k == 1:
res.append... | 87 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ = {
"""configuration_bert""": ["""B... | 322 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIFICAT... | 87 | 0 |
"""simple docstring"""
def a__ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE = 0 , __SCREAMING_SNAKE_CASE = 0 ) -> int:
__lowerCAmelCase: int = right or len(lowercase_ ) - 1
if left > right:
return -1
... | 346 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : Any = {"""configuration_xlnet""": ["""XLNET_PRETRAINED_CONFI... | 87 | 0 |
"""simple docstring"""
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def ... | 373 |
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 : Optional[Any] = logging.get_logger(__name__)
_lowerCamelCase : ... | 87 | 0 |
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
lowercase : Tuple = """src/transformers"""
... | 542 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
fro... | 87 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import F... | 517 |
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> dict:
"""simple docstring"""
A__ = f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return requests.get(lowercase_ ).json()
def... | 87 | 0 |
'''simple docstring'''
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from ... | 432 |
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen
from ..table impo... | 87 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : List[Any] = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : Optional[int] = {
"""MIT/ast-finetuned-audioset-10-10-0.4593""": (
"""http... | 400 |
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMod... | 87 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case_ : int = {"""configuration_vit""": ["""VIT_PRETRAINED_CO... | 138 |
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 torc... | 87 | 0 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
__magic_name__: Any = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1), 6: (3, 2), ... | 324 |
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
_lowerCamelCase : Dict = 6_378_137.0
_lowerCamelCase : Union[str, Any] = 6_356_752.314_245
_lowerCamelCase : List[Any] = 6378137
def SCREAMING_SNAKE_CASE ... | 87 | 0 |
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTes... | 140 |
import heapq
import sys
import numpy as np
_lowerCamelCase : Any = tuple[int, int]
class UpperCamelCase_ :
'''simple docstring'''
def __init__( self : Any) ->str:
'''simple docstring'''
A__ = []
A__ = ... | 87 | 0 |
"""simple docstring"""
# 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... | 355 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 87 | 0 |
def UpperCamelCase__ ( UpperCAmelCase_ ) -> str:
'''simple docstring'''
return "".join(chr(ord(lowercase_ ) - 32 ) if '''a''' <= char <= '''z''' else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod() | 322 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCamelCase : int = logging.get_logger("""transformers.models.speecht5""")
def SCREAMING_SNAKE_CASE ( lowercase_ , ... | 87 | 0 |
"""simple docstring"""
class snake_case :
def __init__( self : Dict , UpperCamelCase__ : Dict , UpperCamelCase__ : Optional[Any] , UpperCamelCase__ : Union[str, Any])-> str:
'''simple docstring'''
__lowerCAmelCase: ... | 346 |
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 ModelTest... | 87 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE_ = {
"""configuration_blip""": [
"""BLIP_PRETRAI... | 373 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
_lowerCamelCase : int = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE ( lowercase_ , low... | 87 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase : Optional[Any] = {"""configuration_yolos""": ["""YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """YolosConfig""", """YolosOnnxConfig"""]}
try:
if n... | 542 |
class UpperCamelCase_ : # Public class to implement a graph
'''simple docstring'''
def __init__( self : str , UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : list[list[bool]]) ->None:
'''simple docstring'''... | 87 | 0 |
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class SCREAMING_SNAKE_CASE ( pl.LightningModule ):
'''simple docstring'''
def __init__( ... | 517 |
from __future__ import annotations
import requests
_lowerCamelCase : str = set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories c... | 87 | 0 |
'''simple docstring'''
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
_lowerCAmelCase = """scheduler_config.json"""
class ... | 432 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class UpperCamelCase_ ( unittest.TestCase ):
'''simple docstring'''
UpperCAmelCase__ = JukeboxTokenizer
UpperCAmelCase__ = {
'''artist''': '''Z... | 87 | 0 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_SCREAMING_SNAKE_CASE : int = logging.get_logger("transformers.models.speecht5")
def UpperCamelCase_( snake_cas... | 400 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : str = logging.get_logger(__name__)
_lowerCamelCase : List[str] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class UpperCamelCase... | 87 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependency... | 138 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def SCREAMING_SNAKE_CASE ( ) -> None:
"""simple docstring"""
assert or_gate(0 , 0 ) == 0
... | 87 | 0 |
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen
from ..table im... | 324 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import torch.nn as nn
from ... | 87 | 0 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, 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, ra... | 140 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
_lowerCamelCase : str = 299792458
# Symbols
_lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase : int = symbols("""ct x y z""")
def... | 87 | 0 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
UpperCamelCase__ :Optional[int] = input("""Enter image url: """).strip()
print(F"""Downloading image from {url} ...""")
UpperCamelCase__ :Union[str, Any] ... | 355 |
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
A__ = []
def generate(lowercase_ , lowercase_ ):
if k == 1:
res.append... | 87 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ = {
"""configuration_pix2struct""": [
"""PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Pix2StructConfig""",
"""P... | 322 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIFICAT... | 87 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class snake... | 346 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : Any = {"""configuration_xlnet""": ["""XLNET_PRETRAINED_CONFI... | 87 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/main/config.jso... | 373 |
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 : Optional[Any] = logging.get_logger(__name__)
_lowerCamelCase : ... | 87 | 0 |
def snake_case__ ( lowerCamelCase_ ):
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
A : Optional[Any] = []
def generate(lowerCamelCase_ , lowerCamelCase_ ):
if k == 1:
res.append(tuple... | 542 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
fro... | 87 | 0 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SN... | 517 |
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> dict:
"""simple docstring"""
A__ = f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return requests.get(lowercase_ ).json()
def... | 87 | 0 |
'''simple docstring'''
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 UpperCamelCase ( ... | 432 |
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen
from ..table impo... | 87 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.te... | 400 |
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMod... | 87 | 0 |
'''simple docstring'''
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB... | 138 |
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 torc... | 87 | 0 |
import math
from collections.abc import Callable
def UpperCamelCase ( _A, _A, _A ):
"""simple docstring"""
__magic_name__ : List[str] = xa
__magic_name__ : List[Any] = xa
while True:
if x_n == x_na or function(lowerca... | 324 |
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
_lowerCamelCase : Dict = 6_378_137.0
_lowerCamelCase : Union[str, Any] = 6_356_752.314_245
_lowerCamelCase : List[Any] = 6378137
def SCREAMING_SNAKE_CASE ... | 87 | 0 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class lowerCamelCase (UpperCAmelCase__ ):
"""simple docstring"""
lowerCamelCase__ = '''EncodecFeatureExtractor'''
lowerCamelCase__ = ('''T5Tokenizer''',... | 140 |
import heapq
import sys
import numpy as np
_lowerCamelCase : Any = tuple[int, int]
class UpperCamelCase_ :
'''simple docstring'''
def __init__( self : Any) ->str:
'''simple docstring'''
A__ = []
A__ = ... | 87 | 0 |
"""simple docstring"""
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
... | 355 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 87 | 0 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class UpperCAmelCase__ ( unittest.TestCase ):
'''simple docstring'''
UpperCAmelCase_ = JukeboxTokenizer
UpperCAmelCase_ = {
'''artist''': '''Zac Brown Band'''... | 322 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCamelCase : int = logging.get_logger("""transformers.models.speecht5""")
def SCREAMING_SNAKE_CASE ( lowercase_ , ... | 87 | 0 |
"""simple docstring"""
from itertools import count
def a__ ( __SCREAMING_SNAKE_CASE = 5_0 ) -> int:
__lowerCAmelCase: Any = [1] * min_block_length
for n in count(lowercase_ ):
fill_count_functions.append(1 )
for block_length... | 346 |
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 ModelTest... | 87 | 0 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowercase__ ( lowerCAmelCase : Optional[int] ) -> Dict:
"""simple docstring"""
return ConvertComman... | 373 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
_lowerCamelCase : int = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE ( lowercase_ , low... | 87 | 0 |
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
lowercase : Dict = """src/transformers"""
lowercase : Tuple ... | 542 |
class UpperCamelCase_ : # Public class to implement a graph
'''simple docstring'''
def __init__( self : str , UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : list[list[bool]]) ->None:
'''simple docstring'''... | 87 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE ( metaclass=UpperCAmelCase__ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Union[str, Any] = ['''flax''']
def __init__( self : int... | 517 |
from __future__ import annotations
import requests
_lowerCamelCase : str = set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories c... | 87 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""facebook/... | 432 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class UpperCamelCase_ ( unittest.TestCase ):
'''simple docstring'''
UpperCAmelCase__ = JukeboxTokenizer
UpperCAmelCase__ = {
'''artist''': '''Z... | 87 | 0 |
'''simple docstring'''
from scipy.stats import spearmanr
import datasets
_SCREAMING_SNAKE_CASE : List[Any] = """
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 and +1 with 0... | 400 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : str = logging.get_logger(__name__)
_lowerCamelCase : List[str] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class UpperCamelCase... | 87 | 0 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import cla... | 138 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def SCREAMING_SNAKE_CASE ( ) -> None:
"""simple docstring"""
assert or_gate(0 , 0 ) == 0
... | 87 | 0 |
from __future__ import annotations
__magic_name__: int = 10
def UpperCamelCase ( _A ):
"""simple docstring"""
__magic_name__ : str = 1
__magic_name__ : int = max(lowercase_ )
while placement <= max_digit:
# declar... | 324 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import torch.nn as nn
from ... | 87 | 0 |
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def a__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ):
if openai_co... | 140 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
_lowerCamelCase : str = 299792458
# Symbols
_lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase : int = symbols("""ct x y z""")
def... | 87 | 0 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
f... | 355 |
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
A__ = []
def generate(lowercase_ , lowercase_ ):
if k == 1:
res.append... | 87 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENT... | 322 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIFICAT... | 87 | 0 |
"""simple docstring"""
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
__A = """sshleifer/bart-... | 346 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : Any = {"""configuration_xlnet""": ["""XLNET_PRETRAINED_CONFI... | 87 | 0 |
"""simple docstring"""
SCREAMING_SNAKE_CASE_ = {
"""Pillow""": """Pillow<10.0.0""",
"""accelerate""": """accelerate>=0.20.3""",
"""av""": """av==9.2.0""",
"""beautifulsoup4""": """beautifulsoup4""",
"""black""": """black~=23.1""",
"""codecarbon""": """codecarbon==1.2.0""... | 373 |
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 : Optional[Any] = logging.get_logger(__name__)
_lowerCamelCase : ... | 87 | 0 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
lowercase : Optional[Any] = logging.get_logger(__name__)
def snake_case__ ( lowerCamelCase_ ):
... | 542 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
fro... | 87 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (... | 517 |
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> dict:
"""simple docstring"""
A__ = f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return requests.get(lowercase_ ).json()
def... | 87 | 0 |
'''simple docstring'''
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_tr... | 432 |
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen
from ..table impo... | 87 | 0 |
'''simple docstring'''
import numpy as np
def UpperCamelCase_( snake_case : int , snake_case : List[Any] ):
'''simple docstring'''
return np.where(vector > 0 , lowercase_ , (alpha * (np.exp(lowercase_ ) - 1)) )
if __name__ == "__main__":
im... | 400 |
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMod... | 87 | 0 |
'''simple docstring'''
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
snake_case_ : Union[str, Any] = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Mach... | 138 |
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 torc... | 87 | 0 |
from __future__ import annotations
__magic_name__: Tuple = tuple[int, int, int]
__magic_name__: Union[str, Any] = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
__magic_name__: List[Any] = """ABCDEFGHIJKLMNOPQRSTUVWXYZ"""
# -----... | 324 |
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
_lowerCamelCase : Dict = 6_378_137.0
_lowerCamelCase : Union[str, Any] = 6_356_752.314_245
_lowerCamelCase : List[Any] = 6378137
def SCREAMING_SNAKE_CASE ... | 87 | 0 |
import os
def a__ ( __UpperCamelCase = "matrix.txt" ):
with open(os.path.join(os.path.dirname(lowercase_ ) , lowercase_ ) ) as in_file:
SCREAMING_SNAKE_CASE_ = in_file.read()
SCREAMING_SNAKE_CASE_ = [[int(lowercase_ ) for cell in row.split("," )] for row... | 140 |
import heapq
import sys
import numpy as np
_lowerCamelCase : Any = tuple[int, int]
class UpperCamelCase_ :
'''simple docstring'''
def __init__( self : Any) ->str:
'''simple docstring'''
A__ = []
A__ = ... | 87 | 0 |
"""simple docstring"""
from __future__ import annotations
import requests
def A_ ( snake_case__ ) -> dict:
_UpperCamelCase :Any = f"https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"
return requests.get(lowercase_ ).json()
def A_ ( ... | 355 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 87 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = ... | 322 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCamelCase : int = logging.get_logger("""transformers.models.speecht5""")
def SCREAMING_SNAKE_CASE ( lowercase_ , ... | 87 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A = {
"""configuration_convnext""": ["""CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP"... | 346 |
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 ModelTest... | 87 | 0 |
"""simple docstring"""
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetF... | 373 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
_lowerCamelCase : int = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE ( lowercase_ , low... | 87 | 0 |
from __future__ import annotations
from collections import namedtuple
def snake_case__ ( lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase_ ):
A : Optional[int] = namedtuple('''result''' , '''name value''' )
if (voltage, current,... | 542 |
class UpperCamelCase_ : # Public class to implement a graph
'''simple docstring'''
def __init__( self : str , UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : list[list[bool]]) ->None:
'''simple docstring'''... | 87 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
Diffusio... | 517 |
from __future__ import annotations
import requests
_lowerCamelCase : str = set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories c... | 87 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils i... | 432 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class UpperCamelCase_ ( unittest.TestCase ):
'''simple docstring'''
UpperCAmelCase__ = JukeboxTokenizer
UpperCAmelCase__ = {
'''artist''': '''Z... | 87 | 0 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def UpperCamelCase_( snake_case : str ):
'''simple docstring'''
def wrapper(*snake_case : Tuple , ... | 400 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : str = logging.get_logger(__name__)
_lowerCamelCase : List[str] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class UpperCamelCase... | 87 | 0 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class A_ ( unittest.TestCase ):
'''simple docstring'''
def a ( self ):
_UpperCamelCase = Vector([1, 2,... | 138 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def SCREAMING_SNAKE_CASE ( ) -> None:
"""simple docstring"""
assert or_gate(0 , 0 ) == 0
... | 87 | 0 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__magic_name__: List[str] = logging.get_logg... | 324 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import torch.nn as nn
from ... | 87 | 0 |
from __future__ import annotations
A : int = [True] * 1_00_00_01
A : Optional[int] = 2
while i * i <= 1_00_00_00:
if seive[i]:
for j in range(i * i, 1_00_00_01, i):
A : Optional[int] = False
i += 1
def a__ ( __UpperCamelCase ... | 140 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
_lowerCamelCase : str = 299792458
# Symbols
_lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase : int = symbols("""ct x y z""")
def... | 87 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ :Any = {"""configuration_xlnet""": ["""XLNE... | 355 |
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
A__ = []
def generate(lowercase_ , lowercase_ ):
if k == 1:
res.append... | 87 | 0 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
UpperCamelCase__ = datasets.logging.get_logger(__name__)
UpperCamelCase__ = """\
@InProceedings{moosavi2019minimum,... | 322 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIFICAT... | 87 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vis... | 346 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : Any = {"""configuration_xlnet""": ["""XLNET_PRETRAINED_CONFI... | 87 | 0 |
"""simple docstring"""
import heapq
import sys
import numpy as np
SCREAMING_SNAKE_CASE_ = tuple[int, int]
class _UpperCAmelCase :
def __init__( self ) -> str:
UpperCAmelCase = []
UpperCAmelCase = set()
... | 373 |
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 : Optional[Any] = logging.get_logger(__name__)
_lowerCamelCase : ... | 87 | 0 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
lowercase : str = pd.read_csv("sample_data.csv", header=None)
lowercase : List[... | 542 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
fro... | 87 | 0 |
'''simple docstring'''
from manim import *
class SCREAMING_SNAKE_CASE ( UpperCAmelCase__ ):
'''simple docstring'''
def __UpperCAmelCase ( self : List[str] ):
"""simple docstring"""
_snake_case : Any = Recta... | 517 |
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> dict:
"""simple docstring"""
A__ = f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return requests.get(lowercase_ ).json()
def... | 87 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowerCAmelCase = {
"""configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_... | 432 |
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen
from ..table impo... | 87 | 0 |
'''simple docstring'''
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
_SCREAMING_SNAKE_CASE : Optional[Any] ... | 400 |
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMod... | 87 | 0 |
'''simple docstring'''
class A_ : # Public class to implement a graph
'''simple docstring'''
def __init__( self , A_ , A_ , A_ ):
_UpperCamelCase = row
_UpperCamelCase = col
_UpperCamelCase = graph
def a ... | 138 |
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 torc... | 87 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__magic_name__: Any = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__magi... | 324 |
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
_lowerCamelCase : Dict = 6_378_137.0
_lowerCamelCase : Union[str, Any] = 6_356_752.314_245
_lowerCamelCase : List[Any] = 6378137
def SCREAMING_SNAKE_CASE ... | 87 | 0 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A : Dict = logging.get_logger(__name__)
A : Union[str, Any] = {
"""vocab_file""": """vocab.json""",
"""merges_file""":... | 140 |
import heapq
import sys
import numpy as np
_lowerCamelCase : Any = tuple[int, int]
class UpperCamelCase_ :
'''simple docstring'''
def __init__( self : Any) ->str:
'''simple docstring'''
A__ = []
A__ = ... | 87 | 0 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Th... | 355 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 87 | 0 |
import math
def UpperCamelCase__ ( UpperCAmelCase_ = 100 ) -> int:
'''simple docstring'''
_lowercase : Dict = sum(i * i for i in range(1 , n + 1 ) )
_lowercase : List[str] = int(math.pow(sum(range(1 ... | 322 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCamelCase : int = logging.get_logger("""transformers.models.speecht5""")
def SCREAMING_SNAKE_CASE ( lowercase_ , ... | 87 | 0 |
"""simple docstring"""
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
__A = TypeVar("T")
class snake_case ( Generic[T]... | 346 |
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 ModelTest... | 87 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diff... | 373 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
_lowerCamelCase : int = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE ( lowercase_ , low... | 87 | 0 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class __lowercase :
"""simple docstring"""
def __init__( self , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCA... | 542 |
class UpperCamelCase_ : # Public class to implement a graph
'''simple docstring'''
def __init__( self : str , UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : list[list[bool]]) ->None:
'''simple docstring'''... | 87 | 0 |
'''simple docstring'''
import re
def lowerCamelCase__ ( a__) -> str:
"""simple docstring"""
if len(re.findall('[ATCG]' , lowercase_)) != len(lowercase_):
raise ValueError('Invalid Strand')
return dna.translate(dna.maketrans('ATCG' , 'TAGC'))
if __name__... | 517 |
from __future__ import annotations
import requests
_lowerCamelCase : str = set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories c... | 87 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
"""feature_extraction_mctct""": ["""MC... | 432 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class UpperCamelCase_ ( unittest.TestCase ):
'''simple docstring'''
UpperCAmelCase__ = JukeboxTokenizer
UpperCAmelCase__ = {
'''artist''': '''Z... | 87 | 0 |
'''simple docstring'''
import math
from collections.abc import Iterator
from itertools import takewhile
def UpperCamelCase_( snake_case : Union[str, Any] ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif numb... | 400 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : str = logging.get_logger(__name__)
_lowerCamelCase : List[str] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class UpperCamelCase... | 87 | 0 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, 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 ...tes... | 138 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def SCREAMING_SNAKE_CASE ( ) -> None:
"""simple docstring"""
assert or_gate(0 , 0 ) == 0
... | 87 | 0 |
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