code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def lowercase ( A_ )-> Optional[int]:
'''simple docstring'''
a : str = [
... | 40 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import P... | 46 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A : str ={
'''configuration_x_clip''': [
'''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''XCLIPConfig''',
... | 41 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import ... | 46 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( __A = "The quick brown fox jumps over the lazy dog" , ) -> bool:
_snake_case = set()
# Replace all the whitespace in our sentence
_snake_case = input_str.replace(' ' , '' )
for alpha in input_str:
if "a" <= alpha.... | 42 |
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = {
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "... | 46 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase = {'''configuration_xglm''': ['''XGLM_PRETRAINED_CONFI... | 43 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
... | 46 | 0 |
"""simple docstring"""
import argparse
import json
from tqdm import tqdm
def SCREAMING_SNAKE_CASE ( ) -> int:
_lowerCAmelCase : Tuple = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"""--src_path""" ,type=_lowerCamelCase ,defau... | 44 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, 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 ... | 46 | 0 |
"""simple docstring"""
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipeline... | 45 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import ... | 46 | 0 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _lowerCAmelCase ( _UpperCamelCase : Dict , _UpperCamelCase : Any=False ) -> Optional[Any]:
"""simple docstring"""
... | 47 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_... | 46 | 0 |
import numpy as np
from transformers import Pipeline
def A ( _SCREAMING_SNAKE_CASE ) -> Optional[int]:
lowerCamelCase : Dict = np.max(_SCREAMING_SNAKE_CASE ,axis=-1 ,keepdims=_SCREAMING_SNAKE_CASE )
lowerCamelCase : Dict = np.exp(outputs -... | 48 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torc... | 46 | 0 |
from abc import ABC, abstractmethod
from typing import List, Optional
class _A ( __UpperCAmelCase ):
def __init__( self : Optional[int]):
'''simple docstring'''
self.test()
def _lowerCamelCase ( self : int):
'''simple ... | 49 |
"""simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
SCREAMING_SNAKE_CASE__ = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n ... | 46 | 0 |
from __future__ import annotations
from typing import Any
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase ) -> None:
create_state_space_tree(_UpperCAmelCase , [] , 0 )
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase )... | 50 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
S... | 46 | 0 |
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
... | 51 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for... | 46 | 0 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import HeunDiscreteScheduler
fro... | 52 |
"""simple docstring"""
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__) # pylint: disable=invalid-name
... | 46 | 0 |
'''simple docstring'''
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class snake_case ( unittest.TestCase ):
"""s... | 53 |
"""simple docstring"""
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..tab... | 46 | 0 |
"""simple docstring"""
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
... | 54 |
"""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()
SCREAM... | 46 | 0 |
'''simple docstring'''
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup... | 55 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWaterm... | 46 | 0 |
'''simple docstring'''
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 acceler... | 56 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, ge... | 46 | 0 |
"""simple docstring"""
import numpy as np
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = int(np.ceil((x_end - xa) / h ) )
__lowerCAmelCase = np.z... | 57 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase )
class lowercase ( _UpperCAmelCase ):
_SCREAMING_SNAKE_CASE = field(def... | 46 | 0 |
'''simple docstring'''
import sys
lowercase_ = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""66896648... | 58 |
"""simple docstring"""
import re
import string
import numpy as np
import datasets
SCREAMING_SNAKE_CASE__ = "\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n"
SCREAMING_SNAKE_CASE__ = "\... | 46 | 0 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def Up... | 59 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
return [ord(SCREAMING_SNAKE_CASE ) - 96 for elem in plain]
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : l... | 46 | 0 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
snake_case__ : List[Any] = '''examples/'''
snake_case__ : int = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init... | 60 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDepen... | 46 | 0 |
"""simple docstring"""
import os
def __a ( __lowerCamelCase ):
UpperCAmelCase_ : List[Any] = len(grid[0] )
UpperCAmelCase_ : Tuple = len(__lowerCamelCase )
UpperCAmelCase_ : List[Any] = 0
UpperCAmelCase_ : List[str] ... | 61 |
"""simple docstring"""
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
while b:
lowerCAmelCase , lowerCAmelCase = b, a % b
return a
def UpperCAmel... | 46 | 0 |
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax import jit
from transform... | 62 |
"""simple docstring"""
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
SCREAMING_SNAKE_CASE__ = "▁"
SCREAMING_SNAKE_CASE__ = {"vocab_file":... | 46 | 0 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers... | 63 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import P... | 46 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : list[int] ):
"""simple docstring"""
_snake_case : Optional[Any] = []
if len(snake_case__ ) == 1:
return [nums.copy()]
for _ in range(len(snake_case__ ) ):
_snake_case ... | 64 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import ... | 46 | 0 |
from __future__ import annotations
from collections import namedtuple
def lowerCAmelCase_ ( __A, __A, __A ) -> tuple:
'''simple docstring'''
UpperCAmelCase__ = namedtuple("result", "name value" )
if (voltage, current, power).count(0... | 65 |
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = {
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "... | 46 | 0 |
"""simple docstring"""
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
... | 66 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
... | 46 | 0 |
'''simple docstring'''
def __lowerCAmelCase ( ) -> int:
return [
a * b * (10_00 - a - b)
for a in range(1 , 9_99 )
for b in range(UpperCamelCase__ , 9_99 )
if (a * a + b * b == (10_00 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(f'{solution(... | 67 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, 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 ... | 46 | 0 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
lowerCAmelCase__ = [
"""Prosecutor: \"No videos were used in the crash investigation\" German papers say they saw a cell phone video of the... | 68 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import ... | 46 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def UpperCAmelCase ( UpperCAmelCase , UpperCAmelCase ) -> float:
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(UpperCAmelCase , ... | 69 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_... | 46 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : int =logging.get_logger(__name__)
A__ : Union[str, Any] ={
'''tiiuae/falcon-40b''': '''https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.jso... | 70 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torc... | 46 | 0 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert imp... | 71 |
"""simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
SCREAMING_SNAKE_CASE__ = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n ... | 46 | 0 |
"""simple docstring"""
from math import isqrt, loga
def snake_case_ ( A_ : int ):
'''simple docstring'''
_lowerCamelCase : Optional[Any] = [True] * max_number
for i in range(2, isqrt(max_number - 1 ) + 1 ):
if is... | 72 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
S... | 46 | 0 |
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch_available():
... | 73 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for... | 46 | 0 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def _snake_case ( snake_case__ : Dict ):
A = [
'encoder.version',
'decoder.version',
'model.encoder.version',
'model... | 74 |
"""simple docstring"""
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__) # pylint: disable=invalid-name
... | 46 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : List[str] = logging.get_logger(__name__)
a_ : Dict = {
"""microsoft/unispeech-large-1500h-cv""": (
"""htt... | 75 |
"""simple docstring"""
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..tab... | 46 | 0 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
a_ = '\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and Collin Burns\n and Saurav Kadavath\n and Akul Arora\n and Steven ... | 76 |
"""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()
SCREAM... | 46 | 0 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def a_ ( _lowerCAmelCase : int = 150_0000 ):
'''simple docstring'''
lowercase__ : defaultdict = defaultdict(_lowerCAmelCase )
lowercase__ : int = 2
while 2 ... | 77 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWaterm... | 46 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ ):
UpperCAmelCase = [0] * len(lowercase_ )
for i in range(1 , len(lowercase_ ) ):
# use last results for better performance - dynamic programming
UpperCAmelCase ... | 78 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, ge... | 46 | 0 |
'''simple docstring'''
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig... | 79 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase )
class lowercase ( _UpperCAmelCase ):
_SCREAMING_SNAKE_CASE = field(def... | 46 | 0 |
'''simple docstring'''
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy... | 80 |
"""simple docstring"""
import re
import string
import numpy as np
import datasets
SCREAMING_SNAKE_CASE__ = "\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n"
SCREAMING_SNAKE_CASE__ = "\... | 46 | 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()
lowerCamelCase_ ... | 81 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
return [ord(SCREAMING_SNAKE_CASE ) - 96 for elem in plain]
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : l... | 46 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
A__ = {"""configuration_beit""": ["""BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BeitConfig""", """BeitOnnxConfig"""]}
... | 82 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDepen... | 46 | 0 |
'''simple docstring'''
from __future__ import annotations
class lowercase__ :
def __init__( self : Optional[int] ,lowerCamelCase__ : Union[str, Any]=None ):
'''simple docstring'''
_UpperCamelCase : Union[str, Any] = data
_UpperCamelCase : ... | 83 |
"""simple docstring"""
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
while b:
lowerCAmelCase , lowerCAmelCase = b, a % b
return a
def UpperCAmel... | 46 | 0 |
"""simple docstring"""
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from d... | 84 |
"""simple docstring"""
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
SCREAMING_SNAKE_CASE__ = "▁"
SCREAMING_SNAKE_CASE__ = {"vocab_file":... | 46 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def UpperCamelCase_( snake_case : str , snake_case : str ):
'''simple docstring'''
snake_case_ = list(snake_case... | 85 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import P... | 46 | 0 |
"""simple docstring"""
import os
from pathlib import Path
def __lowerCAmelCase ():
from torch.utils.cpp_extension import load
__lowerCAmelCase : Dict = Path(_UpperCamelCase ).resolve().parent.parent.parent / 'kernels' / 'deformable_detr'
__lowerCAmelCase : int = ... | 86 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import ... | 46 | 0 |
# flake8: noqa
# Lint as: python3
UpperCamelCase = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disable_... | 87 |
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = {
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "... | 46 | 0 |
def a__ ( A_ ):
'''simple docstring'''
if n_term == "":
return []
__magic_name__ = []
for temp in range(int(A_ ) ):
series.append(f'''1/{temp + 1}''' if series else """1""" )
return series
if __name__ == "__main__":
__lowe... | 88 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
... | 46 | 0 |
'''simple docstring'''
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 ...tes... | 89 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, 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 ... | 46 | 0 |
import argparse
import gc
import json
import os
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 accelerat... | 90 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import ... | 46 | 0 |
"""simple docstring"""
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def _A (__a , __a , __a ) -> Union[str, Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : int = ('... | 91 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_... | 46 | 0 |
from __future__ import annotations
def _a ( SCREAMING_SNAKE_CASE_ : list[int] ):
if len(SCREAMING_SNAKE_CASE_ ) == 0:
return array
__lowerCAmelCase , __lowerCAmelCase = min(SCREAMING_SNAKE_CASE_ ), max(SCREAMING_SNAKE_CASE_ )
... | 92 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torc... | 46 | 0 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_u... | 93 |
"""simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
SCREAMING_SNAKE_CASE__ = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n ... | 46 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
ImageInput,
PILImageResampl... | 94 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
S... | 46 | 0 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, 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_... | 95 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for... | 46 | 0 |
"""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
lowercase__ = logging.get_logger(__name_... | 96 |
"""simple docstring"""
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__) # pylint: disable=invalid-name
... | 46 | 0 |
'''simple docstring'''
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable... | 97 |
"""simple docstring"""
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..tab... | 46 | 0 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for test... | 98 |
"""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()
SCREAM... | 46 | 0 |
def A_ ( A__ = 1000 ) -> int:
return sum(e for e in range(3 , A__ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"""{solution() = }""")
| 99 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWaterm... | 46 | 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
__magic_name__ = TypeVar("T")
class SCREAMING_SNAKE_CASE_ ( Generic[T] ):
... | 100 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, ge... | 46 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pipeli... | 101 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase )
class lowercase ( _UpperCAmelCase ):
_SCREAMING_SNAKE_CASE = field(def... | 46 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils... | 102 |
"""simple docstring"""
import re
import string
import numpy as np
import datasets
SCREAMING_SNAKE_CASE__ = "\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n"
SCREAMING_SNAKE_CASE__ = "\... | 46 | 0 |
from maths.prime_check import is_prime
def UpperCamelCase( __UpperCamelCase : int ):
if not isinstance(__UpperCamelCase ,__UpperCamelCase ):
lowerCAmelCase_ : Union[str, Any] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(__UpperCamelCase )
if... | 103 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
return [ord(SCREAMING_SNAKE_CASE ) - 96 for elem in plain]
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : l... | 46 | 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 M... | 104 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDepen... | 46 | 0 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
... | 105 |
"""simple docstring"""
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
while b:
lowerCAmelCase , lowerCAmelCase = b, a % b
return a
def UpperCAmel... | 46 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 106 |
"""simple docstring"""
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
SCREAMING_SNAKE_CASE__ = "▁"
SCREAMING_SNAKE_CASE__ = {"vocab_file":... | 46 | 0 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a ni... | 107 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import P... | 46 | 0 |
"""simple docstring"""
def a__ ( SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
return " ".join(
"".join(word[::-1] ) if len(SCREAMING_SNAKE_CASE ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.t... | 108 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import ... | 46 | 0 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
... | 109 |
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = {
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "... | 46 | 0 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils im... | 110 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
... | 46 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"""facebook/data2vec-text-bas... | 241 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, 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 ... | 46 | 0 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_available, is_visi... | 59 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import ... | 46 | 0 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class _lowerCamelCase ( _UpperCAmelCase ):
"""simple docstring"""
def _snake_case ( self )->str:
'''simple docstring'''
retur... | 186 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_... | 46 | 0 |
from __future__ import annotations
import unittest
from transformers import LEDConfig, 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
from ...test_pipeline_mixin i... | 124 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torc... | 46 | 0 |
'''simple docstring'''
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
fr... | 151 |
"""simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
SCREAMING_SNAKE_CASE__ = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n ... | 46 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
... | 224 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
S... | 46 | 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_ = {
"configurat... | 251 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for... | 46 | 0 |
def __SCREAMING_SNAKE_CASE ( snake_case_ ):
'''simple docstring'''
def merge(snake_case_ , snake_case_ ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
... | 133 |
"""simple docstring"""
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__) # pylint: disable=invalid-name
... | 46 | 0 |
import sys
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Tuple ) -> Tuple:
'''simple docstring'''
A__ = len(SCREAMING_SNAKE_CASE_ )
A__ = [[0 for x in range(SCREAMING_SNAKE_CASE_ )] for x in range(SCREAMING_SNAKE_CASE_ )]
A__ = [[0 for x ... | 68 |
"""simple docstring"""
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..tab... | 46 | 0 |
"""simple docstring"""
from decimal import Decimal, getcontext
from math import ceil, factorial
def UpperCamelCase ( _lowerCAmelCase : int ) -> Optional[Any]:
if not isinstance(_lowerCAmelCase, _lowerCAmelCase ):
raise TypeError("""Undefined for non-integers"""... | 246 |
"""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()
SCREAM... | 46 | 0 |
"""simple docstring"""
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
__UpperCamelCase = WebClient(token=os.environ['''CI_SLACK_BOT_TOKEN'''])
def... | 113 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWaterm... | 46 | 0 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import Tenso... | 241 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, ge... | 46 | 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,
AutoModelForSequenceClassifica... | 59 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase )
class lowercase ( _UpperCAmelCase ):
_SCREAMING_SNAKE_CASE = field(def... | 46 | 0 |
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
A_ : List[Any] = get_failure_array(SCREAMING_SNAKE_CASE )
# 2) Step through text searching for pattern
A_ , A_ : Optional[Any] = 0, 0 #... | 186 |
"""simple docstring"""
import re
import string
import numpy as np
import datasets
SCREAMING_SNAKE_CASE__ = "\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n"
SCREAMING_SNAKE_CASE__ = "\... | 46 | 0 |
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
lowerCamelCase : Any = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE__ ( lowercase ) -> int:
snake_ca... | 124 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
return [ord(SCREAMING_SNAKE_CASE ) - 96 for elem in plain]
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : l... | 46 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae im... | 151 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDepen... | 46 | 0 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ) -> List[str]:
"""simple docstring"""
while b:
lowerCAmelCase_ ,lowerCAmelCase_ : int = b, a % b
return a
def Up... | 224 |
"""simple docstring"""
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
while b:
lowerCAmelCase , lowerCAmelCase = b, a % b
return a
def UpperCAmel... | 46 | 0 |
'''simple docstring'''
from collections import namedtuple
import requests
from lxml import html # type: ignore
UpperCamelCase_ = namedtuple("covid_data", "cases deaths recovered")
def lowercase__( __UpperCamelCase: str = "https://www.worldometers.info/coronavirus/"... | 251 |
"""simple docstring"""
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
SCREAMING_SNAKE_CASE__ = "▁"
SCREAMING_SNAKE_CASE__ = {"vocab_file":... | 46 | 0 |
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
@maybe_allow_in_graph
... | 133 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import P... | 46 | 0 |
from math import isclose, sqrt
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: float , SCREAMING_SNAKE_CASE_: float , SCREAMING_SNAKE_CASE_: float ) -> Tuple:
'''simple docstring'''
A__ = point_y / 4 / point_x
A__ = 2 * normal_gradient / (1 ... | 68 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import ... | 46 | 0 |
"""simple docstring"""
def UpperCamelCase ( _lowerCAmelCase : list[int] ) -> List[str]:
if not numbers:
return 0
if not isinstance(_lowerCAmelCase, (list, tuple) ) or not all(
isinstance(_lowerCAmelCase, _lowerCAmelCase ) for number in numbers... | 246 |
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = {
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "... | 46 | 0 |
"""simple docstring"""
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageCl... | 113 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
... | 46 | 0 |
"""simple docstring"""
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
lowercase__ = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input("""Sea... | 241 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, 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 ... | 46 | 0 |
def UpperCamelCase ( __lowerCamelCase : int = 10**12 ):
snake_case : Union[str, Any] = 1
snake_case : int = 0
snake_case : int = 1
snake_case : int = 1
while numerator <= 2 * min_to... | 59 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import ... | 46 | 0 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
A_ : Union[str, Any] = int(SCREAMING_SNAKE_CASE ... | 186 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_... | 46 | 0 |
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class __lowercase (_UpperCAmelCase ):
"""simple docstring"""
def UpperCAmelCase ( self , A ) -> List[str]:
with open(A , encoding="... | 124 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torc... | 46 | 0 |
'''simple docstring'''
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_comman... | 151 |
"""simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
SCREAMING_SNAKE_CASE__ = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n ... | 46 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=_UpperCAmelCase ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = ["""flax"""]
def __init__( self : ... | 224 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
S... | 46 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e im... | 251 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for... | 46 | 0 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class __lowerCAmelCase ( _UpperCAmelCase ):
def __init__( self : Op... | 133 |
"""simple docstring"""
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__) # pylint: disable=invalid-name
... | 46 | 0 |
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