code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_de... | 196 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
__lowercase : Any =(
"""4S 3H 2C 7S 5H""",
"""9D 8H 2C 6S 7H""",
"""2D 6D 9D TH 7D""",
"""TC 8C 2S JH 6C""",
"""JH 8S TH AH QH""",
"""TS KS 5S ... | 54 | 0 |
"""simple docstring"""
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
__lowercase : Dict = logging.get_logger(__name__)
def lowerCamelCase_ ( _lowerCamelCase : Any ):
l... | 66 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_availabl... | 66 | 1 |
"""simple docstring"""
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDa... | 505 |
"""simple docstring"""
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from tr... | 505 | 1 |
'''simple docstring'''
import re
import subprocess
import sys
lowerCAmelCase__ = subprocess.check_output("git merge-base main HEAD".split()).decode("utf-8")
lowerCAmelCase__ = (
subprocess.check_output(F'git diff --diff-filter=d --name-only {fork_point_sha}'.split()).decode("ut... | 713 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class lowercase ( a_ ):
pass
class lowercase :
def __init__( self , _snake_case) -> None:
UpperCAmelCase_ : Any = data
Up... | 471 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
def UpperCAmelCase_ ( __a : int ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1,... | 437 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
a_ = re.compile(r"""([A-Z]+)([A-Z][a-z])""")
a_ = re.compile(r"""([a-z\d])([A-Z])""")
a_ = re.compile(r"""(?<!_)_(?!_)""")
a_ = re.compile(r"""(_{2,})""")
a_ = r"""^\w+(\.\w+)*$"""
... | 437 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from... | 701 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"bert-base-uncased": "https://huggingface.co/bert-ba... | 561 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCAmelCase_ : int = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],
}
try:
... | 21 | '''simple docstring'''
import random
def UpperCamelCase_ ( snake_case_ : int ) -> bool:
'''simple docstring'''
__lowerCAmelCase = num - 1
__lowerCAmelCase = 0
while s % 2 == 0:
__lowerCAmelCase = s // 2
t += 1
for _ in range(... | 427 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, ... | 487 |
"""simple docstring"""
from manim import *
class a__ ( __magic_name__ ):
def a_ ( self : str):
"""simple docstring"""
__UpperCAmelCase : List[str] = Rectangle(height=0.5 , width=0.5)
__UpperCAmelCase : List[str] = Rectangle(heigh... | 487 | 1 |
def lowerCamelCase__ ( _lowercase , _lowercase ):
'''simple docstring'''
if density <= 0:
raise ValueError('''Impossible fluid density''' )
if bulk_modulus <= 0:
raise ValueError('''Impossible bulk modulus''' )
return (bulk_modulus / density) ** 0.5
if __name... | 30 |
"""simple docstring"""
from math import ceil, sqrt
def lowercase__ ( lowerCAmelCase : int = 1_000_000 ) -> int:
"""simple docstring"""
UpperCAmelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if o... | 373 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A__ = {
"configuration_blenderbot_small": [
"BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCH... | 717 |
from __future__ import annotations
def _lowercase ( a_ : list[int] ) -> int:
'''simple docstring'''
if not nums:
return 0
__magic_name__ = nums[0]
__magic_name__ = 0
for num in nums[1:]:
__magic_name__, __magic_name... | 184 | 0 |
from collections.abc import Sequence
def lowerCamelCase_ ( lowerCAmelCase__ : Sequence[int] | None = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
A = n... | 106 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
__lowerCAmelCase = TypeVar("""T""")
class lowerCamelCase_ ( Generic[T] ):
__lowercase : deque[T] # Cache store of keys
__lowercase : set[T] # References of the... | 147 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Generic, TypeVar
_lowercase = TypeVar("""T""")
class UpperCAmelCase_ ( Generic[T] ):
'''simple docstring'''
def __init__( self , _lowercase ):
"""simple docstr... | 717 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
loggi... | 162 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
... | 58 | """simple docstring"""
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules... | 159 | 0 |
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
__a = (
'This metric will be removed from the library soon, metrics should be ha... | 715 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'snap-research/efficientformer-l1-300': (
'https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/... | 409 | 0 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if is_v... | 187 |
from itertools import count
def a(lowercase__ = 50 ):
'''simple docstring'''
snake_case_ = [1] * min_block_length
for n in count(lowercase__ ):
fill_count_functions.append(1 )
for block_length in range(lowercase__ , n + 1 ):
for block_start in range(n - block_len... | 187 | 1 |
from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
__UpperCAmelCase = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
__UpperCAmelCase = typing.Union[np.floataa, int, float] # noqa: UP007
def snak... | 218 |
def snake_case_ (__A : int = 1_0**9 ) -> int:
__lowerCAmelCase : Any = 1
__lowerCAmelCase : Optional[int] = 2
__lowerCAmelCase : List[Any] = 0
__lowerCAmelCase : Union[str, Any] = 0
__lowerCAmelCase :... | 218 | 1 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def UpperCamelCase ( lowercase_ : str ) -> Dict:
'''simple docstring'''
def decorator(lowercase_ : Optional[Any] ):
lowercase =getattr(lowercase_ , '''handle_key''' ... | 72 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_d... | 72 | 1 |
'''simple docstring'''
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase : Tuple ... | 712 | '''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 datasets.config import ... | 30 | 0 |
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def _lowerCamelCase( ) -> Any:
__snake_case ... | 524 | # limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
deprecate(... | 524 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def __UpperCamelCase ( _lowercase ) -> None:
_lowercase : List[Any] = analyze_text(_lowercase )
_lowercase : Any ... | 710 |
'''simple docstring'''
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def __UpperCamelCase ( _lowercase ) -> None:
_lowercase , _lowercase : List[Any] = analyze_text(_lowercase )
_lowercase ... | 4 | 0 |
"""simple docstring"""
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
SCREAMING_SNAKE_CASE_ = '''\
@inproceedings{kakwani2020indicnlpsuite,
title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Mult... | 426 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase = logging.get_logger(__name__)
lowercase = {
'''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json''',
}
class __A( UpperCAmelCa... | 272 | 0 |
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common... | 714 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 284 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__A : List[Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvail... | 394 |
'''simple docstring'''
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 lowerCAmelCase_ ( a : Tuple ):
a__ = int(a )
... | 394 | 1 |
"""simple docstring"""
def A ( snake_case__ = 50 ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start... | 616 |
"""simple docstring"""
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, S... | 616 | 1 |
'''simple docstring'''
def lowercase__( _UpperCamelCase : Union[str, Any] )-> Tuple:
"""simple docstring"""
_UpperCamelCase = [0] * len(_UpperCamelCase )
_UpperCamelCase = []
_UpperCamelCase = [1] * len(_UpperCamelCase )
for values in g... | 138 |
'''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
snake_case_ : Optional[int] = '''scheduler_config.json'... | 138 | 1 |
def lowerCAmelCase__(__snake_case ,__snake_case ) -> int:
'''simple docstring'''
if len(__snake_case ) != len(__snake_case ):
raise ValueError('''String lengths must match!''' )
lowerCamelCase__ = 0
for chara, chara in zip(__snake_case ,__snake_ca... | 29 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __A ( lowerCAmelCase ):
'''simple docstring'''
lowerCAmelCase_ = """ClapFeatureExtractor"""
lowerCAmelCase_ = ("""RobertaTokenizer""", """RobertaToken... | 29 | 1 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
t... | 9 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class _UpperCAmelCase ( snake_case_ ):
"""simple docstring"""
def __init__( self : int , __UpperCAmelCase : Optional[... | 330 | 0 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
lowerCamelCase_ : Union[str,... | 709 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase_ : Dict = {"""configuration_glpn""": ["""GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GLPNConfig"""]}
try:
if not is_vision_available():
raise Op... | 246 | 0 |
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
snake_case : Optional[int] = get_logger(__name__)
snake_case : Union[str, Any] = R"\n Args:\n input_ids (`jnp.ndarray` ... | 124 |
from typing import Dict
from .base import GenericTensor, Pipeline
class _snake_case ( snake_case ):
def SCREAMING_SNAKE_CASE ( self , _a=None , _a=None , _a=None , **_a ):
if tokenize_kwargs is None:
__magic_name__ : Tuple = {}
if tr... | 124 | 1 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
A_ = logging.get_logger(__name__)
class UpperC... | 123 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_toke... | 123 | 1 |
# Function to print upper half of diamond (pyramid)
def __lowerCAmelCase ( a__ ) -> List[str]:
for i in range(0 , a__ ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(''' ''' , end='''''' )
for _ in range(0 , i + 1... | 219 |
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
A : Any = logging.get_logger(__name__)
class __A:
def __init__( self , _snake_case , _sn... | 219 | 1 |
'''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resi... | 216 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipeline... | 216 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_snake_case : str = logging.get_logger(__name__)
_snake_case : str = {
'kssteven/ibert-roberta-b... | 81 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def __lowerCAmelCase ( __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , ):
for nxt, d in graph[v]:
if... | 226 | 0 |
import copy
import random
from transformers import CLIPTokenizer
class A__ ( _UpperCAmelCase ):
def __init__( self , *lowerCamelCase , **lowerCamelCase ) -> List[Any]:
"""simple docstring"""
super().__init__(*lowercase... | 704 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_ut... | 336 | 0 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE_ = tuple[int, int, int]
SCREAMING_SNAKE_CASE_ = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
SCREAMING_SNAKE_CASE_ = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
# -... | 523 | '''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_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_... | 523 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor... | 396 |
"""simple docstring"""
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvis... | 396 | 1 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxM... | 12 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( UpperCAmelCase_ ):
__lowerCAmelCase : int = (DDPMScheduler,)
def lowercase__ ( self , **SCREAMING_SNAKE_CASE_):
'''simple docstring'''
... | 12 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
__UpperCamelCase : str = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json... | 700 |
'''simple docstring'''
def lowercase ( lowerCAmelCase : list[list[int]] , lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : list[int]):
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
# 2. Valida... | 417 | 0 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class lowercase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
UpperCamelCase = '''MCTCTFeatureExtractor'''
UpperCam... | 82 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create... | 82 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
a_ : str ... | 710 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _snake_case ( unittest.TestCase ):
def SCREAMING_SNAKE_CASE__ ( self) -> str:
debug_launcher(test_script.main)
de... | 444 | 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_ ( __snake_case ):
def __init__( self , _lowerCAmelCase , ... | 66 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from typing import Any
class snake_case :
"""simple docstring"""
def __init__( self : Optional[int] ):
__UpperCamelCase = []
__UpperCamelCase = 0
__UpperCamelCase = 0
... | 399 | 0 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require... | 224 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__snake_case :Any ={'configuration_speech_encoder_decoder': ['SpeechEncoderDecoderConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAv... | 224 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionXLI... | 490 |
'''simple docstring'''
import operator as op
def UpperCAmelCase_ (__a : List[str] ):
"""simple docstring"""
_a : Dict = []
_a : List[str] = lambda __a , __a : int(x / y ) # noqa: E731 integer division operation
_a ... | 229 | 0 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class A_ ( snake_case_ ):
UpperCAmelCase__ = ['''image_processor''', '''feature_extractor''']
UpperCAmelCase__ = '''TvltImageProcessor'''
UpperCAmelCase__ = '''TvltFea... | 468 |
"""simple docstring"""
def _lowerCAmelCase ( __lowerCamelCase:list ):
'''simple docstring'''
__magic_name__ = len(__lowerCamelCase )
for i in range(1 , __lowerCamelCase ):
__magic_name__ = collection[i]
... | 468 | 1 |
def a__ ( lowercase__ , lowercase__ ):
'''simple docstring'''
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
... | 54 |
import re
def __UpperCamelCase ( _lowerCAmelCase ) -> str:
"""simple docstring"""
if len(re.findall("""[ATCG]""" , _lowerCAmelCase ) ) != len(_lowerCAmelCase ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans(""... | 662 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
__lowercase ... | 563 |
from __future__ import annotations
def _lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('''One and only one argumen... | 563 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vis... | 51 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : List[Any] = {'configuration_xlnet': ['XL... | 51 | 1 |
from __future__ import annotations
def UpperCAmelCase ( UpperCamelCase__ ) -> int:
'''simple docstring'''
if not nums:
return 0
__lowerCAmelCase = nums[0]
__lowerCAmelCase = 0
for num in nums[1:]:
__lowerCAmelCase ... | 704 |
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=logging.INFO
)
__A : Optional[Any] = logging.getLogger(__name__)
if __name__ == "__main__":
__A : int... | 334 | 0 |
'''simple docstring'''
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available... | 407 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase_ = {
"configuration_altclip": [
"ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"AltCLIPConfig",
"AltCLIPTextConfig",
... | 611 | 0 |
'''simple docstring'''
def __lowercase ( __SCREAMING_SNAKE_CASE ) -> List[str]:
"""simple docstring"""
__a = len(__SCREAMING_SNAKE_CASE )
while cur > 1:
# Find the maximum number in arr
__a = arr.index(max(arr[0:cur] ) )
... | 201 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE_ = {
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': ['RagTokenize... | 201 | 1 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def a ( __UpperCAmelCase : str , __UpperCAmelCase : str = "cpu" , __UpperCAmelCase : Union[str, None] = None ) -> None:
__ma... | 96 |
"""simple docstring"""
def a ( __UpperCAmelCase : List[Any] ) -> str:
__magic_name__: Optional[int] = [0] * len(__UpperCAmelCase )
__magic_name__: str = []
__magic_name__: Any = []
__magic_name__: Union[... | 96 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
SCREAMING_SNAKE_CASE__ : Optional[int] = {"""vocab_file""": """vocab.tx... | 714 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipelin... | 233 | 0 |
# This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
... | 593 | from typing import Any
import numpy as np
def lowerCamelCase_ ( UpperCamelCase__ : np.ndarray ):
'''simple docstring'''
return np.array_equal(UpperCamelCase__, matrix.conjugate().T )
def lowerCamelCase_ ( Up... | 240 | 0 |
'''simple docstring'''
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMix... | 39 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
lowerCAmelCase : Optional[Any] = logging.... | 39 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, id... | 527 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
lowerCAmelCase_ : Tuple = 'docs/source/en/_toctree.yml'
def UpperCAmelCase ( A : Union[str, Any] ):
SCREAMING_SNAKE_CASE : Dict = defaultdi... | 527 | 1 |
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_ti... | 702 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tenso... | 526 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
a : Tuple = {'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
a ... | 555 |
'''simple docstring'''
def __lowercase ( __SCREAMING_SNAKE_CASE = 10**9 ) -> int:
"""simple docstring"""
__a = 1
__a = 2
__a = 0
__a = 0
__a = 0
while perimeter <= max_perimeter:
perimeters_sum += perimeter
... | 582 | 0 |
"""simple docstring"""
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
__lowercase = datasets.load_iris()
__lowercase = np.array(data["""data"""])
__lowercase = np.ar... | 710 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipel... | 135 | 0 |
"""simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
_lowerCAmelCase : Dict = '''__DUMMY_TRANSFORMERS_USER__'''
_lowerCAmelCase : Optional[int] = '''D... | 46 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : str = {
'''xlm-... | 682 | 0 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> bool:
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 708 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 12 | 0 |
def a_ ( lowerCAmelCase_ : str ):
__lowerCAmelCase = ''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def a_ ( lowerCAmelCase_ : str ):
__lowerCAmelCase = ... | 53 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class lowerCamelCase__ ( _A):
"""simple ... | 2 | 0 |
'''simple docstring'''
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def snake_case_ (UpperCamelCase : Any , UpperCamelCase : List[Any] , UpperCamelCase : Tuple , UpperCamelCase : ... | 703 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
_snake_case : str = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company tha... | 377 | 0 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class A_ ( __lowerCamelCase ):
'''simple docstring'''
def __init__( self , sn... | 84 |
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
if digit_amount > 0:
return round(number - int(__SCREAMING_SNAKE_CASE ) , __SCREAMING_SNAKE_CASE )
return number - int(__SCREAMING_SNAKE_CASE )
if __name__ == "__main__":
print(decimal_isolate(1.53, 0)... | 84 | 1 |
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parametri... | 702 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False... | 328 | 0 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def _a ( )-> int:
SCREAMING_SNAKE_CASE_ = ArgumentParser('Diffusers CLI tool' , usage='diffusers-cli <command> [<args>]' )
SCREAMING_SNAKE_CASE_ = parser.add_subparsers(... | 360 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE: Any = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_a... | 360 | 1 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def __Uppe... | 711 |
'''simple docstring'''
def __UpperCAmelCase ( SCREAMING_SNAKE_CASE__: int, SCREAMING_SNAKE_CASE__: bool = False ) -> bool:
"""simple docstring"""
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n % 10 not in (1, 3, 7, 9): # ca... | 270 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __magic_name__ (snake_case_ ):
'''simpl... | 33 |
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCamelCase_ ( snake_case_ ):
'''simple docstring'''
def __init__( se... | 198 | 0 |
"""simple docstring"""
# 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... | 74 |
"""simple docstring"""
_UpperCamelCase = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_... | 74 | 1 |
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttention, ImageClassif... | 16 |
from __future__ import annotations
def __a ( A__ : list[int | str] ):
create_state_space_tree(A__ , [] , 0 , [0 for i in range(len(A__ ) )] )
def __a ( A__ : list[int | str] , A__ : list[int | str] , A__ : int , A__... | 16 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class __magic_name__:
def __init__( self : Optional[int] , __UpperCamelCase : Collection[float] | None = None ):
'''simpl... | 701 |
'''simple docstring'''
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def snake_case__ ( a , a , a , a , a ) -> Optional[int]:
'''simple docstring'''
snake_case__ = StableDi... | 566 | 0 |
'''simple docstring'''
def snake_case_ (UpperCamelCase : str ):
'''simple docstring'''
_a = [int(UpperCamelCase ) for i in ip_va_address.split('''.''' ) if i.isdigit()]
return len(UpperCamelCase ) == 4 and all(0 <= int(UpperCamelCase ) <=... | 22 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case : str = {
'configuration_layou... | 22 | 1 |
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
class lowerCAmelCa... | 706 |
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_common import OnnxPipelineT... | 531 | 0 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokeniza... | 4 | from heapq import heappop, heappush
import numpy as np
def __lowercase ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , ) -> tuple[float | int, list[tuple[int, int]]]:
'''simple docstring'''
__lowercase , __lowercase = grid.shape
__low... | 321 | 0 |
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 ..table import array_... | 693 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_in... | 693 | 1 |
import collections
import os
import re
from pathlib import Path
A_ : List[str] = 'src/transformers'
# Matches is_xxx_available()
A_ : Any = re.compile(r'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
A_ : Optional[int] = re.compile(r'^_impor... | 456 |
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
A_ : Any = logging.get_logger(__name__)
class _a :
'''simple docstring'''
UpperCAmelCase__: str = None
@experimental
def UpperC... | 456 | 1 |
import os
import sys
import unittest
__UpperCamelCase : str = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model... | 458 |
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import To... | 458 | 1 |
def __lowercase ( __lowerCAmelCase : list ):
if len(__lowerCAmelCase ) <= 1:
return [tuple(__lowerCAmelCase )]
a__ = []
def generate(__lowerCAmelCase : int , __lowerCAmelCase : list ):
if k == 1:
... | 335 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : Dict = logging.get_logger(__name__)
snake_case : List[str] = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json''',
}
class ... | 335 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
__lowerCAmelCase = logging.get_logger... | 718 |
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class UpperCAmelCase__ ( unittest.TestCase ):
"""simple docstring"""
def __lowercase ( self : Union[str, Any] ):
... | 319 | 0 |
'''simple docstring'''
import math
def __UpperCAmelCase ( A : Tuple ) -> str:
UpperCAmelCase_ : int = [True] * n
UpperCAmelCase_ : Optional[Any] = False
UpperCAmelCase_ : Optional[int] = False
UpperCA... | 541 |
import collections
import os
import re
from pathlib import Path
UpperCAmelCase = '''src/transformers'''
# Matches is_xxx_available()
UpperCAmelCase = re.compile(R'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
UpperCAmelCase = re.compile(R'''^_import_struc... | 84 | 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... | 719 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
fr... | 349 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_ava... | 398 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_: Tuple = logging.get_logger(__name__)
A_: str = {
'BridgeTower/bridgetower-base': 'https://huggingface.co/BridgeTower/bridgetower-base/blob/main/config.json',
... | 398 | 1 |
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, require_pyazr, require_zstandard
@pyt... | 709 | """simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneratio... | 632 | 0 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sentencepiece
@slow # ... | 66 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : List[str] ="""Speech2TextFeatureExtractor"""
__Up... | 636 | 0 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils imp... | 703 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
"facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json",
# Se... | 548 | 0 |
def lowerCamelCase_ ( UpperCAmelCase__ , UpperCAmelCase__ ):
"""simple docstring"""
a_ = [[] for _ in range(__lowercase )]
a_ = key - 1
if key <= 0:
raise ValueError("""Height of grid can't be 0 or negative""" )
... | 483 | import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import rep... | 670 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import fl... | 720 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase = logging.get_logger(__nam... | 245 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
'facebook/data... | 14 |
# Copyright 2022 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... | 557 | 0 |
'''simple docstring'''
__snake_case = {
'''km/h''': 1.0,
'''m/s''': 3.6,
'''mph''': 1.60_9344,
'''knot''': 1.852,
}
__snake_case = {
'''km/h''': 1.0,
'''m/s''': 0.2_7777_7778,
'''mph''': 0.6_2137_1192,
'''knot''': 0.5_3995_6803,
}
def a ( __a , ... | 719 |
'''simple docstring'''
import torch
from torch import nn
class lowercase ( nn.Module ):
"""simple docstring"""
def __init__( self , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_=1 , UpperCamelCase_=False... | 280 | 0 |
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=__SCREAMING_SNAKE_CASE):
_UpperCAmelCase : Union[str, Any] = ["""torch""", """scipy"""]
def __init__( self , *__magic_name__ , **__magic_name__ ):
requires_backends(... | 681 |
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def _a ( lowerCamelCase ):
# vision encoder
if "img_encoder.pos_embed" in name:
lowerCamelCase : Tuple = name.replace("""img_encoder.pos_... | 681 | 1 |
'''simple docstring'''
from torch import nn
def _lowercase ( lowerCamelCase__ ) -> List[Any]:
"""simple docstring"""
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif a... | 10 | '''simple docstring'''
def _lowercase ( lowerCamelCase__ , lowerCamelCase__ ) -> List[str]:
"""simple docstring"""
__UpperCAmelCase : Dict = (boundary[1] - boundary[0]) / steps
__UpperCAmelCase : Tuple = boundary[0... | 10 | 1 |
"""simple docstring"""
def lowercase ( lowerCAmelCase__ ):
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 29 |
"""simple docstring"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
a : int = numpy.array([0, 0])
a : Optional[Any] = numpy.array([0.5, 0.866_0254])
a : Tuple =... | 633 | 0 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class _UpperCAmelCase ( _UpperCAmelCase ):
... | 705 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
... | 141 | 0 |
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import T... | 84 |
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from transformers import Aut... | 326 | 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_F... | 646 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 646 | 1 |
'''simple docstring'''
def snake_case_ (UpperCamelCase : list[int] , UpperCamelCase : list[int] ):
'''simple docstring'''
_a = len(UpperCamelCase )
print('''The following activities are selected:''' )
# The first activ... | 22 |
"""simple docstring"""
import functools
def A ( _A, _A ):
"""simple docstring"""
snake_case_ :Optional[Any] = len(_A )
snake_case_ :Optional[int] = len(_A )
@functools.cache
def min_distance(_A, _A ) -> int:
# if firs... | 584 | 0 |
def SCREAMING_SNAKE_CASE ( snake_case_ : Tuple , snake_case_ : List[Any] , snake_case_ : Tuple=False ):
if isinstance(snake_case_ , snake_case_ ) and isinstance(snake_case_ , snake_case_ ):
snake_case__ : int = len(... | 719 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 25 | 0 |
"""simple docstring"""
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 ... | 595 |
"""simple docstring"""
from math import ceil
def lowercase_ ( _lowercase : Any , _lowercase : Dict ):
'''simple docstring'''
UpperCAmelCase : List[str] = list(range(0 , _lowercase ) )
UpperCAmelCase : List[Any] = ... | 595 | 1 |
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class __magic_name__ ( A__ ):
def __init__( self : str , UpperCamelCase__ : Dict , UpperCamelCase__ ... | 717 |
from dataclasses import dataclass
from typing import Dict, 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 .attention_processor import AttentionProcessor, AttnProcessor
from .modelin... | 457 | 0 |
'''simple docstring'''
from itertools import permutations
def _SCREAMING_SNAKE_CASE ( UpperCamelCase__ : tuple ):
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
... | 442 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_ava... | 442 | 1 |
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from transformers.utils import l... | 717 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoImageProcessor, ResNetCo... | 202 | 0 |
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