code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
__UpperCamelCase : int = """
# 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
"""
__UpperCamelCase : ... | 80 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.... | 625 | 0 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
_snake_case : str = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def lowerCAmelCase_ ( _... | 81 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( A , A , A , A=1024 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 625 | 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 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from... | 625 | 0 |
"""simple docstring"""
lowerCAmelCase__ = [
(1000, '''M'''),
(900, '''CM'''),
(500, '''D'''),
(400, '''CD'''),
(100, '''C'''),
(90, '''XC'''),
(50, '''L'''),
(40, '''XL'''),
(10, '''X'''),
(9, '''IX'''),
(5, '''V'''),
(4, '''IV'''),
(1, ''... | 83 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 | 0 |
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_tokenization_common import Tokeniz... | 84 |
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 _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 | 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_vision_available
fr... | 85 |
from __future__ import annotations
import requests
UpperCamelCase_ = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories c... | 625 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_availab... | 86 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFea... | 625 | 0 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> Dict:
"""simple docstring"""
A__ = FileLock(str(tmpdir / '''foo.lock''' ) )
A__ = FileLock(str(tmpdir / '''foo.l... | 87 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ = {
'configuration_owlvit':... | 625 | 0 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowercase__ ( A_ ,A_ ):
@register_to_config
def __init... | 88 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTim... | 625 | 0 |
import unittest
from knapsack import greedy_knapsack as kp
class _lowerCamelCase( unittest.TestCase ):
def UpperCamelCase ( self) -> Dict:
"""simple docstring"""
_lowercase : Optional[Any] = [10, 20, 30, 40, 50, 60]
_lowercase : Opt... | 89 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_config... | 625 | 0 |
'''simple docstring'''
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vi... | 90 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
for i in range(len(A ) - 1 , 0 , -1 ):
UpperCAmelCase__ =False
for j in range(A , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
UpperCAme... | 625 | 0 |
"""simple docstring"""
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] ) -> None:
A = {} # Mapping from char to TrieNode
A = False
def _SCREAMING_SNAKE_CASE ( self : Optional[Any] ,A_ : list[str] ) -... | 91 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 625 | 0 |
'''simple docstring'''
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_ima... | 92 |
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_ = {
'junnyu/roformer_chinese_... | 625 | 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 import ... | 93 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'dist... | 94 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
# See all Don... | 625 | 0 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_mod... | 95 |
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_availabl... | 625 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
resca... | 96 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'EncodecFeatureExtractor'
__UpperCamelCase ... | 625 | 0 |
import numpy as np
class lowercase__:
"""simple docstring"""
def __init__( self : List[str] ) -> str:
lowercase_ = (0, 0)
lowercase_ = None
lowercase_ = 0
lowercase_ = 0
lowercase_ = 0
def __eq__( self : Dict ... | 97 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCAmelCase ( A , A=7 ):
'''simple docstring'''
UpperCAmelCase__ =None
if token is not None:
UpperCAmelCase__ ... | 625 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Tuple = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Opti... | 98 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 625 | 0 |
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers import GradientAccumulator, crea... | 99 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_S... | 625 | 0 |
def __snake_case ( lowerCAmelCase_ , lowerCAmelCase_ ) -> int:
while a != 0:
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = b % a, a
return b
def __snake_case ( lowerCAmelCase_ , lowerCAmelCase_ ) -> int:
if gcd(... | 100 |
import inspect
import unittest
from transformers import YolosConfig
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 ConfigTester
... | 625 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Union[str, Any] =logging.get_logger(__name__)
lowerCAmelCase__ : List[Any] ={
'BAAI/AltCLIP': 'https://huggingface.co/BA... | 101 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed... | 625 | 0 |
"""simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.mode... | 102 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.... | 625 | 0 |
"""simple docstring"""
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
snake_case = datasets.load_iris()
snake_case = np.array(data['''data'''])
snake_case = np.array(data[... | 103 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( A , A , A , A=1024 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 625 | 0 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int, UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
return int(input_a == input_a == 0 )
def _lowerCamelCase ( ) -> None:
"""simple d... | 104 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from... | 625 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase__ : Union[str, Any] = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokeniza... | 105 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 | 0 |
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa... | 106 |
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 _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 | 0 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( __snake_case : int = 4_0_0_0_0_0_0 ):
_A = []
_A , _A = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(__snake_case )
_A , _A = b, a + b
return sum(__s... | 107 |
from __future__ import annotations
import requests
UpperCamelCase_ = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories c... | 625 | 0 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscre... | 108 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFea... | 625 | 0 |
'''simple docstring'''
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# -... | 109 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ = {
'configuration_owlvit':... | 625 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}
try:
if no... | 47 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTim... | 625 | 0 |
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
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_configu... | 383 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_config... | 625 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstr... | 92 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
for i in range(len(A ) - 1 , 0 , -1 ):
UpperCAmelCase__ =False
for j in range(A , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
UpperCAme... | 625 | 0 |
'''simple docstring'''
from __future__ import annotations
__lowerCamelCase : List[str] = tuple[int, int, int]
__lowerCamelCase : str = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
__lowerCamelCase : Optional[int] = 'ABCDEFGHIJKLMNOPQRSTUV... | 404 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 625 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class __UpperCAmelCase :
'''simple docstring'''
def __init__( self : Dict , _lowercase : Any) -> None:
A_ = value
A_ = None
... | 366 |
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_ = {
'junnyu/roformer_chinese_... | 625 | 0 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
A_ : int =2_0_0
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that genera... | 650 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 | 0 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_... | 317 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
# See all Don... | 625 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def SCREAMING_SNAKE_CASE ( a_ : List[Any] ):
__a = SwinConfig(image_size=192 ... | 539 |
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_availabl... | 625 | 0 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def __snake_case ( *UpperCAmelCase_ : List[str] , UpperCAmelCase_ : Union[str, Any] = None , UpperCAmelCase_ : List[Any]=True , Upper... | 675 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'EncodecFeatureExtractor'
__UpperCamelCase ... | 625 | 0 |
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def __magic_name__ ( lowercase_ , lowercase_ , lowercase_ , lowercase_ , lowercase_ ) -> Dict:
'''simple docstring'''
UpperCam... | 606 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCAmelCase ( A , A=7 ):
'''simple docstring'''
UpperCAmelCase__ =None
if token is not None:
UpperCAmelCase__ ... | 625 | 0 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
__lowerCAmelCase ={
"text_branch": "text_model",
"audio_branch": "audio_model.audio_encoder",
"attn": "attention.self",
"self.proj": "output.dense",
... | 333 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 625 | 0 |
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
SCREAMING_SNAKE_CASE__ = l... | 47 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_S... | 625 | 0 |
from math import factorial
_snake_case = {str(digit): factorial(digit) for digit in range(10)}
def _a ( __lowercase ) -> Dict:
"""simple docstring"""
if not isinstance(__lowercase , __lowercase ):
raise TypeError('Parameter number must be int' )... | 383 |
import inspect
import unittest
from transformers import YolosConfig
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 ConfigTester
... | 625 | 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,
EfficientFormerForImageClassificationWithTea... | 92 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed... | 625 | 0 |
'''simple docstring'''
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
... | 404 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.... | 625 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 366 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( A , A , A , A=1024 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 625 | 0 |
"""simple docstring"""
from math import factorial
A_ : Optional[int] ={str(d): factorial(d) for d in range(1_0)}
def SCREAMING_SNAKE_CASE_ ( snake_case : List[str] )-> Optional[int]:
return sum(DIGIT_FACTORIAL[d] for d in str(snake_case ) )
def SCREAMING_SNAK... | 650 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from... | 625 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"""junnyu/roformer_chinese_small""": """ht... | 317 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 | 0 |
'''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = "T5Config"
class __lowe... | 539 |
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 _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ : Tuple = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 675 |
from __future__ import annotations
import requests
UpperCamelCase_ = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories c... | 625 | 0 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQ... | 606 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFea... | 625 | 0 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase =logging.get_logger(__name__)
__lowerCAmelCase ={
"google/efficien... | 333 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ = {
'configuration_owlvit':... | 625 | 0 |
def UpperCAmelCase__ ( lowerCamelCase_ : int , lowerCamelCase_ : List[str] , lowerCamelCase_ : List[str] , lowerCamelCase_ : Any , lowerCamelCase_ : Union[str, Any] ):
if index == number_of_items:
return 0... | 47 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTim... | 625 | 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 nic... | 383 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_config... | 625 | 0 |
'''simple docstring'''
from __future__ import annotations
import pandas as pd
def _lowerCAmelCase ( __magic_name__ : List[str] , __magic_name__ : List[str] , __magic_name__ : Union[str, Any] ) -> Union[str, Any]:
lowercase : Tuple =[0] * no_... | 92 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
for i in range(len(A ) - 1 , 0 , -1 ):
UpperCAmelCase__ =False
for j in range(A , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
UpperCAme... | 625 | 0 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _a (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCamelCase ={}
_Up... | 404 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 625 | 0 |
'''simple docstring'''
def lowerCamelCase( SCREAMING_SNAKE_CASE_ ) -> List[str]:
A_ = [1]
A_ , A_ , A_ = 0, 0, 0
A_ = ugly_nums[ia] * 2
A_ = ugly_nums[ia] * 3
A_ = ugly_nums[ia] * 5
for _ in range(1 ,SCREAMING_SNAKE_CASE_ ):
... | 366 |
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_ = {
'junnyu/roformer_chinese_... | 625 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokeni... | 650 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tensor, lo... | 317 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
# See all Don... | 625 | 0 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class __lowercase ( __magic_name__ ):
def UpperCamelCase__ ( self ) -> List[str]:
return [
{"co... | 539 |
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_availabl... | 625 | 0 |
'''simple docstring'''
import os
def __snake_case ( ):
with open(os.path.dirname(UpperCAmelCase_ ) + "/p022_names.txt" ) as file:
lowerCamelCase_ = str(file.readlines()[0] )
lowerCamelCase_ = names.replace("\"" , "" ).split("," )
names... | 675 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'EncodecFeatureExtractor'
__UpperCamelCase ... | 625 | 0 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__a : Optional[int] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__a : Optional[int] = [file f... | 606 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCAmelCase ( A , A=7 ):
'''simple docstring'''
UpperCAmelCase__ =None
if token is not None:
UpperCAmelCase__ ... | 625 | 0 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_available
f... | 333 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 625 | 0 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
... | 47 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_S... | 625 | 0 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTe... | 383 |
import inspect
import unittest
from transformers import YolosConfig
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 ConfigTester
... | 625 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ = {"""processing_layoutxlm""": ["""... | 92 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed... | 625 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale... | 404 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.... | 625 | 0 |
'''simple docstring'''
from copy import deepcopy
class __UpperCAmelCase :
'''simple docstring'''
def __init__( self : Optional[int] , _lowercase : List[str] = None , _lowercase : Optional[int] = None) -> None:
if arr is None ... | 366 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( A , A , A , A=1024 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 625 | 0 |
"""simple docstring"""
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
A_ : str ... | 650 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from... | 625 | 0 |
def UpperCAmelCase__ ( __snake_case ) -> Dict:
if len(__snake_case ) < 2:
return collection
def circle_sort_util(__snake_case , __snake_case , __snake_case ) -> bool:
_A = False
if low == high:
return swapped
_A = low
... | 317 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( a_ : Any , a_ : Any , a_ : Tuple , a_ : Optional[int] , a_ : Optional[Any] , ):
__a = [redshift, radiation_density, matter_density, dark_... | 539 |
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 _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 | 0 |
'''simple docstring'''
a_ : Any = frozenset(
[
"""prompt""",
"""height""",
"""width""",
"""guidance_scale""",
"""negative_prompt""",
"""prompt_embeds""",
"""negative_prompt_embeds""",
"""cross_attention_kwargs""",... | 675 |
from __future__ import annotations
import requests
UpperCamelCase_ = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories c... | 625 | 0 |
class __UpperCAmelCase :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
UpperCamelCase = n
UpperCamelCase = [None] * self.n
... | 606 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFea... | 625 | 0 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.modeling_aut... | 333 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ = {
'configuration_owlvit':... | 625 | 0 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def UpperCAmelCase__ ( lowerCamelCase_ : Optional[Any] ):
return np.dot(lowerCamelCase_ , lowerCamelCase_ )
class _UpperCamelCase:
def ... | 47 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTim... | 625 | 0 |
# 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.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet imp... | 383 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_config... | 625 | 0 |
'''simple docstring'''
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version(""">=""", FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from ... | 92 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
for i in range(len(A ) - 1 , 0 , -1 ):
UpperCAmelCase__ =False
for j in range(A , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
UpperCAme... | 625 | 0 |
'''simple docstring'''
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
__lowerCamelCase : Dict = logging... | 404 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 625 | 0 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def lowerCamelCase( SCREAMING_SNAKE_CASE_ ) -> int:
return np.maximum(0 ,SCREAMING_SNAKE_CASE_ )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 366 |
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_ = {
'junnyu/roformer_chinese_... | 625 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE_ ( snake_case : Optional[Any] = 4_000_000 )-> str:
_lowerCamelCase = []
_lowerCamelCase , _lowerCamelCase = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.ap... | 650 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 | 0 |
def UpperCAmelCase__ ( __snake_case ) -> Dict:
if upper_limit < 0:
raise ValueError('''Limit for the Catalan sequence must be ≥ 0''' )
_A = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
_A = 1
if upper_limit > 0:
_A = 1
# ... | 317 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
# See all Don... | 625 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
"microsoft/wavlm-base": "https://huggingface.co/microsoft/wavlm-base/re... | 539 |
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_availabl... | 625 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class snake_case :
"""simple docstring"""
_lowerCamelCase = 42
_lowerCamelC... | 675 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'EncodecFeatureExtractor'
__UpperCamelCase ... | 625 | 0 |
def __magic_name__ ( lowercase_ ) -> int:
'''simple docstring'''
if number > 0:
raise ValueError("input must be a negative integer" )
UpperCamelCase = len(bin(lowercase_ )[3:] )
UpperCamelCase = bin(abs(lowercase_ ) - ... | 606 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCAmelCase ( A , A=7 ):
'''simple docstring'''
UpperCAmelCase__ =None
if token is not None:
UpperCAmelCase__ ... | 625 | 0 |
from ...processing_utils import ProcessorMixin
class __magic_name__ ( _a):
_UpperCAmelCase : str = 'SpeechT5FeatureExtractor'
_UpperCAmelCase : Any = 'SpeechT5Tokenizer'
def __init__( self : Optional[Any] ,__SCREAMING_SNAKE_CASE : Any ,__SCREAMING_SNAKE_CASE : List[Any] ... | 333 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 625 | 0 |
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def UpperCAmelCase__ ( lowerCamelCase_ : int ):
__a : List[str] = [
'encoder.version',
'decoder.version',
... | 47 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_S... | 625 | 0 |
from sklearn.metrics import fa_score
import datasets
_snake_case = '\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'
_snake_case = '\nArgs:\n predictions (`list` of `int`): Predicted ... | 383 |
import inspect
import unittest
from transformers import YolosConfig
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 ConfigTester
... | 625 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCamelCase_ = {"""tokenization_bertweet""": ["""BertweetTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_bertweet import BertweetTokenizer
else:
import sys
UpperCamelCase_ ... | 92 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed... | 625 | 0 |
'''simple docstring'''
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase ( lowercase_):
"""simple docstring"""
lowerCAmelCase_ = (UnCLIPScheduler,)
def UpperCamelCase__ ( self : ... | 404 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.... | 625 | 0 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformer... | 366 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( A , A , A , A=1024 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 625 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A_ : List[str] ={
"""configuration_distilbert""": [
"""DI... | 650 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from... | 625 | 0 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class _snake_case ( nn.Module ):
"""simple docstring"""
lowerCamelCase_ = 4_2
lowerCamelCase_ ... | 317 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 | 0 |
'''simple docstring'''
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class __lowercase ( __magic_name__ ):
_a = """EncodecFeatureExtractor"""
_a = ("""T5Tokenizer""", ... | 539 |
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 _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 | 0 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def __snake_case ( UpperCAmelCase_ : int , UpperCAmelCase_ : int , UpperCAmelCase_ ... | 675 |
from __future__ import annotations
import requests
UpperCamelCase_ = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories c... | 625 | 0 |
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__a : Optional[int] = argparse.ArgumentParser()
parser.add_argument("""--dump_path""", defau... | 606 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFea... | 625 | 0 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
__lowerCA... | 333 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ = {
'configuration_owlvit':... | 625 | 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 HeunDis... | 47 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTim... | 625 | 0 |
def _a ( __lowercase , __lowercase , __lowercase , __lowercase ) -> Union[str, Any]:
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
# 2. Validate that next vertex is not already in path
return not any... | 383 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_config... | 625 | 0 |
'''simple docstring'''
import os
from math import logaa
def _lowerCAmelCase ( __magic_name__ : Dict = "base_exp.txt" ) -> int:
lowercase : List[str] =0
lowercase : Optional[int] =0
for i, line in enumerate(open(os.path.join(os.path.dirname(_... | 92 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
for i in range(len(A ) - 1 , 0 , -1 ):
UpperCAmelCase__ =False
for j in range(A , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
UpperCAme... | 625 | 0 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICE... | 404 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 625 | 0 |
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