code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> Optional[int]:
"""simple docstring"""
__snake_case = (boundary[1] - boundary[0]) / steps
__snake_case = boundary[0]
__snake_case ... | 721 |
"""simple docstring"""
import baseaa
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bytes:
"""simple docstring"""
return baseaa.baaencode(string.encode("utf-8" ) )
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
... | 614 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_mgp_str""": ["""MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MgpstrConfig"""],
"""processing_mgp_str""": ... | 700 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Conf... | 614 | 0 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> list:
"""simple docstring"""
__snake_case = len(SCREAMING_SNAKE_CASE )
for i in range(1 , SCREAMING_SNAKE_CASE ):
__snake_case = collection[i]
... | 701 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-... | 614 | 0 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Conf... | 702 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_SCREAMING_SNAKE_CASE = {
"""configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_... | 614 | 0 |
"""simple docstring"""
import numpy as np
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> np.array:
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> np.array:
"""simple docstring"""
... | 703 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 614 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_SCREAMING_SNAKE_CASE = {"""configuration_yolos""": ["""YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """YolosConfig""", """YolosOnnxCon... | 704 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __magic_name__ ( lowercase__ ):
def ... | 614 | 0 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ) -> list[f... | 705 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __UpperCamelCase ( ) -> tuple[list[int], int]:
"""simple docstring"""
__snake_case = [randint(-10_00 , ... | 614 | 0 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> Optional[Any]:
"""simple docstring"""
__snake_case = [0] * len(SCREAMING_SNAKE_CASE )
__snake_case = []
__snake_case = [1] * len(SCREAMING_SNAKE_CASE )... | 706 |
"""simple docstring"""
# 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 Ba... | 614 | 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... | 707 |
"""simple docstring"""
from heapq import heappop, heappush
import numpy as np
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ) -> tuple[float | int, list[tuple[int, int]]]:
"""simp... | 614 | 0 |
"""simple docstring"""
from maths.prime_factors import prime_factors
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
__snake_case = F'''Input valu... | 708 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
d... | 614 | 0 |
"""simple docstring"""
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE=() , ... | 709 |
"""simple docstring"""
from __future__ import annotations
_SCREAMING_SNAKE_CASE = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],... | 614 | 0 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __UpperCamelCase ( ) -> tuple[list[int], int]:
"""simple docstring"""
__snake_case = [randint(-10_00 , ... | 710 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = 1_00 , ) -> float:
"""simple docstring... | 614 | 0 |
"""simple docstring"""
import argparse
import json
import os
import re
from collections import OrderedDict
from os.path import basename, dirname
import fairseq
import torch
from fairseq import hub_utils
from fairseq.data.dictionary import Dictionary
from transformers import FSMTConfig, FSMTForConditionalGener... | 711 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not postfix_notation:
return 0
__snake_case = {"+", "-", "*", "/"}
__sna... | 614 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_SCREAMING_SNAKE_CASE = {"""conf... | 712 |
"""simple docstring"""
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class __magic_name__ :
_SCREAMING_SNAKE_CASE : float
_SCREAMING_SNAKE_CASE : TreeNode | None = None
_SCREAMING_SNAKE_CASE : TreeNode... | 614 | 0 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_SCREAMING_SNAKE_CASE = logging.get_logger("""transformers.models.speecht5""")
def __lowercase ( SCREAMING_SNAKE_CA... | 713 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> list:
"""simple docstring"""
__snake_case = len(SCREAMING_SNAKE_CASE )
for i in range(1 , SCREAMING_SNAKE_CASE ):
__snake_case = collection[i]
... | 614 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxConfig"""],
"""toke... | 714 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConf... | 614 | 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,
is_vision_available,
)
_SCREAMING_SNAKE_CASE = {
"""co... | 715 |
"""simple docstring"""
from collections.abc import Sequence
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("Input sequence should not be empty" )
__snake_case = ... | 614 | 0 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
_SCREAMING_SNAKE_CASE = """
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Sim... | 716 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_to... | 614 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_SCREAMING_SNAKE_CASE ={
"""configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
"""tok... | 717 |
"""simple docstring"""
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .s... | 614 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
_SCREAMING_SNAKE_CASE = {
"""google/tapas-base-finetuned-sqa""": (
"""https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
),
"""google/tapas-base-finetuned-wtq""": (
... | 718 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ... | 614 | 0 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> float:
"""simple docstring"""
if discount_rate < 0:
raise ValueError("Discount rate cannot be negative" )
if not cash_flows:
raise ValueE... | 719 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 614 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoF... | 720 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = 10 , SCREAMING_SNAKE_CASE = 10_00 , SCREAMING_SNAKE_CASE = True ) -> int:
"""simple docstring"""
assert (
isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )
... | 614 | 0 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction... | 721 |
"""simple docstring"""
import baseaa
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bytes:
"""simple docstring"""
return baseaa.baaencode(string.encode("utf-8" ) )
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
... | 614 | 0 |
"""simple docstring"""
from random import randint, random
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = False , SCREAMING_SNAKE_CASE = False , SCREAMING_SNAKE_CASE = 5 , ) -> l... | 700 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Conf... | 614 | 0 |
"""simple docstring"""
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
_SCREAMING_SNAKE_CASE = abspath(join(dirname(... | 701 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-... | 614 | 0 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glu... | 702 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_SCREAMING_SNAKE_CASE = {
"""configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_... | 614 | 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 = {
"""... | 703 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 614 | 0 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
class __magic_name__ ... | 704 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __magic_name__ ( lowercase__ ):
def ... | 614 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_SCREAMING_SNAKE_CASE = {"""configuration_sew""": ["""SEW_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWConfig"""]}
try:
if not is_torch_available():
... | 705 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __UpperCamelCase ( ) -> tuple[list[int], int]:
"""simple docstring"""
__snake_case = [randint(-10_00 , ... | 614 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_SCREAMING_SNAKE_CASE : Tuple = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"... | 706 |
"""simple docstring"""
# 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 Ba... | 614 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils im... | 707 |
"""simple docstring"""
from heapq import heappop, heappush
import numpy as np
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ) -> tuple[float | int, list[tuple[int, int]]]:
"""simp... | 614 | 0 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = 10 ) -> str:
"""simple docstring"""
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) or n < 0:
raise ValueError("Invalid input" )
__snake_case = 10**... | 708 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
d... | 614 | 0 |
"""simple docstring"""
_SCREAMING_SNAKE_CASE = [0, 2, 4, 6, 8]
_SCREAMING_SNAKE_CASE = [1, 3, 5, 7, 9]
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> int:
... | 709 |
"""simple docstring"""
from __future__ import annotations
_SCREAMING_SNAKE_CASE = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],... | 614 | 0 |
"""simple docstring"""
import inspect
import unittest
class __magic_name__ ( unittest.TestCase ):
def lowerCAmelCase ( self : Union[str, Any] ):
try:
import diffusers # noqa: F401
except ImportError:
... | 710 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = 1_00 , ) -> float:
"""simple docstring... | 614 | 0 |
"""simple docstring"""
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( S... | 711 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not postfix_notation:
return 0
__snake_case = {"+", "-", "*", "/"}
__sna... | 614 | 0 |
"""simple docstring"""
class __magic_name__ :
def __init__( self : Dict , snake_case_ : list[int] ):
__snake_case = len(snake_case_ )
__snake_case = [0] * len_array
if len_array > 0:
... | 712 |
"""simple docstring"""
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class __magic_name__ :
_SCREAMING_SNAKE_CASE : float
_SCREAMING_SNAKE_CASE : TreeNode | None = None
_SCREAMING_SNAKE_CASE : TreeNode... | 614 | 0 |
"""simple docstring"""
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __lowercase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = "x" , SCREAMING_SNAKE_CASE = 10**-10 , SCREAMING_SNAKE_CASE = 1 , ... | 713 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> list:
"""simple docstring"""
__snake_case = len(SCREAMING_SNAKE_CASE )
for i in range(1 , SCREAMING_SNAKE_CASE ):
__snake_case = collection[i]
... | 614 | 0 |
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
DPR_CONTEXT_ENCODER... | 714 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConf... | 614 | 0 |
"""simple docstring"""
from __future__ import annotations
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> list[str]:
"""simple docstring"""
if nth_term == "":
return [""]
__snake_case = int(SCREAMING_SNA... | 715 |
"""simple docstring"""
from collections.abc import Sequence
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("Input sequence should not be empty" )
__snake_case = ... | 614 | 0 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_avai... | 716 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_to... | 614 | 0 |
"""simple docstring"""
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.... | 717 |
"""simple docstring"""
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .s... | 614 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class ... | 718 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ... | 614 | 0 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = 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, ... | 719 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 614 | 0 |
"""simple docstring"""
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformer... | 720 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = 10 , SCREAMING_SNAKE_CASE = 10_00 , SCREAMING_SNAKE_CASE = True ) -> int:
"""simple docstring"""
assert (
isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )
... | 614 | 0 |
"""simple docstring"""
from __future__ import annotations
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> dict[str, float]:
"""simple docstring"""
if (voltage, current, resistance).count(0 ) != 1:
... | 721 |
"""simple docstring"""
import baseaa
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bytes:
"""simple docstring"""
return baseaa.baaencode(string.encode("utf-8" ) )
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
... | 614 | 0 |
"""simple docstring"""
from __future__ import annotations
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
__snake_case = 2
__snake_case = []
while i * i <= n:
if n % i:
... | 700 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Conf... | 614 | 0 |
"""simple docstring"""
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __magic_name__ ( unittest.TestCase ):
def lowerCAmelCase ... | 701 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-... | 614 | 0 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = 10_00 ) -> int:
"""simple docstring"""
__snake_case , __snake_case = 1, 1
__snake_case = []
for i in range(1 , n + 1 ):
__snake_case ... | 702 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_SCREAMING_SNAKE_CASE = {
"""configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_... | 614 | 0 |
"""simple docstring"""
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_v... | 703 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 614 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
_SCREAMING_SNAKE_CASE = TypeVar("""T""")
class __magic_name__ ( Generic[T] ):
def __init__( self : str , snak... | 704 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __magic_name__ ( lowercase__ ):
def ... | 614 | 0 |
"""simple docstring"""
from __future__ import annotations
_SCREAMING_SNAKE_CASE = """Muhammad Umer Farooq"""
_SCREAMING_SNAKE_CASE = """MIT"""
_SCREAMING_SNAKE_CASE = """1.0.0"""
_SCREAMING_SNAKE_CASE = """Muhammad Umer Farooq"""
_SCREAMING_SNAKE_CASE = ... | 705 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __UpperCamelCase ( ) -> tuple[list[int], int]:
"""simple docstring"""
__snake_case = [randint(-10_00 , ... | 614 | 0 |
"""simple docstring"""
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 GradientAcc... | 706 |
"""simple docstring"""
# 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 Ba... | 614 | 0 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
if number > 0:
raise ValueError("input must be a negative integer" )
__snake_case = len(bin(SCREAMING_SNAKE_CASE )[3:] )... | 707 |
"""simple docstring"""
from heapq import heappop, heappush
import numpy as np
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ) -> tuple[float | int, list[tuple[int, int]]]:
"""simp... | 614 | 0 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
__snake_case = len(SCREAMING_SNAKE_CASE )
__snake_case = len(SCREAMING_SNAKE_CASE )
__snake_case ... | 708 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
d... | 614 | 0 |
"""simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers ... | 709 |
"""simple docstring"""
from __future__ import annotations
_SCREAMING_SNAKE_CASE = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],... | 614 | 0 |
"""simple docstring"""
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelT... | 710 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = 1_00 , ) -> float:
"""simple docstring... | 614 | 0 |
"""simple docstring"""
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoenc... | 711 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not postfix_notation:
return 0
__snake_case = {"+", "-", "*", "/"}
__sna... | 614 | 0 |
"""simple docstring"""
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeat... | 712 |
"""simple docstring"""
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class __magic_name__ :
_SCREAMING_SNAKE_CASE : float
_SCREAMING_SNAKE_CASE : TreeNode | None = None
_SCREAMING_SNAKE_CASE : TreeNode... | 614 | 0 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
_SCREAMING_SNAKE_CASE = TypeVar("""_T""")
class __magic_name__ ( Generic[_T] ):
def __init__( self : Tuple , snake_case_ : Iterable[_T] | None... | 713 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> list:
"""simple docstring"""
__snake_case = len(SCREAMING_SNAKE_CASE )
for i in range(1 , SCREAMING_SNAKE_CASE ):
__snake_case = collection[i]
... | 614 | 0 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
_SCREAMING_SNAKE_CASE = TypeVar("""T""")
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
return (position - 1) // 2
def __UpperCamelCase ( ... | 714 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConf... | 614 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids... | 715 |
"""simple docstring"""
from collections.abc import Sequence
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("Input sequence should not be empty" )
__snake_case = ... | 614 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not postfix_notation:
return 0
__snake_case = {"+", "-", "*", "/"}
__sna... | 716 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_to... | 614 | 0 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class __magic_name__ ( lowercase__ ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = (CMStochasticIterativeScheduler,)
_SCR... | 717 |
"""simple docstring"""
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .s... | 614 | 0 |
"""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 __UpperCamelCase ( SCREAMI... | 718 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ... | 614 | 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 __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ... | 719 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 614 | 0 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
"""simple docstring"""
def decorator(SCREAMING_SNAKE_CASE ):
__snake_case = getattr(SCREAMING... | 720 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = 10 , SCREAMING_SNAKE_CASE = 10_00 , SCREAMING_SNAKE_CASE = True ) -> int:
"""simple docstring"""
assert (
isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )
... | 614 | 0 |
"""simple docstring"""
from math import factorial, radians
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = 18 , SCREAMING_SNAKE_CASE = 10 ) -> float:
"""simple docstring"""
__snake_case = angle_in_degrees - ((angle_in_degree... | 721 |
"""simple docstring"""
import baseaa
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bytes:
"""simple docstring"""
return baseaa.baaencode(string.encode("utf-8" ) )
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
... | 614 | 0 |
"""simple docstring"""
from __future__ import annotations
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
if len(SCREAMING_SNAKE_CASE ) < 2:
raise ValueError("Monogons and Digons are not polygons in the Euclidean space" )
if ... | 700 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Conf... | 614 | 0 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = 1 , SCREAMING_SNAKE_CASE = 10_00 ) -> int:
"""simple docstring"""
__snake_case = 1
__snake_case = 0
for divide_by_number in range(SCREAMING_SNAKE_CASE ... | 701 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-... | 614 | 0 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> Any:
"""simple docstring"""
__snake_case = 0
__snake_case = len(SCREAMING_SNAKE_CASE ) - 1
while left <= right:
# avo... | 702 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_SCREAMING_SNAKE_CASE = {
"""configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_... | 614 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformer... | 703 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 614 | 0 |
"""simple docstring"""
_SCREAMING_SNAKE_CASE = """
# 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... | 704 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __magic_name__ ( lowercase__ ):
def ... | 614 | 0 |
"""simple docstring"""
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class __magic_name__ :
def __init__( self : List[... | 705 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __UpperCamelCase ( ) -> tuple[list[int], int]:
"""simple docstring"""
__snake_case = [randint(-10_00 , ... | 614 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_SCREAMING_SNAKE_CASE : int = logging.get_logger(__nam... | 706 |
"""simple docstring"""
# 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 Ba... | 614 | 0 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt=""... | 707 |
"""simple docstring"""
from heapq import heappop, heappush
import numpy as np
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ) -> tuple[float | int, list[tuple[int, int]]]:
"""simp... | 614 | 0 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
__snake_case = BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE , params=SCRE... | 708 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
d... | 614 | 0 |
"""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, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from dif... | 709 |
"""simple docstring"""
from __future__ import annotations
_SCREAMING_SNAKE_CASE = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],... | 614 | 0 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_a... | 710 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = 1_00 , ) -> float:
"""simple docstring... | 614 | 0 |
"""simple docstring"""
import math
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
__snake_case = F'''Input value of [number={number}] must be an ... | 711 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not postfix_notation:
return 0
__snake_case = {"+", "-", "*", "/"}
__sna... | 614 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"""uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/mai... | 712 |
"""simple docstring"""
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class __magic_name__ :
_SCREAMING_SNAKE_CASE : float
_SCREAMING_SNAKE_CASE : TreeNode | None = None
_SCREAMING_SNAKE_CASE : TreeNode... | 614 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/... | 713 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> list:
"""simple docstring"""
__snake_case = len(SCREAMING_SNAKE_CASE )
for i in range(1 , SCREAMING_SNAKE_CASE ):
__snake_case = collection[i]
... | 614 | 0 |
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_t... | 714 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConf... | 614 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
def __UpperCamelCase ( SCREAMING_SNAKE_... | 715 |
"""simple docstring"""
from collections.abc import Sequence
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("Input sequence should not be empty" )
__snake_case = ... | 614 | 0 |
"""simple docstring"""
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhon... | 716 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_to... | 614 | 0 |
"""simple docstring"""
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
Auto... | 717 |
"""simple docstring"""
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .s... | 614 | 0 |
"""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_bert import BertTokenizer
_SCREAMING_SNAKE_CASE = logging.get_logger(__nam... | 718 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ... | 614 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.u... | 719 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 614 | 0 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from tr... | 720 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = 10 , SCREAMING_SNAKE_CASE = 10_00 , SCREAMING_SNAKE_CASE = True ) -> int:
"""simple docstring"""
assert (
isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )
... | 614 | 0 |
"""simple docstring"""
import baseaa
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bytes:
"""simple docstring"""
return baseaa.baaencode(string.encode("utf-8" ) )
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
... | 721 |
"""simple docstring"""
import baseaa
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bytes:
"""simple docstring"""
return baseaa.baaencode(string.encode("utf-8" ) )
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
... | 614 | 0 |
"""simple docstring"""
def _lowercase ( __snake_case ) -> "list[int]":
if upper_limit < 0:
raise ValueError("Limit for the Catalan sequence must be ≥ 0" )
__lowerCAmelCase : int = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__low... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case = 3 ,__snake_case = 7 ,__snake_case = 1_000_000 ) -> int:
__lowerCAmelCase : Optional[Any] = 0
__lowerCAmelCase : List[str] = 1
for current_denominator in range(1 ,limit + 1 ... | 615 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = ['transformers', 'torch', 'note_seq']
def __init__( self: List[str] ,... | 615 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = ['torch', 'scipy']
def __init__( self: Tuple , *_SCREAMING_SNAKE_C... | 615 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowercase ( __snake_case ) -> int:
if not nums:
return 0
__lowerCAmelCase : str = nums[0]
__lowerCAmelCase : Optional[Any] = 0
for num in nums[1:]:
__lowerCAme... | 615 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__snake_case : ... | 615 | 1 |
"""simple docstring"""
def _lowercase ( __snake_case = 1_000 ) -> int:
__lowerCAmelCase : List[Any] = 2**power
__lowerCAmelCase : List[str] = 0
while n:
__lowerCAmelCase , __lowerCAmelCase : Tuple = r + n % 10, n // 10
re... | 615 |
"""simple docstring"""
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoMod... | 615 | 1 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def _lowercase ( __snake_case ) -> Any:
return choice(__snake_case )
def _lowercase ( __snake_case ,__snake_case ) -> int:
__lowerCAmelCase :... | 615 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
... | 615 | 1 |
"""simple docstring"""
import os
from collections.abc import Iterator
def _lowercase ( __snake_case = "." ) -> Iterator[str]:
for dir_path, dir_names, filenames in os.walk(__snake_case ):
__lowerCAmelCase : Dict = [d for d in dir_names if d != "scr... | 615 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
__snake_case : Tuple = logging.getLogger(__name__)
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE... | 615 | 1 |
"""simple docstring"""
from __future__ import annotations
__snake_case : Optional[int] = [True] * 1_000_001
__snake_case : int = 2
while i * i <= 1_000_000:
if seive[i]:
for j in range(i * i, 1_000_001, i):
__snake_case : List[str] = Fal... | 615 |
"""simple docstring"""
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__snake_case : Tuple = logging.get_logger(__name__)
def _lowerc... | 615 | 1 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup,... | 615 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@staticmethod
@abstractmethod
def _SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CAS... | 615 | 1 |
"""simple docstring"""
def _lowercase ( __snake_case ,__snake_case ) -> list:
__lowerCAmelCase : List[str] = len(__snake_case )
__lowerCAmelCase : Dict = []
for i in range(len(__snake_case ) - pat_len + 1 ):
__lowerCAmelCase ... | 615 |
"""simple docstring"""
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('hub/hopper-medium-v2/unet/hor32', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/unet/hor128', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/value_function', exist_ok=True)
... | 615 | 1 |
"""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 transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
f... | 615 |
"""simple docstring"""
import unittest
from knapsack import knapsack as k
class A__ ( unittest.TestCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self: Optional[int]) -> List[Any]:
"""simple docstring"""
... | 615 | 1 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is... | 615 |
"""simple docstring"""
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_ba... | 615 | 1 |
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