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 |
|---|---|---|---|---|
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
lowerCamelCase = logging.getLogger(__name__)
@dataclass
class lowercase__ ( SC... | 82 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 82 | 1 |
"""simple docstring"""
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = f"""{sampling_rate}"""
UpperCAmelCase_ = ... | 82 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
... | 82 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transfo... | 82 |
"""simple docstring"""
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCamelCase = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
UpperCAmelCase_ = mf_k... | 82 |
"""simple docstring"""
lowerCamelCase = """Alexander Joslin"""
import operator as op
from .stack import Stack
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = {"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}
UpperCAmelCase_ = Stack()
... | 82 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import TypedDict
class lowercase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
UpperCamelCase = 42
UpperCamelCase = 42
def a__ ( lowerCAmelCase__ ):
... | 82 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = int(number**0.5 )
return number == sq * sq
def a__ ( lowerCAmelCase__ , lowerCAmel... | 82 | 1 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = sorted(zip(lowerCAmelCase__ , lowerCAmelCase__ ) ... | 82 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise... | 82 | 1 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
f... | 82 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lower... | 82 | 1 |
"""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=... | 82 |
"""simple docstring"""
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 82 | 1 |
"""simple docstring"""
import gc
import threading
import time
import psutil
import torch
class lowercase__ :
'''simple docstring'''
def __init__( self : Tuple ) -> Dict:
'''simple docstring'''
Uppe... | 82 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create... | 82 | 1 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""t5-small""": """https://hugg... | 82 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = sorted(zip(lowerCAmelCase__ , lowerCAmelCase__ ) ... | 82 | 1 |
"""simple docstring"""
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowerCamelCase = parse(importlib.metadata.version("""torch"""))
def a__ ( lowerCAmelCase__ , lowerCAmel... | 82 |
"""simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
lowerCamelCase = re.compile(r"""\b(a|an|the)\b""", re.UNICODE)
lowerCamelCase = None
def a__ ( ):
UpperCAmelCase_ = ... | 82 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowerCamelCase = logging.get_logger(__name__)
class lowercase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float(moles / volume ) * nfactor )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float((moles * 0... | 82 | 1 |
"""simple docstring"""
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
... | 82 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
lowerCamelCase = 6_378_137.0
lowerCamelCase = 6_356_752.314_245
lowerCamelCase = 6_378_137
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ... | 82 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""L... | 82 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids... | 82 | 1 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ = None , lowerCAmelCase__ = None , lowerCAmelCase__ = False , ):
UpperCAmelCase_ = cipher_alphabet or [chr(lowerCAmelCase__ ) for i in... | 82 |
"""simple docstring"""
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowerCamelCase = 50_000
lowerCamelCase = 5_000
lowerCamelCase , lowerCamelCase = os.path.split(__file__)
lowerCamelCase = os.pat... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(lowerCAmelCase__ , n - 1 , lowerCAmelCase__ ) * a) % mod
... | 82 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowercase__ ( SCREAMING_SNAKE_CASE ):
... | 82 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 82 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowerCamelCase = False
class lowercase_... | 82 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return x if y == 0 else greatest_common_divisor(lowerCAmelCase__ , x % y )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return (x * y) // greatest_common_divisor(lowerCA... | 82 | 1 |
"""simple docstring"""
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
lowerCamelCase = ... | 82 |
"""simple docstring"""
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
... | 82 | 1 |
"""simple docstring"""
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_commo... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = 0
UpperCAmelCase_ = len(lowerCAmelCase__ )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase__ ):
if arr[i] > arr[j]:
... | 82 | 1 |
"""simple docstring"""
from sklearn.metrics import fa_score
import datasets
lowerCamelCase = """
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
"""
lowerCamelCase = """
Ar... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if number > 0:
raise ValueError("input must be a negative integer" )
UpperCAmelCase_ = len(bin(lowerCAmelCase__ )[3:] )
UpperCAmelCase_ = bin(abs(lowerCAmelCase__ ) - (1 << binary_num... | 82 | 1 |
"""simple docstring"""
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
lowerCamelCase = """Usage of script: script_name <size_of_canvas:int>"""
lowerCamelCase = [0] * 100 + [1] * 10
random.shuffle(cho... | 82 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..imag... | 82 | 1 |
"""simple docstring"""
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ... | 82 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 82 | 1 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class lowercase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self : Optional[int] , _UpperCAmel... | 82 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = set()
# To detect a back edge, keep track of vertices currently in the recursion stack
UpperCAmelCase_ = set()
return any(
node not in visited and depth_first_s... | 82 |
"""simple docstring"""
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCamelCase = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and... | 82 | 1 |
"""simple docstring"""
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class lowercase__ ( pl.LightningModule ):
'''simple docstring'''
def __in... | 82 |
"""simple docstring"""
lowerCamelCase = """Alexander Joslin"""
import operator as op
from .stack import Stack
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = {"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}
UpperCAmelCase_ = Stack()
... | 82 | 1 |
"""simple docstring"""
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_av... | 82 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = int(number**0.5 )
return number == sq * sq
def a__ ( lowerCAmelCase__ , lowerCAmel... | 82 | 1 |
"""simple docstring"""
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,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
... | 82 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise... | 82 | 1 |
"""simple docstring"""
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_d... | 82 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lower... | 82 | 1 |
"""simple docstring"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
lowerCamelCase = numpy.array([0, 0])
lowerCamelCase = numpy.array([0.5, 0.8_660_254])
lowerCamelCase = numpy.array([1, 0... | 82 |
"""simple docstring"""
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 82 | 1 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class lowercase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
UpperCamelCase = '''MCTCTFeatureExtractor'''
UpperCam... | 82 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create... | 82 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
lowerCamelCase = loggi... | 82 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = sorted(zip(lowerCAmelCase__ , lowerCAmelCase__ ) ... | 82 | 1 |
"""simple docstring"""
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class lowercase__ ( unittest.TestCase ):
'''simple docstring'''
def lowercase__ ... | 82 |
"""simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
lowerCamelCase = re.compile(r"""\b(a|an|the)\b""", re.UNICODE)
lowerCamelCase = None
def a__ ( ):
UpperCAmelCase_ = ... | 82 | 1 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class lowercase__ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _UpperCAmelCase : Union[str, Any] ) -> Any:
... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float(moles / volume ) * nfactor )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float((moles * 0... | 82 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowercase__ ( SCREAMING_SNAKE_CASE ):
... | 82 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
lowerCamelCase = 6_378_137.0
lowerCamelCase = 6_356_752.314_245
lowerCamelCase = 6_378_137
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ... | 82 | 1 |
"""simple docstring"""
import functools
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
# Validation
if not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ) or not all(isinstance(lowerCAmelCase__ , lowerCAmelCase__ ) for day in days ):
... | 82 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if len(lowerCAmelCase__ ) <= 1:
return lst
UpperCAmelCase_ = 1
while i < len(lowerCAmelCase__ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
... | 82 |
"""simple docstring"""
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowerCamelCase = 50_000
lowerCamelCase = 5_000
lowerCamelCase , lowerCamelCase = os.path.split(__file__)
lowerCamelCase = os.pat... | 82 | 1 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from... | 82 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowercase__ ( SCREAMING_SNAKE_CASE ):
... | 82 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .to... | 82 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowerCamelCase = False
class lowercase_... | 82 | 1 |
"""simple docstring"""
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from ... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return x if y == 0 else greatest_common_divisor(lowerCAmelCase__ , x % y )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return (x * y) // greatest_common_divisor(lowerCA... | 82 | 1 |
"""simple docstring"""
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
... | 82 |
"""simple docstring"""
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
... | 82 | 1 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
lowerCamelCase = """\
@INPROCEEDINGS{Papineni02bleu:a,
author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},
... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = 0
UpperCAmelCase_ = len(lowerCAmelCase__ )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase__ ):
if arr[i] > arr[j]:
... | 82 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
lowerCamelCase = logging.get_logger(__name__)
class lowercase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def _... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if number > 0:
raise ValueError("input must be a negative integer" )
UpperCAmelCase_ = len(bin(lowerCAmelCase__ )[3:] )
UpperCAmelCase_ = bin(abs(lowerCAmelCase__ ) - (1 << binary_num... | 82 | 1 |
"""simple docstring"""
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
lowerCamelCase = logging.get_logger(__name__)
def a__ ( lowerCAmelCase__=None , l... | 82 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..imag... | 82 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileNetVaConfig
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_confi... | 82 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 82 | 1 |
"""simple docstring"""
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 trans... | 82 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
... | 82 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase = {"""configuration_deit""": ["""DEIT_PRETRAINED_CONFIG_ARCHIVE... | 82 |
"""simple docstring"""
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCamelCase = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and... | 82 | 1 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..imag... | 82 |
"""simple docstring"""
lowerCamelCase = """Alexander Joslin"""
import operator as op
from .stack import Stack
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = {"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}
UpperCAmelCase_ = Stack()
... | 82 | 1 |
"""simple docstring"""
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...... | 82 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = int(number**0.5 )
return number == sq * sq
def a__ ( lowerCAmelCase__ , lowerCAmel... | 82 | 1 |
"""simple docstring"""
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_availabl... | 82 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise... | 82 | 1 |
"""simple docstring"""
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 = {
"""bert-b... | 82 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lower... | 82 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase = {"""configuration_unispeech""": ["""UNISPEECH_PRETRAINED_CONFIG... | 82 |
"""simple docstring"""
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 82 | 1 |
"""simple docstring"""
import os
def a__ ( ):
with open(os.path.dirname(lowerCAmelCase__ ) + "/p022_names.txt" ) as file:
UpperCAmelCase_ = str(file.readlines()[0] )
UpperCAmelCase_ = names.replace("\"" , "" ).split("," )
... | 82 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create... | 82 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase... | 82 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = sorted(zip(lowerCAmelCase__ , lowerCAmelCase__ ) ... | 82 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase = {
"""configuration_blip_2""": [
"""BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Blip2Config""",
"""... | 82 |
"""simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
lowerCamelCase = re.compile(r"""\b(a|an|the)\b""", re.UNICODE)
lowerCamelCase = None
def a__ ( ):
UpperCAmelCase_ = ... | 82 | 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 timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float(moles / volume ) * nfactor )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float((moles * 0... | 82 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""funnel-transformer/small""": """https://huggingface.co/funnel-transformer/small/resolve/main/config.json"... | 82 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
lowerCamelCase = 6_378_137.0
lowerCamelCase = 6_356_752.314_245
lowerCamelCase = 6_378_137
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ... | 82 | 1 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase__ ):
return len(set(lowerCAmelCase__ ) ) == len(lowerCAmelCase__ )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 82 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids... | 82 | 1 |
"""simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
lowerCamelCase = re.compile(r"""\b(a|an|the)\b""", re.UNICODE)
lowerCamelCase = None
def a__ ( ):
UpperCAmelCase_ = ... | 82 |
"""simple docstring"""
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowerCamelCase = 50_000
lowerCamelCase = 5_000
lowerCamelCase , lowerCamelCase = os.path.split(__file__)
lowerCamelCase = os.pat... | 82 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common i... | 82 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowercase__ ( SCREAMING_SNAKE_CASE ):
... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = 0
UpperCAmelCase_ = number
while duplicate > 0:
UpperCA... | 82 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowerCamelCase = False
class lowercase_... | 82 | 1 |
"""simple docstring"""
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def a__ ( lowerCAmelCase__ = True , *lowerCAmelCase__ , **lowerCAmelCase__ ):
if not is_tqdm_available... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return x if y == 0 else greatest_common_divisor(lowerCAmelCase__ , x % y )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return (x * y) // greatest_common_divisor(lowerCA... | 82 | 1 |
"""simple docstring"""
from collections import deque
class lowercase__ :
'''simple docstring'''
def __init__( self : int , _UpperCAmelCase : str , _UpperCAmelCase : int , _UpperCAmelCase : int )... | 82 |
"""simple docstring"""
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
... | 82 | 1 |
"""simple docstring"""
import unittest
import numpy as np
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ = None , ):
UpperCAmelCase_ = np.shape(lowerCAmelCase__ )
UpperCAmelCase_ = ... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = 0
UpperCAmelCase_ = len(lowerCAmelCase__ )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase__ ):
if arr[i] > arr[j]:
... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return x if y == 0 else greatest_common_divisor(lowerCAmelCase__ , x % y )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return (x * y) // greatest_common_divisor(lowerCA... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if number > 0:
raise ValueError("input must be a negative integer" )
UpperCAmelCase_ = len(bin(lowerCAmelCase__ )[3:] )
UpperCAmelCase_ = bin(abs(lowerCAmelCase__ ) - (1 << binary_num... | 82 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lower... | 82 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..imag... | 82 | 1 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_ba... | 82 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 82 | 1 |
"""simple docstring"""
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
... | 82 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
assert (
isinstance(lowerCAmelCase__ , lowerCAmelCase__ ) and number_of_steps > 0
), f"""number_of_steps needs to be positive integer, your input {number_of_steps}"""
if number_of_steps == 1:
... | 82 |
"""simple docstring"""
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCamelCase = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and... | 82 | 1 |
"""simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class low... | 82 |
"""simple docstring"""
lowerCamelCase = """Alexander Joslin"""
import operator as op
from .stack import Stack
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = {"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}
UpperCAmelCase_ = Stack()
... | 82 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase = {
"""configuration_electra""... | 82 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = int(number**0.5 )
return number == sq * sq
def a__ ( lowerCAmelCase__ , lowerCAmel... | 82 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encoder... | 82 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise... | 82 | 1 |
"""simple docstring"""
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
... | 82 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lower... | 82 | 1 |
"""simple docstring"""
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils i... | 82 |
"""simple docstring"""
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 82 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@da... | 82 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create... | 82 | 1 |
"""simple docstring"""
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
... | 82 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = sorted(zip(lowerCAmelCase__ , lowerCAmelCase__ ) ... | 82 | 1 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
lowerCamelCase = 6_378_137.0
lowerCamelCase = 6_356_752.314_245
lowerCamelCase = 6_378_137
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ... | 82 |
"""simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
lowerCamelCase = re.compile(r"""\b(a|an|the)\b""", re.UNICODE)
lowerCamelCase = None
def a__ ( ):
UpperCAmelCase_ = ... | 82 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase = {
"""configuration_resnet""": ["""RESNET_PRETRAINED_CONFIG... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float(moles / volume ) * nfactor )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float((moles * 0... | 82 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerca... | 82 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
lowerCamelCase = 6_378_137.0
lowerCamelCase = 6_356_752.314_245
lowerCamelCase = 6_378_137
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ... | 82 | 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
fro... | 82 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids... | 82 | 1 |
"""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/... | 82 |
"""simple docstring"""
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowerCamelCase = 50_000
lowerCamelCase = 5_000
lowerCamelCase , lowerCamelCase = os.path.split(__file__)
lowerCamelCase = os.pat... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = 0
UpperCAmelCase_ = len(lowerCAmelCase__ )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase__ ):
if arr[i] > arr[j]:
... | 82 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowercase__ ( SCREAMING_SNAKE_CASE ):
... | 82 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""shi-... | 82 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowerCamelCase = False
class lowercase_... | 82 | 1 |
"""simple docstring"""
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transforme... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return x if y == 0 else greatest_common_divisor(lowerCAmelCase__ , x % y )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return (x * y) // greatest_common_divisor(lowerCA... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ... | 82 |
"""simple docstring"""
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
... | 82 | 1 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelC... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = 0
UpperCAmelCase_ = len(lowerCAmelCase__ )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase__ ):
if arr[i] > arr[j]:
... | 82 | 1 |
"""simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if number > 0:
raise ValueError("input must be a negative integer" )
UpperCAmelCase_ = len(bin(lowerCAmelCase__ )[3:] )
UpperCAmelCase_ = bin(abs(lowerCAmelCase__ ) - (1 << binary_num... | 82 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase = {
"""configuration_longformer""": [
"""LONG... | 82 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..imag... | 82 | 1 |
"""simple docstring"""
lowerCamelCase = 9.80_665
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ = g ):
if fluid_density <= 0:
raise ValueError("Impossible fluid density" )
if volume < 0:
raise ValueError("Impos... | 82 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 82 | 1 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class lowercase__ ( nn.Module ):
'''simple docstring'''
UpperCamelCase = 42
UpperCamelCase = jnp.floataa
def lowercase__ ( self : Uni... | 82 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if number > 0:
raise ValueError("input must be a negative integer" )
UpperCAmelCase_ = len(bin(lowerCAmelCase__ )[3:] )
UpperCAmelCase_ = bin(abs(lowerCAmelCase__ ) - (1 << binary_num... | 82 |
"""simple docstring"""
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCamelCase = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and... | 82 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise... | 82 |
"""simple docstring"""
lowerCamelCase = """Alexander Joslin"""
import operator as op
from .stack import Stack
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = {"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}
UpperCAmelCase_ = Stack()
... | 82 | 1 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids... | 82 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = int(number**0.5 )
return number == sq * sq
def a__ ( lowerCAmelCase__ , lowerCAmel... | 82 | 1 |
"""simple docstring"""
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, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNet... | 82 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise... | 82 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""sayakpaul/vit-msn-base""": """https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json""",
... | 82 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lower... | 82 | 1 |
"""simple docstring"""
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
lowerCamelCase = re.compile(r"""^(?P<major>\d+)""" r"""\.(?P<minor>\d+)""" r"""\.(?P<patch>\d+)$""")
@total_... | 82 |
"""simple docstring"""
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 82 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowerCamelCase = {
"""configuration_ernie""": ["""ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ErnieConfig""", """... | 82 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create... | 82 | 1 |
"""simple docstring"""
from collections.abc import Callable
class lowercase__ :
'''simple docstring'''
def __init__( self : Tuple , _UpperCAmelCase : Callable | None = None ) -> None:
'''simple docstring'''
... | 82 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = sorted(zip(lowerCAmelCase__ , lowerCAmelCase__ ) ... | 82 | 1 |
"""simple docstring"""
import warnings
warnings.warn(
"""memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: """
"""`from accelerate import find_executable_batch_size` to avoid this warning.""",
FutureWarning,
)
... | 82 |
"""simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
lowerCamelCase = re.compile(r"""\b(a|an|the)\b""", re.UNICODE)
lowerCamelCase = None
def a__ ( ):
UpperCAmelCase_ = ... | 82 | 1 |
"""simple docstring"""
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_ava... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float(moles / volume ) * nfactor )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float((moles * 0... | 82 | 1 |
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