code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
a__ = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned"""
""" Distillation"""
... | 317 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformer... | 317 | 1 |
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...test_pipe... | 317 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : Any , ... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : int = 100 ) -> int:
_snake_case : List[Any] = n * (n + 1) * (2 * n + 1) / 6
_snake_case : Optional[int] = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __name__ == "__main__":
print(F'''{s... | 317 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : str , ... | 317 | 1 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
Re... | 317 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : List[Any] , ... | 317 | 1 |
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common ... | 317 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowercase ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> int:
return getitem, k
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , S... | 317 | 1 |
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from trans... | 317 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@require_torch
... | 317 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}
class snake_case ( SCREAMING... | 317 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
a__ = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paws""",... | 317 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamemb... | 317 |
import pprint
import requests
a__ = """https://zenquotes.io/api"""
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
... | 317 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/re... | 317 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indic... | 317 | 1 |
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
... | 317 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Optional[Any] = ["""torch"""]
def __init__( self : Union[str, Any] , *lowerC... | 317 | 1 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils... | 317 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""google/efficientnet-b7""": ... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : int ) -> int:
if n == 1 or not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
return 0
elif n == 2:
return 1
else:
_snake_case : Optional[Any] = [0, 1]
for i in range(2 , n + 1 ):
sequence.appen... | 317 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CA... | 317 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2Config"""],
... | 317 | 1 |
a__ = {
"joule": 1.0,
"kilojoule": 10_00,
"megajoule": 1_00_00_00,
"gigajoule": 10_00_00_00_00,
"wattsecond": 1.0,
"watthour": 36_00,
"kilowatthour": 3_60_00_00,
"newtonmeter": 1.0,
"calorie_nutr": 41_86.8,
"kilocalorie_nutr": 4_18_68_00.00,
"electronvol... | 317 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructu... | 317 | 1 |
from __future__ import annotations
class snake_case :
'''simple docstring'''
def __init__( self : str , lowerCAmelCase : str , lowerCAmelCase : str) -> Dict:
"""simple docstring"""
_snake_case , _snake_ca... | 317 |
import torch
from torch import nn
class snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self : int , lowerCAmelCase : Tuple , lowerCAmelCase : int , lowerCAmelCase : Any , lowerCAmelCase : T... | 317 | 1 |
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def lowercase ( SCREAMING_SNAKE_CASE__ : Sequence[float] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int... | 317 |
from ...processing_utils import ProcessorMixin
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : int = ["""image_processor""", """feature_extractor"""]
snake_case_ : List[Any] = """T... | 317 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
a__ = {
"""configuration_roc_bert""": ["""ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RoCBertConfig"""],
"""tokenization_roc_bert""": ["""RoCBertT... | 317 |
import unittest
import numpy as np
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, prepare_image_inputs
if is_torch_available():
... | 317 | 1 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Optional[Any] = ["""torch"""]
def __init__( self : Union[str, Any] , *lowerC... | 317 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/re... | 317 | 1 |
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
a__ = logging.get_logger(__name__)
def lowercase ( SCREAMING_SNAKE_CASE__ : List[str] , SCREAM... | 317 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from dat... | 317 | 1 |
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
a__ = """src/transformers"""
a__ = """docs/source/en/tasks"""
... | 317 |
from __future__ import annotations
from typing import TypedDict
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : str
snake_case_ : int
def lowercase ( SCREAMING_SNAKE_CASE__ : st... | 317 | 1 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jn... | 317 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_mo... | 317 | 1 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
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 b... | 317 |
def lowercase ( SCREAMING_SNAKE_CASE__ : str ) -> list:
_snake_case : Optional[Any] = [0] * len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , len(SCREAMING_SNAKE_CASE__ ) ):
# use last results for better performance - dynamic programming
_snake_case : Optiona... | 317 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""funnel-transformer/small""": """https://huggingface.co/funnel-transformer/small/resolve/main/config.json""",
"""funnel-transformer/small-base""": """https://hug... | 317 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformer... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : list , SCREAMING_SNAKE_CASE__ : list ) -> float:
_validate_point(SCREAMING_SNAKE_CASE__ )
_validate_point(SCREAMING_SNAKE_CASE__ )
if len(SCREAMING_SNAKE_CASE__ ) != len(SCREAMING_SNAKE_CASE__ ):
raise ValueError("""Both points must... | 317 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : Any , ... | 317 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
a__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_copies # noqa: E402
# This is the referenc... | 317 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : str , ... | 317 | 1 |
import pprint
import requests
a__ = """https://zenquotes.io/api"""
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
... | 317 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : List[Any] , ... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : Any ) -> Optional[Any]:
_snake_case : Optional[Any] = len(SCREAMING_SNAKE_CASE__ )
_snake_case : Union[str, Any] = sum(SCREAMING_SNAKE_CASE__ )
_snake_case : Union[str, Any] = [[False for x in range(s + 1 )]... | 317 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowercase ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> int:
return getitem, k
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , S... | 317 | 1 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import... | 317 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@require_torch
... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : list[int] , SCREAMING_SNAKE_CASE__ : int ) -> int:
def count_of_possible_combinations(SCREAMING_SNAKE_CASE__ : int ) -> int:
if target < 0:
return 0
if target == 0:
return 1
retu... | 317 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
a__ = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paws""",... | 317 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a__ = {
"""configuration_pix2struct""": [
"""PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Pix2StructConfig""",
"""Pix2StructTex... | 317 |
import pprint
import requests
a__ = """https://zenquotes.io/api"""
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
... | 317 | 1 |
from typing import Any
class snake_case :
'''simple docstring'''
def __init__( self : Union[str, Any] , lowerCAmelCase : Any) -> Union[str, Any]:
"""simple docstring"""
_snake_case : Optional[Any] = data
... | 317 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indic... | 317 | 1 |
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import Grad... | 317 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Optional[Any] = ["""torch"""]
def __init__( self : Union[str, Any] , *lowerC... | 317 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ = {
"""configuration_upernet""": ["""UperNetConfig"""],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAv... | 317 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""google/efficientnet-b7""": ... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , ) -> float:
_snake_case : List[Any] = [redshift, radiation_densi... | 317 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 | 1 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructu... | 317 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2Config"""],
... | 317 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : int = ["""image_processor""", """toke... | 317 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructu... | 317 | 1 |
from statistics import mean, stdev
def lowercase ( SCREAMING_SNAKE_CASE__ : list , SCREAMING_SNAKE_CASE__ : int = 3 ) -> list:
_snake_case : Any = min(SCREAMING_SNAKE_CASE__ )
_snake_case : List[Any] = max(SCREAMING_SNAKE_CASE__ )
# normalize data... | 317 |
import torch
from torch import nn
class snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self : int , lowerCAmelCase : Tuple , lowerCAmelCase : int , lowerCAmelCase : Any , lowerCAmelCase : T... | 317 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
a__ = logging.get_logger(__name... | 317 |
from ...processing_utils import ProcessorMixin
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : int = ["""image_processor""", """feature_extractor"""]
snake_case_ : List[Any] = """T... | 317 | 1 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
a__ = {
"""configuration_gpt_neox_japanese""": ["""GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXJapaneseConfig"""],
"""tokenizatio... | 317 |
import unittest
import numpy as np
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, prepare_image_inputs
if is_torch_available():
... | 317 | 1 |
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 317 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/re... | 317 | 1 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
a__ = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow("""""", """|""", """|"""),
dat... | 317 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from dat... | 317 | 1 |
from math import sqrt
def lowercase ( SCREAMING_SNAKE_CASE__ : int ) -> bool:
assert isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) and (
number >= 0
), "'number' must been an int and positive"
_snake_case : Tuple = True
# 0 and 1 are n... | 317 |
from __future__ import annotations
from typing import TypedDict
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : str
snake_case_ : int
def lowercase ( SCREAMING_SNAKE_CASE__ : st... | 317 | 1 |
import math
from datetime import datetime, timedelta
def lowercase ( SCREAMING_SNAKE_CASE__ : int ) -> datetime:
_snake_case : List[str] = year % 19
_snake_case : Any = year % 4
_snake_case : Optional[Any] = year % 7
_snake_case : int... | 317 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_mo... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : list ) -> list:
for i in range(len(SCREAMING_SNAKE_CASE__ ) - 1 , 0 , -1 ):
_snake_case : List[Any] = False
for j in range(SCREAMING_SNAKE_CASE__ , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
_snake_case ,... | 317 |
def lowercase ( SCREAMING_SNAKE_CASE__ : str ) -> list:
_snake_case : Optional[Any] = [0] * len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , len(SCREAMING_SNAKE_CASE__ ) ):
# use last results for better performance - dynamic programming
_snake_case : Optiona... | 317 | 1 |
from __future__ import annotations
def lowercase ( SCREAMING_SNAKE_CASE__ : list[float] ) -> float:
_snake_case : Dict = 0.0_0
_snake_case : Tuple = 0
for resistor in resistors:
if resistor <= 0:
_snake_case : Any = F'''Resistor at inde... | 317 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformer... | 317 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 317 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : Any , ... | 317 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ = {
"""configuration_roformer""": ["""ROFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP"... | 317 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : str , ... | 317 | 1 |
import math
def lowercase ( SCREAMING_SNAKE_CASE__ : int ) -> list[int]:
_snake_case : List[str] = []
_snake_case : Optional[int] = 2
_snake_case : List[str] = int(math.sqrt(SCREAMING_SNAKE_CASE__ ) ) # Size of every segment
_snake_case :... | 317 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : List[Any] , ... | 317 | 1 |
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxruntime as ort
... | 317 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowercase ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> int:
return getitem, k
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , S... | 317 | 1 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""nielsr/canine-s""": 20_48,
}
# Unicode defines 1,114,112 total “codepoints”
a__ = 1_11_41_12
# ... | 317 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@require_torch
... | 317 | 1 |
from __future__ import annotations
def lowercase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ) -> list[list[int]]:
_snake_case : list[list[int]] = []
create_all_state(1 , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , [] , SCRE... | 317 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
a__ = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paws""",... | 317 | 1 |
import operator as op
a__ = """scaler.pt"""
a__ = """pytorch_model"""
a__ = """random_states"""
a__ = """optimizer"""
a__ = """scheduler"""
a__ = """pytorch_model.bin"""
a__ = """pytorch_model.bin.index.json"""
a__ = """model.safetensors"""
a__ = """model.safetensors.inde... | 317 |
import pprint
import requests
a__ = """https://zenquotes.io/api"""
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
... | 317 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""",
]
}
try:
if not is_torch_available():
... | 317 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indic... | 317 | 1 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class snake_case ( SCREAMIN... | 317 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Optional[Any] = ["""torch"""]
def __init__( self : Union[str, Any] , *lowerC... | 317 | 1 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin... | 317 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""google/efficientnet-b7""": ... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : list ) -> list:
_snake_case : Any = len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , SCREAMING_SNAKE_CASE__ ):
_snake_case : List[Any] = collection[i]
_snake_case : Optional[Any] = 0
_snake_case : ... | 317 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if i... | 317 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2Config"""],
... | 317 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.testing_utils impo... | 317 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructu... | 317 | 1 |
from __future__ import annotations
from typing import TypedDict
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : str
snake_case_ : int
def lowercase ( SCREAMING_SNAKE_CASE__ : st... | 317 |
import torch
from torch import nn
class snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self : int , lowerCAmelCase : Tuple , lowerCAmelCase : int , lowerCAmelCase : Any , lowerCAmelCase : T... | 317 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
"""feature_extraction_mctct""": ["""MCTCTFeatureExtractor"""],
"""pr... | 317 |
from ...processing_utils import ProcessorMixin
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : int = ["""image_processor""", """feature_extractor"""]
snake_case_ : List[Any] = """T... | 317 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
a__ = {"""configuration_vit""": ["""VIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTConfig""",... | 317 |
import unittest
import numpy as np
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, prepare_image_inputs
if is_torch_available():
... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , SCREAMING_SNAKE_CASE__ : Optional[Any] , SCREAMING_SNAKE_CASE__ : Optional[Any]=False ) -> Dict:
if isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) and isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE... | 317 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/re... | 317 | 1 |
import unittest
import numpy as np
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, prepare_image_inputs
if is_torch_available():
... | 317 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from dat... | 317 | 1 |
import requests
def lowercase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ) -> None:
_snake_case : str = {"""Content-Type""": """application/json"""}
_snake_case : Tuple = requests.post(SCREAMING_SNAKE_CASE__ , json={"""text""":... | 317 |
from __future__ import annotations
from typing import TypedDict
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : str
snake_case_ : int
def lowercase ( SCREAMING_SNAKE_CASE__ : st... | 317 | 1 |
import pytest
a__ = """__dummy_dataset1__"""
a__ = """
import json
import os
import datasets
REPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"
URLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": REPO_URL + \"wikiann-bn-validation.... | 317 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_mo... | 317 | 1 |
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
a__ = {
# 1536-bit
5: {
"""prime""": int(
"""FFFFFFF... | 317 |
def lowercase ( SCREAMING_SNAKE_CASE__ : str ) -> list:
_snake_case : Optional[Any] = [0] * len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , len(SCREAMING_SNAKE_CASE__ ) ):
# use last results for better performance - dynamic programming
_snake_case : Optiona... | 317 | 1 |
import math
import qiskit
def lowercase ( SCREAMING_SNAKE_CASE__ : int = 1 , SCREAMING_SNAKE_CASE__ : int = 1 , SCREAMING_SNAKE_CASE__ : int = 1 ) -> qiskit.result.counts.Counts:
if (
isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ )
or ... | 317 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformer... | 317 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM,
... | 317 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : Any , ... | 317 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
a__ = {
"""configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5OnnxConfig"""],
}
try:
if not is_torch_ava... | 317 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : str , ... | 317 | 1 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common im... | 317 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : List[Any] , ... | 317 | 1 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : str , ... | 317 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowercase ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> int:
return getitem, k
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , S... | 317 | 1 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_b... | 317 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@require_torch
... | 317 | 1 |
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
a__ = 0
a__ = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, 0, ... | 317 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
a__ = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paws""",... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ) -> str:
if not (isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) and isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ )):
raise ValueError("""longest_common_substring() ... | 317 |
import pprint
import requests
a__ = """https://zenquotes.io/api"""
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
... | 317 | 1 |
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 .tokenization_mvp import MvpTokenizer... | 317 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indic... | 317 | 1 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from dat... | 317 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Optional[Any] = ["""torch"""]
def __init__( self : Union[str, Any] , *lowerC... | 317 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class snake_case ( SCREAMING_SNAKE_CASE_ )... | 317 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""google/efficientnet-b7""": ... | 317 | 1 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code... | 317 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2Config"""],
... | 317 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2Config"""],
... | 317 | 1 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils... | 317 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructu... | 317 | 1 |
import requests
a__ = """""" # <-- Put your OpenWeatherMap appid here!
a__ = """https://api.openweathermap.org/data/2.5/"""
def lowercase ( SCREAMING_SNAKE_CASE__ : str = "Chicago" , SCREAMING_SNAKE_CASE__ : str = APPID ) -> dict:
return requests.get(URL_BASE + ... | 317 |
import torch
from torch import nn
class snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self : int , lowerCAmelCase : Tuple , lowerCAmelCase : int , lowerCAmelCase : Any , lowerCAmelCase : T... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : int = 1_000_000 ) -> int:
_snake_case : Any = limit + 1
_snake_case : Tuple = [0] * limit
for first_term in range(1 , SCREAMING_SNAKE_CASE__ ):
for n in range(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , ... | 317 |
from ...processing_utils import ProcessorMixin
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : int = ["""image_processor""", """feature_extractor"""]
snake_case_ : List[Any] = """T... | 317 | 1 |
a__ = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.609_344,
"knot": 1.852,
}
a__ = {
"km/h": 1.0,
"m/s": 0.277_777_778,
"mph": 0.621_371_192,
"knot": 0.539_956_803,
}
def lowercase ( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ :... | 317 |
import unittest
import numpy as np
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, prepare_image_inputs
if is_torch_available():
... | 317 | 1 |
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)
def lowercas... | 317 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/re... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : int ) -> int:
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise TypeError("""Input value must be an 'int' type""" )
_snake_case : List[Any] = 0
while number:
position += 1
number >>= 1
ret... | 317 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from dat... | 317 | 1 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
... | 317 |
from __future__ import annotations
from typing import TypedDict
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : str
snake_case_ : int
def lowercase ( SCREAMING_SNAKE_CASE__ : st... | 317 | 1 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowercase ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> int:
return getitem, k
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , S... | 317 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_mo... | 317 | 1 |
from __future__ import annotations
def lowercase ( SCREAMING_SNAKE_CASE__ : list[int] ) -> bool:
return len(set(SCREAMING_SNAKE_CASE__ ) ) == len(SCREAMING_SNAKE_CASE__ )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 317 |
def lowercase ( SCREAMING_SNAKE_CASE__ : str ) -> list:
_snake_case : Optional[Any] = [0] * len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , len(SCREAMING_SNAKE_CASE__ ) ):
# use last results for better performance - dynamic programming
_snake_case : Optiona... | 317 | 1 |
from math import isqrt
def lowercase ( SCREAMING_SNAKE_CASE__ : int ) -> list[int]:
_snake_case : List[Any] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , SCREAMING_SNAKE_CASE__ , SCREAMING... | 317 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformer... | 317 | 1 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplatePro... | 317 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : Any , ... | 317 | 1 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
a__ = TypeVar("""T""")
class snake_case ( Generic[T] ):
'''simple docstring'''
def __init__( self : Optional[Any] , lowerCAmelC... | 317 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : str , ... | 317 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
a__ = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""SPEECHT5_PRETRAIN... | 317 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
a__ = logging.get_logger(__name__)
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def __init__( self : List[Any] , ... | 317 | 1 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowercase ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> int:
return getitem, k
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , S... | 317 | 1 |
from ...processing_utils import ProcessorMixin
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : int = ["""image_processor""", """feature_extractor"""]
snake_case_ : List[Any] = """T... | 317 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@require_torch
... | 317 | 1 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
a__ = get_tests_dir() + ""... | 317 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
a__ = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paws""",... | 317 | 1 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowercase ( SCREAMING_SNAKE_CASE__ : Tuple , SCREAMING_SNAKE_CASE__ : bool = True , SCREAMING_SNAKE_CASE__ : float = math.inf , SCREAMING_SNAKE_CASE__ : float = -math.i... | 317 |
import pprint
import requests
a__ = """https://zenquotes.io/api"""
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def lowercase ( ) -> list:
return requests.get(API_ENDPOINT_URL + """/random""" ).json()
... | 317 | 1 |
def lowercase ( SCREAMING_SNAKE_CASE__ : Dict , SCREAMING_SNAKE_CASE__ : str ) -> List[str]:
_snake_case : Any = [0 for i in range(r + 1 )]
# nc0 = 1
_snake_case : Any = 1
for i in range(1 , n + 1 ):
# to compute current row from previous row.
... | 317 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indic... | 317 | 1 |
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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indic... | 317 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Optional[Any] = ["""torch"""]
def __init__( self : Union[str, Any] , *lowerC... | 317 | 1 |
class snake_case :
'''simple docstring'''
def __init__( self : Any , lowerCAmelCase : int , lowerCAmelCase : List[str]=None , lowerCAmelCase : Dict=None) -> Dict:
"""simple docstring"""
_snake_case : Any ... | 317 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ = logging.get_logger(__name__)
a__ = {
"""google/efficientnet-b7""": ... | 317 | 1 |
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_uti... | 317 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 | 1 |
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