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 |
|---|---|---|---|---|
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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_im... | 613 | def snake_case__ ( lowercase ):
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: int = 0, 0, 0
lowerCAmelCase_: Union[str, Any] = ugly_nums[ia] * 2
lowerCAmelCase_: str = ugly_nums[ia] * 3
lowerCAmelCase_... | 613 | 1 |
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokeniza... | 613 | import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def snake_case__ ( lowercase ):
return Envi... | 613 | 1 |
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
a : List[str] = False
class _lowercase ( unittest.TestCase ):
... | 613 | def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: list[list[str]] = [[] for _ in range(lowercase )]
lowerCAmelCase_: Optional[Any] = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative" )
if key == 1 or len(lowercase ... | 613 | 1 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def snake_case__ ( lowercase , lowercase , lowercase = "x" , lowercase = 10**-10 , lowercase = 1 , ):
lowerCAmelCase_: Optional[int] = symbols(lowercase )
lowerCAme... | 613 | import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,
... | 613 | 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():
import torch
if ... | 613 | import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def snake_case__ ( lowercase , l... | 613 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : Dict = {
"""configuration_pix2struct""": [
"""PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Pix2StructConfig""",
"""Pix2Stru... | 613 | from math import isqrt
def snake_case__ ( lowercase ):
lowerCAmelCase_: List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase , lowercase ):
lowerCAmelCas... | 613 | 1 |
def snake_case__ ( lowercase ):
lowerCAmelCase_: Optional[Any] = int(lowercase )
if n_element < 1:
lowerCAmelCase_: int = ValueError("a should be a positive number" )
raise my_error
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowe... | 613 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : int = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BridgeTowerConfig""",
"""Bridge... | 613 | 1 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerForObjectDetection
from tr... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : List[str] = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class _lowercase ( Upper... | 613 | 1 |
from pathlib import Path
import numpy as np
from PIL import Image
def snake_case__ ( lowercase ):
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: Tuple = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2989 * r + 0.5870 * g + 0.1140 * b
def snake_case__ ( lowercase ):
return... | 613 | 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 : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 613 | 1 |
import itertools
import math
def snake_case__ ( lowercase ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes number are in... | 613 | import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available
... | 613 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Any = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class _lowercase ( UpperCAmelCase__ ):
... | 613 | def snake_case__ ( lowercase , lowercase ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
doctest.testm... | 613 | 1 |
from __future__ import annotations
def snake_case__ ( lowercase ):
if len(lowercase ) == 0:
return []
lowerCAmelCase_ , lowerCAmelCase_: Union[str, Any] = min(lowercase ), max(lowercase )
lowerCAmelCase_: str = int(max_value - min_value ) + 1
lowerCAmelC... | 613 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTokenizer, BlipImageProcessor, BlipPr... | 613 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a : List[str] = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MA... | 613 | 1 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def snake_case__ ( lowercase ):
lowerCAmelCase_:... | 613 | 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
a : List[str] = False
class _lowercase ( unittest.TestCase ):
... | 613 | 1 |
def snake_case__ ( lowercase ):
lowerCAmelCase_: Dict = len(lowercase )
for _ in range(lowercase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
lowerCAmelCase_ , lowerCAmelCase_: int = arr[i + 1], arr[i... | 613 | class _lowercase :
'''simple docstring'''
def __init__( self ):
lowerCAmelCase_: dict[str, TrieNode] = {} # Mapping from char to TrieNode
lowerCAmelCase_: str = False
def _a ( self , lowerCamelCase__ ):
for word in ... | 613 | 1 |
import baseaa
def snake_case__ ( lowercase ):
return baseaa.baaencode(string.encode("utf-8" ) )
def snake_case__ ( lowercase ):
return baseaa.baadecode(lowercase ).decode("utf-8" )
if __name__ == "__main__":
a : str = """Hello World!"""
a : Tuple ... | 613 | from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils import Mo... | 613 | 1 |
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load_metric
from .utils import ... | 613 | import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import Te... | 613 | 1 |
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_configuration_common import ConfigTester
from ...test_... | 613 | from __future__ import annotations
def snake_case__ ( lowercase , lowercase ):
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(lowercase ):
print(F'''{i}\t\t{d}''' )
def snake_case__ ( lowercase , lowercase , lowercase ):
... | 613 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
a : Dict = {
"""configuration_audio_spectrogram_transformer""": [
"""AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AS... | 613 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : List[str] = {
"""xlm-mlm-en-2048""": """https://hugg... | 613 | 1 |
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_available,
nested_simplify,
require_tf,
... | 613 | 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 FlaxModelTesterM... | 613 | 1 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ran... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",... | 613 | 1 |
import qiskit
def snake_case__ ( lowercase = 2 ):
lowerCAmelCase_: int = qubits
# Using Aer's simulator
lowerCAmelCase_: int = qiskit.Aer.get_backend("aer_simulator" )
# Creating a Quantum Circuit acting on the q register
lowerCAmelCase_: Tuple = qiskit.Qu... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Any = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class _lowercase ( UpperCAmelCase__ ):
... | 613 | 1 |
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
a : str = argparse.ArgumentParser("""Stable Diffusion script with intel optimization""", add_help=False)
parser.add_argument("""--dpm""", action="""s... | 613 | def snake_case__ ( lowercase ):
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: int = 0, 0, 0
lowerCAmelCase_: Union[str, Any] = ugly_nums[ia] * 2
lowerCAmelCase_: str = ugly_nums[ia] * 3
lowerCAmelCase_... | 613 | 1 |
def snake_case__ ( lowercase ):
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: int = 0, 0, 0
lowerCAmelCase_: Union[str, Any] = ugly_nums[ia] * 2
lowerCAmelCase_: str = ugly_nums[ia] * 3
lowerCAmelCase_... | 613 | import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def snake_case__ ( lowercase ):
return Envi... | 613 | 1 |
import math
from collections.abc import Callable
def snake_case__ ( lowercase , lowercase , lowercase ):
lowerCAmelCase_: float = xa
lowerCAmelCase_: float = xa
while True:
if x_n == x_na or function(lowercase ) == function(lowercase ):
ra... | 613 | def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: list[list[str]] = [[] for _ in range(lowercase )]
lowerCAmelCase_: Optional[Any] = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative" )
if key == 1 or len(lowercase ... | 613 | 1 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case__ ( lowercase , lowercase , lowercase ):
# Construct model
if gpta_config_... | 613 | import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,
... | 613 | 1 |
import unittest
from knapsack import knapsack as k
class _lowercase ( unittest.TestCase ):
'''simple docstring'''
def _a ( self ):
lowerCAmelCase_: Tuple = 0
lowerCAmelCase_: Tuple = [0]
lowerCAmelCase_: List[str] = [0... | 613 | import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def snake_case__ ( lowercase , l... | 613 | 1 |
from __future__ import annotations
def snake_case__ ( lowercase , lowercase , lowercase , lowercase ): # noqa: E741
while r - l > 1:
lowerCAmelCase_: str = (l + r) // 2
if v[m] >= key:
lowerCAmelCase_: Any = m
else:
lowerC... | 613 | from math import isqrt
def snake_case__ ( lowercase ):
lowerCAmelCase_: List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase , lowercase ):
lowerCAmelCas... | 613 | 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():
import torch
if ... | 613 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : int = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BridgeTowerConfig""",
"""Bridge... | 613 | 1 |
from math import isqrt
def snake_case__ ( lowercase ):
lowerCAmelCase_: List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase , lowercase ):
lowerCAmelCas... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : List[str] = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class _lowercase ( Upper... | 613 | 1 |
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 ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWithNoAttention,
BaseModelOutputWithPooli... | 613 | 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 : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 613 | 1 |
from math import factorial
a : Any = {str(d): factorial(d) for d in range(1_0)}
def snake_case__ ( lowercase ):
return sum(DIGIT_FACTORIAL[d] for d in str(lowercase ) )
def snake_case__ ( ):
lowerCAmelCase_: str = 7 * factorial(9 ) + 1
return sum(i for i i... | 613 | import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available
... | 613 | 1 |
import warnings
from functools import wraps
from typing import Callable
def snake_case__ ( lowercase ):
@wraps(lowercase )
def _inner_fn(*lowercase , **lowercase ):
warnings.warn(
(F'''\'{fn.__name__}\' is experimental and might be subject to breaking changes in the future... | 613 | def snake_case__ ( lowercase , lowercase ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
doctest.testm... | 613 | 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 FlaxModelTesterM... | 613 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | 1 |
from __future__ import annotations
a : List[Any] = [-1_0, -5, 0, 5, 5.1, 1_1, 1_3, 2_1, 3, 4, -2_1, -1_0, -5, -1, 0]
a : Union[str, Any] = [-5, 0, 5, 5.1, 1_1, 1_3, 2_1, -1, 4, -1, -1_0, -5, -1, 0, -1]
def snake_case__ ( lowercase ):
lowerCAmelCase_: Tuple ... | 613 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a : List[str] = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MA... | 613 | 1 |
import os
def snake_case__ ( lowercase = "input.txt" ):
with open(os.path.join(os.path.dirname(lowercase ) , lowercase ) ) as input_file:
lowerCAmelCase_: Dict = [
[int(lowercase ) for element in line.split("," )]
for line in input_file.readl... | 613 | 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
a : List[str] = False
class _lowercase ( unittest.TestCase ):
... | 613 | 1 |
import numpy as np
from PIL import Image
def snake_case__ ( lowercase , lowercase , lowercase ):
lowerCAmelCase_: List[str] = np.array(lowercase )
if arr.shape[0] != arr.shape[1]:
raise ValueError("The input array is not a square matrix" )
lowerCAmelCase_: ... | 613 | class _lowercase :
'''simple docstring'''
def __init__( self ):
lowerCAmelCase_: dict[str, TrieNode] = {} # Mapping from char to TrieNode
lowerCAmelCase_: str = False
def _a ( self , lowerCamelCase__ ):
for word in ... | 613 | 1 |
def snake_case__ ( lowercase , lowercase ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
doctest.testm... | 613 | from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils import Mo... | 613 | 1 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from torc... | 613 | import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import Te... | 613 | 1 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,
... | 613 | from __future__ import annotations
def snake_case__ ( lowercase , lowercase ):
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(lowercase ):
print(F'''{i}\t\t{d}''' )
def snake_case__ ( lowercase , lowercase , lowercase ):
... | 613 | 1 |
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForImageClassification,
MobileViTVaForSem... | 613 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : List[str] = {
"""xlm-mlm-en-2048""": """https://hugg... | 613 | 1 |
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
require_torch,
requi... | 613 | 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 FlaxModelTesterM... | 613 | 1 |
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that ther... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",... | 613 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : List[str] = {
"""xlm-mlm-en-2048""": """https://hugg... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Any = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class _lowercase ( UpperCAmelCase__ ):
... | 613 | 1 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
)
from trans... | 613 | def snake_case__ ( lowercase ):
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: int = 0, 0, 0
lowerCAmelCase_: Union[str, Any] = ugly_nums[ia] * 2
lowerCAmelCase_: str = ugly_nums[ia] * 3
lowerCAmelCase_... | 613 | 1 |
def snake_case__ ( lowercase ):
stooge(lowercase , 0 , len(lowercase ) - 1 )
return arr
def snake_case__ ( lowercase , lowercase , lowercase ):
if i >= h:
return
# If first element is smaller than the last then swap them
if arr[i] > arr[h]:... | 613 | import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def snake_case__ ( lowercase ):
return Envi... | 613 | 1 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def snake_case__ ( lowercase , lowercase , lowercase ):
lowerCAmelCase_: Any = 0
if start < end:
lowerCAmelCase_: int = randint(lowercase , lowercase )
lowerC... | 613 | def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: list[list[str]] = [[] for _ in range(lowercase )]
lowerCAmelCase_: Optional[Any] = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative" )
if key == 1 or len(lowercase ... | 613 | 1 |
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax import jit
from transformers import ... | 613 | import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,
... | 613 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Any = {
"""facebook/s2t-small-librispeech-asr""": (
"""https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/confi... | 613 | import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def snake_case__ ( lowercase , l... | 613 | 1 |
def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: list[list[str]] = [[] for _ in range(lowercase )]
lowerCAmelCase_: Optional[Any] = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative" )
if key == 1 or len(lowercase ... | 613 | from math import isqrt
def snake_case__ ( lowercase ):
lowerCAmelCase_: List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase , lowercase ):
lowerCAmelCas... | 613 | 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 import logging
from... | 613 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : int = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BridgeTowerConfig""",
"""Bridge... | 613 | 1 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import BaseTran... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : List[str] = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class _lowercase ( Upper... | 613 | 1 |
def snake_case__ ( lowercase , lowercase ):
return abs(lowercase ) if a == 0 else greatest_common_divisor(b % a , lowercase )
def snake_case__ ( lowercase , lowercase ):
while y: # --> when y=0 then loop will terminate and return x as final GCD.
lowerCAmelCa... | 613 | 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 : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 613 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : List[str] = {
"""configuration_xlm_roberta_xl""": [
"""XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XLMRobertaXLConfig""",
"""XLMRobertaXLOn... | 613 | import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available
... | 613 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a : str = {
"""configuration_layoutlmv3""": [
"""LAYOUTLMV3_PRETRAINED_CONF... | 613 | def snake_case__ ( lowercase , lowercase ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
doctest.testm... | 613 | 1 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torc... | 613 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | 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
a : Optional[int] = logging.get_logger(__name__)
a : Any = {
"""fa... | 613 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a : List[str] = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MA... | 613 | 1 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase__ )
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE... | 613 | 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
a : List[str] = False
class _lowercase ( unittest.TestCase ):
... | 613 | 1 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | class _lowercase :
'''simple docstring'''
def __init__( self ):
lowerCAmelCase_: dict[str, TrieNode] = {} # Mapping from char to TrieNode
lowerCAmelCase_: str = False
def _a ( self , lowerCamelCase__ ):
for word in ... | 613 | 1 |
import os
from distutils.util import strtobool
def snake_case__ ( lowercase , lowercase ):
for e in env_keys:
lowerCAmelCase_: Optional[Any] = int(os.environ.get(lowercase , -1 ) )
if val >= 0:
return val
return default
def snake_case__ ( lowerc... | 613 | from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils import Mo... | 613 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
from .... | 613 | import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import Te... | 613 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : List[str] = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class _lowercase ( Upper... | 613 | from __future__ import annotations
def snake_case__ ( lowercase , lowercase ):
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(lowercase ):
print(F'''{i}\t\t{d}''' )
def snake_case__ ( lowercase , lowercase , lowercase ):
... | 613 | 1 |
import pytest
import datasets
# Import fixture modules as plugins
a : List[str] = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def snake_case__ ( lowercase , lowercase ):
# Mark tests as "unit" by default if not marked as "integration" (or... | 613 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : List[str] = {
"""xlm-mlm-en-2048""": """https://hugg... | 613 | 1 |
class _lowercase :
'''simple docstring'''
def __init__( self ):
lowerCAmelCase_: dict[str, TrieNode] = {} # Mapping from char to TrieNode
lowerCAmelCase_: str = False
def _a ( self , lowerCamelCase__ ):
for word in ... | 613 | 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 FlaxModelTesterM... | 613 | 1 |
from ..utils import DummyObject, requires_backends
class _lowercase ( metaclass=UpperCAmelCase__ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE: Union[str, Any] = ['keras_nlp']
def __init__( self , *lowerCamelCase__ , **lowerCamelCase__ ):
... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",... | 613 | 1 |
a : int = {
0: """0""",
1: """1""",
2: """2""",
3: """3""",
4: """4""",
5: """5""",
6: """6""",
7: """7""",
8: """8""",
9: """9""",
1_0: """a""",
1_1: """b""",
1_2: """c""",
1_3: """d""",
1_4: """e""",
1_5: """f""",
}
def snake_case__... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Any = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class _lowercase ( UpperCAmelCase__ ):
... | 613 | 1 |
from ... import PretrainedConfig
a : Optional[int] = {
"""sijunhe/nezha-cn-base""": """https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json""",
}
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE: Optional[Any] ... | 613 | def snake_case__ ( lowercase ):
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: int = 0, 0, 0
lowerCAmelCase_: Union[str, Any] = ugly_nums[ia] * 2
lowerCAmelCase_: str = ugly_nums[ia] * 3
lowerCAmelCase_... | 613 | 1 |
def snake_case__ ( lowercase ):
lowerCAmelCase_: list[list[int]] = [[0 for _ in range(lowercase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
lowerCAmelCase_: int = 1
for n in range(m + 1 ):
for k in range(1 , lowercase ):
m... | 613 | import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def snake_case__ ( lowercase ):
return Envi... | 613 | 1 |
def snake_case__ ( ):
lowerCAmelCase_: List[Any] = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
lowerCAmelCase_: List[str] = 6
lowerCAmelCase_: Optional[int] = 1
lowerCAmelCase_: Dict = 1901
lowerCAmelCase_: Tuple = 0
while year < 2... | 613 | def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: list[list[str]] = [[] for _ in range(lowercase )]
lowerCAmelCase_: Optional[Any] = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative" )
if key == 1 or len(lowercase ... | 613 | 1 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Prophet... | 613 | import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,
... | 613 | 1 |
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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.set_ver... | 613 | import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def snake_case__ ( lowercase , l... | 613 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",... | 613 | from math import isqrt
def snake_case__ ( lowercase ):
lowerCAmelCase_: List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase , lowercase ):
lowerCAmelCas... | 613 | 1 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transformer import PriorTransformer
from... | 613 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : int = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BridgeTowerConfig""",
"""Bridge... | 613 | 1 |
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def snake_case__ ( lowercase ):
return Envi... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : List[str] = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class _lowercase ( Upper... | 613 | 1 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE: Tuple = 'EncodecFeatureExtractor'
SCREAMING_SNAKE_CASE: ... | 613 | 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 : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 613 | 1 |
import argparse
import os
import re
a : Tuple = """src/diffusers"""
# Pattern that looks at the indentation in a line.
a : Tuple = re.compile(r"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
a : Dict = re.compile(r"""^\s*\"([^\"]+... | 613 | import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available
... | 613 | 1 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class _lowercase ( unittest.TestCase ):
'''simple docstring'''
def _a ( ... | 613 | def snake_case__ ( lowercase , lowercase ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
doctest.testm... | 613 | 1 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_ima... | 613 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | 1 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common... | 613 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a : List[str] = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MA... | 613 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a : Tuple = {
"""configuration_vision_text_dual_encoder""": ["""VisionTextDualEncoderConfig"""],
"""processing... | 613 | 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
a : List[str] = False
class _lowercase ( unittest.TestCase ):
... | 613 | 1 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def snake_case__ ( lowercase ):
return (data["data"], data["target"])
def s... | 613 | class _lowercase :
'''simple docstring'''
def __init__( self ):
lowerCAmelCase_: dict[str, TrieNode] = {} # Mapping from char to TrieNode
lowerCAmelCase_: str = False
def _a ( self , lowerCamelCase__ ):
for word in ... | 613 | 1 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class _lowercase :
'''simple docstring'''
SCREAMING_SNAKE_CASE: int
SCREAMING_SNAKE_CASE: int
class _lowercase :
'''... | 613 | from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils import Mo... | 613 | 1 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def snake_case__ ( lowercase ):
lowerCAmelCase_: int = FileLock(str(tmpdir / "foo.lock" ) )
lowerCAmelCase_: str = FileLock(str(tmpdir / "foo.lock" ) )
lowerCAmelCase_: ... | 613 | import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import Te... | 613 | 1 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
a : Dict = {
"""config""": [
"""EXTERNAL_DATA_FORMAT_SIZE_LIMIT""",
"""OnnxConfig""",
"""OnnxConfigWithPast""",
"""OnnxSeq2SeqConfigWithPast""",
"""PatchingSpec""",
],
"""convert""... | 613 | from __future__ import annotations
def snake_case__ ( lowercase , lowercase ):
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(lowercase ):
print(F'''{i}\t\t{d}''' )
def snake_case__ ( lowercase , lowercase , lowercase ):
... | 613 | 1 |
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
a : List[str] = logging.get_logger(__name__)
a : Opt... | 613 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : List[str] = {
"""xlm-mlm-en-2048""": """https://hugg... | 613 | 1 |
def snake_case__ ( lowercase ):
if not head:
return True
# split the list to two parts
lowerCAmelCase_ , lowerCAmelCase_: List[Any] = head.next, head
while fast and fast.next:
lowerCAmelCase_: List[str] = fast.next.next
lowerCAmelCase_: Any = slo... | 613 | 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 FlaxModelTesterM... | 613 | 1 |
from typing import Dict, Optional
import numpy as np
import datasets
a : List[Any] = """
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For binary (two classes) or multi-clas... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",... | 613 | 1 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class _lowercase ( unittest.TestCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE: Optional[Any] = JukeboxTokenizer
SCREAMING_SNAKE_CASE: List[str] ... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Any = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class _lowercase ( UpperCAmelCase__ ):
... | 613 | 1 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def snake_case__ ( lowercase , lowercase ):
assert isinstance(lowercase , ... | 613 | def snake_case__ ( lowercase ):
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: int = 0, 0, 0
lowerCAmelCase_: Union[str, Any] = ugly_nums[ia] * 2
lowerCAmelCase_: str = ugly_nums[ia] * 3
lowerCAmelCase_... | 613 | 1 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...te... | 613 | import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def snake_case__ ( lowercase ):
return Envi... | 613 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
a : Optional[int] = 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 r... | 613 | def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: list[list[str]] = [[] for _ in range(lowercase )]
lowerCAmelCase_: Optional[Any] = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative" )
if key == 1 or len(lowercase ... | 613 | 1 |
from __future__ import annotations
import math
from collections.abc import Callable
def snake_case__ ( lowercase , lowercase , lowercase , lowercase = 100 , ):
lowerCAmelCase_: Union[str, Any] = x_start
lowerCAmelCase_: List[Any] = fnc(lowercase ... | 613 | import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,
... | 613 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
a : List[str] = {"""tokenization_wav2vec2_phoneme""": ["""Wav2Vec2PhonemeCTCTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
a : List[Any] ... | 613 | import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def snake_case__ ( lowercase , l... | 613 | 1 |
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if not is_tf_available() and not ... | 613 | from math import isqrt
def snake_case__ ( lowercase ):
lowerCAmelCase_: List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase , lowercase ):
lowerCAmelCas... | 613 | 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 : Union[str, Any] = get_te... | 613 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : int = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BridgeTowerConfig""",
"""Bridge... | 613 | 1 |
from math import factorial, radians
def snake_case__ ( lowercase , lowercase = 18 , lowercase = 10 ):
lowerCAmelCase_: Optional[int] = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Converting from degrees to radians
lowerCAmelCase_: List[Any] = rad... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : List[str] = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class _lowercase ( Upper... | 613 | 1 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
def __init__( sel... | 613 | 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 : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 613 | 1 |
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
a : Union[str, Any] = namedtuple(
"""_TestCommandArgs""",
[
... | 613 | import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available
... | 613 | 1 |
from __future__ import annotations
class _lowercase :
'''simple docstring'''
def __init__( self , lowerCamelCase__ ):
lowerCAmelCase_: str = TypeError(
"Matrices must be formed from a list of zero or more lists containing at "
"least one ... | 613 | def snake_case__ ( lowercase , lowercase ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
doctest.testm... | 613 | 1 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
a : int = logging.get_logger("""transformers.models.speecht5""")
def snake_case__ ( lowercase , lowercase , lowercase ):
... | 613 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | 1 |
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