code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
def a__ ( UpperCAmelCase : int ):
if isinstance(__a , __a ):
raise TypeError('''\'float\' object cannot be interpreted as an integer''' )
if isinstance(__a , __a ):
raise TypeError('''\'str\' object cannot be interpreted as an integer''' )
if nu... | 350 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common imp... | 99 | 0 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class __UpperCAmelCase ( lowercase__ ):
def __init__( self : Tuple, __A : str="", __A : str="train" ):
assert os.path.isdir(lowercase_ )
UpperCAmel... | 351 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Train... | 99 | 0 |
def a__ ( UpperCAmelCase : int = 600_851_475_143 ) -> int:
try:
UpperCAmelCase : int = int(_snake_case )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <= 0:
raise ValueError('''Par... | 352 |
from ..utils import DummyObject, requires_backends
class __UpperCAmelCase ( metaclass=lowerCamelCase__ ):
UpperCamelCase = ["""onnx"""]
def __init__( self : int, *__A : Optional[Any], **__A : Dict ):
requires_backends(self, ['''on... | 99 | 0 |
import requests
def a__ ( UpperCAmelCase : Optional[Any] , UpperCAmelCase : Union[str, Any] ) -> Dict:
UpperCAmelCase : Tuple = {'Content-Type': 'application/json'}
UpperCAmelCase : List[str] = requests.post(_A , json={'''text''': me... | 353 |
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 is_sentencepiece_a... | 99 | 0 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowerCamelCase : List[Any] = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3... | 354 |
from math import log
from scipy.constants import Boltzmann, physical_constants
_lowerCamelCase : Tuple = 3_0_0 # TEMPERATURE (unit = K)
def a__ ( UpperCAmelCase : float , UpperCAmelCase : float , UpperCAmelCase : float , ) -> f... | 99 | 0 |
from importlib import import_module
from .logging import get_logger
_lowerCamelCase : str = get_logger(__name__)
class __UpperCAmelCase :
def __init__( self : str, __A : str, __A : Any=None ):
UpperCAmelCase : str = ... | 355 |
from __future__ import annotations
import queue
class __UpperCAmelCase :
def __init__( self : str, __A : Union[str, Any] ):
UpperCAmelCase : Dict = data
UpperCAmelCase : Tuple = None
UpperCAmelCase : Any = None
... | 99 | 0 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
_lowerCamelCase : int = 5_0_0_0_0
_lowerCamelCase : Union[str, Any] = 5_0_0_0
_lowerCamelCase , _lowerCamelCase : Optional[int] = ... | 356 |
import inspect
import unittest
from transformers import BitConfig
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_backbone_common import BackboneTesterMixin
from ...test_conf... | 99 | 0 |
"""simple docstring"""
def a__ ( UpperCAmelCase : Optional[int] , UpperCAmelCase : List[Any] , UpperCAmelCase : Any , UpperCAmelCase : Optional[int] , UpperCAmelCase : Optional[Any] , UpperCAmelCase : str ) ... | 357 |
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
if is_torch_available():
import torch
if is_vision_availa... | 99 | 0 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class __UpperCAmelCase ( nn.Module ):
UpperCamelCase = 42
UpperCamelCase = jnp.floataa
def __magic_name__ ( self : Dict ):
UpperCAmelCase : Tuple = nn.Conv(
... | 358 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.modeling... | 99 | 0 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaTokenizer
else:
_l... | 359 |
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 tr... | 99 | 0 |
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface_hub.utils as hf_hub_... | 360 |
def a__ ( UpperCAmelCase : int ) -> bool:
if not isinstance(UpperCAmelCase , UpperCAmelCase ):
UpperCAmelCase : List[str] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(UpperCAmelCase )
if number < 0:
return Fal... | 99 | 0 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_accelera... | 361 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
_lowerCamelCase : int = datasets.logging.get_logger(__name__)
_lowerCamelCase : Any = "\\n@InProceedings... | 99 | 0 |
def a__ ( UpperCAmelCase : Union[str, Any] ) -> bool:
if number < 0:
raise ValueError('''number must not be negative''' )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 362 |
def a__ ( UpperCAmelCase : int , UpperCAmelCase : int ) -> str:
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
UpperCAmelCase : List[Any] = str(bin(UpperCAmelCase ) )[2:] # remove the leading "... | 99 | 0 |
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def a__ ( ) -> List[Any]:
raise RuntimeError('''CUDA out of memory.''' )
class __UpperCAmelCase ( nn.Modu... | 363 |
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils.te... | 99 | 0 |
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
... | 364 |
import unittest
from transformers import DebertaVaConfig, 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
from... | 99 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
_lowerCamelCase : Tuple = {
"configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJapaneseConfig"],
... | 365 |
import logging
import os
from .state import PartialState
class __UpperCAmelCase ( logging.LoggerAdapter ):
@staticmethod
def __magic_name__ ( __A : str ):
UpperCAmelCase : Dict = PartialState()
return not main_process_only or (main_process_only a... | 99 | 0 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
_lowerCamelCase : Union[str, Any] = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow("", "... | 366 |
import torch
from torch import nn
class __UpperCAmelCase ( nn.Module ):
def __init__( self : List[Any], __A : List[Any], __A : Optional[Any], __A : int, __A : List[Any], __A : int=1, __A : List[str]=False ):
... | 99 | 0 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def a__ ( UpperCAmelCase : str , UpperCAmelCase : complex , UpperCAmelCase : str = "x" , UpperCAmelCase : float = 10**-10 , UpperCAmelCase : ... | 367 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging import get_logger... | 99 | 0 |
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from .... | 368 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import ... | 99 | 0 |
def a__ ( UpperCAmelCase : int , UpperCAmelCase : int ) -> int:
return abs(_snake_case ) if a == 0 else greatest_common_divisor(b % a , _snake_case )
def a__ ( UpperCAmelCase : int , UpperCAmelCase : int ) -... | 369 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : str = {"configuration_xlnet": ["XLNET_PRETRAINED_CONFIG_AR... | 99 | 0 |
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny vocab first, and then a tiny model - so the outcome is truly tiny -
# all files ~60KB. As compared to ta... | 370 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def a__ ( UpperCAmelCase : int ) -> Dict:
# A local function to see if a dot lands in the circle.
def is_in_circle(UpperCAmelCase : float , Upper... | 99 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCamelCase : Optional[Any] = {
"configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
"tokenization_biogpt": [... | 371 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 99 | 0 |
import unittest
from transformers import DebertaVaConfig, 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
from... | 350 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common imp... | 99 | 0 |
def a__ ( UpperCAmelCase : str ) -> list[int]:
UpperCAmelCase : Union[str, Any] = [0 for i in range(len(_UpperCAmelCase ) )]
# initialize interval's left pointer and right pointer
UpperCAmelCase : Optional[int] = 0, 0
for i in range(1 ,... | 351 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Train... | 99 | 0 |
from math import pow
def a__ ( UpperCAmelCase : Optional[int] , UpperCAmelCase : Any , UpperCAmelCase : Any , UpperCAmelCase : List[str] , UpperCAmelCase : Tuple , ) -> tuple[int, int]:
if current_sum == needed_sum:
... | 352 |
from ..utils import DummyObject, requires_backends
class __UpperCAmelCase ( metaclass=lowerCamelCase__ ):
UpperCamelCase = ["""onnx"""]
def __init__( self : int, *__A : Optional[Any], **__A : Dict ):
requires_backends(self, ['''on... | 99 | 0 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test... | 353 |
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 is_sentencepiece_a... | 99 | 0 |
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 a__ ( UpperCAmelCase ... | 354 |
from math import log
from scipy.constants import Boltzmann, physical_constants
_lowerCamelCase : Tuple = 3_0_0 # TEMPERATURE (unit = K)
def a__ ( UpperCAmelCase : float , UpperCAmelCase : float , UpperCAmelCase : float , ) -> f... | 99 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class __UpperCAmelCase ( lowerCAmelCase__ ):
def __init__( self : Optional[int], __A : List[str], __A : str ):
UpperCAmelCase : Dict = params... | 355 |
from __future__ import annotations
import queue
class __UpperCAmelCase :
def __init__( self : str, __A : Union[str, Any] ):
UpperCAmelCase : Dict = data
UpperCAmelCase : Tuple = None
UpperCAmelCase : Any = None
... | 99 | 0 |
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
PixaStructTextConfig,
Pi... | 356 |
import inspect
import unittest
from transformers import BitConfig
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_backbone_common import BackboneTesterMixin
from ...test_conf... | 99 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import log... | 357 |
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
if is_torch_available():
import torch
if is_vision_availa... | 99 | 0 |
def a__ ( UpperCAmelCase : Union[str, Any] ) -> List[str]:
stooge(A__ , 0 , len(A__ ) - 1 )
return arr
def a__ ( UpperCAmelCase : Optional[int] , UpperCAmelCase : Union[str, Any] , UpperCAmelCase : Optional... | 358 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.modeling... | 99 | 0 |
import argparse
from .config import config_command_parser
from .config_args import default_config_file, load_config_from_file # noqa: F401
from .default import default_command_parser
from .update import update_command_parser
def a__ ( UpperCAmelCase : List[Any]=None ) -> Optional[i... | 359 |
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 tr... | 99 | 0 |
def a__ ( UpperCAmelCase : int ) -> List[Any]:
UpperCAmelCase : Union[str, Any] = 0
UpperCAmelCase : Dict = len(a__ )
for i in range(n - 1 ):
for j in range(i + 1 , a__ ):
if arr[i] > arr[j]:
num_inversions += 1
... | 360 |
def a__ ( UpperCAmelCase : int ) -> bool:
if not isinstance(UpperCAmelCase , UpperCAmelCase ):
UpperCAmelCase : List[str] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(UpperCAmelCase )
if number < 0:
return Fal... | 99 | 0 |
import math
def a__ ( UpperCAmelCase : int ) -> str:
UpperCAmelCase : Any = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(UpperCAmelCase )
def a__ ( UpperCAmelCase : float = 1 / 12_345 ... | 361 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
_lowerCamelCase : int = datasets.logging.get_logger(__name__)
_lowerCamelCase : Any = "\\n@InProceedings... | 99 | 0 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def a__ ( UpperCAmelCase : int ) -> str:
def wrapper(*UpperCAmelCase : List[str] , **UpperCAmelCase : Optional... | 362 |
def a__ ( UpperCAmelCase : int , UpperCAmelCase : int ) -> str:
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
UpperCAmelCase : List[Any] = str(bin(UpperCAmelCase ) )[2:] # remove the leading "... | 99 | 0 |
from __future__ import annotations
def a__ ( UpperCAmelCase : Optional[Any] = 4 ) -> int:
UpperCAmelCase : Optional[int] = abs(lowercase__ ) or 4
return [[1 + x + y * row_size for x in range(lowercase__ )] for y in range(lowercase__ )]
def a__ ... | 363 |
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils.te... | 99 | 0 |
from collections.abc import Sequence
def a__ ( UpperCAmelCase : int , UpperCAmelCase : Union[str, Any] = False ) -> float:
if not arr:
return 0
UpperCAmelCase : Any = 0 if allow_empty_subarrays else float('''-inf''' )
UpperCAmelCase : ... | 364 |
import unittest
from transformers import DebertaVaConfig, 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
from... | 99 | 0 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaagf, RegNetYa... | 365 |
import logging
import os
from .state import PartialState
class __UpperCAmelCase ( logging.LoggerAdapter ):
@staticmethod
def __magic_name__ ( __A : str ):
UpperCAmelCase : Dict = PartialState()
return not main_process_only or (main_process_only a... | 99 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 366 |
import torch
from torch import nn
class __UpperCAmelCase ( nn.Module ):
def __init__( self : List[Any], __A : List[Any], __A : Optional[Any], __A : int, __A : List[Any], __A : int=1, __A : List[str]=False ):
... | 99 | 0 |
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
_lowerCamelCase : str = logging.get_logger(__nam... | 367 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging import get_logger... | 99 | 0 |
from __future__ import annotations
def a__ ( UpperCAmelCase : list[int] , UpperCAmelCase : list[int] , UpperCAmelCase : int ) -> tuple[float, list[float]]:
UpperCAmelCase : int = list(range(len(UpperCAmelCase ) ) )
Upper... | 368 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import ... | 99 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
_lowerCamelCase : int = {
"configuration_speecht5": [
"SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SPEECHT5_... | 369 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : str = {"configuration_xlnet": ["XLNET_PRETRAINED_CONFIG_AR... | 99 | 0 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied from diffusers.... | 370 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def a__ ( UpperCAmelCase : int ) -> Dict:
# A local function to see if a dot lands in the circle.
def is_in_circle(UpperCAmelCase : float , Upper... | 99 | 0 |
def a__ ( UpperCAmelCase : Union[str, Any] , UpperCAmelCase : Union[str, Any] ) -> Dict:
# Check if the input is valid
if not len(UpperCAmelCase ) == len(UpperCAmelCase ) == 3:
raise ValueError('''Please enter a valid equation.''' )
if equatio... | 371 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 99 | 0 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __UpperCAmelCase ( a_ , unittest.TestCase ):
UpperCamelCase = CTRLTokenizer
Upper... | 350 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common imp... | 99 | 0 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor import ... | 351 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Train... | 99 | 0 |
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def a__ ( UpperCAmelCase : Dict , UpperCAmelCase : Any=1 ) -> Tuple:
if n_shave_prefix_segments >= 0:
return ".".join(path.split('''.''' )[n_sh... | 352 |
from ..utils import DummyObject, requires_backends
class __UpperCAmelCase ( metaclass=lowerCamelCase__ ):
UpperCamelCase = ["""onnx"""]
def __init__( self : int, *__A : Optional[Any], **__A : Dict ):
requires_backends(self, ['''on... | 99 | 0 |
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 TemplateProcessing
... | 353 |
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 is_sentencepiece_a... | 99 | 0 |
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
_lowerCamelCase : Dict = '''scheduler_config.json'''
class __UpperCAmel... | 354 |
from math import log
from scipy.constants import Boltzmann, physical_constants
_lowerCamelCase : Tuple = 3_0_0 # TEMPERATURE (unit = K)
def a__ ( UpperCAmelCase : float , UpperCAmelCase : float , UpperCAmelCase : float , ) -> f... | 99 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : Union[str, Any] = logging.get_logger(__name__)
_lowerCamelCase : Optional[int] = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/vivit-b-1... | 355 |
from __future__ import annotations
import queue
class __UpperCAmelCase :
def __init__( self : str, __A : Union[str, Any] ):
UpperCAmelCase : Dict = data
UpperCAmelCase : Tuple = None
UpperCAmelCase : Any = None
... | 99 | 0 |
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 356 |
import inspect
import unittest
from transformers import BitConfig
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_backbone_common import BackboneTesterMixin
from ...test_conf... | 99 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMA... | 357 |
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
if is_torch_available():
import torch
if is_vision_availa... | 99 | 0 |
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
_lowerCamelCase : Optional[Any] = ... | 358 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.modeling... | 99 | 0 |
from __future__ import annotations
import requests
_lowerCamelCase : Optional[int] = set(
"approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_... | 359 |
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 tr... | 99 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCamelCase : Tuple = {
"configuration_canine": ["CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CanineConfig"],
"tokenization_canine": ["CanineT... | 360 |
def a__ ( UpperCAmelCase : int ) -> bool:
if not isinstance(UpperCAmelCase , UpperCAmelCase ):
UpperCAmelCase : List[str] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(UpperCAmelCase )
if number < 0:
return Fal... | 99 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.functional import Interp... | 361 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
_lowerCamelCase : int = datasets.logging.get_logger(__name__)
_lowerCamelCase : Any = "\\n@InProceedings... | 99 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCAmelCase ( lowerCamelCase__ ):
UpperCamelCase = ["""image_processor""", """tokenizer"""]
UpperCamelCase = """CLIPImageProcessor"""
Up... | 362 |
def a__ ( UpperCAmelCase : int , UpperCAmelCase : int ) -> str:
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
UpperCAmelCase : List[Any] = str(bin(UpperCAmelCase ) )[2:] # remove the leading "... | 99 | 0 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...image_p... | 363 |
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils.te... | 99 | 0 |
import mpmath # for roots of unity
import numpy as np
class __UpperCAmelCase :
def __init__( self : Dict, __A : Optional[int]=None, __A : Any=None ):
# Input as list
UpperCAmelCase : Union[str, Any] = list(poly_a or [0] )[:]
... | 364 |
import unittest
from transformers import DebertaVaConfig, 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
from... | 99 | 0 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerFast
fro... | 365 |
import logging
import os
from .state import PartialState
class __UpperCAmelCase ( logging.LoggerAdapter ):
@staticmethod
def __magic_name__ ( __A : str ):
UpperCAmelCase : Dict = PartialState()
return not main_process_only or (main_process_only a... | 99 | 0 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : Tuple = logging.get_logger(__name__)
_lowerCamelCase : Optional[Any] = {
'facebook/encodec_24khz': 'https:/... | 366 |
import torch
from torch import nn
class __UpperCAmelCase ( nn.Module ):
def __init__( self : List[Any], __A : List[Any], __A : Optional[Any], __A : int, __A : List[Any], __A : int=1, __A : List[str]=False ):
... | 99 | 0 |
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTeacher,
Effi... | 367 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging import get_logger... | 99 | 0 |
from collections import deque
from .hash_table import HashTable
class __UpperCAmelCase ( _a ):
def __init__( self : List[str], *__A : Dict, **__A : Tuple ):
super().__init__(*__A, **__A )
def __magic_name__ ( self : L... | 368 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import ... | 99 | 0 |
import operator as op
_lowerCamelCase : int = "scaler.pt"
_lowerCamelCase : Any = "pytorch_model"
_lowerCamelCase : int = "random_states"
_lowerCamelCase : str = "optimizer"
_lowerCamelCase : Dict = "schedu... | 369 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : str = {"configuration_xlnet": ["XLNET_PRETRAINED_CONFIG_AR... | 99 | 0 |
import math
def a__ ( UpperCAmelCase : int ) -> Dict:
UpperCAmelCase : Optional[int] = []
UpperCAmelCase : int = 2
UpperCAmelCase : List[Any] = int(math.sqrt(snake_case_ ) ) # Size of every segment
UpperCAmelCase : List[... | 370 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def a__ ( UpperCAmelCase : int ) -> Dict:
# A local function to see if a dot lands in the circle.
def is_in_circle(UpperCAmelCase : float , Upper... | 99 | 0 |
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 FlaxModelTeste... | 371 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 99 | 0 |
def a__ ( UpperCAmelCase : Any = 600_851_475_143 ):
try:
UpperCAmelCase : Optional[Any] = int(__a )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <= 0:
raise ValueError('''Parameter n must b... | 350 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common imp... | 99 | 0 |
def a__ ( UpperCAmelCase : int ) -> Optional[int]:
if n == 1 or not isinstance(A__ , A__ ):
return 0
elif n == 2:
return 1
else:
UpperCAmelCase : Any = [0, 1]
for i in range(2 , n + 1 ):
sequence.append(sequence[i - 1] ... | 351 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Train... | 99 | 0 |
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface_hub.utils as hf_hub_... | 352 |
from ..utils import DummyObject, requires_backends
class __UpperCAmelCase ( metaclass=lowerCamelCase__ ):
UpperCamelCase = ["""onnx"""]
def __init__( self : int, *__A : Optional[Any], **__A : Dict ):
requires_backends(self, ['''on... | 99 | 0 |
import sys
from collections import defaultdict
class __UpperCAmelCase :
def __init__( self : List[Any] ):
UpperCAmelCase : Dict = []
def __magic_name__ ( self : Optional[Any], __A : List[Any] ):
return self.node_posit... | 353 |
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 is_sentencepiece_a... | 99 | 0 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --host <host> --ke... | 354 |
from math import log
from scipy.constants import Boltzmann, physical_constants
_lowerCamelCase : Tuple = 3_0_0 # TEMPERATURE (unit = K)
def a__ ( UpperCAmelCase : float , UpperCAmelCase : float , UpperCAmelCase : float , ) -> f... | 99 | 0 |
from __future__ import annotations
def a__ ( UpperCAmelCase : int , UpperCAmelCase : Any , UpperCAmelCase : Any , UpperCAmelCase : int , UpperCAmelCase : str , ) -> int:
UpperCAmelCase : Optional[Any] = le... | 355 |
from __future__ import annotations
import queue
class __UpperCAmelCase :
def __init__( self : str, __A : Union[str, Any] ):
UpperCAmelCase : Dict = data
UpperCAmelCase : Tuple = None
UpperCAmelCase : Any = None
... | 99 | 0 |
from __future__ import annotations
_lowerCamelCase : Optional[int] = [-1_0, -5, 0, 5, 5.1, 1_1, 1_3, 2_1, 3, 4, -2_1, -1_0, -5, -1, 0]
_lowerCamelCase : Tuple = [-5, 0, 5, 5.1, 1_1, 1_3, 2_1, -1, 4, -1, -1_0, -5, -1, 0, -1]
def a__ ( UpperCAmelCase : ... | 356 |
import inspect
import unittest
from transformers import BitConfig
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_backbone_common import BackboneTesterMixin
from ...test_conf... | 99 | 0 |
"""simple docstring"""
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : Tuple = logging.get_logger(__name__)
# TODO Update this
_lowerCamelCase : List[str] ... | 357 |
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
if is_torch_available():
import torch
if is_vision_availa... | 99 | 0 |
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def a__ ( UpperCAmelCase : Any ... | 358 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.modeling... | 99 | 0 |
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def a__ ( UpperCAmelCase ... | 359 |
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 tr... | 99 | 0 |
import numpy as np
def a__ ( UpperCAmelCase : int , UpperCAmelCase : List[str] , UpperCAmelCase : str = 1E-12 , UpperCAmelCase : Tuple = 100 , ) -> tuple[float, np.ndarray]:
assert np.shape(UpperCAmelCase )[0] == np.shape(UpperCA... | 360 |
def a__ ( UpperCAmelCase : int ) -> bool:
if not isinstance(UpperCAmelCase , UpperCAmelCase ):
UpperCAmelCase : List[str] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(UpperCAmelCase )
if number < 0:
return Fal... | 99 | 0 |
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class __UpperCAmelCase :
def __init__( self : Union[str, Any], __A : List[... | 361 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
_lowerCamelCase : int = datasets.logging.get_logger(__name__)
_lowerCamelCase : Any = "\\n@InProceedings... | 99 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def a__ ( UpperCAmelCase : Any , UpperCAmelCase : List[Any]=1_000 ) -> Union[str, Any]:
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
UpperCAmelCase : int =... | 362 |
def a__ ( UpperCAmelCase : int , UpperCAmelCase : int ) -> str:
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
UpperCAmelCase : List[Any] = str(bin(UpperCAmelCase ) )[2:] # remove the leading "... | 99 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():
from tra... | 363 |
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils.te... | 99 | 0 |
class __UpperCAmelCase :
def __init__( self : Dict, __A : Union[str, Any] ):
UpperCAmelCase : Any = size
UpperCAmelCase : str = [0] * size
UpperCAmelCase : Any = [0] * size
@staticmethod
def __magic_name__ ( ... | 364 |
import unittest
from transformers import DebertaVaConfig, 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
from... | 99 | 0 |
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __UpperCAmelCase ( unittest.TestCase ):
@prope... | 365 |
import logging
import os
from .state import PartialState
class __UpperCAmelCase ( logging.LoggerAdapter ):
@staticmethod
def __magic_name__ ( __A : str ):
UpperCAmelCase : Dict = PartialState()
return not main_process_only or (main_process_only a... | 99 | 0 |
from collections.abc import Sequence
def a__ ( UpperCAmelCase : Any = None ) -> Union[str, Any]:
if nums is None or not nums:
raise ValueError('''Input sequence should not be empty''' )
UpperCAmelCase : Optional[int] = nums[0]
for i in range(1 ,... | 366 |
import torch
from torch import nn
class __UpperCAmelCase ( nn.Module ):
def __init__( self : List[Any], __A : List[Any], __A : Optional[Any], __A : int, __A : List[Any], __A : int=1, __A : List[str]=False ):
... | 99 | 0 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class __UpperCAmelCase :
UpperCamelCase = 42 # [batch_size x 3]
UpperCamelCase = 42 # [batch_size x 3]
UpperCamelCase = 42 # [batch_... | 367 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging import get_logger... | 99 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...utils ... | 368 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import ... | 99 | 0 |
import comet # From: unbabel-comet
import torch
import datasets
_lowerCamelCase : int = datasets.logging.get_logger(__name__)
_lowerCamelCase : List[Any] = "\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C an... | 369 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : str = {"configuration_xlnet": ["XLNET_PRETRAINED_CONFIG_AR... | 99 | 0 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import ca... | 370 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def a__ ( UpperCAmelCase : int ) -> Dict:
# A local function to see if a dot lands in the circle.
def is_in_circle(UpperCAmelCase : float , Upper... | 99 | 0 |
from __future__ import annotations
import bisect
def a__ ( UpperCAmelCase : int , UpperCAmelCase : int , UpperCAmelCase : Union[str, Any] = 0 , UpperCAmelCase : Optional[int] = -1 ) -> int:
if hi < 0:
UpperCAmelCase : Opti... | 371 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 99 | 0 |
_lowerCamelCase : dict[tuple[int, int, int], int] = {}
def a__ ( UpperCAmelCase : int , UpperCAmelCase : int , UpperCAmelCase : int ):
# if we are absent twice, or late 3 consecutive days,
# no further prize strings are possible
... | 350 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common imp... | 99 | 0 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
@require... | 351 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Train... | 99 | 0 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def a__ ( UpperCAmelCase : dict ) -> tuple:
return (dat... | 352 |
from ..utils import DummyObject, requires_backends
class __UpperCAmelCase ( metaclass=lowerCamelCase__ ):
UpperCamelCase = ["""onnx"""]
def __init__( self : int, *__A : Optional[Any], **__A : Dict ):
requires_backends(self, ['''on... | 99 | 0 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
_lowerCamelCase : Union[str, Any] = logging.getLogger()
@unittest.skip("""Temporarily... | 353 |
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 is_sentencepiece_a... | 99 | 0 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
_lowerCamelCase : Union[str, Any] = version.parse(importlib_metadata.version("nltk"))
if NLTK_VERSION >= version.Version("3.6.4"):
from nltk import word_toke... | 354 |
from math import log
from scipy.constants import Boltzmann, physical_constants
_lowerCamelCase : Tuple = 3_0_0 # TEMPERATURE (unit = K)
def a__ ( UpperCAmelCase : float , UpperCAmelCase : float , UpperCAmelCase : float , ) -> f... | 99 | 0 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __UpperCAmelCase ( lowerCamelCase__ ):
UpperCamelCase = (EulerDiscreteScheduler,)
UpperCamelCase = 1_0
de... | 355 |
from __future__ import annotations
import queue
class __UpperCAmelCase :
def __init__( self : str, __A : Union[str, Any] ):
UpperCAmelCase : Dict = data
UpperCAmelCase : Tuple = None
UpperCAmelCase : Any = None
... | 99 | 0 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Config... | 356 |
import inspect
import unittest
from transformers import BitConfig
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_backbone_common import BackboneTesterMixin
from ...test_conf... | 99 | 0 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class __UpperCAmelCase ( datasets.BeamBasedBuilder ):
def __magic_name__ ( ... | 357 |
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
if is_torch_available():
import torch
if is_vision_availa... | 99 | 0 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
from... | 358 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.modeling... | 99 | 0 |
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 359 |
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 tr... | 99 | 0 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from tra... | 360 |
def a__ ( UpperCAmelCase : int ) -> bool:
if not isinstance(UpperCAmelCase , UpperCAmelCase ):
UpperCAmelCase : List[str] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(UpperCAmelCase )
if number < 0:
return Fal... | 99 | 0 |
import qiskit
def a__ ( UpperCAmelCase : int , UpperCAmelCase : int ) -> qiskit.result.counts.Counts:
UpperCAmelCase : Optional[Any] = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
UpperCAme... | 361 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
_lowerCamelCase : int = datasets.logging.get_logger(__name__)
_lowerCamelCase : Any = "\\n@InProceedings... | 99 | 0 |
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