code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from __future__ import annotations
import math
def a__ ( lowerCAmelCase : List[Any] , lowerCAmelCase : Union[str, Any] , lowerCAmelCase : Tuple , lowerCAmelCase : str , lowerCAmelCase : Optional[Any] ):
... | 704 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availab... | 660 | 0 |
"""simple docstring"""
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
A__ : List[Any] = {
"facebook/maskformer-swin-b... | 705 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .schedulin... | 660 | 0 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenizer, FlaxM... | 706 |
"""simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class _lowercase ... | 660 | 0 |
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
A__ : List[str] = {
"gwf-440k": {
... | 707 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 660 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class _lowercase ( A_ ):
'''simple docstring'''
def __init__( self , __UpperCamelCase , __UpperCamelCase , __Upper... | 708 |
"""simple docstring"""
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(lowerCAmelCase , lowerCAmelCase ):
raise TypeError("Input value must be a 'int' ... | 660 | 0 |
"""simple docstring"""
from collections.abc import Callable
def a__ ( lowerCAmelCase : Callable[[float], float] , lowerCAmelCase : float , lowerCAmelCase : float ):
'''simple docstring'''
UpperCAmelCase__ : float = a
UpperCAme... | 709 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_availab... | 660 | 0 |
"""simple docstring"""
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_m... | 710 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import _LazyModule
A__ : List[str] = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
A__ : Any = _LazyMod... | 660 | 0 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def a__ ( lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCas... | 711 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class _lowercase ( lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstrin... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_comm... | 712 |
"""simple docstring"""
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 a__ ( lowerCAmelCase : List[Any] , lowerCAmelCase : An... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase : list , lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : int ):
'''simple docstring'''
UpperCAmelCase__ : Any = []
... | 713 |
"""simple docstring"""
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
A__ : Optional[int] = ["""small""", """medium""", """large"""]
A__ : Optional[int] = """lm_head.decoder.weight"""
A__ : Dict = """lm_head.weight"""
de... | 660 | 0 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class... | 714 |
"""simple docstring"""
from math import isqrt
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j... | 660 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simpl... | 715 |
"""simple docstring"""
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerB... | 660 | 0 |
"""simple docstring"""
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
A__ : Optional[int] = re.compile(R"""^(?P<major>\d+)""" R"""\.(?P<minor>\d+)""" R"""\.(?P<patch>\d+)$""")
@total_ordering
@dataclass
cla... | 716 |
"""simple docstring"""
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def a__ ( lowerCAmelCase : List[str] ):
'''simple docstring'''
def wrapper(*lowerCAmelCase : Any , ... | 660 | 0 |
"""simple docstring"""
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... | 717 |
"""simple docstring"""
from manim import *
class _lowercase ( lowerCAmelCase_ ):
'''simple docstring'''
def lowerCAmelCase__ ( self )-> Tuple:
UpperCAmelCase__ : str = Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase... | 660 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.traini... | 718 |
"""simple docstring"""
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
A__ : Tuple = logging.get_logger(__name__... | 660 | 0 |
"""simple docstring"""
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 a__ ( lo... | 719 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_co... | 660 | 0 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
A__ : Optional[Any] = TypeVar("""T""")
A__ : List[str] = Union[List[T], Tuple[T, ...]]
A__ : int = Union[T, List[T], Dict[str, T]]
A__ : List[str] = Union[str... | 720 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A__ : Union[str, Any] = logging.... | 660 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from ... | 721 |
"""simple docstring"""
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTok... | 660 | 0 |
"""simple docstring"""
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, prepa... | 700 |
"""simple docstring"""
from timeit import timeit
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
if number < 0:
raise ValueError("the value of input must not be negative" )
UpperCAmelCase__ : Tuple = 0
while number:
numbe... | 660 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase : List[str] ):
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6, 8],
... | 701 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _lowercase ( unittest.TestCase , lowerCAmelCase_ ):
'''simple docstring'''
def lowerCAmelCase__ ( self )-> Dict:
Uppe... | 660 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
A__ : Any = {
"""sample_size""": 32,
"""in_channels""": 3,
"""out_channels""": 3,
"""layers_per_block""": 2... | 702 |
"""simple docstring"""
def a__ ( lowerCAmelCase : list , lowerCAmelCase : list ):
'''simple docstring'''
_validate_point(lowerCAmelCase )
_validate_point(lowerCAmelCase )
if len(lowerCAmelCase ) != len(lowerCAmelCase ):
raise ValueError("Both ... | 660 | 0 |
import random
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
UpperCAmelCase__ : Union[str, Any] = num - 1
UpperCAmelCase__ : Dict = 0
while s % 2 == 0:
UpperCAmelCase__ : Tuple = s // 2
t ... | 703 |
"""simple docstring"""
import math
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
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 mul... | 660 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_... | 704 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availab... | 660 | 0 |
"""simple docstring"""
from sklearn.metrics import recall_score
import datasets
A__ : Optional[int] = """
Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:
Recall = TP / (TP + FN)
Where TP is the true posi... | 705 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .schedulin... | 660 | 0 |
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def a__ ( lowerCAmelCase : int = 100 ):
'''simpl... | 706 |
"""simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class _lowercase ... | 660 | 0 |
A__ : Optional[int] = 8.314_4598
def a__ ( lowerCAmelCase : float , lowerCAmelCase : float ):
'''simple docstring'''
if temperature < 0:
raise Exception("Temperature cannot be less than 0 K" )
if molar_mass <= 0:
raise Except... | 707 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 660 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : Optional[Any] = logging.get_logger(__name__)
A__ : Dict = {
"""Salesforce/blip-vqa-base""": """https://huggingface.c... | 708 |
"""simple docstring"""
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(lowerCAmelCase , lowerCAmelCase ):
raise TypeError("Input value must be a 'int' ... | 660 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
CommonSchedulerState,
FlaxKarrasDiffusionSchedulers,
... | 709 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_availab... | 660 | 0 |
"""simple docstring"""
import inspect
import unittest
from math import floor
from transformers import CvtConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ... | 710 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import _LazyModule
A__ : List[str] = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
A__ : Any = _LazyMod... | 660 | 0 |
"""simple docstring"""
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models... | 711 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class _lowercase ( lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstrin... | 660 | 0 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistep... | 712 |
"""simple docstring"""
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 a__ ( lowerCAmelCase : List[Any] , lowerCAmelCase : An... | 660 | 0 |
"""simple docstring"""
import warnings
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__ : str = logging.get_logger(__name__)
A__ ... | 713 |
"""simple docstring"""
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
A__ : Optional[int] = ["""small""", """medium""", """large"""]
A__ : Optional[int] = """lm_head.decoder.weight"""
A__ : Dict = """lm_head.weight"""
de... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase : str , lowerCAmelCase : str ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = get_failure_array(lowerCAmelCase )
# 2) Step through text searching for pa... | 714 |
"""simple docstring"""
from math import isqrt
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
A__ : List[str] = TypeVar("""T""")
class _lowercase ( Generic[T] ):
'''simple docstring'''
def __init__( self , _... | 715 |
"""simple docstring"""
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerB... | 660 | 0 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common ... | 716 |
"""simple docstring"""
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def a__ ( lowerCAmelCase : List[str] ):
'''simple docstring'''
def wrapper(*lowerCAmelCase : Any , ... | 660 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : str = logging.get_logger(__name__)
class _lowercase ( lowerCAmelCase_ ):
'''simple docstring'''
_A = 'timm_backbone'
def __in... | 717 |
"""simple docstring"""
from manim import *
class _lowercase ( lowerCAmelCase_ ):
'''simple docstring'''
def lowerCAmelCase__ ( self )-> Tuple:
UpperCAmelCase__ : str = Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase... | 660 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase : dict ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = set()
# edges = list of graph's edges
UpperCAmelCase__ : Tuple = get_edges(lowerCAmelCase )
# While there are still eleme... | 718 |
"""simple docstring"""
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
A__ : Tuple = logging.get_logger(__name__... | 660 | 0 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_image... | 719 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_co... | 660 | 0 |
"""simple docstring"""
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def a__ ( lowerCAmelCase : List[str] ):
'''simple docstring'''
def wrapper(*lowerCAmelCase : Any , ... | 720 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A__ : Union[str, Any] = logging.... | 660 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase : List[str]):
'''simple docstring'''
UpperCAmelCase__ : Dict = [0] * len(lowerCAmelCase)
UpperCAmelCase__ : Any = []
UpperCAmelCase__ : str = [1] * len(lowerCAmelCase)
... | 721 |
"""simple docstring"""
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTok... | 660 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_... | 700 |
"""simple docstring"""
from timeit import timeit
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
if number < 0:
raise ValueError("the value of input must not be negative" )
UpperCAmelCase__ : Tuple = 0
while number:
numbe... | 660 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
A__ : Dict = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""tokenizat... | 701 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _lowercase ( unittest.TestCase , lowerCAmelCase_ ):
'''simple docstring'''
def lowerCAmelCase__ ( self )-> Dict:
Uppe... | 660 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
A__ : Dict = {
"""albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/config.json""",
"""albert-l... | 702 |
"""simple docstring"""
def a__ ( lowerCAmelCase : list , lowerCAmelCase : list ):
'''simple docstring'''
_validate_point(lowerCAmelCase )
_validate_point(lowerCAmelCase )
if len(lowerCAmelCase ) != len(lowerCAmelCase ):
raise ValueError("Both ... | 660 | 0 |
A__ : Union[str, Any] = {"""a""": ["""c""", """b"""], """b""": ["""d""", """e"""], """c""": [], """d""": [], """e""": []}
A__ : Union[str, Any] = ["""a""", """b""", """c""", """d""", """e"""]
def a__ ( lowerCAmelCase : Any , lowerCAmelCase : List[str]... | 703 |
"""simple docstring"""
import math
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
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 mul... | 660 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if v... | 704 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availab... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
A__ : Optional[int] = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
A__ : Dict = typing.Union[np.floataa, int, float] # noq... | 705 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .schedulin... | 660 | 0 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ... | 706 |
"""simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class _lowercase ... | 660 | 0 |
def a__ ( lowerCAmelCase : int = 10**9 ):
'''simple docstring'''
UpperCAmelCase__ : Any = 1
UpperCAmelCase__ : Tuple = 2
UpperCAmelCase__ : List[Any] = 0
UpperCAmelCase__ : List[Any] = 0
UpperC... | 707 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 660 | 0 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_availab... | 708 |
"""simple docstring"""
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(lowerCAmelCase , lowerCAmelCase ):
raise TypeError("Input value must be a 'int' ... | 660 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase : int = 100_0000 ):
'''simple docstring'''
UpperCAmelCase__ : List[str] = set(range(3 , lowerCAmelCase , 2 ) )
primes.add(2 )
for p in range(3 , lowerCAmelCase , 2 ):... | 709 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_availab... | 660 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transfor... | 710 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import _LazyModule
A__ : List[str] = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
A__ : Any = _LazyMod... | 660 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_uti... | 711 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class _lowercase ( lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstrin... | 660 | 0 |
"""simple docstring"""
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 a__ ( lowerCAmelCase : List[Any] , lowerCAmelCase : An... | 712 |
"""simple docstring"""
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 a__ ( lowerCAmelCase : List[Any] , lowerCAmelCase : An... | 660 | 0 |
"""simple docstring"""
A__ : str = """
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/hug... | 713 |
"""simple docstring"""
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
A__ : Optional[int] = ["""small""", """medium""", """large"""]
A__ : Optional[int] = """lm_head.decoder.weight"""
A__ : Dict = """lm_head.weight"""
de... | 660 | 0 |
"""simple docstring"""
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
A__ : Opt... | 714 |
"""simple docstring"""
from math import isqrt
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j... | 660 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A__ : Optional[Any] = {"""configuration_xlnet""": ["""X... | 715 |
"""simple docstring"""
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerB... | 660 | 0 |
"""simple docstring"""
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Co... | 716 |
"""simple docstring"""
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def a__ ( lowerCAmelCase : List[str] ):
'''simple docstring'''
def wrapper(*lowerCAmelCase : Any , ... | 660 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
A__ : List[Any] = logging.get_log... | 717 |
"""simple docstring"""
from manim import *
class _lowercase ( lowerCAmelCase_ ):
'''simple docstring'''
def lowerCAmelCase__ ( self )-> Tuple:
UpperCAmelCase__ : str = Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase... | 660 | 0 |
"""simple docstring"""
import argparse
import os
import re
A__ : int = """src/diffusers"""
# Pattern that looks at the indentation in a line.
A__ : Optional[int] = re.compile(R"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
A__ : Tuple =... | 718 |
"""simple docstring"""
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
A__ : Tuple = logging.get_logger(__name__... | 660 | 0 |
"""simple docstring"""
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_loggin... | 719 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_co... | 660 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A__ : Union[str, Any] = logging.... | 720 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A__ : Union[str, Any] = logging.... | 660 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
A__ : Union[str, Any] = logging.get_logger(__name__)
class _lowercase ( lowerCAmelCase_ ):
'''simple docstring'''
def __i... | 721 |
"""simple docstring"""
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTok... | 660 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
if num < 0:
return False
UpperCAmelCase__ : int = num
UpperCAmelCase__ : int = 0
while num > 0:
UpperCAmelCase__ : Any ... | 700 |
"""simple docstring"""
from timeit import timeit
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
if number < 0:
raise ValueError("the value of input must not be negative" )
UpperCAmelCase__ : Tuple = 0
while number:
numbe... | 660 | 0 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
A__ : List[str] = logging.get_logger(__name__)
A__ : Tuple = {
"""google/umt5-small""": """https... | 701 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _lowercase ( unittest.TestCase , lowerCAmelCase_ ):
'''simple docstring'''
def lowerCAmelCase__ ( self )-> Dict:
Uppe... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class _lowercase :
'''simple docstring'''
def __init__( self , __UpperCamelCase )-> str:
UpperCAmelCase__ : list[dict] = []
self.adlist.append(
... | 702 |
"""simple docstring"""
def a__ ( lowerCAmelCase : list , lowerCAmelCase : list ):
'''simple docstring'''
_validate_point(lowerCAmelCase )
_validate_point(lowerCAmelCase )
if len(lowerCAmelCase ) != len(lowerCAmelCase ):
raise ValueError("Both ... | 660 | 0 |
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def a__ ( lowerCAmelCase : str ):
'''simple docstring'''
return x + 2
class _lowercase ( unittest.TestCase ):
'''simple docs... | 703 |
"""simple docstring"""
import math
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
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 mul... | 660 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase : list ):
'''simple docstring'''
if len(lowerCAmelCase ) <= 1:
return [tuple(lowerCAmelCase )]
UpperCAmelCase__ : str = []
def generate(lowerCAmelCase : int , lowerCAmelCase : ... | 704 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availab... | 660 | 0 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
A__ : Union[str, Any] = """\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Gr... | 705 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .schedulin... | 660 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : Dict = logging.get_logger(__name__)
A__ : str = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/git-base/resolve/main/config.js... | 706 |
"""simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class _lowercase ... | 660 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_camembert import... | 707 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 660 | 0 |
"""simple docstring"""
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerB... | 708 |
"""simple docstring"""
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(lowerCAmelCase , lowerCAmelCase ):
raise TypeError("Input value must be a 'int' ... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def a__ ( lowerCAmelCase : Callable[[int | float], int | float] , lowerCAmelCase : int | float , lowerCAmelCase : int | float , lowerCAmelCase : ... | 709 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_availab... | 660 | 0 |
"""simple docstring"""
import qiskit
def a__ ( lowerCAmelCase : int , lowerCAmelCase : int ):
'''simple docstring'''
UpperCAmelCase__ : List[str] = qiskit.Aer.get_backend("aer_simulator" )
# Create a Quantum Circuit act... | 710 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import _LazyModule
A__ : List[str] = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
A__ : Any = _LazyMod... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase : list[int] ):
'''simple docstring'''
if len(lowerCAmelCase ) == 0:
return array
UpperCAmelCase__ : Union[str, Any] = min(lowerCAmelCase ), max(lowerCAmelCase ... | 711 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class _lowercase ( lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstrin... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
A__ : Optional[Any] = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def a__ ( lowerCAmelCase : list[list[int]] , lowerCAmelCase : list[int] , lowerCAmelCase ... | 712 |
"""simple docstring"""
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 a__ ( lowerCAmelCase : List[Any] , lowerCAmelCase : An... | 660 | 0 |
"""simple docstring"""
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_ava... | 713 |
"""simple docstring"""
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
A__ : Optional[int] = ["""small""", """medium""", """large"""]
A__ : Optional[int] = """lm_head.decoder.weight"""
A__ : Dict = """lm_head.weight"""
de... | 660 | 0 |
"""simple docstring"""
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 impo... | 714 |
"""simple docstring"""
from math import isqrt
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
def a__ ( lowerCAmelCase : list[list[int]] ):
'''simple docstring'''
UpperCAmelCase__ : Optional[int] = len(lowerCAmelCase )
# We need to create solution object to save path.
UpperCAmelCase__ ... | 715 |
"""simple docstring"""
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerB... | 660 | 0 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational... | 716 |
"""simple docstring"""
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def a__ ( lowerCAmelCase : List[str] ):
'''simple docstring'''
def wrapper(*lowerCAmelCase : Any , ... | 660 | 0 |
"""simple docstring"""
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def a__ ( lowerCAmelCase : Any ):
'''simple docstring'''
monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings" , set() )
... | 717 |
"""simple docstring"""
from manim import *
class _lowercase ( lowerCAmelCase_ ):
'''simple docstring'''
def lowerCAmelCase__ ( self )-> Tuple:
UpperCAmelCase__ : str = Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase... | 660 | 0 |
"""simple docstring"""
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_u... | 718 |
"""simple docstring"""
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
A__ : Tuple = logging.get_logger(__name__... | 660 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase : list , lowerCAmelCase : list ):
'''simple docstring'''
_validate_point(lowerCAmelCase )
_validate_point(lowerCAmelCase )
if len(lowerCAmelCase ) != len(lowerCAmelCase ):
raise ValueError("Both ... | 719 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_co... | 660 | 0 |
"""simple docstring"""
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _lowercase ( unittest.TestCase ):
def lowerCAmelCase__ ( self )-> List[Any]:
debug_launcher... | 720 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A__ : Union[str, Any] = logging.... | 660 | 0 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class _lowercase ( lowerCAmelCase_ ):
'''simple docstring'''
_A = (UnCLIPScheduler,)
def lowerCAmelCase__ ( self , ... | 721 |
"""simple docstring"""
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTok... | 660 | 0 |
"""simple docstring"""
import requests
A__ : Optional[int] = """YOUR API KEY"""
def a__ ( lowerCAmelCase : str , lowerCAmelCase : str = giphy_api_key ):
'''simple docstring'''
UpperCAmelCase__ : str = "+".join(query.split() )
... | 700 |
"""simple docstring"""
from timeit import timeit
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
if number < 0:
raise ValueError("the value of input must not be negative" )
UpperCAmelCase__ : Tuple = 0
while number:
numbe... | 660 | 0 |
"""simple docstring"""
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
deprecate(
"""pipelines_utils""",
"""0.22.0""",
"""Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from dif... | 701 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _lowercase ( unittest.TestCase , lowerCAmelCase_ ):
'''simple docstring'''
def lowerCAmelCase__ ( self )-> Dict:
Uppe... | 660 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def a__ ( lowerCAmelCase : str , lowerCAmelCase : Tuple , lowerCAme... | 702 |
"""simple docstring"""
def a__ ( lowerCAmelCase : list , lowerCAmelCase : list ):
'''simple docstring'''
_validate_point(lowerCAmelCase )
_validate_point(lowerCAmelCase )
if len(lowerCAmelCase ) != len(lowerCAmelCase ):
raise ValueError("Both ... | 660 | 0 |
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
@require_sentencepiece
@require_... | 703 |
"""simple docstring"""
import math
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
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 mul... | 660 | 0 |
"""simple docstring"""
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
A__ : Any = lo... | 704 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availab... | 660 | 0 |
"""simple docstring"""
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisio... | 705 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .schedulin... | 660 | 0 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str] = logging.get_logger(__name__)
A__ : int = {
"""facebook/encodec_24khz""": """https://huggingface.co/facebook/encodec_24... | 706 |
"""simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class _lowercase ... | 660 | 0 |
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("""9.1.0"""):
A__ : Tuple = {
"""linear""": PIL.Image.Resampling.BILINEAR,
"""bilinear""": PIL.Image.Resampling.... | 707 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 660 | 0 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", l... | 708 |
"""simple docstring"""
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(lowerCAmelCase , lowerCAmelCase ):
raise TypeError("Input value must be a 'int' ... | 660 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A__ : Union[str, Any] = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG... | 709 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_availab... | 660 | 0 |
"""simple docstring"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import Pretr... | 710 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import _LazyModule
A__ : List[str] = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
A__ : Any = _LazyMod... | 660 | 0 |
"""simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class _lowercase :
'''simple docstring'''
def __init__( self , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCas... | 711 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class _lowercase ( lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstrin... | 660 | 0 |
"""simple docstring"""
A__ : int = {
"""Pillow""": """Pillow<10.0.0""",
"""accelerate""": """accelerate>=0.20.3""",
"""av""": """av==9.2.0""",
"""beautifulsoup4""": """beautifulsoup4""",
"""black""": """black~=23.1""",
"""codecarbon""": """codecarbon==1.2.0""",
"""cooki... | 712 |
"""simple docstring"""
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 a__ ( lowerCAmelCase : List[Any] , lowerCAmelCase : An... | 660 | 0 |
"""simple docstring"""
import numpy as np
def a__ ( lowerCAmelCase : np.array ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 713 |
"""simple docstring"""
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
A__ : Optional[int] = ["""small""", """medium""", """large"""]
A__ : Optional[int] = """lm_head.decoder.weight"""
A__ : Dict = """lm_head.weight"""
de... | 660 | 0 |
"""simple docstring"""
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docs... | 714 |
"""simple docstring"""
from math import isqrt
def a__ ( lowerCAmelCase : int ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j... | 660 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class _lowercase :
'''simple docstring'''
def __init__( self , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase = 0 )-> None:
UpperCAmelCase__ : Dict = ... | 715 |
"""simple docstring"""
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerB... | 660 | 0 |
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