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 |
|---|---|---|---|---|
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface import Hugg... | 688 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ) -> int:
return int((input_a, input_a).count(1 ) != 0 )
def __SCREAMING_SNAKE_CASE ( ) -> None:
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ... | 688 | 1 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
... | 688 |
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 version.parse(fairseq.__vers... | 688 | 1 |
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinis... | 688 |
from __future__ import annotations
import math
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : int ) -> float:
__lowercase = u
for i in range(1 , SCREAMING_SNAKE_CASE ):
__lowercase = temp * (u - i)
ret... | 688 | 1 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Prophe... | 688 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> int:
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
__lowercase = F"""Input value of [number={number}] must be an integer"""
raise TypeError(SCREAMING_SNAKE_CASE )
if number... | 688 | 1 |
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEmbeddings,
BertLayer,
... | 688 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __SCREAMING_SNAKE_CASE ( ) -> List[str]:
__lowercase = ArgumentParser('Diffusers CLI tool' , usage='diffusers-cli <command> [<args>]' )
__lowercase = parser.add_subparsers(help='diffusers-cl... | 688 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE... | 688 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Prophe... | 688 | 1 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class A__ ( lowerCAmelCase__ ):
def __init__( self : List[str] , _UpperCAmelCase : str="" , _UpperCAmelCase : int="train" ) -> Tuple:
"""simple... | 688 |
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import T... | 688 | 1 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( lowerCAmelCase__ ):
lowerCAme... | 688 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ra... | 688 | 1 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
sk... | 688 |
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
class... | 688 | 1 |
import enum
import shutil
import sys
SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__ = shutil.get_terminal_size()
SCREAMING_SNAKE_CASE__ = {"""UP""": """A""", """DOWN""": """B""", """RIGHT""": """C""", """LEFT""": """D"""}
class A__ ( enum.Enum ):
lowerCAmelCase__ :... | 688 |
import string
from math import logaa
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : str ) -> int:
__lowercase = document.translate(
str.maketrans('' , '' , string.punctuation ) ).replace('\n' , ''... | 688 | 1 |
from math import asin, atan, cos, radians, sin, sqrt, tan
SCREAMING_SNAKE_CASE__ = 6378137.0
SCREAMING_SNAKE_CASE__ = 6356752.314245
SCREAMING_SNAKE_CASE__ = 637_8137
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : flo... | 688 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
# TODO: upload to AWS
SCREAMING_SNAKE_CASE__ = {
"""yjernite/retribert-base-uncased""": (
"""https://huggingface.co/yjernite/retribert-base-unc... | 688 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""shi-labs/dinat-mini-in1... | 688 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconConfig"""],
}
try:
if not is_torch_available():
... | 688 | 1 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransformer,... | 688 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( lowerCAmelCase__ ):
lowerCAme... | 688 | 1 |
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
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
def __SC... | 688 |
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
SCREAMING_SNAKE_CASE... | 688 | 1 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class A__ ( unittest.TestCase ):
def a__ ( self : Dict ) -> Optional[Any]:
"""simp... | 688 |
import math
import sys
import cva
import numpy as np
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : np.ndarray , SCREAMING_SNAKE_CASE : float ) -> np.ndarray:
# For applying gaussian function for each element in matrix.
__lowercase = math.sqrt(SCREAMING_SNAKE_CASE... | 688 | 1 |
# 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 applicab... | 688 |
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():
... | 688 | 1 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
def __SCREAMING_SNAKE_CASE ( SC... | 688 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""google/umt5-small""": """https://huggingface.co/g... | 688 | 1 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> str:
if number > 0:
raise ValueError('input must be a negative integer' )
__lowercase = len(bin(SCREAMING_SNAKE_CASE )[3:] )
__lowercase = bin(abs(SCREAMING_SNAKE_CASE ) - (1 << binary_number_le... | 688 |
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 logging
if TYPE_CHECKING:
... | 688 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPanoramaPipeline,
UNet... | 688 |
from pathlib import Path
import numpy as np
from PIL import Image
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : np.ndarray ) -> np.ndarray:
__lowercase , __lowercase , __lowercase = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2_989 * r + 0.5_870 * g + 0.1_140... | 688 | 1 |
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 AutoTokeniz... | 688 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENAI... | 688 | 1 |
SCREAMING_SNAKE_CASE__ = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],
"""G""": ["""C"""],
}
def __SCREAMING_SNAKE_CASE ... | 688 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_bert""": ["""B... | 688 | 1 |
import pytest
import datasets
# Import fixture modules as plugins
SCREAMING_SNAKE_CASE__ = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : List[Any] , SCREAMING_SNAKE_CASE : Tuple ) -... | 688 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def __SCREAMING_SNAK... | 688 | 1 |
from __future__ import annotations
import os
from typing import Any
import requests
SCREAMING_SNAKE_CASE__ = """https://api.github.com"""
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
SCREAMING_SNAKE_CASE__ = BASE_URL + """/user"""
# http... | 688 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ) -> int:
return int((input_a, input_a).count(1 ) != 0 )
def __SCREAMING_SNAKE_CASE ( ) -> None:
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ... | 688 | 1 |
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : Optional[int] ) -> Tuple:
# encoder.embeddings ... | 688 |
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 version.parse(fairseq.__vers... | 688 | 1 |
import math
from numpy import inf
from scipy.integrate import quad
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : float ) -> float:
if num <= 0:
raise ValueError('math domain error' )
return quad(SCREAMING_SNAKE_CASE , 0 , SCREAMING_SNAKE_CASE , ... | 688 |
from __future__ import annotations
import math
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : int ) -> float:
__lowercase = u
for i in range(1 , SCREAMING_SNAKE_CASE ):
__lowercase = temp * (u - i)
ret... | 688 | 1 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_utils impo... | 688 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> int:
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
__lowercase = F"""Input value of [number={number}] must be an integer"""
raise TypeError(SCREAMING_SNAKE_CASE )
if number... | 688 | 1 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from datasets.uti... | 688 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __SCREAMING_SNAKE_CASE ( ) -> List[str]:
__lowercase = ArgumentParser('Diffusers CLI tool' , usage='diffusers-cli <command> [<args>]' )
__lowercase = parser.add_subparsers(help='diffusers-cl... | 688 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""facebook/wav2vec2-base-960h""": """https://huggingface.co/facebook/wav2vec2-base-960h/res... | 688 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Prophe... | 688 | 1 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
SCREAMING_SNAKE_CASE__ = logging.getLogger(__name__)
class A__ :
def __init__( self : Union[str, Any] ... | 688 |
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import T... | 688 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}
class A... | 688 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ra... | 688 | 1 |
class A__ :
def __init__( self : Union[str, Any] , _UpperCAmelCase : Optional[Any] , _UpperCAmelCase : Optional[Any] , _UpperCAmelCase : Any ) -> Dict:
"""simple docstring"""
__lowercase = None
__l... | 688 |
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
class... | 688 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
SCREAMING_SNAKE_CASE__ = {
"""configuration_ernie""": ["""ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ErnieConfig""", """ErnieOnnxConfig"""],
}
try:
... | 688 |
import string
from math import logaa
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : str ) -> int:
__lowercase = document.translate(
str.maketrans('' , '' , string.punctuation ) ).replace('\n' , ''... | 688 | 1 |
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,
Pix... | 688 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
# TODO: upload to AWS
SCREAMING_SNAKE_CASE__ = {
"""yjernite/retribert-base-uncased""": (
"""https://huggingface.co/yjernite/retribert-base-unc... | 688 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""caidas/swin2sr-classicalsr-x2-64""": (
"""https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/conf... | 688 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconConfig"""],
}
try:
if not is_torch_available():
... | 688 | 1 |
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
SCREAMING_SNAKE_CASE... | 688 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( lowerCAmelCase__ ):
lowerCAme... | 688 | 1 |
# 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 .scheduling_utils_flax import (
C... | 688 |
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
SCREAMING_SNAKE_CASE... | 688 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SN... | 688 |
import math
import sys
import cva
import numpy as np
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : np.ndarray , SCREAMING_SNAKE_CASE : float ) -> np.ndarray:
# For applying gaussian function for each element in matrix.
__lowercase = math.sqrt(SCREAMING_SNAKE_CASE... | 688 | 1 |
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
require_torch_min... | 688 |
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():
... | 688 | 1 |
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_fnet import F... | 688 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""google/umt5-small""": """https://huggingface.co/g... | 688 | 1 |
import string
from math import logaa
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : str ) -> int:
__lowercase = document.translate(
str.maketrans('' , '' , string.punctuation ) ).replace('\n' , ''... | 688 |
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 logging
if TYPE_CHECKING:
... | 688 | 1 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTest... | 688 |
from pathlib import Path
import numpy as np
from PIL import Image
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : np.ndarray ) -> np.ndarray:
__lowercase , __lowercase , __lowercase = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2_989 * r + 0.5_870 * g + 0.1_140... | 688 | 1 |
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_logging
sys.path.append(os.path... | 688 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENAI... | 688 | 1 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : str ) -> str:
return " ".join(
''.join(word[::-1] ) if len(SCREAMING_SNAKE_CASE ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_lon... | 688 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_bert""": ["""B... | 688 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {"""configuration_mbart""": ["""MBART_P... | 688 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def __SCREAMING_SNAK... | 688 | 1 |
from pathlib import Path
import numpy as np
from PIL import Image
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : np.ndarray ) -> np.ndarray:
__lowercase , __lowercase , __lowercase = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2_989 * r + 0.5_870 * g + 0.1_140... | 688 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ) -> int:
return int((input_a, input_a).count(1 ) != 0 )
def __SCREAMING_SNAKE_CASE ( ) -> None:
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ... | 688 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@require... | 688 |
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 version.parse(fairseq.__vers... | 688 | 1 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.set_verbosity... | 688 |
from __future__ import annotations
import math
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : int ) -> float:
__lowercase = u
for i in range(1 , SCREAMING_SNAKE_CASE ):
__lowercase = temp * (u - i)
ret... | 688 | 1 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class A__ ( lowerCAmelCase__ , unittest.TestCase ):
lo... | 688 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> int:
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
__lowercase = F"""Input value of [number={number}] must be an integer"""
raise TypeError(SCREAMING_SNAKE_CASE )
if number... | 688 | 1 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
SCREAMING_SNAKE_CASE__ = Path(__file__).resolve().parents[3] / """src"""
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io # no... | 688 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __SCREAMING_SNAKE_CASE ( ) -> List[str]:
__lowercase = ArgumentParser('Diffusers CLI tool' , usage='diffusers-cli <command> [<args>]' )
__lowercase = parser.add_subparsers(help='diffusers-cl... | 688 | 1 |
from math import pi
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ) -> float:
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 688 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Prophe... | 688 | 1 |
class A__ :
def __init__( self : Any ) -> Any:
"""simple docstring"""
__lowercase = ''
__lowercase = ''
__lowercase = []
def a__ ( self : str , _UpperCAmelCase : int ... | 688 |
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import T... | 688 | 1 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class A__ ( lowerCAmelCase__ ):
def __init__( self : Union[str, Any] , _UpperCAmelCase : Optional[int] , _UpperCAmelCase : Tuple... | 688 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ra... | 688 | 1 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ = {
"""facebook/mask2former-swin-small-coco-instance""": (
"""https://huggingface.co/facebook/mask2for... | 688 |
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
class... | 688 | 1 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int = 1000000 ) -> int:
__lowercase = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , SCREAMING_SNAKE_C... | 688 |
import string
from math import logaa
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : str ) -> int:
__lowercase = document.translate(
str.maketrans('' , '' , string.punctuation ) ).replace('\n' , ''... | 688 | 1 |
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 ... | 688 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
# TODO: upload to AWS
SCREAMING_SNAKE_CASE__ = {
"""yjernite/retribert-base-uncased""": (
"""https://huggingface.co/yjernite/retribert-base-unc... | 688 | 1 |
from __future__ import annotations
import requests
SCREAMING_SNAKE_CASE__ = set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories created_u... | 688 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconConfig"""],
}
try:
if not is_torch_available():
... | 688 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_blenderbot""": [
"""BLENDERBOT_PRETRAINE... | 688 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( lowerCAmelCase__ ):
lowerCAme... | 688 | 1 |
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class A__ ( lowerCAmelCase__ , unittest.TestCase ):
lowe... | 688 |
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
SCREAMING_SNAKE_CASE... | 688 | 1 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ) -> int:
return int((input_a, input_a).count(1 ) != 0 )
def __SCREAMING_SNAKE_CASE ( ) -> None:
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ... | 688 |
import math
import sys
import cva
import numpy as np
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : np.ndarray , SCREAMING_SNAKE_CASE : float ) -> np.ndarray:
# For applying gaussian function for each element in matrix.
__lowercase = math.sqrt(SCREAMING_SNAKE_CASE... | 688 | 1 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class A__ ( unittest.TestCase ):
def a__ ( self : Union[str, Any] ) -> Optional[int]:
"""simple docstring"""
... | 688 |
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():
... | 688 | 1 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)... | 688 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""google/umt5-small""": """https://huggingface.co/g... | 688 | 1 |
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
)
SCREAMING_SNAKE_CASE__ = logging.ge... | 688 |
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 logging
if TYPE_CHECKING:
... | 688 | 1 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : bytes , SCREAMING_SNAKE_CASE : int ) -> np.array:
__lowercase = F"""{sampling_rate}"""
__lowercase = ... | 688 |
from pathlib import Path
import numpy as np
from PIL import Image
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : np.ndarray ) -> np.ndarray:
__lowercase , __lowercase , __lowercase = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2_989 * r + 0.5_870 * g + 0.1_140... | 688 | 1 |
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accel... | 688 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENAI... | 688 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""microsoft/unispeech-sat-base-100h-libri-ft""": (
"""https://huggingface.co/micros... | 688 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_bert""": ["""B... | 688 | 1 |
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS
logging... | 688 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def __SCREAMING_SNAK... | 688 | 1 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int = 1000 ) -> int:
__lowercase = 2**power
__lowercase = 0
while n:
__lowercase , __lowercase = r + n % 10, n // 10
return r
if __name__ == "__main__":
print(solution(int(str(input()).strip... | 688 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ) -> int:
return int((input_a, input_a).count(1 ) != 0 )
def __SCREAMING_SNAKE_CASE ( ) -> None:
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ... | 688 | 1 |
from __future__ import annotations
from math import ceil, floor, sqrt
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int = 2000000 ) -> int:
__lowercase = [0]
__lowercase = 42
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ):
triang... | 688 |
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 version.parse(fairseq.__vers... | 688 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
RandomHorizontalFlip,
... | 688 |
from __future__ import annotations
import math
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : int ) -> float:
__lowercase = u
for i in range(1 , SCREAMING_SNAKE_CASE ):
__lowercase = temp * (u - i)
ret... | 688 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_S... | 688 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> int:
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
__lowercase = F"""Input value of [number={number}] must be an integer"""
raise TypeError(SCREAMING_SNAKE_CASE )
if number... | 688 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""junnyu/roformer_chinese_smal... | 688 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __SCREAMING_SNAKE_CASE ( ) -> List[str]:
__lowercase = ArgumentParser('Diffusers CLI tool' , usage='diffusers-cli <command> [<args>]' )
__lowercase = parser.add_subparsers(help='diffusers-cl... | 688 | 1 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIF... | 688 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Prophe... | 688 | 1 |
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=lowerCAmelCase__ ):
lowerCAmelCase__ : Tuple = ["transformers", "torch", "note_seq"]
def __init__( self : Union[str, Any] , *_UpperCAmelCase : Any , **_UpperCAmelCase ... | 688 |
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import T... | 688 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 688 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ra... | 688 | 1 |
import os
SCREAMING_SNAKE_CASE__ = {"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1000}
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : str ) -> int:
__lowercase = 0
__lowercase = 0
while index < len(SCREAMING_SN... | 688 |
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
class... | 688 | 1 |
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 version.parse(fairseq.__vers... | 688 |
import string
from math import logaa
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : str ) -> int:
__lowercase = document.translate(
str.maketrans('' , '' , string.punctuation ) ).replace('\n' , ''... | 688 | 1 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils im... | 688 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
# TODO: upload to AWS
SCREAMING_SNAKE_CASE__ = {
"""yjernite/retribert-base-uncased""": (
"""https://huggingface.co/yjernite/retribert-base-unc... | 688 | 1 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers import (
Efficien... | 688 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconConfig"""],
}
try:
if not is_torch_available():
... | 688 | 1 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ra... | 688 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( lowerCAmelCase__ ):
lowerCAme... | 688 | 1 |
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 __SCREAMING_SNAKE_CASE ... | 688 |
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
SCREAMING_SNAKE_CASE... | 688 | 1 |
from __future__ import annotations
import math
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> bool:
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 m... | 688 |
import math
import sys
import cva
import numpy as np
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : np.ndarray , SCREAMING_SNAKE_CASE : float ) -> np.ndarray:
# For applying gaussian function for each element in matrix.
__lowercase = math.sqrt(SCREAMING_SNAKE_CASE... | 688 | 1 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
class A__ ( lowerCAmelCase__ ):
def __init__( self : str , *_UpperCAmelCase : List[str] ... | 688 |
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():
... | 688 | 1 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : bool = False ) -> list[float]:
... | 688 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""google/umt5-small""": """https://huggingface.co/g... | 688 | 1 |
import pprint
import requests
SCREAMING_SNAKE_CASE__ = """https://zenquotes.io/api"""
def __SCREAMING_SNAKE_CASE ( ) -> list:
return requests.get(API_ENDPOINT_URL + '/today' ).json()
def __SCREAMING_SNAKE_CASE ( ) -> list:
return requests.get(API_ENDPOINT_URL ... | 688 |
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 logging
if TYPE_CHECKING:
... | 688 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {"""configuration_unispeech""": ["""UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP""", """UniSpeechConfig""... | 688 |
from pathlib import Path
import numpy as np
from PIL import Image
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : np.ndarray ) -> np.ndarray:
__lowercase , __lowercase , __lowercase = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2_989 * r + 0.5_870 * g + 0.1_140... | 688 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class A__ ( lowerCAmelCase__ ):
lowerCAmelCase__ : Union[str, Any] = ["image_processor", "tokenizer"]
lowerCAmelCase__ : str = "CLIPImageProcess... | 688 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENAI... | 688 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET... | 688 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_bert""": ["""B... | 688 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""BridgeTower/bridgetower-base""": """https://huggingface.co/BridgeTower/brid... | 688 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def __SCREAMING_SNAK... | 688 | 1 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ra... | 688 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ) -> int:
return int((input_a, input_a).count(1 ) != 0 )
def __SCREAMING_SNAKE_CASE ( ) -> None:
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ... | 688 | 1 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : Any ) -> List[Any]:
__lowercase = len(SCREAMING_SNAKE_CASE )
while cur > 1:
# Find the maximum number in arr
__lowercase = arr.index(max(arr[0:cur] ) )
# Reverse from 0 to mi
__lowercase... | 688 |
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 version.parse(fairseq.__vers... | 688 | 1 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : Optional[Any] , SCREAMING_SNAKE_CASE : ... | 688 |
from __future__ import annotations
import math
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : int ) -> float:
__lowercase = u
for i in range(1 , SCREAMING_SNAKE_CASE ):
__lowercase = temp * (u - i)
ret... | 688 | 1 |
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
SCREAMING_SNAKE_CASE__ = logging.getLogger(__n... | 688 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> int:
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
__lowercase = F"""Input value of [number={number}] must be an integer"""
raise TypeError(SCREAMING_SNAKE_CASE )
if number... | 688 | 1 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def __SCREAMING_SNAK... | 688 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __SCREAMING_SNAKE_CASE ( ) -> List[str]:
__lowercase = ArgumentParser('Diffusers CLI tool' , usage='diffusers-cli <command> [<args>]' )
__lowercase = parser.add_subparsers(help='diffusers-cl... | 688 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/config.json""",
# See all XGLM models ... | 688 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Prophe... | 688 | 1 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : str ) -> Any:
monkeypatch.setattr('datasets.utils.deprecation_utils._emitted_deprecation_warnings' , set() )
@pytest.fixture
def ... | 688 |
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import T... | 688 | 1 |
import math
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : list , SCREAMING_SNAKE_CASE : int ) -> int:
__lowercase = len(SCREAMING_SNAKE_CASE )
__lowercase = int(math.floor(math.sqrt(SCREAMING_SNAKE_CASE ) ) )
__lowercase = 0
while... | 688 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ra... | 688 | 1 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
SCREAMING_SNAKE_CASE__ = logging.getLogger(__name__)
class A__ ( lowerCAmelCase__ ):
def __init__( se... | 688 |
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
class... | 688 | 1 |
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_t... | 688 |
import string
from math import logaa
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : str ) -> int:
__lowercase = document.translate(
str.maketrans('' , '' , string.punctuation ) ).replace('\n' , ''... | 688 | 1 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> int:
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
__lowercase = F"""Input value of [number={number}] must be an integer"""
raise TypeError(SCREAMING_SNAKE_CASE )
if number... | 688 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
# TODO: upload to AWS
SCREAMING_SNAKE_CASE__ = {
"""yjernite/retribert-base-uncased""": (
"""https://huggingface.co/yjernite/retribert-base-unc... | 688 | 1 |
from math import isqrt, loga
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> list[int]:
__lowercase = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , SCREAMING_SNAK... | 688 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconConfig"""],
}
try:
if not is_torch_available():
... | 688 | 1 |
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