code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
def __lowerCamelCase ( lowerCamelCase__ : list[int] , lowerCamelCase__ : list[int] ):
'''simple docstring'''
lowerCamelCase = len(lowerCamelCase__ )
print("""The following activities are selected:""" )
# The first activity is always selecte... | 66 |
class __lowercase :
"""simple docstring"""
def __init__( self ) -> None:
'''simple docstring'''
lowerCamelCase = {} # Mapping from char to TrieNode
lowerCamelCase = False
def __A ( self , A ) -> ... | 66 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Dict = {
"configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}
try:
if not is_torch_available():
raise OptionalD... | 66 |
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
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmel... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : int = 3 , lowerCamelCase__ : int = 7 , lowerCamelCase__ : int = 1000000 ):
'''simple docstring'''
lowerCamelCase = 0
lowerCamelCase = 1
for current_denominator in range(1 ,... | 66 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __lowercase ( pl.LightningModule ):
"""simple docstring"""
def __init__( self , A ) -> Any:
... | 66 | 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_to... | 66 |
UpperCAmelCase : Tuple = "Tobias Carryer"
from time import time
class __lowercase :
"""simple docstring"""
def __init__( self , A , A , A , A=int(time() ) ) -> Optional[int]: # noqa: B008
'''simple docstring'''
... | 66 | 1 |
import math
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] , lowerCamelCase__ : Union[str, Any] ):
'''simple docstring'''
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(lowerCamelCase_... | 66 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerc... | 66 | 1 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_vision_available
fro... | 66 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Union[str, Any] = {
"configuration_mobilebert": [
"MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_M... | 66 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenizer
else:
UpperCAmelCase : Opt... | 66 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase : str =... | 66 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"... | 66 |
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
UpperCAmelCase : Optional[Any] = logging.get_logger(... | 66 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.set_... | 66 |
def __lowerCamelCase ( ):
'''simple docstring'''
lowerCamelCase = []
lowerCamelCase = 1
while len(lowerCamelCase__ ) < 1E6:
constant.append(str(lowerCamelCase__ ) )
i += 1
lowerCamelCase = """""".join(lowerCamelCase__ ... | 66 | 1 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __lowercase ( a_ , unittest.TestCase ):
"""simple docstring"""
UpperCamelCase : Lis... | 66 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("""socket.socket""" )
@patch("""builtins.open""" )
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] , lowerCamelCase__ : Dict ):
'''simple docstring'''
low... | 66 | 1 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def __lowerCamelCase ( lowerCamelCase__ : str ):
'''simple docstring'''
lowerCamelCase , lowerCamelCase = analyze_text(lowerCamelCase__ ... | 66 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils impor... | 66 | 1 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
UpperCAmelCase : Any = "\\n@misc{wu2016googles,\n title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n author={Yonghui ... | 66 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : List[Any] = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/AltCLIP/resolve/main/conf... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : int ):
'''simple docstring'''
if length <= 0 or not isinstance(lowerCamelCase__ , lowerCamelCase__ ):
raise ValueError("""Length must be a positive integer.""" )
return [n * (2 * n - 1) for n in range(lowerCamelCase... | 66 |
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,
UN... | 66 | 1 |
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa: F401
deprecate(
... | 66 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Dict = logging.get_logger(__name__)
UpperCAmelCase : Any = {
"google/switch-base-8": "https://huggingface.co/google/switch-base-8/blob/main/config.json",
}
class __lowercase ( ... | 66 | 1 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase : Union[str, Any] ... | 66 |
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
UpperCAmelCase : Optional[int] = logging.getLogger(__... | 66 | 1 |
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def __lowerCamelCase ( lowerCamelCase__ : List[str] , lowerCamelCase__ : Dict , lowerCamelCase__ : Optional[Any] , lowerCamelCase__ : ... | 66 |
import math
import tensorflow as tf
from packaging import version
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] ):
'''simple docstring'''
lowerCamelCase = tf.convert_to_tensor(lowerCamelCase__ )
lowerCamelCase = 0.5 * (1.0 + tf.math.... | 66 | 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 HuggingFace
... | 66 |
def __lowerCamelCase ( lowerCamelCase__ : Any ):
'''simple docstring'''
lowerCamelCase = [0] * len(lowerCamelCase__ )
lowerCamelCase = []
lowerCamelCase = []
lowerCamelCase = 0
for values in graph.values():
f... | 66 | 1 |
import enum
import shutil
import sys
UpperCAmelCase, UpperCAmelCase : int = shutil.get_terminal_size()
UpperCAmelCase : List[Any] = {"UP": "A", "DOWN": "B", "RIGHT": "C", "LEFT": "D"}
class __lowercase ( enum.Enum ):
"""simple docstring"""
UpperCamelCase : ... | 66 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __lowerCamelCase ( lowerCamelCase__ : List[Any] , lowerCamelCase__ : List[str] , lowerCamelCase__ : str ):
'''simple docstring'''
lowerCamelCase = 0... | 66 | 1 |
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __lowerCamelCase ( lowerCamelCase__ : np.ndarray , lowerCamelCase__ : np.ndarray ):
'''simple docstring'''
return math.sqrt(sum(pow(a - b , 2 ) for... | 66 |
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
Upper... | 66 | 1 |
from math import isclose, sqrt
def __lowerCamelCase ( lowerCamelCase__ : float , lowerCamelCase__ : float , lowerCamelCase__ : float ):
'''simple docstring'''
lowerCamelCase = point_y / 4 / point_x
lowerCamelCase = 2 *... | 66 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"... | 66 | 1 |
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def __lowerCamelCase ( lowerCamelCase__ : List[Any] ):
'''simple docstring'''
lowerCamelCase = [
"""encoder.version""",
... | 66 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
UpperCAmelCase : str = {
"text_branch": "text_model",
"audio_branch": "audio_model.audio_encoder",
"attn": "attention.self",
"self.proj": "output.de... | 66 | 1 |
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ... | 66 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice... | 66 | 1 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] ):
'''simple docstring'''
lowerCamelCase = {}
lowerCamelCase = job["""started_at"""]
low... | 66 |
class __lowercase :
"""simple docstring"""
def __init__( self ) -> None:
'''simple docstring'''
lowerCamelCase = {} # Mapping from char to TrieNode
lowerCamelCase = False
def __A ( self , A ) -> ... | 66 | 1 |
from math import isqrt, loga
def __lowerCamelCase ( lowerCamelCase__ : int ):
'''simple docstring'''
lowerCamelCase = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 ... | 66 |
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
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmel... | 66 | 1 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformers.utils import loggin... | 66 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __lowercase ( pl.LightningModule ):
"""simple docstring"""
def __init__( self , A ) -> Any:
... | 66 | 1 |
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
UpperCAmelCase : Tuple = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False)
parser.add_argument("--dpm", action="st... | 66 |
UpperCAmelCase : Tuple = "Tobias Carryer"
from time import time
class __lowercase :
"""simple docstring"""
def __init__( self , A , A , A , A=int(time() ) ) -> Optional[int]: # noqa: B008
'''simple docstring'''
... | 66 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
UpperCAmelCase : Dict = {
"facebook/nllb-moe-54B": "https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json",
}
class __lower... | 66 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerc... | 66 | 1 |
import logging
import os
from .state import PartialState
class __lowercase ( logging.LoggerAdapter ):
"""simple docstring"""
@staticmethod
def __A ( A ) -> Union[str, Any]:
'''simple docstring'''
lowerCamelCase = PartialState()
... | 66 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Union[str, Any] = {
"configuration_mobilebert": [
"MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_M... | 66 | 1 |
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
Upper... | 66 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase : str =... | 66 | 1 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configura... | 66 |
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
UpperCAmelCase : Optional[Any] = logging.get_logger(... | 66 | 1 |
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
UpperCAmelCase : List[Any] = TypeVar("T")
class __lowercase ( Generic[T] ):
"""simple docstring"""
def __init__( self , A , A ) -> ... | 66 |
def __lowerCamelCase ( ):
'''simple docstring'''
lowerCamelCase = []
lowerCamelCase = 1
while len(lowerCamelCase__ ) < 1E6:
constant.append(str(lowerCamelCase__ ) )
i += 1
lowerCamelCase = """""".join(lowerCamelCase__ ... | 66 | 1 |
from __future__ import annotations
UpperCAmelCase : List[str] = 10
def __lowerCamelCase ( lowerCamelCase__ : list[int] ):
'''simple docstring'''
lowerCamelCase = 1
lowerCamelCase = max(lowerCamelCase__ )
while placement <= max_di... | 66 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("""socket.socket""" )
@patch("""builtins.open""" )
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] , lowerCamelCase__ : Dict ):
'''simple docstring'''
low... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : str ):
'''simple docstring'''
lowerCamelCase = [int(lowerCamelCase__ ) for i in ip_va_address.split(""".""" ) if i.isdigit()]
return len(lowerCamelCase__ ) == 4 and all(0 <= int(lowerCamelCase__ ) <= 254 for o... | 66 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils impor... | 66 | 1 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing
... | 66 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : List[Any] = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/AltCLIP/resolve/main/conf... | 66 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
logging,
)
logging.set_... | 66 |
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,
UN... | 66 | 1 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
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_common... | 66 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Dict = logging.get_logger(__name__)
UpperCAmelCase : Any = {
"google/switch-base-8": "https://huggingface.co/google/switch-base-8/blob/main/config.json",
}
class __lowercase ( ... | 66 | 1 |
import os
def __lowerCamelCase ( ):
'''simple docstring'''
with open(os.path.dirname(lowerCamelCase__ ) + """/p022_names.txt""" ) as file:
lowerCamelCase = str(file.readlines()[0] )
lowerCamelCase = names.replace("""\"""" , """"... | 66 |
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
UpperCAmelCase : Optional[int] = logging.getLogger(__... | 66 | 1 |
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
UpperCAmelCase : Tuple = 1.054_571_817e-34 # unit of ℏ : J * s
UpperCAmelCase : Optional[int] = 3e8 # unit of c : m * s^-1
def ... | 66 |
import math
import tensorflow as tf
from packaging import version
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] ):
'''simple docstring'''
lowerCamelCase = tf.convert_to_tensor(lowerCamelCase__ )
lowerCamelCase = 0.5 * (1.0 + tf.math.... | 66 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : Union[str, Any] = {
"uclanlp/visualbert-vqa": "https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json",
"uclanlp... | 66 |
def __lowerCamelCase ( lowerCamelCase__ : Any ):
'''simple docstring'''
lowerCamelCase = [0] * len(lowerCamelCase__ )
lowerCamelCase = []
lowerCamelCase = []
lowerCamelCase = 0
for values in graph.values():
f... | 66 | 1 |
import math
import tensorflow as tf
from packaging import version
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] ):
'''simple docstring'''
lowerCamelCase = tf.convert_to_tensor(lowerCamelCase__ )
lowerCamelCase = 0.5 * (1.0 + tf.math.... | 66 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __lowerCamelCase ( lowerCamelCase__ : List[Any] , lowerCamelCase__ : List[str] , lowerCamelCase__ : str ):
'''simple docstring'''
lowerCamelCase = 0... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : int = 100 ):
'''simple docstring'''
lowerCamelCase = (n * (n + 1) // 2) ** 2
lowerCamelCase = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(f"""{solution() ... | 66 |
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
Upper... | 66 | 1 |
def __lowerCamelCase ( ):
'''simple docstring'''
lowerCamelCase = []
lowerCamelCase = 1
while len(lowerCamelCase__ ) < 1E6:
constant.append(str(lowerCamelCase__ ) )
i += 1
lowerCamelCase = """""".join(lowerCamelCase__ ... | 66 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"... | 66 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vision... | 66 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
UpperCAmelCase : str = {
"text_branch": "text_model",
"audio_branch": "audio_model.audio_encoder",
"attn": "attention.self",
"self.proj": "output.de... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : float , lowerCamelCase__ : float ):
'''simple docstring'''
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 * mass * abs(lowerCamelCase__ ) * abs(lowerCamelCase__ )
... | 66 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice... | 66 | 1 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAmelCase : List[str] = {
"t5-small": "https://huggingface.co/t5-s... | 66 |
class __lowercase :
"""simple docstring"""
def __init__( self ) -> None:
'''simple docstring'''
lowerCamelCase = {} # Mapping from char to TrieNode
lowerCamelCase = False
def __A ( self , A ) -> ... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : int ):
'''simple docstring'''
lowerCamelCase = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def __lowerCamelCase ( lowerCamelCase__ : int = 5000 ):
'''simple docstring'''
lowerC... | 66 |
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
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmel... | 66 | 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_verbosi... | 66 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __lowercase ( pl.LightningModule ):
"""simple docstring"""
def __init__( self , A ) -> Any:
... | 66 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
logging.s... | 66 |
UpperCAmelCase : Tuple = "Tobias Carryer"
from time import time
class __lowercase :
"""simple docstring"""
def __init__( self , A , A , A , A=int(time() ) ) -> Optional[int]: # noqa: B008
'''simple docstring'''
... | 66 | 1 |
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
require_tf,
... | 66 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerc... | 66 | 1 |
import re
from filelock import FileLock
try:
import nltk
UpperCAmelCase : Tuple = True
except (ImportError, ModuleNotFoundError):
UpperCAmelCase : int = False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.download("punkt", quiet=True)
def __lowerCamelCase ... | 66 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Union[str, Any] = {
"configuration_mobilebert": [
"MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_M... | 66 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Tuple = {
"configuration_git": ["GIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GitConfig", "GitVisionConfig"],
"processing_git": ["GitProcessor"],
}
try:
if not is_to... | 66 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase : str =... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : str , lowerCamelCase__ : int ):
'''simple docstring'''
return [sentence[i : i + ngram_size] for i in range(len(lowerCamelCase__ ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest import testmod
testmo... | 66 |
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
UpperCAmelCase : Optional[Any] = logging.get_logger(... | 66 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
from diffusers.uti... | 66 |
def __lowerCamelCase ( ):
'''simple docstring'''
lowerCamelCase = []
lowerCamelCase = 1
while len(lowerCamelCase__ ) < 1E6:
constant.append(str(lowerCamelCase__ ) )
i += 1
lowerCamelCase = """""".join(lowerCamelCase__ ... | 66 | 1 |
from __future__ import annotations
def __lowerCamelCase ( lowerCamelCase__ : list[int] , lowerCamelCase__ : int ):
'''simple docstring'''
lowerCamelCase = 0
lowerCamelCase = len(lowerCamelCase__ ) - 1
while i < j:
if nu... | 66 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("""socket.socket""" )
@patch("""builtins.open""" )
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] , lowerCamelCase__ : Dict ):
'''simple docstring'''
low... | 66 | 1 |
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : Dict = r"\n Args:\n input_ids (`torch.L... | 66 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils impor... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : int = 100 ):
'''simple docstring'''
lowerCamelCase = n * (n + 1) * (2 * n + 1) / 6
lowerCamelCase = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __name__ == "__main__":
print(f... | 66 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : List[Any] = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/AltCLIP/resolve/main/conf... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : Any ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
lowerCamelCase = len(lowerCamelCase__ )
lowerCamelCase = max(lowerCamelCase__ )
low... | 66 |
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,
UN... | 66 | 1 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
... | 66 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Dict = logging.get_logger(__name__)
UpperCAmelCase : Any = {
"google/switch-base-8": "https://huggingface.co/google/switch-base-8/blob/main/config.json",
}
class __lowercase ( ... | 66 | 1 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def __lowerCamelCase ( lowerCamelCase__ : str , lowerCamelCase__ : str ):
'''simple docstring'''
lowerCamelCase = list(lowerCamelCase__ )
lowe... | 66 |
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
UpperCAmelCase : Optional[int] = logging.getLogger(__... | 66 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCAmelCase : int = {
"configuration_altclip": [
"ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"AltCLIPConfig",
"AltCLIPTextConfig",
... | 66 |
import math
import tensorflow as tf
from packaging import version
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] ):
'''simple docstring'''
lowerCamelCase = tf.convert_to_tensor(lowerCamelCase__ )
lowerCamelCase = 0.5 * (1.0 + tf.math.... | 66 | 1 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenizer... | 66 |
def __lowerCamelCase ( lowerCamelCase__ : Any ):
'''simple docstring'''
lowerCamelCase = [0] * len(lowerCamelCase__ )
lowerCamelCase = []
lowerCamelCase = []
lowerCamelCase = 0
for values in graph.values():
f... | 66 | 1 |
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastapi.routing import APIRoute
... | 66 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __lowerCamelCase ( lowerCamelCase__ : List[Any] , lowerCamelCase__ : List[str] , lowerCamelCase__ : str ):
'''simple docstring'''
lowerCamelCase = 0... | 66 | 1 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def __lowerCamelCase ( lowerCamelCase__ : Tuple , lowerCamelCas... | 66 |
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
Upper... | 66 | 1 |
from math import factorial
def __lowerCamelCase ( lowerCamelCase__ : int = 20 ):
'''simple docstring'''
lowerCamelCase = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
lowerCamelCase = n // 2
return... | 66 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"... | 66 | 1 |
from scipy.stats import pearsonr
import datasets
UpperCAmelCase : str = "\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption that ea... | 66 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
UpperCAmelCase : str = {
"text_branch": "text_model",
"audio_branch": "audio_model.audio_encoder",
"attn": "attention.self",
"self.proj": "output.de... | 66 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAmelCase : Optional[Any] = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-... | 66 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice... | 66 | 1 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
UpperCAmelCase : str = {
"text_branch": "text_model",
"audio_branch": "audio_model.audio_encoder",
"attn": "attention.self",
"self.proj": "output.de... | 66 |
class __lowercase :
"""simple docstring"""
def __init__( self ) -> None:
'''simple docstring'''
lowerCamelCase = {} # Mapping from char to TrieNode
lowerCamelCase = False
def __A ( self , A ) -> ... | 66 | 1 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def __lowerCamelCase ( lowerCamelCase__ : dict ):
'... | 66 |
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
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmel... | 66 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Union[str, Any] = {
"configuration_mobilebert": [
"MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_M... | 66 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __lowercase ( pl.LightningModule ):
"""simple docstring"""
def __init__( self , A ) -> Any:
... | 66 | 1 |
UpperCAmelCase : List[Any] = [0, 2, 4, 6, 8]
UpperCAmelCase : Optional[Any] = [1, 3, 5, 7, 9]
def __lowerCamelCase ( lowerCamelCase__ : int , lowerCamelCase__ : int , lowerCamelCase__ : list[int] , lowerCamelCase__ : int ):
... | 66 |
UpperCAmelCase : Tuple = "Tobias Carryer"
from time import time
class __lowercase :
"""simple docstring"""
def __init__( self , A , A , A , A=int(time() ) ) -> Optional[int]: # noqa: B008
'''simple docstring'''
... | 66 | 1 |
from __future__ import annotations
import numpy as np
def __lowerCamelCase ( lowerCamelCase__ : list[float] ):
'''simple docstring'''
return np.maximum(0 , lowerCamelCase__ )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 66 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerc... | 66 | 1 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def __lowerCamelCase ( lowerCamelCase__ : Namespace ):
'''simple docstring'''
return ConvertCommand(
args.model_type , args.tf_checkpoint ... | 66 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Union[str, Any] = {
"configuration_mobilebert": [
"MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_M... | 66 | 1 |
from jiwer import compute_measures
import datasets
UpperCAmelCase : Optional[int] = "\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL to MER and WIL: improved evalu... | 66 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase : str =... | 66 | 1 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
def __lowerCamelCase ( lowerCamelCase__ : Any ):
... | 66 |
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
UpperCAmelCase : Optional[Any] = logging.get_logger(... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : int , lowerCamelCase__ : int ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
lowerCamelCase = str(bin(lowerCamelCase__ ) )[2:] ... | 66 |
def __lowerCamelCase ( ):
'''simple docstring'''
lowerCamelCase = []
lowerCamelCase = 1
while len(lowerCamelCase__ ) < 1E6:
constant.append(str(lowerCamelCase__ ) )
i += 1
lowerCamelCase = """""".join(lowerCamelCase__ ... | 66 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Union[str, Any] = {"configuration_reformer": ["REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "R... | 66 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("""socket.socket""" )
@patch("""builtins.open""" )
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] , lowerCamelCase__ : Dict ):
'''simple docstring'''
low... | 66 | 1 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class __lowercase :
"""simple docstring"""
UpperCamelCase : torch.Tensor # [batch_size x 3]
UpperCamelCase : torch.Tensor # [batch_size x 3]
UpperCamelCase : torch.Ten... | 66 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils impor... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : int , lowerCamelCase__ : int ):
'''simple docstring'''
return 1 if input_a == input_a else 0
def __lowerCamelCase ( ):
'''simple docstring'''
assert xnor_gate(0 , 0 ) == 1
assert x... | 66 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : List[Any] = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/AltCLIP/resolve/main/conf... | 66 | 1 |
import re
def __lowerCamelCase ( lowerCamelCase__ : str ):
'''simple docstring'''
lowerCamelCase = re.compile(
R"""^(?:0|94|\+94|0{2}94)""" R"""7(0|1|2|4|5|6|7|8)""" R"""(-| |)""" R"""\d{7}$""" )
return bool(re.search(lowerCamelCase__ , low... | 66 |
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,
UN... | 66 | 1 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCAmelCase : Tuple = "\\n@misc{chen2021evaluating,\n title={Evaluating Large Langu... | 66 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Dict = logging.get_logger(__name__)
UpperCAmelCase : Any = {
"google/switch-base-8": "https://huggingface.co/google/switch-base-8/blob/main/config.json",
}
class __lowercase ( ... | 66 | 1 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def __lowerCamelCase ( ):
'''simple docstring'''
lowerCamelCase , lowerCamelCase = 9, 14 # noqa: F841
lowerCamelCase = [
[0, 1, 4],
... | 66 |
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
UpperCAmelCase : Optional[int] = logging.getLogger(__... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : int , lowerCamelCase__ : int ):
'''simple docstring'''
if number < 0 or shift_amount < 0:
raise ValueError("""both inputs must be positive integers""" )
lowerCamelCase = str(bin(lowerCamelCase__ ... | 66 |
import math
import tensorflow as tf
from packaging import version
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] ):
'''simple docstring'''
lowerCamelCase = tf.convert_to_tensor(lowerCamelCase__ )
lowerCamelCase = 0.5 * (1.0 + tf.math.... | 66 | 1 |
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
clas... | 66 |
def __lowerCamelCase ( lowerCamelCase__ : Any ):
'''simple docstring'''
lowerCamelCase = [0] * len(lowerCamelCase__ )
lowerCamelCase = []
lowerCamelCase = []
lowerCamelCase = 0
for values in graph.values():
f... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : str ):
'''simple docstring'''
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(lowerCamelCase__ ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__("doctest").testmod()
| 66 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __lowerCamelCase ( lowerCamelCase__ : List[Any] , lowerCamelCase__ : List[str] , lowerCamelCase__ : str ):
'''simple docstring'''
lowerCamelCase = 0... | 66 | 1 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
UpperCAmelCase : List[str] = Lock()
def __lowerCamelCase ( lowerCamelCase__ : List[Any] , lowerCamelCase__ : Union[str, Any] , lowerC... | 66 |
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
Upper... | 66 | 1 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
UpperCAmelCase : List[str] = {
"configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJapaneseConfig"],
"tokeniz... | 66 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"... | 66 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
UpperCAmelCase : int = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the referenc... | 66 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
UpperCAmelCase : str = {
"text_branch": "text_model",
"audio_branch": "audio_model.audio_encoder",
"attn": "attention.self",
"self.proj": "output.de... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : list[list[int | float]] ):
'''simple docstring'''
lowerCamelCase = len(lowerCamelCase__ )
lowerCamelCase = len(matrix[0] )
lowerCamelCase = min(lowerCamelCase__ , lowerCamelCase__... | 66 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice... | 66 | 1 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIFICATIO... | 66 |
class __lowercase :
"""simple docstring"""
def __init__( self ) -> None:
'''simple docstring'''
lowerCamelCase = {} # Mapping from char to TrieNode
lowerCamelCase = False
def __A ( self , A ) -> ... | 66 | 1 |
from graphs.minimum_spanning_tree_kruskal import kruskal
def __lowerCamelCase ( ):
'''simple docstring'''
lowerCamelCase = 9
lowerCamelCase = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, 6, 1],
[2, 8, 2],
... | 66 |
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
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmel... | 66 | 1 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __lowerCamelCase ( lowerCamelCase__ : List[Any] , lowerCamelCase__ : List[str] , lowerCamelCase__ : str ):
'''simple docstring'''
lowerCamelCase = 0... | 66 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __lowercase ( pl.LightningModule ):
"""simple docstring"""
def __init__( self , A ) -> Any:
... | 66 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Dict = logging.get_logger(__name__)
UpperCAmelCase : Optional[int] = {
"BridgeTower/bridgetower-base": "https://huggingface.co/BridgeTower/bri... | 66 |
UpperCAmelCase : Tuple = "Tobias Carryer"
from time import time
class __lowercase :
"""simple docstring"""
def __init__( self , A , A , A , A=int(time() ) ) -> Optional[int]: # noqa: B008
'''simple docstring'''
... | 66 | 1 |
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class __lowercase :
"""simple docstring"""
pass
| 66 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerc... | 66 | 1 |
import operator as op
def __lowerCamelCase ( lowerCamelCase__ : Optional[int] ):
'''simple docstring'''
lowerCamelCase = []
lowerCamelCase = lambda lowerCamelCase__ , lowerCamelCase__ : int(x / y ) # noqa: E731 integer division op... | 66 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Union[str, Any] = {
"configuration_mobilebert": [
"MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_M... | 66 | 1 |
def __lowerCamelCase ( lowerCamelCase__ : int , lowerCamelCase__ : int ):
'''simple docstring'''
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowerCamelCase__ , int(b / 2 ) ) * actual_power(lowerCamelCase__ , int(b ... | 66 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase : str =... | 66 | 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 logging
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAm... | 66 |
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
UpperCAmelCase : Optional[Any] = logging.get_logger(... | 66 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : int = {
"speechbrain/m-ctc-t-large": "https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json",
# See all M-... | 66 |
def __lowerCamelCase ( ):
'''simple docstring'''
lowerCamelCase = []
lowerCamelCase = 1
while len(lowerCamelCase__ ) < 1E6:
constant.append(str(lowerCamelCase__ ) )
i += 1
lowerCamelCase = """""".join(lowerCamelCase__ ... | 66 | 1 |
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp_space_optuna,
default_... | 66 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("""socket.socket""" )
@patch("""builtins.open""" )
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] , lowerCamelCase__ : Dict ):
'''simple docstring'''
low... | 66 | 1 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
UpperCAmelCase : Tuple = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=None, type=str, required=True, help="Path ... | 66 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils impor... | 66 | 1 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("""socket.socket""" )
@patch("""builtins.open""" )
def __lowerCamelCase ( lowerCamelCase__ : Optional[Any] , lowerCamelCase__ : Dict ):
'''simple docstring'''
low... | 66 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : List[Any] = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/AltCLIP/resolve/main/conf... | 66 | 1 |
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