code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
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 timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
... | 627 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 627 | 1 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
__SCREAMING_SNAKE_CASE = n - k
# Calculate C(n,k)
for i in range(a__ ):
... | 627 |
'''simple docstring'''
# 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
#
# ... | 627 | 1 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
return number | (1 << position)
def a__ ( a__ , a__ ):
"""simple docstring"""
return number & ~(1 << position)
def a__ ( a__ , a__ ):
"""simple docst... | 627 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fro... | 627 | 1 |
'''simple docstring'''
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = [
"""decoder.version""",
"""decoder.o... | 627 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 627 | 1 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tok... | 627 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowerCAmelCase__ ( a , a ):
"""simple docstring"""
@register_to_config
de... | 627 | 1 |
'''simple docstring'''
import math
def a__ ( a__ ):
"""simple docstring"""
return math.sqrt(a__ ) * math.sqrt(a__ ) == num
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = n
while left <= ... | 627 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)... | 627 | 1 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
UpperCAmelCase : Optiona... | 627 |
'''simple docstring'''
import math
def a__ ( a__ ):
"""simple docstring"""
return math.sqrt(a__ ) * math.sqrt(a__ ) == num
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = n
while left <= ... | 627 | 1 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE = np.shape(a__ )
if rows != columns:
__SCREAMING_SNAKE_CASE = (
"""'table... | 627 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase : Any = 'src/transformers'
# This is to make sure the transfo... | 627 | 1 |
'''simple docstring'''
# 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
#
# ... | 627 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {}
__SCREAM... | 627 | 1 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Tokeni... | 627 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 627 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfi... | 627 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = math.sqrt(a__ )
__SCREAMING_SNAKE_CASE = 1 / (sigma * math.sqrt(2 * math.pi ))
return cons * np.exp(-((img /... | 627 | 1 |
'''simple docstring'''
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCAmelCase : str = '.'
# Internal... | 627 |
'''simple docstring'''
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if v... | 627 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
UpperCAmelCa... | 627 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfi... | 627 | 1 |
'''simple docstring'''
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_... | 627 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main... | 627 | 1 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
UpperCAmelCase : List[str] = '\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding... | 627 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittes... | 627 | 1 |
'''simple docstring'''
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def a__ ( a__ , a__ , a__ , a__=5 ):
"""simple docstring"""
assert masked_input.count("""<mask>""" ) == 1
__SCREAMING_SNAKE_CASE = torch.tensor(tokenize... | 627 |
'''simple docstring'''
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 lowerCAmelCase__ ( ... | 627 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
UpperCAmelCase : Optional[Any] = {
'google/tapas-base-finetuned-sqa': (
'https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'
),
'google/tapas-base-finetuned-wtq': (
'htt... | 627 |
'''simple docstring'''
UpperCAmelCase : Tuple = range(2, 2_0 + 1)
UpperCAmelCase : int = [1_0**k for k in range(ks[-1] + 1)]
UpperCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def a__ ( a__ , a__ , a__ , a__ ):
"""simple docstri... | 627 | 1 |
'''simple docstring'''
UpperCAmelCase : int = '0.21.0'
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader im... | 627 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 627 | 1 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : Optional[Any] , __SCREAMING_SNAKE_CASE : Union[str, Any] , __SCREAMING_SNAKE_CASE : List[str] , __SCREAMING_SNAKE_CASE : Dict ) -> List[str]:
"""simple docst... | 627 |
'''simple docstring'''
from math import isqrt
def a__ ( a__ ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(a__ ) + 1 ) )
def a__ ( a__ = 10**6 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
... | 627 | 1 |
'''simple docstring'''
import math
def a__ ( a__ = 1_00 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = sum(i * i for i in range(1 , n + 1 ) )
__SCREAMING_SNAKE_CASE = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return square_of_sum - s... | 627 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Any = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowerCAmelCase__ ( a ):
... | 627 | 1 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 627 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 627 | 1 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class lowerCAmelCase__ ( a ):
"""simple docstring"""... | 627 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase__ ( a ):
"""simple docstring"""
lowerCAmelCase__ = ["image_processor", "tokenizer"]
lowerCAmelCase__ = "CLIPImageProcesso... | 627 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 627 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 627 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def a__ ( a__ , a__ ):
"""simple docstring"""
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(a__ , a__ ) ) )
def a__ ( a_... | 627 |
'''simple docstring'''
# 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
#
# ... | 627 | 1 |
'''simple docstring'''
def a__ ( a__ ): # noqa: E741
"""simple docstring"""
__SCREAMING_SNAKE_CASE = len(a__ )
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = [0] * n
__SCREAMING_SNAKE_CASE = [False] * n
__SCREAMING_SNAKE_CASE = [False] * n... | 627 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fro... | 627 | 1 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase : Any = 'src/transformers'
# This is to make sure the transfo... | 627 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 627 | 1 |
'''simple docstring'''
import math
class lowerCAmelCase__ :
"""simple docstring"""
def UpperCAmelCase__ ( self : List[Any] , __SCREAMING_SNAKE_CASE : list[list[float]] , __SCREAMING_SNAKE_CASE : list[int] ) -> int:
"""simple docstring"""
... | 627 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowerCAmelCase__ ( a , a ):
"""simple docstring"""
@register_to_config
de... | 627 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.traini... | 627 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)... | 627 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(a ) ,... | 627 |
'''simple docstring'''
import math
def a__ ( a__ ):
"""simple docstring"""
return math.sqrt(a__ ) * math.sqrt(a__ ) == num
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = n
while left <= ... | 627 | 1 |
'''simple docstring'''
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... | 627 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase : Any = 'src/transformers'
# This is to make sure the transfo... | 627 | 1 |
'''simple docstring'''
import sys
UpperCAmelCase : Any = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'6689664895... | 627 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {}
__SCREAM... | 627 | 1 |
'''simple docstring'''
from collections.abc import Callable
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : int , __SCREAMING_SNAKE_CASE : Callable | None = None ) -> None:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = []
... | 627 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 627 | 1 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
return int((input_a, input_a).count(0 ) == 0 )
def a__ ( ):
"""simple docstring"""
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 ,... | 627 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = math.sqrt(a__ )
__SCREAMING_SNAKE_CASE = 1 / (sigma * math.sqrt(2 * math.pi ))
return cons * np.exp(-((img /... | 627 | 1 |
'''simple docstring'''
def a__ ( a__ = 10_00 ):
"""simple docstring"""
return sum(e for e in range(3 , a__ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f"""{solution() = }""")
| 627 |
'''simple docstring'''
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if v... | 627 | 1 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase__ ( a ):
"""simple docstring"""
lowerCAmelCase__ = ["image_processor", "tokenizer"]
lowerCAmelCase__ = "AutoImageProcessor"
lowerCAmelCas... | 627 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfi... | 627 | 1 |
'''simple docstring'''
from collections.abc import Sequence
from queue import Queue
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : Union[str, Any] , __SCREAMING_SNAKE_CASE : str , __SCREAMING_SNAKE_CASE : List[str] , __SCREAMING_SNAKE_CASE :... | 627 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main... | 627 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProc... | 627 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittes... | 627 | 1 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
UpperCAmelCase : int = '\\n@inproceedings{snover-etal-2006-study,\n title = "A Study of Translation Edit Rate with Targeted Human Annotation",\n author = "Snover, Matthew and... | 627 |
'''simple docstring'''
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 lowerCAmelCase__ ( ... | 627 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmel... | 627 |
'''simple docstring'''
UpperCAmelCase : Tuple = range(2, 2_0 + 1)
UpperCAmelCase : int = [1_0**k for k in range(ks[-1] + 1)]
UpperCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def a__ ( a__ , a__ , a__ , a__ ):
"""simple docstri... | 627 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
... | 627 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 627 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_s... | 627 |
'''simple docstring'''
from math import isqrt
def a__ ( a__ ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(a__ ) + 1 ) )
def a__ ( a__ = 10**6 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
... | 627 | 1 |
'''simple docstring'''
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = current_set.copy()
for row_index, row in enumerate(a__ ):
__SCREAMING_SNAKE_CASE = row[0]
for column_index, column in enumerate(a__ ):
if magnitude == ... | 627 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Any = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowerCAmelCase__ ( a ):
... | 627 | 1 |
'''simple docstring'''
from math import isqrt, loga
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , a__ , ... | 627 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 627 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_inputs
if is_torch_ava... | 627 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase__ ( a ):
"""simple docstring"""
lowerCAmelCase__ = ["image_processor", "tokenizer"]
lowerCAmelCase__ = "CLIPImageProcesso... | 627 | 1 |
'''simple docstring'''
import requests
UpperCAmelCase : Dict = 'YOUR API KEY'
def a__ ( a__ , a__ = giphy_api_key ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = """+""".join(query.split() )
__SCREAMING_SNAKE_CASE = F'https://api.giphy.com/v1/gif... | 627 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 627 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase__ ( a ):
"""simple docstring"""
lowerCAmelCase__ = ["image_processor", "tokenizer"]
lowerCAmelCase__ = "CLIPImageProcesso... | 627 |
'''simple docstring'''
# 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
#
# ... | 627 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS... | 627 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fro... | 627 | 1 |
'''simple docstring'''
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(2_7))
print(perfect_cube(4))
| 627 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 627 | 1 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_availabl... | 627 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowerCAmelCase__ ( a , a ):
"""simple docstring"""
@register_to_config
de... | 627 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
... | 627 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)... | 627 | 1 |
'''simple docstring'''
from __future__ import annotations
import requests
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = F'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
return requests.get(a__ ).json()
def a__ ( a... | 627 |
'''simple docstring'''
import math
def a__ ( a__ ):
"""simple docstring"""
return math.sqrt(a__ ) * math.sqrt(a__ ) == num
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = n
while left <= ... | 627 | 1 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
UpperCAmelCas... | 627 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase : Any = 'src/transformers'
# This is to make sure the transfo... | 627 | 1 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def a__ ( a__ , a__ , a__ , a__ , a__ , a__ , a__ , a__ , a__ , ):
"""simple docstring"""
for nxt, d in graph[v]:
if nxt in... | 627 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {}
__SCREAM... | 627 | 1 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from... | 627 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 627 | 1 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 627 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = math.sqrt(a__ )
__SCREAMING_SNAKE_CASE = 1 / (sigma * math.sqrt(2 * math.pi ))
return cons * np.exp(-((img /... | 627 | 1 |
'''simple docstring'''
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
UpperCAmelCase : int = Mapping[str, np.ndarray]
UpperCAmelCase : int = Mapping[str, Any] ... | 627 |
'''simple docstring'''
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if v... | 627 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json... | 627 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfi... | 627 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import D... | 627 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main... | 627 | 1 |
'''simple docstring'''
import numpy as np
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : Any ) -> List[str]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = (0, 0)
__SCREAMING_SNAKE_CASE = None
__SCREAMING_SNAKE_CAS... | 627 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittes... | 627 | 1 |
'''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
UpperCAmelCase : int = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
'... | 627 |
'''simple docstring'''
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 lowerCAmelCase__ ( ... | 627 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
UpperCAmelCase : Tuple = TypeVar('T')
class lowerCAmelCase__ ( Generic[T] ):
"""simple docstring"""
def __init__( self : Tuple , __SCREA... | 627 |
'''simple docstring'''
UpperCAmelCase : Tuple = range(2, 2_0 + 1)
UpperCAmelCase : int = [1_0**k for k in range(ks[-1] + 1)]
UpperCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def a__ ( a__ , a__ , a__ , a__ ):
"""simple docstri... | 627 | 1 |
'''simple docstring'''
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse('3.8'):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
UpperCAmelCa... | 627 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 627 | 1 |
'''simple docstring'''
import cmath
import math
def a__ ( a__ , a__ , a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = math.radians(a__ )
__SCREAMING_SNAKE_CASE = math.radians(a__ )
# Convert voltage and current to rectangular form... | 627 |
'''simple docstring'''
from math import isqrt
def a__ ( a__ ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(a__ ) + 1 ) )
def a__ ( a__ = 10**6 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
... | 627 | 1 |
'''simple docstring'''
def a__ ( a__ , a__ , a__ ):
"""simple docstring"""
if principal <= 0:
raise Exception("""Principal borrowed must be > 0""" )
if rate_per_annum < 0:
raise Exception("""Rate of interest must be >= 0""" )
if years_to_repay <= ... | 627 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Any = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowerCAmelCase__ ( a ):
... | 627 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : int = logging.get_logger(__name__)
class lowerCAmelCase__ ( a ):
"""simple docstring"""
def __init__( self : Optional[Any]... | 627 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 627 | 1 |
'''simple docstring'''
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 DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils imp... | 627 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase__ ( a ):
"""simple docstring"""
lowerCAmelCase__ = ["image_processor", "tokenizer"]
lowerCAmelCase__ = "CLIPImageProcesso... | 627 | 1 |
'''simple docstring'''
from __future__ import annotations
UpperCAmelCase : Tuple = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def a__ ( a__ , a__ , a__ , a__ , a__ , ):
"""simple docstring"""
__SCREAM... | 627 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 627 | 1 |
'''simple docstring'''
# 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
#
# ... | 627 |
'''simple docstring'''
# 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
#
# ... | 627 | 1 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"""kwargs, expected""" , [
({"""num_shards""": 0, """max_num_jobs""": 1}, []),
({"""num_shards""": 10, """max_n... | 627 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fro... | 627 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common... | 627 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 627 | 1 |
'''simple docstring'''
from math import sqrt
def a__ ( a__ = 1_00_00_00 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for ... | 627 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowerCAmelCase__ ( a , a ):
"""simple docstring"""
@register_to_config
de... | 627 | 1 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowerCAmelCase__ ( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCas... | 627 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)... | 627 | 1 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fro... | 627 |
'''simple docstring'''
import math
def a__ ( a__ ):
"""simple docstring"""
return math.sqrt(a__ ) * math.sqrt(a__ ) == num
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = n
while left <= ... | 627 | 1 |
'''simple docstring'''
import argparse
UpperCAmelCase : Optional[int] = 'docs/source/_static/js/custom.js'
def a__ ( a__ ):
"""simple docstring"""
with open(a__ , encoding="""utf-8""" , newline="""\n""" ) as f:
__SCREAMING_SNAKE_CASE = f.read... | 627 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase : Any = 'src/transformers'
# This is to make sure the transfo... | 627 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
UpperCAmelCase : Optional[int] = loggi... | 627 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {}
__SCREAM... | 627 | 1 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def a__ ( a__ , a__ ... | 627 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 627 | 1 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
UpperCAmelCase : Optional[Any] = parse(importlib.metadata.version('torch'))
def a__ ( a__ , a__ , a__ ):
... | 627 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = math.sqrt(a__ )
__SCREAMING_SNAKE_CASE = 1 / (sigma * math.sqrt(2 * math.pi ))
return cons * np.exp(-((img /... | 627 | 1 |
'''simple docstring'''
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 OptionalDependencyNotAvai... | 627 |
'''simple docstring'''
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if v... | 627 | 1 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFA... | 627 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfi... | 627 | 1 |
'''simple docstring'''
import math
import qiskit
def a__ ( a__ = 1 , a__ = 1 , a__ = 1 ):
"""simple docstring"""
if (
isinstance(a__ , a__ )
or isinstance(a__ , a__ )
or isinstance(a__ , a__ )
):
raise TypeEr... | 627 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main... | 627 | 1 |
'''simple docstring'''
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compu... | 627 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittes... | 627 | 1 |
'''simple docstring'''
def a__ ( a__ = 50 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
... | 627 |
'''simple docstring'''
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 lowerCAmelCase__ ( ... | 627 | 1 |
'''simple docstring'''
from string import ascii_uppercase
UpperCAmelCase : Dict = {str(ord(c) - 5_5): c for c in ascii_uppercase}
def a__ ( a__ , a__ ):
"""simple docstring"""
if isinstance(a__ , a__ ):
raise TypeError("""int() can't convert non-st... | 627 |
'''simple docstring'''
UpperCAmelCase : Tuple = range(2, 2_0 + 1)
UpperCAmelCase : int = [1_0**k for k in range(ks[-1] + 1)]
UpperCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def a__ ( a__ , a__ , a__ , a__ ):
"""simple docstri... | 627 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Any = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowerCAmelCase__ ( a ):
... | 627 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 627 | 1 |
'''simple docstring'''
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class lowerCAmelCase__ ( unittest.TestCase ):
"""simple docstring"""
lowerCAmelCase__ = JukeboxTokenizer
lowerCAmelCase__ = {
"artist": "Zac B... | 627 |
'''simple docstring'''
from math import isqrt
def a__ ( a__ ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(a__ ) + 1 ) )
def a__ ( a__ = 10**6 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
... | 627 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 627 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Any = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowerCAmelCase__ ( a ):
... | 627 | 1 |
'''simple docstring'''
import random
def a__ ( a__ , a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = a[left_index]
__SCREAMING_SNAKE_CASE = left_index + 1
for j in range(left_index + 1 , a__ ):
if a[j] < pivot:
... | 627 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 627 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperC... | 627 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase__ ( a ):
"""simple docstring"""
lowerCAmelCase__ = ["image_processor", "tokenizer"]
lowerCAmelCase__ = "CLIPImageProcesso... | 627 | 1 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def a__ ( ):
"""simple docstring"""
print("""Making key files...""" )
make_key_files("""rsa""" , 1... | 627 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 627 | 1 |
'''simple docstring'''
def a__ ( a__ , a__ = " " ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = []
__SCREAMING_SNAKE_CASE = 0
for index, char in enumerate(a__ ):
if char == separator:
split_words.append(string[last_index:index] )
... | 627 |
'''simple docstring'''
# 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
#
# ... | 627 | 1 |
'''simple docstring'''
import comet # From: unbabel-comet
import torch
import datasets
UpperCAmelCase : Dict = datasets.logging.get_logger(__name__)
UpperCAmelCase : List[str] = '\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana ... | 627 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fro... | 627 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Tuple = {
'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'],
'feature_extraction_mctct': ['MCTCTFeatureEx... | 627 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 627 | 1 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
UpperCAmelCase : int = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
UpperCAmelCase : List... | 627 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowerCAmelCase__ ( a , a ):
"""simple docstring"""
@register_to_config
de... | 627 | 1 |
'''simple docstring'''
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class lowerCAmelCase__ ( a , a ):
"""simple docs... | 627 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)... | 627 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channe... | 627 |
'''simple docstring'''
import math
def a__ ( a__ ):
"""simple docstring"""
return math.sqrt(a__ ) * math.sqrt(a__ ) == num
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = n
while left <= ... | 627 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Tuple = [
['a... | 627 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase : Any = 'src/transformers'
# This is to make sure the transfo... | 627 | 1 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {}
__SCREAM... | 627 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {}
__SCREAM... | 627 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common i... | 627 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 627 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
... | 627 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = math.sqrt(a__ )
__SCREAMING_SNAKE_CASE = 1 / (sigma * math.sqrt(2 * math.pi ))
return cons * np.exp(-((img /... | 627 | 1 |
'''simple docstring'''
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessin... | 627 |
'''simple docstring'''
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if v... | 627 | 1 |
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