code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase = {
"""configuration_xlm_roberta_xl""": [
"""XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XLMRobertaXLConfig""",
"""XLMRobertaXLOnnx... | 70 | import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class UpperCAmelCase ( tf.keras.optimizers.schedules.LearningRateSchedule ):
... | 70 | 1 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_... | 70 | from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
BertCo... | 70 | 1 |
from __future__ import annotations
import numpy as np
def UpperCamelCase ( __lowercase : list[float] ):
'''simple docstring'''
return np.maximum(0 ,__lowercase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 70 | def UpperCamelCase ( __lowercase : str ):
'''simple docstring'''
A_ : int = len(__lowercase )
A_ : List[Any] = sum(__lowercase )
A_ : List[str] = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(... | 70 | 1 |
def UpperCamelCase ( __lowercase : str ):
'''simple docstring'''
A_ : Union[str, Any] = hex_num.strip()
if not hex_num:
raise ValueError('No value was passed to the function' )
A_ : List[Any] = hex_num[0] == '-'
if is_negative:
A_ : ... | 70 | import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class UpperCAmelCase ( unittest.TestCase ... | 70 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json""",
... | 70 | from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOut... | 70 | 1 |
from PIL import Image
def UpperCamelCase ( __lowercase : Image ):
'''simple docstring'''
A_ , A_ : Any = image.size
A_ : str = 0
A_ : Union[str, Any] = image.load()
for i in range(__lowercase ):
for j in ra... | 70 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCAmelCase = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""tokenization_biogpt""": ["""BioGptT... | 70 | 1 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOut... | 70 | def UpperCamelCase ( __lowercase : list ):
'''simple docstring'''
A_ : str = len(__lowercase )
for _ in range(__lowercase ):
for i in range(_ % 2 ,arr_size - 1 ,2 ):
if arr[i + 1] < arr[i]:
A_ , A_ : Optional[Any] = a... | 70 | 1 |
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
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 (
... | 70 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json""",
... | 70 | 1 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def UpperCamelCase ( __lowercase : Dict ,__lowercase : List[Any]=() ,__lowercase : List[Any]=None ,__lowe... | 70 | import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.uti... | 70 | 1 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
_UpperCAmelCase = False
class UpperCAmelCase ( unittest.TestCase ):
'''simple docst... | 70 | def UpperCamelCase ( __lowercase : str ,__lowercase : int ):
'''simple docstring'''
A_ : int = word.split()
def justify(__lowercase : list ,__lowercase : int ,__lowercase : int ) -> str:
A_ : Optional[Any] = max_width - width... | 70 | 1 |
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class UpperCAmelCase ( ... | 70 | import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback... | 70 | 1 |
def UpperCamelCase ( __lowercase : int ,__lowercase : int ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
A_ : Tuple = str(bin(__lowercase ) )[2:] # remove the leading "0b"
A_ : Union[s... | 70 | 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_available
from ...test_co... | 70 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"""unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json""",
}
class UpperC... | 70 | def UpperCamelCase ( __lowercase : Optional[Any] ,__lowercase : Dict ):
'''simple docstring'''
A_ : Optional[Any] = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def UpperCamelCase ( __lowercase : List[... | 70 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_big_bird i... | 70 | def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
if length <= 0 or not isinstance(__lowercase ,__lowercase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(__lowercase )]
if __name__ == "__main__":
print(h... | 70 | 1 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common imp... | 70 | from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def UpperCamelCase ( ):
'''simple docstring'''
A_ , A_ : Any = 9, 14 # noqa: F841
A_ : str = [
[0, 1, 4],
[0, 7, 8],
... | 70 | 1 |
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 U... | 70 | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 70 | 1 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokenizatio... | 70 | from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class UpperCAmelCase ( __A ):
'''simple docstring'''
... | 70 | 1 |
from maths.prime_check import is_prime
def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
if not isinstance(__lowercase ,__lowercase ):
A_ : List[Any] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(__lowercas... | 70 | import random
def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
A_ : Tuple = num - 1
A_ : Optional[Any] = 0
while s % 2 == 0:
A_ : Optional[int] = s // 2
t += 1
for _ in range(5 ):
A_ ... | 70 | 1 |
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
_UpperCAmelCase = """."""
if __name__ == "__main__":
_UpperCAmelCase = os.path.join(REPO_PATH, """utils/documentation_tests.txt""")
_Uppe... | 70 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCAmelCase = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxConfig"""],
"""tokenizat... | 70 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"""google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
"""google/fnet-large""": """https://hugging... | 70 | import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class UpperCAmelCase ( ... | 70 | 1 |
def UpperCamelCase ( __lowercase : list ):
'''simple docstring'''
A_ : str = len(__lowercase )
for _ in range(__lowercase ):
for i in range(_ % 2 ,arr_size - 1 ,2 ):
if arr[i + 1] < arr[i]:
A_ , A_ : Optional[Any] = a... | 70 | import numpy as np
_UpperCAmelCase = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x""", """y""", """z"""],
]
... | 70 | 1 |
def UpperCamelCase ( __lowercase : int ,__lowercase : Tuple ):
'''simple docstring'''
A_ : Any = (boundary[1] - boundary[0]) / steps
A_ : int = boundary[0]
A_ : Any = boundary[1]
A_ : Optional[Any] = make_p... | 70 | from math import sqrt
def UpperCamelCase ( __lowercase : int = 1_00_00_00 ):
'''simple docstring'''
A_ : int = 0
A_ : int = 0
A_ : int
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 ,... | 70 | 1 |
from math import ceil, sqrt
def UpperCamelCase ( __lowercase : int = 1_00_00_00 ):
'''simple docstring'''
A_ : Optional[int] = 0
for outer_width in range(3 ,(limit // 4) + 2 ):
if outer_width**2 > limit:
A_ : int = max(ceil(sqr... | 70 | import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class UpperCAmelCase ( tf.keras.optimizers.schedules.LearningRateSchedule ):
... | 70 | 1 |
from collections import defaultdict
from math import ceil, sqrt
def UpperCamelCase ( __lowercase : int = 1_00_00_00 ,__lowercase : int = 10 ):
'''simple docstring'''
A_ : defaultdict = defaultdict(__lowercase )
for outer_width in range(3 ,(t_limit // ... | 70 | from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
BertCo... | 70 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCAmelCase = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxConfig"""],
"""tokenizat... | 70 | def UpperCamelCase ( __lowercase : str ):
'''simple docstring'''
A_ : int = len(__lowercase )
A_ : List[Any] = sum(__lowercase )
A_ : List[str] = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(... | 70 | 1 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
_UpperCAmelCase ... | 70 | import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class UpperCAmelCase ( unittest.TestCase ... | 70 | 1 |
import csv
import tweepy
# Twitter API credentials
_UpperCAmelCase = """"""
_UpperCAmelCase = """"""
_UpperCAmelCase = """"""
_UpperCAmelCase = """"""
def UpperCamelCase ( __lowercase : str ):
'''simple docstring'''
A_ : Any = ... | 70 | from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOut... | 70 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 70 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCAmelCase = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""tokenization_biogpt""": ["""BioGptT... | 70 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCAmelCase = {
"""configuration_blenderbot_small""": [
"""BLENDERBOT_SM... | 70 | def UpperCamelCase ( __lowercase : list ):
'''simple docstring'''
A_ : str = len(__lowercase )
for _ in range(__lowercase ):
for i in range(_ % 2 ,arr_size - 1 ,2 ):
if arr[i + 1] < arr[i]:
A_ , A_ : Optional[Any] = a... | 70 | 1 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def UpperCamelCase ( ):
'''simple docstring'''
print('Making key files...' )
make_key_files('rsa' ,10_24 )
print('Key fil... | 70 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json""",
... | 70 | 1 |
import unittest
from transformers import XLMConfig, 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 ModelTesterMixin, ... | 70 | import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.uti... | 70 | 1 |
from sklearn.metrics import matthews_corrcoef
import datasets
_UpperCAmelCase = """
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It takes
into account true and fal... | 70 | def UpperCamelCase ( __lowercase : str ,__lowercase : int ):
'''simple docstring'''
A_ : int = word.split()
def justify(__lowercase : list ,__lowercase : int ,__lowercase : int ) -> str:
A_ : Optional[Any] = max_width - width... | 70 | 1 |
def UpperCamelCase ( __lowercase : float ,__lowercase : int ):
'''simple docstring'''
if digit_amount > 0:
return round(number - int(__lowercase ) ,__lowercase )
return number - int(__lowercase )
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(de... | 70 | import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback... | 70 | 1 |
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def UpperCamelCase ( __lowerca... | 70 | 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_available
from ...test_co... | 70 | 1 |
import random
class UpperCAmelCase :
'''simple docstring'''
@staticmethod
def lowerCAmelCase_ ( lowercase ):
"""simple docstring"""
A_ : Dict = [ord(lowercase ) for i in text]
A_ : Optional[int] ... | 70 | def UpperCamelCase ( __lowercase : Optional[Any] ,__lowercase : Dict ):
'''simple docstring'''
A_ : Optional[Any] = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def UpperCamelCase ( __lowercase : List[... | 70 | 1 |
from math import isqrt, loga
def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
A_ : Dict = [True] * max_number
for i in range(2 ,isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 ,__lowercase ,__lowercase ):
... | 70 | def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
if length <= 0 or not isinstance(__lowercase ,__lowercase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(__lowercase )]
if __name__ == "__main__":
print(h... | 70 | 1 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constan... | 70 | from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def UpperCamelCase ( ):
'''simple docstring'''
A_ , A_ : Any = 9, 14 # noqa: F841
A_ : str = [
[0, 1, 4],
[0, 7, 8],
... | 70 | 1 |
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class UpperCAmelCase ( unittest.TestCase... | 70 | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 70 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcessor,
BertTokenizer... | 70 | from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class UpperCAmelCase ( __A ):
'''simple docstring'''
... | 70 | 1 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_available():
import torch
... | 70 | import random
def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
A_ : Tuple = num - 1
A_ : Optional[Any] = 0
while s % 2 == 0:
A_ : Optional[int] = s // 2
t += 1
for _ in range(5 ):
A_ ... | 70 | 1 |
import math
import sys
def UpperCamelCase ( __lowercase : str ):
'''simple docstring'''
A_ : Optional[Any] = ''
try:
with open(__lowercase ,'rb' ) as binary_file:
A_ : int = binary_file.read()
for dat in data:
A_ : ... | 70 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCAmelCase = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxConfig"""],
"""tokenizat... | 70 | 1 |
def UpperCamelCase ( __lowercase : str ,__lowercase : bool = False ):
'''simple docstring'''
if not isinstance(__lowercase ,__lowercase ):
A_ : Union[str, Any] = f'''Expected string as input, found {type(__lowercase )}'''
raise ValueError(__lowercase )... | 70 | import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class UpperCAmelCase ( ... | 70 | 1 |
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def UpperCamelCase ( __lowercase : str ,__lowercase : float | Decimal ,__lowercase : float = 10**-10 ):
'''simple docstring'''
A_ : str ... | 70 | import numpy as np
_UpperCAmelCase = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x""", """y""", """z"""],
]
... | 70 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"""microsoft/swinv2-tiny-patch4-window8-256""": (
"""https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/confi... | 70 | from math import sqrt
def UpperCamelCase ( __lowercase : int = 1_00_00_00 ):
'''simple docstring'''
A_ : int = 0
A_ : int = 0
A_ : int
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 ,... | 70 | 1 |
_UpperCAmelCase = {
"""A""": """.-""", """B""": """-...""", """C""": """-.-.""", """D""": """-..""", """E""": """.""", """F""": """..-.""", """G""": """--.""",
"""H""": """....""", """I""": """..""", """J""": """.---""", """K""": """-.-""", """L""": """.-..""", """M""": """--""", """N""": """-.""",
... | 70 | import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class UpperCAmelCase ( tf.keras.optimizers.schedules.LearningRateSchedule ):
... | 70 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 70 | from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
BertCo... | 70 | 1 |
from __future__ import annotations
import pandas as pd
def UpperCamelCase ( __lowercase : list[int] ,__lowercase : list[int] ,__lowercase : int ):
'''simple docstring'''
A_ : Union[str, Any] = [0] * no_of_processes
A_ : Union[str, Any] ... | 70 | def UpperCamelCase ( __lowercase : str ):
'''simple docstring'''
A_ : int = len(__lowercase )
A_ : List[Any] = sum(__lowercase )
A_ : List[str] = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(... | 70 | 1 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError("""To use the rich extension, install rich with `pip install rich`""")
| 70 | import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class UpperCAmelCase ( unittest.TestCase ... | 70 | 1 |
_UpperCAmelCase = 8.314_4598
def UpperCamelCase ( __lowercase : float ,__lowercase : float ):
'''simple docstring'''
if temperature < 0:
raise Exception('Temperature cannot be less than 0 K' )
if molar_mass <= 0:
raise Exception('Molar mass cannot be less ... | 70 | from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOut... | 70 | 1 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def UpperCamelCase ( __lowercase : Union[str, Any] ,__lowercase : int ,__lowercase : List[Any] ):
'''simple docstring'''
A_ : Union[str, Any] = {
'en': 'Machine learnin... | 70 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCAmelCase = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""tokenization_biogpt""": ["""BioGptT... | 70 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_... | 70 | def UpperCamelCase ( __lowercase : list ):
'''simple docstring'''
A_ : str = len(__lowercase )
for _ in range(__lowercase ):
for i in range(_ % 2 ,arr_size - 1 ,2 ):
if arr[i + 1] < arr[i]:
A_ , A_ : Optional[Any] = a... | 70 | 1 |
def UpperCamelCase ( __lowercase : str ,__lowercase : int ):
'''simple docstring'''
A_ : int = word.split()
def justify(__lowercase : list ,__lowercase : int ,__lowercase : int ) -> str:
A_ : Optional[Any] = max_width - width... | 70 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json""",
... | 70 | 1 |
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
_UpperCAmelCase = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
""">""": operato... | 70 | import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.uti... | 70 | 1 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
_UpperCAmelCase = get_tests_di... | 70 | def UpperCamelCase ( __lowercase : str ,__lowercase : int ):
'''simple docstring'''
A_ : int = word.split()
def justify(__lowercase : list ,__lowercase : int ,__lowercase : int ) -> str:
A_ : Optional[Any] = max_width - width... | 70 | 1 |
# limitations under the License.
# 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 .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
d... | 70 | import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback... | 70 | 1 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_UpperCAmelCase = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("""3.7"""):
r... | 70 | 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_available
from ...test_co... | 70 | 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 timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import Bit... | 70 | def UpperCamelCase ( __lowercase : Optional[Any] ,__lowercase : Dict ):
'''simple docstring'''
A_ : Optional[Any] = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def UpperCamelCase ( __lowercase : List[... | 70 | 1 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase ( __A ):
'''simple docstring'''
lowerCamelCase_ = (KDPMaDiscreteScheduler,)
... | 70 | def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
if length <= 0 or not isinstance(__lowercase ,__lowercase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(__lowercase )]
if __name__ == "__main__":
print(h... | 70 | 1 |
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttention, ImageClassifierO... | 70 | from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def UpperCamelCase ( ):
'''simple docstring'''
A_ , A_ : Any = 9, 14 # noqa: F841
A_ : str = [
[0, 1, 4],
[0, 7, 8],
... | 70 | 1 |
_UpperCAmelCase = range(2, 20 + 1)
_UpperCAmelCase = [10**k for k in range(ks[-1] + 1)]
_UpperCAmelCase = {}
def UpperCamelCase ( __lowercase : List[Any] ,__lowercase : Union[str, Any] ,__lowercase : int ,__lowercase : str ):
'''simple docstring'''
... | 70 | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 70 | 1 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('socket.socket' )
@patch('builtins.open' )
def UpperCamelCase ( __lowercase : Any ,__lowercase : Any ):
'''simple docstring'''
A_ : Tuple = Mock()
A_ : ... | 70 | from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class UpperCAmelCase ( __A ):
'''simple docstring'''
... | 70 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class UpperCAmelCase ( unittest.TestCase ... | 70 | import random
def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
A_ : Tuple = num - 1
A_ : Optional[Any] = 0
while s % 2 == 0:
A_ : Optional[int] = s // 2
t += 1
for _ in range(5 ):
A_ ... | 70 | 1 |
def UpperCamelCase ( __lowercase : Optional[Any] ,__lowercase : Dict ):
'''simple docstring'''
A_ : Optional[Any] = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def UpperCamelCase ( __lowercase : List[... | 70 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCAmelCase = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxConfig"""],
"""tokenizat... | 70 | 1 |
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
_UpperCAmelCase = logging.get_logger(__name__)
class UpperCAmelCase ( __A ):
'''simple docstring'''
def __init__( self , *lowercase , **lowerc... | 70 | import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class UpperCAmelCase ( ... | 70 | 1 |
import random
def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
A_ : Tuple = num - 1
A_ : Optional[Any] = 0
while s % 2 == 0:
A_ : Optional[int] = s // 2
t += 1
for _ in range(5 ):
A_ ... | 70 | import numpy as np
_UpperCAmelCase = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x""", """y""", """z"""],
]
... | 70 | 1 |
def UpperCamelCase ( __lowercase : int ,__lowercase : int ,__lowercase : list[list[int]] ):
'''simple docstring'''
def update_area_of_max_square(__lowercase : int ,__lowercase : int ) -> int:
# BASE CASE
if row >= rows or col >= cols:
return 0
A_ ... | 70 | from math import sqrt
def UpperCamelCase ( __lowercase : int = 1_00_00_00 ):
'''simple docstring'''
A_ : int = 0
A_ : int = 0
A_ : int
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 ,... | 70 | 1 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
_U... | 70 | import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class UpperCAmelCase ( tf.keras.optimizers.schedules.LearningRateSchedule ):
... | 70 | 1 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceClassificatio... | 70 | from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
BertCo... | 70 | 1 |
from ...configuration_utils import PretrainedConfig
_UpperCAmelCase = {
"""google/tapas-base-finetuned-sqa""": (
"""https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
),
"""google/tapas-base-finetuned-wtq""": (
"""https://huggingface.co/google... | 70 | def UpperCamelCase ( __lowercase : str ):
'''simple docstring'''
A_ : int = len(__lowercase )
A_ : List[Any] = sum(__lowercase )
A_ : List[str] = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(... | 70 | 1 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelera... | 70 | import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class UpperCAmelCase ( unittest.TestCase ... | 70 | 1 |
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 = logging.get_logger(__name__)
_UpperCAmelCase = {
"""google/mo... | 70 | from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOut... | 70 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin
@flax.struct... | 70 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCAmelCase = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""tokenization_biogpt""": ["""BioGptT... | 70 | 1 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCAmelCase ( __A ):
'''simple docstring'''
lowerCamelCase_ = CustomTokenizer
pass
| 70 | def UpperCamelCase ( __lowercase : list ):
'''simple docstring'''
A_ : str = len(__lowercase )
for _ in range(__lowercase ):
for i in range(_ % 2 ,arr_size - 1 ,2 ):
if arr[i + 1] < arr[i]:
A_ , A_ : Optional[Any] = a... | 70 | 1 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = """htt... | 70 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json""",
... | 70 | 1 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_avail... | 70 | import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.uti... | 70 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"""microsoft/unispeech-large-1500h-cv""": (
"""https://huggingface.co/microsoft/unispeech-large-15... | 70 | def UpperCamelCase ( __lowercase : str ,__lowercase : int ):
'''simple docstring'''
A_ : int = word.split()
def justify(__lowercase : list ,__lowercase : int ,__lowercase : int ) -> str:
A_ : Optional[Any] = max_width - width... | 70 | 1 |
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since ... | 70 | import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback... | 70 | 1 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaTokenizer
else:... | 70 | 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_available
from ...test_co... | 70 | 1 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...... | 70 | def UpperCamelCase ( __lowercase : Optional[Any] ,__lowercase : Dict ):
'''simple docstring'''
A_ : Optional[Any] = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def UpperCamelCase ( __lowercase : List[... | 70 | 1 |
# flake8: noqa
# Lint as: python3
_UpperCAmelCase = [
"""VerificationMode""",
"""Version""",
"""disable_progress_bar""",
"""enable_progress_bar""",
"""is_progress_bar_enabled""",
"""experimental""",
]
from .info_utils import VerificationMode
from .logging import disable_progr... | 70 | def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
if length <= 0 or not isinstance(__lowercase ,__lowercase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(__lowercase )]
if __name__ == "__main__":
print(h... | 70 | 1 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def UpperCamelCase ( __lowercase : NDArray[floataa] ,__lowercase : NDArray[floataa] ,__lowercase : list[int] ,__lowercase : int ,):
'''simple docstring'''
... | 70 | from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def UpperCamelCase ( ):
'''simple docstring'''
A_ , A_ : Any = 9, 14 # noqa: F841
A_ : str = [
[0, 1, 4],
[0, 7, 8],
... | 70 | 1 |
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerate.test_utils impo... | 70 | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 70 | 1 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
_UpperCAmelCa... | 70 | from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class UpperCAmelCase ( __A ):
'''simple docstring'''
... | 70 | 1 |
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class UpperCAmelCase ( __A ):
'''simple docstring'''
def __lt__( self , lowercase ):
"""simple docstri... | 70 | import random
def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
A_ : Tuple = num - 1
A_ : Optional[Any] = 0
while s % 2 == 0:
A_ : Optional[int] = s // 2
t += 1
for _ in range(5 ):
A_ ... | 70 | 1 |
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 import TFModelTeste... | 70 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCAmelCase = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxConfig"""],
"""tokenizat... | 70 | 1 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCamelCase ( __lowercase : Dict ):
'''simple docstring'''
A_ : Dict = args.pruning_method
A_ : Optional[in... | 70 | import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class UpperCAmelCase ( ... | 70 | 1 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():
f... | 70 | import numpy as np
_UpperCAmelCase = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x""", """y""", """z"""],
]
... | 70 | 1 |
import os
# Precomputes a list of the 100 first triangular numbers
_UpperCAmelCase = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def UpperCamelCase ( ):
'''simple docstring'''
A_ : str = os.path.dirname(os.path.realpath(__lowercase ) )
A_ : Tu... | 70 | from math import sqrt
def UpperCamelCase ( __lowercase : int = 1_00_00_00 ):
'''simple docstring'''
A_ : int = 0
A_ : int = 0
A_ : int
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 ,... | 70 | 1 |
def UpperCamelCase ( __lowercase : int = 10 ):
'''simple docstring'''
if not isinstance(__lowercase ,__lowercase ) or n < 0:
raise ValueError('Invalid input' )
A_ : Tuple = 10**n
A_ : Tuple = 2_84_33 * (pow(2 ,7_83_04_57 ,__lowercase ))... | 70 | import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class UpperCAmelCase ( tf.keras.optimizers.schedules.LearningRateSchedule ):
... | 70 | 1 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def UpperCamelCase ( __lowercase : str ,__lowercase : bool = True ,__lowercase : float = math.inf ,__lowercase : float = -math.inf ,__lowercase : float = math.inf ,__lowercase : f... | 70 | from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
BertCo... | 70 | 1 |
import requests
def UpperCamelCase ( __lowercase : str ,__lowercase : str ):
'''simple docstring'''
A_ : str = {'Content-Type': 'application/json'}
A_ : int = requests.post(__lowercase ,json={'text': message_body} ,headers=__lowercase ... | 70 | def UpperCamelCase ( __lowercase : str ):
'''simple docstring'''
A_ : int = len(__lowercase )
A_ : List[Any] = sum(__lowercase )
A_ : List[str] = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(... | 70 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase = {
"""configuration_trajectory_transformer""": [
"""TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""TrajectoryTransformerConfig""",
... | 70 | import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class UpperCAmelCase ( unittest.TestCase ... | 70 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
BertCo... | 70 | from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOut... | 70 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_UpperCAmelCase = {
"""configuration_clip""": [
""... | 70 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCAmelCase = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""tokenization_biogpt""": ["""BioGptT... | 70 | 1 |
def UpperCamelCase ( __lowercase : str ,__lowercase : str ):
'''simple docstring'''
if len(__lowercase ) != len(__lowercase ):
raise ValueError('String lengths must match!' )
A_ : Optional[int] = 0
for chara, chara in zip(__lowercase ,__lowercase ... | 70 | def UpperCamelCase ( __lowercase : list ):
'''simple docstring'''
A_ : str = len(__lowercase )
for _ in range(__lowercase ):
for i in range(_ % 2 ,arr_size - 1 ,2 ):
if arr[i + 1] < arr[i]:
A_ , A_ : Optional[Any] = a... | 70 | 1 |
from __future__ import annotations
import math
def UpperCamelCase ( __lowercase : float ,__lowercase : int ):
'''simple docstring'''
A_ : int = u
for i in range(1 ,__lowercase ):
A_ : Any = temp * (u - i)
return temp
... | 70 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json""",
... | 70 | 1 |
from __future__ import annotations
def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
A_ : Tuple = str(__lowercase )
return len(__lowercase ) == 9 and set(__lowercase ) == set('123456789' )
def UpperCamelCase ( ):
'''sim... | 70 | import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.uti... | 70 | 1 |
def UpperCamelCase ( __lowercase : int = 50 ):
'''simple docstring'''
A_ : List[Any] = [1] * (length + 1)
for row_length in range(3 ,length + 1 ):
for block_length in range(3 ,row_length + 1 ):
for block_start in range(row_length - block_length ):
... | 70 | def UpperCamelCase ( __lowercase : str ,__lowercase : int ):
'''simple docstring'''
A_ : int = word.split()
def justify(__lowercase : list ,__lowercase : int ,__lowercase : int ) -> str:
A_ : Optional[Any] = max_width - width... | 70 | 1 |
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def UpperCamelCase ( __lowercase : List[Any] ):
'''simple docstring'''
return x + 2
class UpperCAmelCase ( unittest.TestCase ):
... | 70 | import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback... | 70 | 1 |
import numpy as np
from transformers import Pipeline
def UpperCamelCase ( __lowercase : str ):
'''simple docstring'''
A_ : List[str] = np.max(__lowercase ,axis=-1 ,keepdims=__lowercase )
A_ : Optional[Any] = np.exp(outputs - maxes )
... | 70 | 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_available
from ...test_co... | 70 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.