code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoToke... | 701 |
from numpy import exp, pi, sqrt
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = 0.0 ,lowerCAmelCase__ = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 72 | 0 |
from __future__ import annotations
def UpperCamelCase__ ( lowerCAmelCase__ = 4 ):
lowercase = abs(_SCREAMING_SNAKE_CASE ) or 4
return [[1 + x + y * row_size for x in range(_SCREAMING_SNAKE_CASE )] for y in range(_SCREAMING_SNAKE_CASE )]
def UpperCamelCase__ ( lowerCAm... | 702 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class A_ :
_A :int
_A :int
class A_ :
def __init__( self : List[str] , snake_case__ : int ... | 72 | 0 |
__SCREAMING_SNAKE_CASE : Optional[Any] ={
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-",... | 703 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : str =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : str ={
'''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2vec-a... | 72 | 0 |
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_channel_dimension_format,
)
... | 704 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = [
"""decoder.version""",
"""decoder.output_projection.weight""",
"""_float... | 72 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image... | 705 |
from __future__ import annotations
import bisect
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ = 0 ,lowerCAmelCase__ = -1 ):
if hi < 0:
lowercase = len(lowerCAmelCase__ )
while lo < hi:
lowercase = lo + (hi - lo) //... | 72 | 0 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
__SCREAMING_SNAKE_CASE : List[Any] =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE... | 706 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmel... | 72 | 0 |
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__SCREAMING_SNAKE_CASE : Optional[int] =... | 707 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A_ ( __a ):
_A ... | 72 | 0 |
import warnings
from ..trainer import Trainer
from ..utils import logging
__SCREAMING_SNAKE_CASE : Tuple =logging.get_logger(__name__)
class A_ ( __A ):
def __init__( self : Any , snake_case__ : Any=None , **snake_case__ : ... | 708 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...f... | 72 | 0 |
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from transformers import Aut... | 709 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
... | 72 | 0 |
from __future__ import annotations
def UpperCamelCase__ ( lowerCAmelCase__ ):
if len(lowerCamelCase__ ) == 0:
return array
lowercase = min(lowerCamelCase__ ), max(lowerCamelCase__ )
# Compute the variables
lowercase = _max - _min + 1
lowercase ... | 710 |
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
__SCREAMING_SNAKE_CASE : List[Any] ='''.'''
if __name__ == "__main__":
__SCREAMING_SNAKE_CASE : List[str] =os.... | 72 | 0 |
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
__SCREAMING_SNAKE_CASE : str ={
'<': operator.lt,
'<=': operator.le,
'==': operator.eq,
'!=': operator.ne,
'>=': operator.ge,
'>': operator.gt,
}... | 711 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Tuple ={
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ... | 72 | 0 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class A_ ( UpperCamelCase_ ):
_A :List[Any] = """ClapFeatureExtractor"""
_A :List[Any] = ("""RobertaTokenizer""", """RobertaTokenizerFast""")
def __init_... | 712 |
import argparse
import os
import re
import packaging.version
__SCREAMING_SNAKE_CASE : Optional[int] ='''examples/'''
__SCREAMING_SNAKE_CASE : Any ={
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")... | 72 | 0 |
from graphs.minimum_spanning_tree_kruskal import kruskal
def UpperCamelCase__ ( ):
lowercase = 9
lowercase = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, 6, 1],
[2, 8, 2],
[8, 6, 6],
[2, 3, 7],
[2, 5, 4... | 713 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Union[str, Any] =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Tuple ={
'''google/pix2struct-textcaps-b... | 72 | 0 |
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ):
if height >= 1:
move_tower(height - 1 ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ )
move_disk(lowerCAmelCase__ ,lowerCAmelCase__ )
move_... | 714 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils import R... | 72 | 0 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
__SCREAMING_SNAKE_CASE : Dict =logging.getLogge... | 715 |
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
FEATUR... | 72 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@req... | 716 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" ,[
["""full:README.md""", """dataset_infos.json"""],
["""empty:README.md""", """dataset_infos.json"""... | 72 | 0 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, valid_im... | 717 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = args.pruning_method
lowercase = args.threshold
lowercase = args.model_na... | 72 | 0 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
... | 718 |
# using dfs for finding eulerian path traversal
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__=None ):
lowercase = (path or []) + [u]
for v in graph[u]:
if visited_edge[u][v] is False:
lowercase , l... | 72 | 0 |
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ):
return int((input_a, input_a).count(0 ) != 0 )
def UpperCamelCase__ ( ):
assert nand_gate(0 ,0 ) == 1
assert nand_gate(0 ,1 ) == 1
assert nand_gate(1 ,0 ) == 1
assert nand_gate(1 ,1... | 719 |
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
f... | 72 | 0 |
from math import factorial
def UpperCamelCase__ ( lowerCAmelCase__ = 20 ):
lowercase = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
lowercase = n // 2
return int(factorial(lowerCAmelCase__ ) / (factorial(lowerCAmelCase__ ... | 720 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class A_ :
def __init__( self : List[str] , snake_case__ : Union[str, Any] ):
lowercase = data
lowercase = [0X6_7_4_5_2_3_0_1, 0Xe_f_c_d_a_b... | 72 | 0 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def UpperCamelCase__ ( lowerCAmelCase__ ):
return ConvertCommand(
args.model_type ,args.tf_checkpoint ,args.pytorch_dump_output ,args.config ,args.finetunin... | 721 |
class A_ :
def __init__( self : Optional[Any] , snake_case__ : Dict , snake_case__ : Union[str, Any] ):
lowercase = name
lowercase = val
def __str__( self : str ):
return F"""{self... | 72 | 0 |
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
__SCREAMING_SNAKE_CASE : str =6_378_137.0
__SCREAMING_SNAKE_CASE : Optional[int] =6_356_752.314_245
__SCREAMING_SNAKE_CASE : Optional[Any] =6_378_137
... | 700 |
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, ImageClassifierOutp... | 72 | 0 |
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
__SCREAMING_SNAKE_CASE : Optional[int] =re.compile(R'''^(?P<major>\d+)''' R'''\.(?P<minor>\d+)''' R'''\.(?P<patch>\d+)$''')
@total_order... | 701 |
from numpy import exp, pi, sqrt
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = 0.0 ,lowerCAmelCase__ = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 72 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstrings, add_start_docstrin... | 702 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class A_ :
_A :int
_A :int
class A_ :
def __init__( self : List[str] , snake_case__ : int ... | 72 | 0 |
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_modeling_comm... | 703 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : str =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : str ={
'''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2vec-a... | 72 | 0 |
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
__SCREAMING_SNAKE_CASE : Optional[Any] =HUGGINGFACE_HUB_CACHE
__SCREAMING_SNAKE_CASE : Tuple ="config.json"
__SCREAMING_SNAKE_CASE : Optional[Any] ="diffusion_py... | 704 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = [
"""decoder.version""",
"""decoder.output_projection.weight""",
"""_float... | 72 | 0 |
def UpperCamelCase__ ( ):
for n in range(1 ,1_000_000 ):
yield n * (n + 1) // 2
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = 1
lowercase = 2
while i * i <= n:
lowercase = 0
while n % i == 0:
n //= i
... | 705 |
from __future__ import annotations
import bisect
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ = 0 ,lowerCAmelCase__ = -1 ):
if hi < 0:
lowercase = len(lowerCAmelCase__ )
while lo < hi:
lowercase = lo + (hi - lo) //... | 72 | 0 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = True ,lowerCAmelCase__ = math.inf ,lowerCAmelCase__ = -math.inf ,lowerCAmelCase__ = math.inf ,lowerCAmelCase__ = -math.inf ,lowe... | 706 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmel... | 72 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__SCREAMING_SNAKE_CASE : Optional[int] ={
'''configuration_canine''': ['''CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CanineConfig'''],
'''... | 707 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A_ ( __a ):
_A ... | 72 | 0 |
from collections.abc import Callable
import numpy as np
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ):
'''simple docstring'''
lowercase = int(np.ceil((x_end - xa) / step_size ) )
lowerca... | 708 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...f... | 72 | 0 |
import random
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ):
lowercase = [], [], []
for element in data:
if element < pivot:
less.append(_lowercase )
elif element > pivot:
greater.append(_lowercase )
else:
... | 709 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
... | 72 | 0 |
from collections.abc import Iterable
from typing import Any
class A_ :
def __init__( self : Optional[int] , snake_case__ : int | None = None ):
lowercase = value
lowercase = None # Added in order to delete a node easier
low... | 710 |
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
__SCREAMING_SNAKE_CASE : List[Any] ='''.'''
if __name__ == "__main__":
__SCREAMING_SNAKE_CASE : List[str] =os.... | 72 | 0 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A_ ( __UpperCAmelCase ):
_A :Optio... | 711 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Tuple ={
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ... | 72 | 0 |
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_torch_neuroncore,
)
from trans... | 712 |
import argparse
import os
import re
import packaging.version
__SCREAMING_SNAKE_CASE : Optional[int] ='''examples/'''
__SCREAMING_SNAKE_CASE : Any ={
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")... | 72 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__SCREAMING_SNAKE_CASE : Any ={
'''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
'''token... | 713 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Union[str, Any] =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Tuple ={
'''google/pix2struct-textcaps-b... | 72 | 0 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__SCREAMING_SNAKE_CASE : List[str] =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : str ={
'''nielsr/canine-s''': 2_048,
}... | 714 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils import R... | 72 | 0 |
from statistics import mean, stdev
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = 3 ):
lowercase = min(SCREAMING_SNAKE_CASE_ )
lowercase = max(SCREAMING_SNAKE_CASE_ )
# normalize data
return [round((x - x_min) / (x_max - x_min) ,SCREAMING_SNAKE... | 715 |
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
FEATUR... | 72 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 716 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" ,[
["""full:README.md""", """dataset_infos.json"""],
["""empty:README.md""", """dataset_infos.json"""... | 72 | 0 |
from typing import List
from .keymap import KEYMAP, get_character
def UpperCamelCase__ ( lowerCAmelCase__ ):
def decorator(lowerCAmelCase__ ):
lowercase = getattr(lowerCAmelCase__ ,"""handle_key""" ,[] )
handle += [key]
setattr(lowerCAmelCase__ ,"""... | 717 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = args.pruning_method
lowercase = args.threshold
lowercase = args.model_na... | 72 | 0 |
def UpperCamelCase__ ( lowerCAmelCase__ ):
return "".join([hex(__lowerCAmelCase )[2:].zfill(2 ).upper() for byte in list(__lowerCAmelCase )] )
def UpperCamelCase__ ( lowerCAmelCase__ ):
# Check data validity, following RFC3548
# https://www.ietf.org/rfc/rfc3548.txt
... | 718 |
# using dfs for finding eulerian path traversal
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__=None ):
lowercase = (path or []) + [u]
for v in graph[u]:
if visited_edge[u][v] is False:
lowercase , l... | 72 | 0 |
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
__SCREAMING_SNAKE_CASE : Union[str, Any] =abspath(join(dirnam... | 719 |
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
f... | 72 | 0 |
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ):
while second != 0:
lowercase = first & second
first ^= second
lowercase = c << 1
return first
if __name__ == "__main__":
import doctest
doctest.testmod()
__SCREAMING_SN... | 720 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class A_ :
def __init__( self : List[str] , snake_case__ : Union[str, Any] ):
lowercase = data
lowercase = [0X6_7_4_5_2_3_0_1, 0Xe_f_c_d_a_b... | 72 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__SCREAMING_SNAKE_CASE : Tuple ={"configuration_deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeiTConfig", "... | 721 |
class A_ :
def __init__( self : Optional[Any] , snake_case__ : Dict , snake_case__ : Union[str, Any] ):
lowercase = name
lowercase = val
def __str__( self : str ):
return F"""{self... | 72 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Dict =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Tuple ={
'''funnel-transformer/small''': '''https://huggingface.co/funnel-transformer/small/resolve... | 700 |
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, ImageClassifierOutp... | 72 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__SCREAMING_SNAKE_CASE : int =R'''
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control th... | 701 |
from numpy import exp, pi, sqrt
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = 0.0 ,lowerCAmelCase__ = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 72 | 0 |
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ )... | 702 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class A_ :
_A :int
_A :int
class A_ :
def __init__( self : List[str] , snake_case__ : int ... | 72 | 0 |
import re
import string
import numpy as np
import datasets
__SCREAMING_SNAKE_CASE : Optional[Any] ='\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n'
__SCREAMING_SNAKE_CASE : ... | 703 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : str =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : str ={
'''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2vec-a... | 72 | 0 |
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = 1
lowercase = 2
while i * i <= n:
lowercase = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1
if n > 1:
n_di... | 704 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = [
"""decoder.version""",
"""decoder.output_projection.weight""",
"""_float... | 72 | 0 |
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 A_ ( unittest.TestCase ):
def SCREAMING_SNAKE_CASE__ ( self : List[str] ):
lo... | 705 |
from __future__ import annotations
import bisect
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ = 0 ,lowerCAmelCase__ = -1 ):
if hi < 0:
lowercase = len(lowerCAmelCase__ )
while lo < hi:
lowercase = lo + (hi - lo) //... | 72 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Optional[Any] =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : List[Any] ={
"""microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/ma... | 706 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmel... | 72 | 0 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoModelWithLMHead,
... | 707 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A_ ( __a ):
_A ... | 72 | 0 |
def UpperCamelCase__ ( lowerCAmelCase__ ):
'''simple docstring'''
if bit_count < 0:
raise ValueError("""The given input must be positive""" )
# get the generated string sequence
lowercase = gray_code_sequence_string(__UpperCamelCase )
#
# convert them ... | 708 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...f... | 72 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, Stabl... | 709 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
... | 72 | 0 |
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__SCREAMING_SNAKE_CASE : Optional[Any] =... | 710 |
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
__SCREAMING_SNAKE_CASE : List[Any] ='''.'''
if __name__ == "__main__":
__SCREAMING_SNAKE_CASE : List[str] =os.... | 72 | 0 |
import copy
import re
class A_ :
_A :List[Any] = '''hp'''
_A :Dict = {}
_A :Optional[Any] = None
@classmethod
def SCREAMING_SNAKE_CASE__ ( cls : Optional[Any] , snake_case__ : Dict , snake... | 711 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Tuple ={
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ... | 72 | 0 |
from collections import UserDict
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... | 712 |
import argparse
import os
import re
import packaging.version
__SCREAMING_SNAKE_CASE : Optional[int] ='''examples/'''
__SCREAMING_SNAKE_CASE : Any ={
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")... | 72 | 0 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.p... | 713 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Union[str, Any] =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Tuple ={
'''google/pix2struct-textcaps-b... | 72 | 0 |
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_channel_dimension_format,
)
... | 714 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils import R... | 72 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__SCREAMING_SNAKE_CASE : str ={}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvail... | 715 |
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
FEATUR... | 72 | 0 |
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class A_ ( tf.keras.layers.Layer ):
def __init__( self : int ... | 716 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" ,[
["""full:README.md""", """dataset_infos.json"""],
["""empty:README.md""", """dataset_infos.json"""... | 72 | 0 |
import re
def UpperCamelCase__ ( lowerCAmelCase__ ):
if len(re.findall("""[ATCG]""" ,lowerCAmelCase__ ) ) != len(lowerCAmelCase__ ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans("""ATCG""" ,"""TAGC""" ) )
if __name__ == "__main__":
... | 717 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = args.pruning_method
lowercase = args.threshold
lowercase = args.model_na... | 72 | 0 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging import get_lo... | 718 |
# using dfs for finding eulerian path traversal
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__=None ):
lowercase = (path or []) + [u]
for v in graph[u]:
if visited_edge[u][v] is False:
lowercase , l... | 72 | 0 |
from itertools import product
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ):
lowercase = sides_number
lowercase = max_face_number * dice_number
lowercase = [0] * (max_total + 1)
lowercase = 1
lowercase = range(_lowerCamelC... | 719 |
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
f... | 72 | 0 |
# Copyright 2022 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 app... | 720 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class A_ :
def __init__( self : List[str] , snake_case__ : Union[str, Any] ):
lowercase = data
lowercase = [0X6_7_4_5_2_3_0_1, 0Xe_f_c_d_a_b... | 72 | 0 |
from math import isqrt, loga
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = [True] * max_number
for i in range(2 ,isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 ,lowerCAmelCase__ ,lowerCAmelCase__ ):
lowe... | 721 |
class A_ :
def __init__( self : Optional[Any] , snake_case__ : Dict , snake_case__ : Union[str, Any] ):
lowercase = name
lowercase = val
def __str__( self : str ):
return F"""{self... | 72 | 0 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import To... | 700 |
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, ImageClassifierOutp... | 72 | 0 |
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
f... | 701 |
from numpy import exp, pi, sqrt
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = 0.0 ,lowerCAmelCase__ = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 72 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class A_ ( unittest.TestCase ):
def SCREAMING_SNAKE_CASE... | 702 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class A_ :
_A :int
_A :int
class A_ :
def __init__( self : List[str] , snake_case__ : int ... | 72 | 0 |
from string import ascii_uppercase
__SCREAMING_SNAKE_CASE : Tuple ={str(ord(c) - 55): c for c in ascii_uppercase}
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ):
if isinstance(SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ ):
raise TypeError("""i... | 703 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : str =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : str ={
'''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2vec-a... | 72 | 0 |
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,
... | 704 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = [
"""decoder.version""",
"""decoder.output_projection.weight""",
"""_float... | 72 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : int =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Optional[int] ={
'''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/re... | 705 |
from __future__ import annotations
import bisect
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ = 0 ,lowerCAmelCase__ = -1 ):
if hi < 0:
lowercase = len(lowerCAmelCase__ )
while lo < hi:
lowercase = lo + (hi - lo) //... | 72 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False)
def ... | 706 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmel... | 72 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def UpperCamelCase__ ( lowerCAmelCase__ ):
if (
(cp >= 0X4e00 and cp <= 0X9fff)
or (cp >= 0X3400 and cp <= 0X4dbf) #
or (cp... | 707 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A_ ( __a ):
_A ... | 72 | 0 |
from typing import Any
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,):
'''simple docstring'''
_validation(
_A ,_A ,_A ,_A ,_A ,)
# Creates data structures and fill initi... | 708 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...f... | 72 | 0 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
__SCREAMING_SNAKE_CASE : Optional[Any] =logging.get_logger(__name__)
class A_ ( _A ):
def __init__( self : Tuple , *snake_case__ : ... | 709 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
... | 72 | 0 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class A_ ( nn.Module ):
d... | 710 |
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
__SCREAMING_SNAKE_CASE : List[Any] ='''.'''
if __name__ == "__main__":
__SCREAMING_SNAKE_CASE : List[str] =os.... | 72 | 0 |
from math import pi, sqrt, tan
def UpperCamelCase__ ( lowerCAmelCase__ ):
if side_length < 0:
raise ValueError("""surface_area_cube() only accepts non-negative values""" )
return 6 * side_length**2
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lo... | 711 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Tuple ={
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ... | 72 | 0 |
from math import factorial
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ):
if n < k or k < 0:
raise ValueError("""Please enter positive integers for n and k where n >= k""" )
return factorial(lowerCamelCase_ ) // (factorial(lowerCamelCase_ ) * factorial(n - k... | 712 |
import argparse
import os
import re
import packaging.version
__SCREAMING_SNAKE_CASE : Optional[int] ='''examples/'''
__SCREAMING_SNAKE_CASE : Any ={
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")... | 72 | 0 |
import sys
from collections import defaultdict
class A_ :
def __init__( self : Optional[int] ):
lowercase = []
def SCREAMING_SNAKE_CASE__ ( self : str , snake_case__ : Optional[Any] ):
return self.node_positio... | 713 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Union[str, Any] =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : Tuple ={
'''google/pix2struct-textcaps-b... | 72 | 0 |
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 impor... | 714 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils import R... | 72 | 0 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__SCREAMING_SNAKE_CASE : Optional[int] =logging.get_logger(__name__)
__SCREAMI... | 715 |
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
FEATUR... | 72 | 0 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
fr... | 716 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" ,[
["""full:README.md""", """dataset_infos.json"""],
["""empty:README.md""", """dataset_infos.json"""... | 72 | 0 |
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
__SCREAMING_SNAKE_CASE : List[Any] ='src/transformers'
# This is to make sure the transformers... | 717 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = args.pruning_method
lowercase = args.threshold
lowercase = args.model_na... | 72 | 0 |
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before to... | 718 |
# using dfs for finding eulerian path traversal
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__=None ):
lowercase = (path or []) + [u]
for v in graph[u]:
if visited_edge[u][v] is False:
lowercase , l... | 72 | 0 |
from math import factorial
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ):
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
raise ValueError("""the function i... | 719 |
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
f... | 72 | 0 |
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
__SCREAMING_SNAKE_CASE : Any =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE ... | 720 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class A_ :
def __init__( self : List[str] , snake_case__ : Union[str, Any] ):
lowercase = data
lowercase = [0X6_7_4_5_2_3_0_1, 0Xe_f_c_d_a_b... | 72 | 0 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --host <host> ... | 721 |
class A_ :
def __init__( self : Optional[Any] , snake_case__ : Dict , snake_case__ : Union[str, Any] ):
lowercase = name
lowercase = val
def __str__( self : str ):
return F"""{self... | 72 | 0 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class A_ ( __UpperCAmelCase ):
_A :List[str] = "Wav2Vec2F... | 700 |
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, ImageClassifierOutp... | 72 | 0 |
class A_ :
def __init__( self : List[str] , snake_case__ : Optional[int] ):
lowercase = set_counts
lowercase = max(__lowerCamelCase )
lowercase = len(__lowerCamelCase )
lowercase = [1] * num_sets
... | 701 |
from numpy import exp, pi, sqrt
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = 0.0 ,lowerCAmelCase__ = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 72 | 0 |
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ):
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
lowercase = str(bin(UpperCamelCase__ ) )[2:] # remove the leading "0b"
lowercase = str(bin(UpperCamelCa... | 702 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class A_ :
_A :int
_A :int
class A_ :
def __init__( self : List[str] , snake_case__ : int ... | 72 | 0 |
def UpperCamelCase__ ( lowerCAmelCase__ ):
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6, 8],
8: [5, 7],
},
{
... | 703 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : str =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : str ={
'''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2vec-a... | 72 | 0 |
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class lowercase ( _UpperCAmelCase , unittest.TestCase ):
_A :str = DownBlockaD # noqa F405
_A :... | 704 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def UpperCamelCase__ ( lowerCAmelCase__ ):
lowercase = [
"""decoder.version""",
"""decoder.output_projection.weight""",
"""_float... | 72 | 0 |
# Copyright 2023 The HuggingFace Inc. 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 b... | 705 |
from __future__ import annotations
import bisect
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ = 0 ,lowerCAmelCase__ = -1 ):
if hi < 0:
lowercase = len(lowerCAmelCase__ )
while lo < hi:
lowercase = lo + (hi - lo) //... | 72 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__SCREAMING_SNAKE_CASE : Dict =logging.get_logger(__name__)
__SCREAMING_SNA... | 706 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmel... | 72 | 0 |
def UpperCamelCase__ ( lowerCAmelCase__ ):
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
lowercase = sum(lowerCAmelCase__ ) / len(lowerCAmelCase__ ) # Calculate the average
return sum(abs(x - average ) for x i... | 707 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A_ ( __a ):
_A ... | 72 | 0 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils import R... | 708 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...f... | 72 | 0 |
from math import factorial
def UpperCamelCase__ ( lowerCAmelCase__ = 100 ):
return sum(map(lowerCAmelCase__ ,str(factorial(lowerCAmelCase__ ) ) ) )
if __name__ == "__main__":
print(solution(int(input('''Enter the Number: ''').strip())))
| 709 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
... | 72 | 0 |
import unittest
from transformers import DonutProcessor
__SCREAMING_SNAKE_CASE : str ='''naver-clova-ix/donut-base'''
class A_ ( unittest.TestCase ):
def SCREAMING_SNAKE_CASE__ ( self : int ):
lowercase = DonutProcessor.from_pretrained(... | 710 |
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
__SCREAMING_SNAKE_CASE : List[Any] ='''.'''
if __name__ == "__main__":
__SCREAMING_SNAKE_CASE : List[str] =os.... | 72 | 0 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
__SCREAMING_SNAKE_CASE : Any =object()
# For specifying empty leaf dict `{}`
__SCREAMING_SNAKE_CASE : Any ... | 711 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Tuple ={
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ... | 72 | 0 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class A_ ( pl.LightningModule ):
def __init__( self : str , snake_case__ : int ):
super().__init_... | 712 |
import argparse
import os
import re
import packaging.version
__SCREAMING_SNAKE_CASE : Optional[int] ='''examples/'''
__SCREAMING_SNAKE_CASE : Any ={
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")... | 72 | 0 |
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