code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 20 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowerCAmelCase: Optional[Any] = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'S... | 20 | 1 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase: List[Any] = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface... | 20 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase: str = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'google/bigbird-roberta... | 20 | 1 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_co... | 20 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.set_... | 20 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING:
... | 20 |
from __future__ import annotations
from typing import Any
class lowercase_ :
def __init__( self , lowercase_) -> None:
a__ =num_of_nodes
a__ =[]
a__ ={}
def __UpperCamelCase ( self , lowercase_ , low... | 20 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase: Dict = {
'configuration_mobilenet_v2': [
'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'MobileNetV2Config',
'Mobi... | 20 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a nice... | 20 | 1 |
def _lowercase( __a : list ):
a__ =len(__a )
for i in range(1 , __a ):
a__ =collection[i]
a__ =0
a__ =i - 1
while low <= high:
a__ =(low + high) // 2
... | 20 |
from __future__ import annotations
_lowerCAmelCase: str = '#'
class lowercase_ :
def __init__( self) -> None:
a__ ={}
def __UpperCamelCase ( self , lowercase_) -> None:
a__ =self._trie
for char in tex... | 20 | 1 |
from __future__ import annotations
from decimal import Decimal
from numpy import array
def _lowercase( __a : list[list[float]] ):
a__ =Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementation only works for 2x2 matrices
if... | 20 |
_lowerCAmelCase: List[str] = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
def _lowercase( ):
a__ =input('Enter message: ' )
a__ =input('Enter key [alphanumeric]: ' )
a__ =input('Encrypt/Decrypt [e/d]: ' )
if mode.lower().startswith('e' ):
... | 20 | 1 |
def _lowercase( __a : str ):
a__ =[0 for i in range(len(__a ) )]
# initialize interval's left pointer and right pointer
a__ , a__ =0, 0
for i in range(1 , len(__a ) ):
# case when current index is inside the interva... | 20 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
ComputeEnvironment,
... | 20 | 1 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _lowercase( __a : int , __a : int , __a : int , __a : int , __a : int , __a : int ):
# prepare kernel
... | 20 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransforme... | 20 | 1 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def _lowercase( __a : Optional[int] ):
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
class lowercase_ (lowercase__ ):
... | 20 |
from manim import *
class lowercase_ (lowercase__ ):
def __UpperCamelCase ( self) -> List[Any]:
a__ =Rectangle(height=0.5 , width=0.5)
a__ =Rectangle(height=0.46 , width=0.46).set_stroke(width=0)
a__ =[mem.copy() for... | 20 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase: Dict = logging.get_logger(__name__)
_lowerCAmelCase: Tuple = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
# See all GLPN ... | 20 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentParser, TrainingArguments... | 20 | 1 |
import math
from collections.abc import Iterator
from itertools import takewhile
def _lowercase( __a : int ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, ... | 20 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase: List[Any] = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface... | 20 | 1 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a nice... | 20 |
from typing import Dict, List, Optional, Tuple, 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... | 20 | 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 ...image_... | 20 |
from importlib import import_module
from .logging import get_logger
_lowerCAmelCase: str = get_logger(__name__)
class lowercase_ :
def __init__( self , lowercase_ , lowercase_=None) -> Tuple:
a__ =attrs or []
if module is not Non... | 20 | 1 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_vision_available
fro... | 20 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
_lowerCAmelCase: int = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=None, type=str, required=True, help='Path... | 20 | 1 |
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class lowercase_ :
def __init__( self , lowercase_ , lowercase_=sys.maxsize)... | 20 |
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_HASH
from huggingfac... | 20 | 1 |
import warnings
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
_lowerCAmelCase: Optional[int] = logging.get_logger(__name__)
_lowerCAmelC... | 20 |
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.utils impor... | 20 | 1 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
_lowerCAmelCase: List[str] = '%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('Search: ')))
pri... | 20 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.models... | 20 | 1 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class lowercase_ (unittest.TestCase ):
def __UpperCamelCase ( self) -> Lis... | 20 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@require... | 20 | 1 |
class lowercase_ :
def __init__( self) -> str:
a__ =0
a__ =0
a__ ={}
def __UpperCamelCase ( self , lowercase_) -> Dict:
if vertex not in self.adjacency:
a__ ={}
self... | 20 |
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, BlipImageProcessor, Bli... | 20 | 1 |
from __future__ import annotations
_lowerCAmelCase: Tuple = tuple[int, int, int]
_lowerCAmelCase: Any = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
_lowerCAmelCase: int = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
# ----------... | 20 |
def _lowercase( __a : list[int] ):
a__ =len(__a )
for i in range(__a ):
for j in range(i + 1 , __a ):
if numbers[j] < numbers[i]:
a__ , a__ =numbers[j], numbers[i]
return numbers
... | 20 | 1 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase: List[str] = get_tests_dir('fixtures/test_s... | 20 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_common... | 20 | 1 |
from __future__ import annotations
def _lowercase( __a : str , __a : str ):
a__ =get_failure_array(__a )
# 2) Step through text searching for pattern
a__ , a__ =0, 0 # index into text, pattern
while i < len(__a ):
... | 20 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowerCAmelCase: Optional[Any] = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'S... | 20 | 1 |
from __future__ import annotations
_lowerCAmelCase: str = '#'
class lowercase_ :
def __init__( self) -> None:
a__ ={}
def __UpperCamelCase ( self , lowercase_) -> None:
a__ =self._trie
for char in tex... | 20 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase: str = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'google/bigbird-roberta... | 20 | 1 |
from __future__ import annotations
from PIL import Image
# Define glider example
_lowerCAmelCase: Dict = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, ... | 20 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.set_... | 20 | 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 t... | 20 |
from __future__ import annotations
from typing import Any
class lowercase_ :
def __init__( self , lowercase_) -> None:
a__ =num_of_nodes
a__ =[]
a__ ={}
def __UpperCamelCase ( self , lowercase_ , low... | 20 | 1 |
import math
def _lowercase( __a : int ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
ret... | 20 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a nice... | 20 | 1 |
from __future__ import annotations
def _lowercase( __a : int ):
a__ =2
a__ =[]
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(__a )
if n > 1:
... | 20 |
from __future__ import annotations
_lowerCAmelCase: str = '#'
class lowercase_ :
def __init__( self) -> None:
a__ ={}
def __UpperCamelCase ( self , lowercase_) -> None:
a__ =self._trie
for char in tex... | 20 | 1 |
import requests
def _lowercase( __a : str , __a : str ):
a__ ={'Content-Type': 'application/json'}
a__ =requests.post(__a , json={'text': message_body} , headers=__a )
if response.status_code != 200:
a__ =(
... | 20 |
_lowerCAmelCase: List[str] = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
def _lowercase( ):
a__ =input('Enter message: ' )
a__ =input('Enter key [alphanumeric]: ' )
a__ =input('Encrypt/Decrypt [e/d]: ' )
if mode.lower().startswith('e' ):
... | 20 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@require_torch
class ... | 20 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
ComputeEnvironment,
... | 20 | 1 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase_ (lowercase__ ):
snake_c... | 20 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransforme... | 20 | 1 |
_lowerCAmelCase: Optional[Any] = {
0: '0',
1: '1',
2: '2',
3: '3',
4: '4',
5: '5',
6: '6',
7: '7',
8: '8',
9: '9',
10: 'a',
11: 'b',
12: 'c',
13: 'd',
14: 'e',
15: 'f',
}
def _lowercase( __a : float ):
ass... | 20 |
from manim import *
class lowercase_ (lowercase__ ):
def __UpperCamelCase ( self) -> List[Any]:
a__ =Rectangle(height=0.5 , width=0.5)
a__ =Rectangle(height=0.46 , width=0.46).set_stroke(width=0)
a__ =[mem.copy() for... | 20 | 1 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression_s... | 20 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentParser, TrainingArguments... | 20 | 1 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_verbosity_info()
... | 20 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase: List[Any] = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface... | 20 | 1 |
from __future__ import annotations
from typing import Generic, TypeVar
_lowerCAmelCase: Optional[Any] = TypeVar('T')
class lowercase_ (Generic[T] ):
def __init__( self , lowercase_) -> None:
a__ =data
a__ =self
a__ ... | 20 |
from typing import Dict, List, Optional, Tuple, 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... | 20 | 1 |
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope='session' )
def _lowercase( ):
a__ =10
a__ ... | 20 |
from importlib import import_module
from .logging import get_logger
_lowerCAmelCase: str = get_logger(__name__)
class lowercase_ :
def __init__( self , lowercase_ , lowercase_=None) -> Tuple:
a__ =attrs or []
if module is not Non... | 20 | 1 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase_ (lowercase__ ):
snake_case ='ClapFeatureExtractor'
snake_case =('RobertaTokenizer', 'RobertaTokenizerFast')
def __init__( self , lowercase_ , ... | 20 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
_lowerCAmelCase: int = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=None, type=str, required=True, help='Path... | 20 | 1 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_switch_... | 20 |
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_HASH
from huggingfac... | 20 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase: str = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'google/bigbird-roberta... | 20 |
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.utils impor... | 20 | 1 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('dataset_size' , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize('input_in_memory_max_size' , ['default', 0, 100 * 2**20, 900 * 2**20] )
def _lowercase( ... | 20 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.models... | 20 | 1 |
from typing import Dict, List, Optional, Tuple, 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... | 20 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@require... | 20 | 1 |
import argparse
from collections import defaultdict
import yaml
_lowerCAmelCase: int = 'docs/source/en/_toctree.yml'
def _lowercase( __a : Union[str, Any] ):
a__ =defaultdict(__a )
for doc in model_doc:
counts[doc["local"]] += 1
... | 20 |
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, BlipImageProcessor, Bli... | 20 | 1 |
import random
class lowercase_ :
@staticmethod
def __UpperCamelCase ( lowercase_) -> tuple[list[int], list[int]]:
a__ =[ord(lowercase_) for i in text]
a__ =[]
a__ =[]
for i in plain:
a__ =random.... | 20 |
def _lowercase( __a : list[int] ):
a__ =len(__a )
for i in range(__a ):
for j in range(i + 1 , __a ):
if numbers[j] < numbers[i]:
a__ , a__ =numbers[j], numbers[i]
return numbers
... | 20 | 1 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transform... | 20 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_common... | 20 | 1 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_availabl... | 20 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowerCAmelCase: Optional[Any] = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'S... | 20 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,... | 20 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase: str = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'google/bigbird-roberta... | 20 | 1 |
from math import factorial
def _lowercase( __a : int , __a : int , __a : float ):
if successes > trials:
raise ValueError('successes must be lower or equal to trials' )
if trials < 0 or successes < 0:
raise ValueError... | 20 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.set_... | 20 | 1 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Path
from urllib.... | 20 |
from __future__ import annotations
from typing import Any
class lowercase_ :
def __init__( self , lowercase_) -> None:
a__ =num_of_nodes
a__ =[]
a__ ={}
def __UpperCamelCase ( self , lowercase_ , low... | 20 | 1 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxMo... | 20 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a nice... | 20 | 1 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class lowercase_ (lowercase__ ):
def __init__( self , lowercase_ , lowercase_ , lowercase_) -> Union[str, Any]:
a__ =dataset... | 20 |
from __future__ import annotations
_lowerCAmelCase: str = '#'
class lowercase_ :
def __init__( self) -> None:
a__ ={}
def __UpperCamelCase ( self , lowercase_) -> None:
a__ =self._trie
for char in tex... | 20 | 1 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_common... | 20 |
_lowerCAmelCase: List[str] = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
def _lowercase( ):
a__ =input('Enter message: ' )
a__ =input('Enter key [alphanumeric]: ' )
a__ =input('Encrypt/Decrypt [e/d]: ' )
if mode.lower().startswith('e' ):
... | 20 | 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:
_lowerC... | 20 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
ComputeEnvironment,
... | 20 | 1 |
from ..utils import DummyObject, requires_backends
class lowercase_ (metaclass=lowercase__ ):
snake_case =['keras_nlp']
def __init__( self , *lowercase_ , **lowercase_) -> str:
requires_backends(self , ['keras_nlp'])
| 20 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransforme... | 20 | 1 |
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
OpenAIGPTDoubleHeadsM... | 20 |
from manim import *
class lowercase_ (lowercase__ ):
def __UpperCamelCase ( self) -> List[Any]:
a__ =Rectangle(height=0.5 , width=0.5)
a__ =Rectangle(height=0.46 , width=0.46).set_stroke(width=0)
a__ =[mem.copy() for... | 20 | 1 |
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def _lowercase( __a : Optional... | 20 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentParser, TrainingArguments... | 20 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@require... | 20 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase: List[Any] = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface... | 20 | 1 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class lowercase_ (lowercase__ ):
def __init__( self , lowercase_ , lowercase_) -> Tuple:
a__ =params
a__ =np.array(lowercase_)
a__ ... | 20 |
from typing import Dict, List, Optional, Tuple, 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... | 20 | 1 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
ComputeEnvironment,
... | 20 |
from importlib import import_module
from .logging import get_logger
_lowerCAmelCase: str = get_logger(__name__)
class lowercase_ :
def __init__( self , lowercase_ , lowercase_=None) -> Tuple:
a__ =attrs or []
if module is not Non... | 20 | 1 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
f... | 20 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
_lowerCAmelCase: int = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=None, type=str, required=True, help='Path... | 20 | 1 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase_ ... | 20 |
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_HASH
from huggingfac... | 20 | 1 |
import sys
from collections import defaultdict
class lowercase_ :
def __init__( self) -> List[Any]:
a__ =[]
def __UpperCamelCase ( self , lowercase_) -> List[str]:
return self.node_position[vertex]
def __UpperCamelCase ... | 20 |
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.utils impor... | 20 | 1 |
from __future__ import annotations
from collections.abc import Callable
_lowerCAmelCase: Dict = list[list[float | int]]
def _lowercase( __a : Matrix , __a : Matrix ):
a__ =len(__a )
a__ =[[0 for _ in range(size + 1 )] for _ in ... | 20 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.models... | 20 | 1 |
def _lowercase( __a : int ):
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 20 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@require... | 20 | 1 |
import argparse
from collections import defaultdict
def _lowercase( __a : Union[str, Any] , __a : Dict , __a : Union[str, Any] , __a : Optional[int] , __a : Optional[int] ):
a__ =f"""{file}_{class_name}_{test_name}"""
... | 20 |
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, BlipImageProcessor, Bli... | 20 | 1 |
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInput
from ...utils import logging
_... | 20 |
def _lowercase( __a : list[int] ):
a__ =len(__a )
for i in range(__a ):
for j in range(i + 1 , __a ):
if numbers[j] < numbers[i]:
a__ , a__ =numbers[j], numbers[i]
return numbers
... | 20 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowerCAmelCase: Optional[Any] = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'S... | 20 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_common... | 20 | 1 |
from __future__ import annotations
import queue
class lowercase_ :
def __init__( self , lowercase_) -> Dict:
a__ =data
a__ =None
a__ =None
def _lowercase( ):
print('\n********Press N to stop entering at any point o... | 20 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowerCAmelCase: Optional[Any] = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'S... | 20 | 1 |
def _lowercase( __a : list ):
if not isinstance(__a , __a ):
raise ValueError('Input series is not valid, valid series - [2, 4, 6]' )
if len(__a ) == 0:
raise ValueError('Input list must be a non empty list' )
if len(__a ) ... | 20 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase: str = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'google/bigbird-roberta... | 20 | 1 |
from collections import Counter
from timeit import timeit
def _lowercase( __a : str = "" , ):
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values() ) < 2
def _lowercase( __a : str = "" ):
if len(__a ) ... | 20 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.set_... | 20 | 1 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
_lowerCAmelCase: List[str] = datasets.utils.lo... | 20 |
from __future__ import annotations
from typing import Any
class lowercase_ :
def __init__( self , lowercase_) -> None:
a__ =num_of_nodes
a__ =[]
a__ ={}
def __UpperCamelCase ( self , lowercase_ , low... | 20 | 1 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, Fla... | 20 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a nice... | 20 | 1 |
def _lowercase( __a : int ):
a__ =(1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def _lowercase( __a : int = 5000 ):
a__ =[(i * (3 * i - 1)) // 2 for i in range(1 , __a )]
for i, pentagonal_i in enumerate(__a ):
... | 20 |
from __future__ import annotations
_lowerCAmelCase: str = '#'
class lowercase_ :
def __init__( self) -> None:
a__ ={}
def __UpperCamelCase ( self , lowercase_) -> None:
a__ =self._trie
for char in tex... | 20 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 20 |
_lowerCAmelCase: List[str] = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
def _lowercase( ):
a__ =input('Enter message: ' )
a__ =input('Enter key [alphanumeric]: ' )
a__ =input('Encrypt/Decrypt [e/d]: ' )
if mode.lower().startswith('e' ):
... | 20 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase: Optional[int] = {
'configuration_blenderbot': [
'BLENDERBOT_... | 20 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
ComputeEnvironment,
... | 20 | 1 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
_lowerCAmelCase: int = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=None, type=str, required=True, help='Path... | 20 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransforme... | 20 | 1 |
from collections.abc import Callable
import numpy as np
def _lowercase( __a : Callable , __a : float , __a : float , __a : float , __a : float ):
a__ =int(np.ceil((x_end - xa) / step_size ) )
a__ =np.... | 20 |
from manim import *
class lowercase_ (lowercase__ ):
def __UpperCamelCase ( self) -> List[Any]:
a__ =Rectangle(height=0.5 , width=0.5)
a__ =Rectangle(height=0.46 , width=0.46).set_stroke(width=0)
a__ =[mem.copy() for... | 20 | 1 |
from collections.abc import Iterable
from typing import Any
class lowercase_ :
def __init__( self , lowercase_ = None) -> Dict:
a__ =value
a__ =None # Added in order to delete a node easier
a__ =None
a__ =None
... | 20 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentParser, TrainingArguments... | 20 | 1 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def _lowercase( __a : ndarray ):
return np.dot(__a , __a )
class lowercase_ :
def __init__( self , *,
lowercase_ = np.inf ... | 20 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase: List[Any] = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface... | 20 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase: Union[str, Any] = {
'configuration_roformer': ['ROFORMER_PRETRAINED_... | 20 |
from typing import Dict, List, Optional, Tuple, 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... | 20 | 1 |
def _lowercase( __a : int = 5000_0000 ):
a__ =set()
a__ =int((limit - 24) ** (1 / 2) )
a__ =set(range(3 , prime_square_limit + 1 , 2 ) )
primes.add(2 )
for p in range(3 , prime_square_limit + 1 , 2 ):... | 20 |
from importlib import import_module
from .logging import get_logger
_lowerCAmelCase: str = get_logger(__name__)
class lowercase_ :
def __init__( self , lowercase_ , lowercase_=None) -> Tuple:
a__ =attrs or []
if module is not Non... | 20 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
Sta... | 20 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
_lowerCAmelCase: int = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=None, type=str, required=True, help='Path... | 20 | 1 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase( __a : NDArray[floataa] , __a : NDArray[floataa] , __a : list[int] , __a : int , ):
a__ , a__ =co... | 20 |
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_HASH
from huggingfac... | 20 | 1 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransforme... | 20 |
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.utils impor... | 20 | 1 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
log... | 20 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.models... | 20 | 1 |
from maths.prime_check import is_prime
def _lowercase( __a : int ):
if not isinstance(__a , __a ):
a__ =f"""Input value of [number={number}] must be an integer"""
raise TypeError(__a )
if is_prime(__a ) and is_prime(number + 2 ... | 20 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@require... | 20 | 1 |
_lowerCAmelCase: Tuple = 'Alexander Joslin'
import operator as op
from .stack import Stack
def _lowercase( __a : str ):
a__ ={'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
a__ =Stack()
a__ =Stack()
for i in equation:
... | 20 |
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, BlipImageProcessor, Bli... | 20 | 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
_lowerCAmelCase: Tuple = logging.get_logger(__name__)
_lowerCAmelCase: Any = ... | 20 |
def _lowercase( __a : list[int] ):
a__ =len(__a )
for i in range(__a ):
for j in range(i + 1 , __a ):
if numbers[j] < numbers[i]:
a__ , a__ =numbers[j], numbers[i]
return numbers
... | 20 | 1 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
blenderbot,
blenderb... | 20 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_common... | 20 | 1 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase_ (unittest.TestCase ):
def __UpperCamelCase ( self) -> Tuple:
debug_launcher(test_script.main)
def _... | 20 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowerCAmelCase: Optional[Any] = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'S... | 20 | 1 |
def _lowercase( __a : int ):
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
a__ =[0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
a__ =1
if upper_limit > 0:
a__ =1
# ... | 20 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase: str = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'google/bigbird-roberta... | 20 | 1 |
import os
import sys
import unittest
_lowerCAmelCase: int = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find... | 20 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.set_... | 20 | 1 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_common import T... | 20 |
from __future__ import annotations
from typing import Any
class lowercase_ :
def __init__( self , lowercase_) -> None:
a__ =num_of_nodes
a__ =[]
a__ ={}
def __UpperCamelCase ( self , lowercase_ , low... | 20 | 1 |
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.utils impor... | 20 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a nice... | 20 | 1 |
def _lowercase( __a : int = 200_0000 ):
a__ =[0 for i in range(n + 1 )]
a__ =1
a__ =1
for i in range(2 , int(n**0.5 ) + 1 ):
if primality_list[i] == 0:
for j in range(i * i , n + 1 , __a ... | 20 |
from __future__ import annotations
_lowerCAmelCase: str = '#'
class lowercase_ :
def __init__( self) -> None:
a__ ={}
def __UpperCamelCase ( self , lowercase_) -> None:
a__ =self._trie
for char in tex... | 20 | 1 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class lowercase_ :
snake_case =None
def __UpperCamelCase ( self) -> Optional[int]:
a__ =self.feature_extraction_class(**self.feat_extract_dict)
... | 20 |
_lowerCAmelCase: List[str] = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
def _lowercase( ):
a__ =input('Enter message: ' )
a__ =input('Enter key [alphanumeric]: ' )
a__ =input('Encrypt/Decrypt [e/d]: ' )
if mode.lower().startswith('e' ):
... | 20 | 1 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torc... | 20 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
ComputeEnvironment,
... | 20 | 1 |
def _lowercase( __a : int ):
if num < 0:
return False
a__ =num
a__ =0
while num > 0:
a__ =rev_num * 10 + (num % 10)
num //= 10
return num_copy == rev_num
if __name__ == "__main__":
import doctest
doct... | 20 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransforme... | 20 | 1 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .dataclasses import Bnb... | 20 |
from manim import *
class lowercase_ (lowercase__ ):
def __UpperCamelCase ( self) -> List[Any]:
a__ =Rectangle(height=0.5 , width=0.5)
a__ =Rectangle(height=0.46 , width=0.46).set_stroke(width=0)
a__ =[mem.copy() for... | 20 | 1 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pi... | 20 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentParser, TrainingArguments... | 20 | 1 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_available(check_device=False):
... | 20 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase: List[Any] = logging.get_logger(__name__)
_lowerCAmelCase: Any = {
'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface... | 20 | 1 |
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