code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__snake_case = '''__DUMMY_TRANSFORMERS_USER__'''
__snake_case = '''Dummy User'''
__snake_case = '''hf_hZEmnoOEY... | 320 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
... | 259 | 0 |
"""simple docstring"""
__A = 8.314_4598
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> str:
if temperature < 0:
raise Exception('''Temperature cannot be less than 0 K''' )
if molar_mass <= 0:
raise Exception('''Molar mass cannot be less than or equal... | 177 |
import numpy as np
__snake_case = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x""", """y""", """z"""],
]
... | 259 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ... | 319 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def _A ( SCREAMING_SNAK... | 259 | 0 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowerCamelCase = {
'''tiny.en''': '''https://openaipublic.azureedge.net/main/whisper/mo... | 131 |
def _A ( SCREAMING_SNAKE_CASE__ : list[int] , SCREAMING_SNAKE_CASE__ : list[int] ):
UpperCamelCase :Tuple = len(SCREAMING_SNAKE_CASE__ )
print('''The following activities are selected:''' )
# The first activity is always selected
UpperCamelCase ... | 259 | 0 |
"""simple docstring"""
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, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from ... | 98 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/git-base/resolve/main/config.j... | 259 | 0 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, requir... | 143 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__snake_case = """__DUMMY_TRANSFORMERS_USER__"""
__snake_case = """Dummy User"""
__snake_case = """hf_hZEmnoOEYISjraJt... | 259 | 0 |
"""simple docstring"""
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
UpperCAmelCase_ : Any = HfApi()
UpperCAmelCase_ : Optional[Any] = {}
# fmt: off
UpperCAmelCase_ : Any = torch.tensor([
-0.7_5_1_5, -1.6_8_8_3, 0.2_4_2_0, 0.0_3... | 91 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask... | 259 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def lowerCamelCase__ ( _A ):
if "model" in orig_key:
a : Union[str, Any] = orig_key.replace('model.' , '' )
if "norm1" in orig_key:
a : L... | 297 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_commo... | 259 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
snake_case_ : ... | 83 |
def _A ( ):
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def _A ( SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :Optional[int] = 1
UpperCamelCase :List[Any] = 2
while i * i <= n:
UpperCamelCase :str ... | 259 | 0 |
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBertForMaskedLM,
DistilBe... | 253 |
def _A ( SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : Optional[Any] ):
# Return True if there is node that has not iterated.
UpperCamelCase :Tuple = [False] * len(SCRE... | 259 | 0 |
__lowerCAmelCase : List[str] ={
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'dataclasses': 'dataclasses',
... | 9 |
from __future__ import annotations
from typing import Any
def _A ( SCREAMING_SNAKE_CASE__ : list[Any] ):
create_state_space_tree(SCREAMING_SNAKE_CASE__ , [] , 0 )
def _A ( SCREAMING_SNAKE_CASE__ : list[Any] , SCREAMING_SNAKE_CASE__ : list[Any] , SCREAMING... | 259 | 0 |
"""simple docstring"""
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from tra... | 320 |
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,
)... | 259 | 0 |
"""simple docstring"""
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase=() , __UpperCAmelCase=Non... | 177 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def _A ( SCREAMING_SNAKE_CASE__ : Optional[int] , SCREAMING_SNAKE_CASE__ : List[str]=() , SCREAMING_SNAKE_CASE__ : ... | 259 | 0 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/confi... | 319 |
import sys
def _A ( SCREAMING_SNAKE_CASE__ : List[str] ):
UpperCamelCase :Any = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :Any = [[0 for x in range(SCREAMING_SNAKE_CASE__ )] for x in range(SCREAMING_SNAKE_CASE__ )]
UpperCamelCase ... | 259 | 0 |
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_ax... | 131 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case = logging.get_logger(__name__)
__snake_case = """https://... | 259 | 0 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusi... | 98 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.uti... | 259 | 0 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import is_xforme... | 143 |
import math
def _A ( SCREAMING_SNAKE_CASE__ : int = 100 ):
UpperCamelCase :Dict = sum(i * i for i in range(1 , n + 1 ) )
UpperCamelCase :List[str] = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return squ... | 259 | 0 |
"""simple docstring"""
import unittest
from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common ... | 91 |
def _A ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
UpperCamelCase :Any = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :str = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :int = [[False for _ in range(m + 1... | 259 | 0 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowerCAmelCase: Optional[Any] = 5_0_0_0_0_0
lowerCAmelCase , lowerCAmelCase: List[Any] = os.path.split... | 297 |
from math import factorial
__snake_case = {str(digit): factorial(digit) for digit in range(10)}
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise TypeError('''Parameter number must be int''' ... | 259 | 0 |
'''simple docstring'''
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils... | 83 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE... | 259 | 0 |
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from transformers import AutoTo... | 253 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _A ( SCREAMING_SNAKE_CASE__ : str = "isbn/0140328726" ):
UpperCamelCase :Optional[int] = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashe... | 259 | 0 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError('To use the rich extension, install rich with `pip install rich`')
| 9 |
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 259 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/config.json''',
'''google/fnet-large''': ''... | 320 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
... | 259 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
... | 177 |
import numpy as np
__snake_case = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x""", """y""", """z"""],
]
... | 259 | 0 |
'''simple docstring'''
import math
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> Dict:
return math.pow(SCREAMING_SNAKE_CASE__ , 2 ) - a
def SCREAMING_SNAKE_CASE( __lowercase ) -> Dict:
return 2 * x
def SCREAMING_... | 319 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def _A ( SCREAMING_SNAK... | 259 | 0 |
import string
import numpy
def lowerCamelCase_ ( _a , _a ):
"""simple docstring"""
return b if a == 0 else greatest_common_divisor(b % a , SCREAMING_SNAKE_CASE__ )
class _a :
_a : Tuple = string.ascii_... | 131 |
def _A ( SCREAMING_SNAKE_CASE__ : list[int] , SCREAMING_SNAKE_CASE__ : list[int] ):
UpperCamelCase :Tuple = len(SCREAMING_SNAKE_CASE__ )
print('''The following activities are selected:''' )
# The first activity is always selected
UpperCamelCase ... | 259 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] = {
'configuration_timesformer': ['TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TimesformerConfig'],
}
try:
if n... | 98 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/git-base/resolve/main/config.j... | 259 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase__ : List[str] = {
'''configuration_tapas''': ['''TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TapasConfig'''],
'''tokenization_tapas''': ['''Tapa... | 143 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__snake_case = """__DUMMY_TRANSFORMERS_USER__"""
__snake_case = """Dummy User"""
__snake_case = """hf_hZEmnoOEYISjraJt... | 259 | 0 |
"""simple docstring"""
def _A (__a , __a , __a , __a ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Union[str, Any] = len(SCREAMING_SNAKE_CASE__ ), len(grid[0] )
if (
min(SCREAMING_SNAKE_CASE__ , SCRE... | 91 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask... | 259 | 0 |
'''simple docstring'''
import requests
lowerCAmelCase: Optional[Any] = 'https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='
def lowerCamelCase__ ( _A ):
# fetching a list of articles in json format
a : Tuple = requests.get(_NEWS... | 297 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_commo... | 259 | 0 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def A__ ( UpperCAmelCase_ = 3 ):
if isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise TypeError('num... | 83 |
def _A ( ):
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def _A ( SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :Optional[int] = 1
UpperCamelCase :List[Any] = 2
while i * i <= n:
UpperCamelCase :str ... | 259 | 0 |
import math
def A_ ( a = 1_0_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = sum(i * i for i in range(1 , n + 1 ) )
SCREAMING_SNAKE_CASE_ : List[str] = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) ... | 253 |
def _A ( SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : Optional[Any] ):
# Return True if there is node that has not iterated.
UpperCamelCase :Tuple = [False] * len(SCRE... | 259 | 0 |
def _UpperCamelCase ( lowercase__ ):
assert isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ), F'''The input value of [n={number}] is not an integer'''
if number == 1:
return 2
elif number < 1:
__SCREAMING_SNAKE_CASE : ... | 9 |
from __future__ import annotations
from typing import Any
def _A ( SCREAMING_SNAKE_CASE__ : list[Any] ):
create_state_space_tree(SCREAMING_SNAKE_CASE__ , [] , 0 )
def _A ( SCREAMING_SNAKE_CASE__ : list[Any] , SCREAMING_SNAKE_CASE__ : list[Any] , SCREAMING... | 259 | 0 |
"""simple docstring"""
from __future__ import annotations
def A_ ( _lowerCAmelCase : list[int], _lowerCAmelCase : list[int], _lowerCAmelCase : list[int], _lowerCAmelCase : list[list[str]], _lowerCAmelCase : int, ):
"""simple docstring"""
_a ... | 320 |
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,
)... | 259 | 0 |
"""simple docstring"""
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> List[Any]:
# A local function to see if a dot lands in the circle.
def is_in_circle(__UpperCAmelCase ... | 177 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def _A ( SCREAMING_SNAKE_CASE__ : Optional[int] , SCREAMING_SNAKE_CASE__ : List[str]=() , SCREAMING_SNAKE_CASE__ : ... | 259 | 0 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCame... | 319 |
import sys
def _A ( SCREAMING_SNAKE_CASE__ : List[str] ):
UpperCamelCase :Any = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :Any = [[0 for x in range(SCREAMING_SNAKE_CASE__ )] for x in range(SCREAMING_SNAKE_CASE__ )]
UpperCamelCase ... | 259 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
'''junnyu/roformer_chinese_small''': '''htt... | 131 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case = logging.get_logger(__name__)
__snake_case = """https://... | 259 | 0 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def a_ ( lowerCamelCase ):
UpperCAmelCase__ = SwinConfig(image_size=1_9_2 )
if "base" ... | 98 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.uti... | 259 | 0 |
def UpperCamelCase__ ( A__ ) -> Optional[Any]:
snake_case__ : Optional[int] = len(SCREAMING_SNAKE_CASE__ )
for _ in range(SCREAMING_SNAKE_CASE__ ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
snake... | 143 |
import math
def _A ( SCREAMING_SNAKE_CASE__ : int = 100 ):
UpperCamelCase :Dict = sum(i * i for i in range(1 , n + 1 ) )
UpperCamelCase :List[str] = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return squ... | 259 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.ut... | 91 |
def _A ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
UpperCamelCase :Any = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :str = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :int = [[False for _ in range(m + 1... | 259 | 0 |
'''simple docstring'''
import argparse
import os
import re
lowerCAmelCase: Any = 'src/transformers/models/auto'
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
lowerCAmelCase: str = ... | 297 |
from math import factorial
__snake_case = {str(digit): factorial(digit) for digit in range(10)}
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise TypeError('''Parameter number must be int''' ... | 259 | 0 |
'''simple docstring'''
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.data... | 83 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE... | 259 | 0 |
def A_ ( a , a ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : list[list[str]] = [[] for _ in range(SCREAMING_SNAKE_CASE__ )]
SCREAMING_SNAKE_CASE_ : int = key - 1
if key <= 0:
raise ValueError('Height of grid can\'t be... | 253 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _A ( SCREAMING_SNAKE_CASE__ : str = "isbn/0140328726" ):
UpperCamelCase :Optional[int] = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashe... | 259 | 0 |
import os
def _UpperCamelCase ( ):
__SCREAMING_SNAKE_CASE : Dict = os.path.dirname(os.path.realpath(SCREAMING_SNAKE_CASE__ ) )
__SCREAMING_SNAKE_CASE : Optional[Any] = os.path.join(SCREAMING_SNAKE_CASE__ , '''triangle.txt''' )
... | 9 |
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 259 | 0 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
__snake_... | 320 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
... | 259 | 0 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docstring"""
@staticmethod
@abstractmethod
def _snake_case ( _UpperCAmelCase ):
raise NotImplementedError()
@... | 177 |
import numpy as np
__snake_case = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x""", """y""", """z"""],
]
... | 259 | 0 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> List[str]:
A: Optional[int] = get_failure_array(SCREAMING_SNAKE_CASE__ )
# 2) Step through text searching for pattern
A... | 319 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def _A ( SCREAMING_SNAK... | 259 | 0 |
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,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
to_c... | 131 |
def _A ( SCREAMING_SNAKE_CASE__ : list[int] , SCREAMING_SNAKE_CASE__ : list[int] ):
UpperCamelCase :Tuple = len(SCREAMING_SNAKE_CASE__ )
print('''The following activities are selected:''' )
# The first activity is always selected
UpperCamelCase ... | 259 | 0 |
"""simple docstring"""
def a_ ( lowerCamelCase , lowerCamelCase ):
UpperCAmelCase__ = 0
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ ) - 1
while left <= right:
# avoid divided by 0 during interpolation
if sorted_collect... | 98 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/git-base/resolve/main/config.j... | 259 | 0 |
from __future__ import annotations
from typing import Generic, TypeVar
lowerCAmelCase__ : str = TypeVar('''T''')
class __snake_case ( Generic[T] ):
def __init__( self , __UpperCamelCase ) -> None:
'''simple docstring'''
... | 143 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__snake_case = """__DUMMY_TRANSFORMERS_USER__"""
__snake_case = """Dummy User"""
__snake_case = """hf_hZEmnoOEYISjraJt... | 259 | 0 |
"""simple docstring"""
import numpy as np
UpperCAmelCase_ : Union[str, Any] = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", "... | 91 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask... | 259 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase: Tuple = logging.get_logger(__name__)
lowerCAmelCase: Union[str, Any] = {
'uclanlp/visualbert-vqa': 'https://huggingface.co/uclanlp/visualbert... | 297 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_commo... | 259 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
snake_case_ : Dict = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.... | 83 |
def _A ( ):
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def _A ( SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :Optional[int] = 1
UpperCamelCase :List[Any] = 2
while i * i <= n:
UpperCamelCase :str ... | 259 | 0 |
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_available... | 253 |
def _A ( SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : Optional[Any] ):
# Return True if there is node that has not iterated.
UpperCamelCase :Tuple = [False] * len(SCRE... | 259 | 0 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def _UpperCamelCase ( lowercase__ , lowercase__ , lowercase... | 9 |
from __future__ import annotations
from typing import Any
def _A ( SCREAMING_SNAKE_CASE__ : list[Any] ):
create_state_space_tree(SCREAMING_SNAKE_CASE__ , [] , 0 )
def _A ( SCREAMING_SNAKE_CASE__ : list[Any] , SCREAMING_SNAKE_CASE__ : list[Any] , SCREAMING... | 259 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens... | 320 |
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,
)... | 259 | 0 |
"""simple docstring"""
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone imp... | 177 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def _A ( SCREAMING_SNAKE_CASE__ : Optional[int] , SCREAMING_SNAKE_CASE__ : List[str]=() , SCREAMING_SNAKE_CASE__ : ... | 259 | 0 |
'''simple docstring'''
from __future__ import annotations
import pandas as pd
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase ) -> Tuple:
A: int = [0] * no_of_processes
A: Optional[Any] = [0] * no_of... | 319 |
import sys
def _A ( SCREAMING_SNAKE_CASE__ : List[str] ):
UpperCamelCase :Any = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :Any = [[0 for x in range(SCREAMING_SNAKE_CASE__ )] for x in range(SCREAMING_SNAKE_CASE__ )]
UpperCamelCase ... | 259 | 0 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('''socket.socket''' )
@patch('''builtins.open''' )
def lowerCamelCase_ ( _a , _a ):
"""simple docstring"""
lowerCAmelCase__ : Optional[Any] ... | 131 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case = logging.get_logger(__name__)
__snake_case = """https://... | 259 | 0 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDepe... | 98 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.uti... | 259 | 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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
... | 143 |
import math
def _A ( SCREAMING_SNAKE_CASE__ : int = 100 ):
UpperCamelCase :Dict = sum(i * i for i in range(1 , n + 1 ) )
UpperCamelCase :List[str] = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return squ... | 259 | 0 |
"""simple docstring"""
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .uti... | 91 |
def _A ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
UpperCamelCase :Any = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :str = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :int = [[False for _ in range(m + 1... | 259 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
lowerCAmelCase: Optional[Any] = argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForM... | 297 |
from math import factorial
__snake_case = {str(digit): factorial(digit) for digit in range(10)}
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise TypeError('''Parameter number must be int''' ... | 259 | 0 |
'''simple docstring'''
from __future__ import annotations
snake_case_ : List[str] = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class lowercase__ :
def __init__( self : ... | 83 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE... | 259 | 0 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__ver... | 253 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _A ( SCREAMING_SNAKE_CASE__ : str = "isbn/0140328726" ):
UpperCamelCase :Optional[int] = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashe... | 259 | 0 |
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MAX_SHARD_SIZE
from data... | 9 |
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 259 | 0 |
"""simple docstring"""
def A_ ( _lowerCAmelCase : Union[str, Any], _lowerCAmelCase : List[str], _lowerCAmelCase : int, _lowerCAmelCase : Optional[Any] ):
"""simple docstring"""
_a = [False] * len(SCREAMING_SNAKE_CASE__ )
_a = []
... | 320 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
... | 259 | 0 |
"""simple docstring"""
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
fro... | 177 |
import numpy as np
__snake_case = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x""", """y""", """z"""],
]
... | 259 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {}
try:
if not is_sentencepiece_avail... | 319 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def _A ( SCREAMING_SNAK... | 259 | 0 |
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
... | 131 |
def _A ( SCREAMING_SNAKE_CASE__ : list[int] , SCREAMING_SNAKE_CASE__ : list[int] ):
UpperCamelCase :Tuple = len(SCREAMING_SNAKE_CASE__ )
print('''The following activities are selected:''' )
# The first activity is always selected
UpperCamelCase ... | 259 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def a_ ( lowerCamelCase ):
create_state_space_tree(SCREAMING_SNAKE_CASE__ , [] , 0 )
def a_ ( lowerCamelCase , lowerCamelCase , lowerCamelCase ):
if inde... | 98 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/git-base/resolve/main/config.j... | 259 | 0 |
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffusers.schedulers.scheduling_... | 143 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__snake_case = """__DUMMY_TRANSFORMERS_USER__"""
__snake_case = """Dummy User"""
__snake_case = """hf_hZEmnoOEYISjraJt... | 259 | 0 |
"""simple docstring"""
def _A (__a , __a ) -> Union[str, Any]:
"""simple docstring"""
return int((input_a, input_a).count(0 ) != 0 )
def _A () -> str:
"""simple docstring"""
assert nand_gate(0 , 0 ) == 1
assert... | 91 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask... | 259 | 0 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pyt... | 297 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_commo... | 259 | 0 |
'''simple docstring'''
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def A__ ( UpperCAmelCase_ = "isbn/0140328726" ):
_UpperCamelCase : Optional[int] = olid.strip().strip('/' ) # Remove leading/trailing whitespace &... | 83 |
def _A ( ):
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def _A ( SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :Optional[int] = 1
UpperCamelCase :List[Any] = 2
while i * i <= n:
UpperCamelCase :str ... | 259 | 0 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def A_ ( a , ... | 253 |
def _A ( SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : Optional[Any] ):
# Return True if there is node that has not iterated.
UpperCamelCase :Tuple = [False] * len(SCRE... | 259 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : List[Any] =logging.get_logger(__name__)
__lowerCAmelCase : int ={
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class _lowercase ... | 9 |
from __future__ import annotations
from typing import Any
def _A ( SCREAMING_SNAKE_CASE__ : list[Any] ):
create_state_space_tree(SCREAMING_SNAKE_CASE__ , [] , 0 )
def _A ( SCREAMING_SNAKE_CASE__ : list[Any] , SCREAMING_SNAKE_CASE__ : list[Any] , SCREAMING... | 259 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vi... | 320 |
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,
)... | 259 | 0 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 177 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def _A ( SCREAMING_SNAKE_CASE__ : Optional[int] , SCREAMING_SNAKE_CASE__ : List[str]=() , SCREAMING_SNAKE_CASE__ : ... | 259 | 0 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers... | 319 |
import sys
def _A ( SCREAMING_SNAKE_CASE__ : List[str] ):
UpperCamelCase :Any = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :Any = [[0 for x in range(SCREAMING_SNAKE_CASE__ )] for x in range(SCREAMING_SNAKE_CASE__ )]
UpperCamelCase ... | 259 | 0 |
from typing import List
import numpy as np
def lowerCamelCase_ ( _a ):
"""simple docstring"""
lowerCAmelCase__ : int = {key: len(SCREAMING_SNAKE_CASE__ ) for key, value in gen_kwargs.items() if isinstance(SCREAMING_SNAKE_CASE__ , ... | 131 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case = logging.get_logger(__name__)
__snake_case = """https://... | 259 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ..... | 98 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.uti... | 259 | 0 |
import math
from datetime import datetime, timedelta
def UpperCamelCase__ ( A__ ) -> Union[str, Any]:
snake_case__ : int = year % 19
snake_case__ : Union[str, Any] = year % 4
snake_case__ : int = year % 7
snake_case__ ... | 143 |
import math
def _A ( SCREAMING_SNAKE_CASE__ : int = 100 ):
UpperCamelCase :Dict = sum(i * i for i in range(1 , n + 1 ) )
UpperCamelCase :List[str] = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return squ... | 259 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase_ : Dict = {
"""google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/conf... | 91 |
def _A ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
UpperCamelCase :Any = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :str = len(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :int = [[False for _ in range(m + 1... | 259 | 0 |
'''simple docstring'''
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
... | 297 |
from math import factorial
__snake_case = {str(digit): factorial(digit) for digit in range(10)}
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise TypeError('''Parameter number must be int''' ... | 259 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
snake_case_ : List[str] = logging.get_logger(__name__)
def A__ ( UpperCAmelCase_ ):
if isinstance(SCREAMING_SNAKE_CASE__ , np.ndarray ):... | 83 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE... | 259 | 0 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowerCAmelCase : Any = False
class _A ( unittest.TestCase):
pass... | 253 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _A ( SCREAMING_SNAKE_CASE__ : str = "isbn/0140328726" ):
UpperCamelCase :Optional[int] = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashe... | 259 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
RandomHorizontalFlip,
... | 9 |
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 259 | 0 |
"""simple docstring"""
from __future__ import annotations
def A_ ( _lowerCAmelCase : int ):
"""simple docstring"""
_a = str(SCREAMING_SNAKE_CASE__ )
return len(SCREAMING_SNAKE_CASE__ ) == 9 and set(SCREAMING_SNAKE_CASE__ ) == set('''123456789''' )
de... | 320 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
... | 259 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/git-base": "https://huggingface.co/microsoft/git-base/resolve/main/config.json",
}
class ... | 177 |
import numpy as np
__snake_case = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x""", """y""", """z"""],
]
... | 259 | 0 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = lo... | 319 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def _A ( SCREAMING_SNAK... | 259 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ..... | 131 |
def _A ( SCREAMING_SNAKE_CASE__ : list[int] , SCREAMING_SNAKE_CASE__ : list[int] ):
UpperCamelCase :Tuple = len(SCREAMING_SNAKE_CASE__ )
print('''The following activities are selected:''' )
# The first activity is always selected
UpperCamelCase ... | 259 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
lowerCAmelCase__ : str = logging.get_l... | 98 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/git-base/resolve/main/config.j... | 259 | 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 __snake_case ( unittest.TestCase ):
def __a ( self ) -> List[Any]:
... | 143 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__snake_case = """__DUMMY_TRANSFORMERS_USER__"""
__snake_case = """Dummy User"""
__snake_case = """hf_hZEmnoOEYISjraJt... | 259 | 0 |
"""simple docstring"""
import random
def _A (__a , __a , __a = False ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : dict = {i: [] for i in range(SCREAMING_SNAKE_CASE__ )}
# if probability is greater or equal than 1, then g... | 91 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask... | 259 | 0 |
'''simple docstring'''
from math import factorial, radians
def lowerCamelCase__ ( _A , _A = 18 , _A = 10 ):
a : Dict = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Converting from degrees to radians
a : Dict = radians(SCREAMI... | 297 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_commo... | 259 | 0 |
'''simple docstring'''
import cmath
import math
def A__ ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ ):
_UpperCamelCase : Dict = math.radians(SCREAMING_SNAKE_CASE__ )
_UpperCamelCase : int = math.radians(SCREAMING_SNAKE_CASE... | 83 |
def _A ( ):
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def _A ( SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :Optional[int] = 1
UpperCamelCase :List[Any] = 2
while i * i <= n:
UpperCamelCase :str ... | 259 | 0 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common imp... | 253 |
def _A ( SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : Optional[Any] ):
# Return True if there is node that has not iterated.
UpperCamelCase :Tuple = [False] * len(SCRE... | 259 | 0 |
def _UpperCamelCase ( lowercase__ , lowercase__ ):
__SCREAMING_SNAKE_CASE : Any = len(SCREAMING_SNAKE_CASE__ )
__SCREAMING_SNAKE_CASE : str = len(SCREAMING_SNAKE_CASE__ )
__SCREAMING_SNAKE_CASE : int = [[False for _... | 9 |
from __future__ import annotations
from typing import Any
def _A ( SCREAMING_SNAKE_CASE__ : list[Any] ):
create_state_space_tree(SCREAMING_SNAKE_CASE__ , [] , 0 )
def _A ( SCREAMING_SNAKE_CASE__ : list[Any] , SCREAMING_SNAKE_CASE__ : list[Any] , SCREAMING... | 259 | 0 |
"""simple docstring"""
import socket
def lowercase ( ):
'''simple docstring'''
_UpperCAmelCase = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_UpperCAmelCase = socket.gethostname()
_UpperCAmelCase = 1_2312
... | 260 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..... | 260 | 1 |
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