code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
__UpperCamelCase : Optional[Any] = logging.getLogge... | 4 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 4 | 1 |
"""simple docstring"""
from __future__ import annotations
import requests
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
lowerCAmelCase = F'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
return requests.get(_UpperCAmelCase ).json()
def _SCREAMING_SNAKE_C... | 4 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__UpperCamelCase : Union[str, Any] = '''examples/'''
__UpperCamelCase : str = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_v... | 4 | 1 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 4 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import re... | 4 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipelin... | 4 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 4 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin
... | 4 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 4 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Dict = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_M... | 4 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', ... | 4 | 1 |
"""simple docstring"""
class a :
def __init__( self , _snake_case ):
"""simple docstring"""
lowerCAmelCase = set_counts
lowerCAmelCase = max(_snake_case )
lowerCAmelCase = len(_snake_case )
lowerCAmelCase = [1] * num_sets
... | 4 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : ... | 4 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 4 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipelin... | 4 | 1 |
"""simple docstring"""
from datetime import datetime as dt
import os
from github import Github
__UpperCamelCase : Optional[Any] = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
de... | 4 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common i... | 4 | 1 |
"""simple docstring"""
import qiskit
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : int , _UpperCAmelCase : int ):
lowerCAmelCase = qiskit.Aer.get_backend('aer_simulator' )
lowerCAmelCase = qiskit.QuantumCircuit(4 , 2 )
# encode inputs in qubits 0 and 1
if bita ... | 4 |
"""simple docstring"""
from typing import Any
class a :
def __init__( self , _snake_case ):
"""simple docstring"""
lowerCAmelCase = data
lowerCAmelCase = None
def __repr__( self ):
"""simple docstring"""
return F... | 4 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__UpperCamelCase : Union[str, Any] = ... | 4 |
"""simple docstring"""
from __future__ import annotations
import requests
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
lowerCAmelCase = F'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
return requests.get(_UpperCAmelCase ).json()
def _SCREAMING_SNAKE_C... | 4 | 1 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, s... | 4 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : ... | 4 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from... | 4 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
__UpperCamelCase : List[Any] = {
# See all MEGATRON_BERT models at https://huggingface.co/model... | 4 | 1 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__UpperCamelCase : Optional[Any] = logging.get_logger('''transformers.models.speecht5''')
def _SCREAMING_SNAKE_C... | 4 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 4 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCamelCase : Optional[Any] = logging.get_logger(__name... | 4 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decod... | 4 | 1 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common imp... | 4 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__UpperCamelCase : Optional[Any] = tuple[int, int]
class a :
def __init__( self , _snake_case , _snake_case ):
"""simple docstri... | 4 | 1 |
"""simple docstring"""
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
__UpperCamelCase : int = TypeVar('''T''')
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : int ):
return (position - 1) // 2
def _SCREAMING_SNAKE_CASE (_Upp... | 4 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : list , _UpperCAmelCase : list , _UpperCAmelCase ... | 4 | 1 |
"""simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
Ber... | 4 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def _SCREAMING_SNAKE_CASE ... | 4 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import ceil, floor, sqrt
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : int = 200_0000 ):
lowerCAmelCase = [0]
lowerCAmelCase = 42
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ):
triangle_numbers... | 4 |
"""simple docstring"""
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
__UpperCamelCase : List[Any] = logg... | 4 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Optional[int] = logging.get_logger(__name__)
__UpperCamelCase : Dict = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/big... | 4 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__UpperCamelCase : Dict = {'''processing_layo... | 4 | 1 |
"""simple docstring"""
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
__UpperCamelCase : List[Any] = datasets.logging.get_logger(__name__)
__UpperCamelCase : Union[str, Any] = '''\
@inproceedings{bleur... | 4 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : list[float] ):
lowerCAmelCase = 0.00
lowerCAmelCase = 0
for resistor in resistors:
if resistor <= 0:
lowerCAmelCase = F'Resistor at index {index} has a negative or zero... | 4 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__UpperCamelCase : Optional[Any] = {
'''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig''... | 4 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : List[str] = logging.get_logger(__name__)
__UpperCamelCase : Tuple = {
'''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-k... | 4 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
lowerCAmelCase ,lowerCAmelCase = analyze_text(_UpperCAmelCase )
lowerCAmelCase = list(' '... | 4 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 4 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=a__ )
class a ( a__ ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output fo... | 4 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__UpperCamelCase : Union[str, Any] = '''examples/'''
__UpperCamelCase : str = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_v... | 4 | 1 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 4 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import re... | 4 | 1 |
"""simple docstring"""
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : List[Any] ... | 4 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 4 | 1 |
"""simple docstring"""
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def _SCREAMING_SNAKE_CASE ():
lowerCAmelCase ,lowerCAmelCase = 9, 14 # noqa: F841
lowerCAmelCase = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, ... | 4 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 4 | 1 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class a ( a__ , unittest.TestCas... | 4 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', ... | 4 | 1 |
"""simple docstring"""
from __future__ import annotations
class a :
def __init__( self , _snake_case , _snake_case ):
"""simple docstring"""
lowerCAmelCase ,lowerCAmelCase = text, pattern
lowerCAmelCase ,lowerCAmelCase = len(_... | 4 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : ... | 4 | 1 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokeniza... | 4 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipelin... | 4 | 1 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
__UpperCamelCase : int ... | 4 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common i... | 4 | 1 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__UpperCamelCase : str = 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_co... | 4 |
"""simple docstring"""
from typing import Any
class a :
def __init__( self , _snake_case ):
"""simple docstring"""
lowerCAmelCase = data
lowerCAmelCase = None
def __repr__( self ):
"""simple docstring"""
return F... | 4 | 1 |
"""simple docstring"""
from __future__ import annotations
__UpperCamelCase : List[str] = '''#'''
class a :
def __init__( self ):
"""simple docstring"""
lowerCAmelCase = {}
def UpperCamelCase__ ( self , _snake_case ... | 4 |
"""simple docstring"""
from __future__ import annotations
import requests
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
lowerCAmelCase = F'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
return requests.get(_UpperCAmelCase ).json()
def _SCREAMING_SNAKE_C... | 4 | 1 |
"""simple docstring"""
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixi... | 4 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : ... | 4 | 1 |
"""simple docstring"""
# Algorithm for the pigeonhole sorting
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
lowerCAmelCase = min(_UpperCAmelCase ) # min() finds the minimum value
lowerCAmelCase = max(_UpperCAmelCase ) # max() finds the maximum value
lowerCAmelCase ... | 4 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
__UpperCamelCase : List[Any] = {
# See all MEGATRON_BERT models at https://huggingface.co/model... | 4 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
__UpperCamelCase : Union[str, Any] = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPas... | 4 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 4 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCamelCase : Optional[Any] = {
'''configuration_... | 4 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decod... | 4 | 1 |
"""simple docstring"""
import math
import os
import sys
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
lowerCAmelCase = ''
try:
with open(_UpperCAmelCase , 'rb' ) as binary_file:
lowerCAmelCase = binary_file.read()
for dat in data:
lowerCAmelCase = F'{dat... | 4 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__UpperCamelCase : Optional[Any] = tuple[int, int]
class a :
def __init__( self , _snake_case , _snake_case ):
"""simple docstri... | 4 | 1 |
"""simple docstring"""
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__UpperCamelCase : int = logging.get_logger(__name__)
def _SCREAMING_SNAKE_CASE (_Upper... | 4 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : list , _UpperCAmelCase : list , _UpperCAmelCase ... | 4 | 1 |
"""simple docstring"""
class a :
def __init__( self , _snake_case ):
"""simple docstring"""
lowerCAmelCase = size
lowerCAmelCase = [0] * size
lowerCAmelCase = [0] * size
@staticmethod
def UpperCamelCase__ ( _snake_case ):
... | 4 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def _SCREAMING_SNAKE_CASE ... | 4 | 1 |
"""simple docstring"""
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
__UpperCamelCase : List[Any] = logg... | 4 |
"""simple docstring"""
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
__UpperCamelCase : List[Any] = logg... | 4 | 1 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class a ( a__ ):
def __init__( self , _snake_case , _snake_case , _snake_case ):
"""simple doc... | 4 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__UpperCamelCase : Dict = {'''processing_layo... | 4 | 1 |
"""simple docstring"""
class a :
def __init__( self , _snake_case ):
"""simple docstring"""
lowerCAmelCase = arr.split(',' )
def UpperCamelCase__ ( self ):
"""simple docstring"""
lowerCAmelCase = [int(self.array[0... | 4 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : list[float] ):
lowerCAmelCase = 0.00
lowerCAmelCase = 0
for resistor in resistors:
if resistor <= 0:
lowerCAmelCase = F'Resistor at index {index} has a negative or zero... | 4 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : ... | 4 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : List[str] = logging.get_logger(__name__)
__UpperCamelCase : Tuple = {
'''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-k... | 4 | 1 |
"""simple docstring"""
from typing import Any
class a :
def __init__( self , _snake_case ):
"""simple docstring"""
lowerCAmelCase = data
lowerCAmelCase = None
def __repr__( self ):
"""simple docstring"""
return F... | 4 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 4 | 1 |
"""simple docstring"""
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_M... | 4 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__UpperCamelCase : Union[str, Any] = '''examples/'''
__UpperCamelCase : str = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_v... | 4 | 1 |
"""simple docstring"""
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str , _UpperCAmelCase : Any ):
lowerCAmelCase = ... | 4 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import re... | 4 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCamelCase : Optional[int] = {'''configuration_reformer''': ['''... | 4 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 4 | 1 |
"""simple docstring"""
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... | 4 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 4 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cud... | 4 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', ... | 4 | 1 |
"""simple docstring"""
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelD... | 4 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : ... | 4 | 1 |
"""simple docstring"""
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
__UpperCamelCase : Tuple = yaml.safe_load(
'''\
name: ""
allow_empty: false
allow_empty_text... | 4 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipelin... | 4 | 1 |
"""simple docstring"""
import os
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str = "input.txt" ):
with open(os.path.join(os.path.dirname(_UpperCAmelCase ) , _UpperCAmelCase ) ) as input_file:
lowerCAmelCase = [
[int(_UpperCAmelCase ) for element in line.split(',' )]
... | 4 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common i... | 4 | 1 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common i... | 4 |
"""simple docstring"""
from typing import Any
class a :
def __init__( self , _snake_case ):
"""simple docstring"""
lowerCAmelCase = data
lowerCAmelCase = None
def __repr__( self ):
"""simple docstring"""
return F... | 4 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCamelCase : Any = {... | 4 |
"""simple docstring"""
from __future__ import annotations
import requests
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
lowerCAmelCase = F'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
return requests.get(_UpperCAmelCase ).json()
def _SCREAMING_SNAKE_C... | 4 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCamelCase : List[Any] = {'''configuration_... | 4 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : ... | 4 | 1 |
"""simple docstring"""
import math
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : float , _UpperCAmelCase : float ):
if (
not isinstance(_UpperCAmelCase , (int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError('power_factor must be a valid flo... | 4 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
__UpperCamelCase : List[Any] = {
# See all MEGATRON_BERT models at https://huggingface.co/model... | 4 | 1 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__UpperCamelCase : Optional[int] = [
# tf -> hf
('''/''', '''.'''),
... | 4 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 4 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class a ( metaclass=a__ ):
snake_case__ = ['''flax''', '''transformers''']
def __init__( self , *_snake_case , **_snake_case ):
"""simple docstring"""
r... | 4 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decod... | 4 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class a ( unitte... | 4 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__UpperCamelCase : Optional[Any] = tuple[int, int]
class a :
def __init__( self , _snake_case , _snake_case ):
"""simple docstri... | 4 | 1 |
"""simple docstring"""
from __future__ import annotations
from cmath import sqrt
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : int , _UpperCAmelCase : int , _UpperCAmelCase : int ):
if a == 0:
raise ValueError('Coefficient \'a\' must not be zero.' )
lowerCAmelCase ... | 4 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : list , _UpperCAmelCase : list , _UpperCAmelCase ... | 4 | 1 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : int , _UpperCAmelCase : int ):
return int((input_a, input_a).count(1 ) != 0 )
def _SCREAMING_SNAKE_CASE ():
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ) == 1
assert or_gate(1 , 0 ) ... | 4 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def _SCREAMING_SNAKE_CASE ... | 4 | 1 |
"""simple docstring"""
import os
# Precomputes a list of the 100 first triangular numbers
__UpperCamelCase : Optional[int] = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def _SCREAMING_SNAKE_CASE ():
lowerCAmelCase = os.path.dirname(os.path.realpath(_UpperCAmelCase ) )
... | 4 |
"""simple docstring"""
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
__UpperCamelCase : List[Any] = logg... | 4 | 1 |
"""simple docstring"""
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_subproces... | 4 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__UpperCamelCase : Dict = {'''processing_layo... | 4 | 1 |
"""simple docstring"""
from collections import deque
class a :
def __init__( self , _snake_case , _snake_case , _snake_case ):
"""simple docstring"""
lowerCAmelCase = process_name # process name
lowerCAmelCase = arrival_ti... | 4 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : list[float] ):
lowerCAmelCase = 0.00
lowerCAmelCase = 0
for resistor in resistors:
if resistor <= 0:
lowerCAmelCase = F'Resistor at index {index} has a negative or zero... | 4 | 1 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : int , _UpperCAmelCase : int ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(_UpperCAmelCase , int(b / 2 ) ) * actual_power(_UpperCAmelCase , int(b / 2 ) )
else:
return a * actual_pow... | 4 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : List[str] = logging.get_logger(__name__)
__UpperCamelCase : Tuple = {
'''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-k... | 4 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCamelCase : str = {
'''configuration_deberta''': ['''DEBERTA_PRETRAINE... | 4 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 4 | 1 |
"""simple docstring"""
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : Optional[Any]... | 4 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__UpperCamelCase : Union[str, Any] = '''examples/'''
__UpperCamelCase : str = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_v... | 4 | 1 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class a ( tf.keras.layers.Layer ):
def __init__( ... | 4 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import re... | 4 | 1 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import re... | 4 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 4 | 1 |
"""simple docstring"""
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 4 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 4 | 1 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
__UpperCamelCase : Any = logging.get_logger(__name__)
__UpperCamelCase : Optional[Any] = {
'''Intel/dpt-large''': '''h... | 4 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', ... | 4 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Any = {
'''configuration_blip_2''': [
'''BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Blip2Config''',
... | 4 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : ... | 4 | 1 |
"""simple docstring"""
from scipy.stats import pearsonr
import datasets
__UpperCamelCase : Tuple = '''
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the... | 4 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipelin... | 4 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
__UpperCamelCase : List[Any] = {
# See all MEGATRON_BERT models at https://huggingface.co/model... | 4 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common i... | 4 | 1 |
"""simple docstring"""
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
__UpperCamelCase : Union[str, Any] = (
'''4S 3H 2C 7S 5H''',
'''9D 8H 2C 6S 7H''',
'''2D 6D 9D TH 7D''',
'''TC 8C 2S JH 6C''',
'... | 4 |
"""simple docstring"""
from typing import Any
class a :
def __init__( self , _snake_case ):
"""simple docstring"""
lowerCAmelCase = data
lowerCAmelCase = None
def __repr__( self ):
"""simple docstring"""
return F... | 4 | 1 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
__UpperCamelCase : int = TypeVar('''T''')
__UpperCamelCase : Union[str, Any] = Union[List[T], Tuple[T, ...]]
__UpperCamelCase : int = Union[T, List[T], Dict[st... | 4 |
"""simple docstring"""
from __future__ import annotations
import requests
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
lowerCAmelCase = F'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
return requests.get(_UpperCAmelCase ).json()
def _SCREAMING_SNAKE_C... | 4 | 1 |
"""simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trus... | 4 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : ... | 4 | 1 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : List[Any] ):
lowerCAmelCase = test_file.split... | 4 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
__UpperCamelCase : List[Any] = {
# See all MEGATRON_BERT models at https://huggingface.co/model... | 4 | 1 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils ... | 4 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 4 | 1 |
def __lowercase ( snake_case, snake_case ):
"""simple docstring"""
__magic_name__ :Tuple = (boundary[1] - boundary[0]) / steps
__magic_name__ :Optional[int] = boundary[0]
__magic_name__ :Tuple = boundary[1]
__magic_name__ :Union[str, Any] = make_po... | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decod... | 4 | 0 |
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common i... | 1 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
__UpperCamelCase : Optional[Any] = tuple[int, int]
class a :
def __init__( self , _snake_case , _snake_case ):
"""simple docstri... | 4 | 0 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
UpperCAmelCase_ = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Ale... | 2 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : list , _UpperCAmelCase : list , _UpperCAmelCase ... | 4 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Dict = logging.get_logger(__name__)
lowerCAmelCase : Optional[Any] = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/con... | 3 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def _SCREAMING_SNAKE_CASE ... | 4 | 0 |
'''simple docstring'''
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import float... | 5 |
"""simple docstring"""
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
__UpperCamelCase : List[Any] = logg... | 4 | 0 |
from __future__ import annotations
from collections.abc import Iterator
class UpperCamelCase_ :
def __init__( self :Any , __A :int ) -> None:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = value
SCREAMING_SNAKE_CASE__ = No... | 6 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__UpperCamelCase : Dict = {'''processing_layo... | 4 | 0 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def _snake_case ( _snake_case : float ) -> float:
'''simple docstring'''
if num <= 0:
raise ValueError('math domain error' )
return quad(_snake_case ... | 7 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : list[float] ):
lowerCAmelCase = 0.00
lowerCAmelCase = 0
for resistor in resistors:
if resistor <= 0:
lowerCAmelCase = F'Resistor at index {index} has a negative or zero... | 4 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 8 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : List[str] = logging.get_logger(__name__)
__UpperCamelCase : Tuple = {
'''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-k... | 4 | 0 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
def __init__( self : Dict , *_snake_cas... | 9 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 4 | 0 |
def _snake_case ( __snake_case ):
_UpperCamelCase = len(__snake_case )
_UpperCamelCase = sum(__snake_case )
_UpperCamelCase = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1 , n + 1 ):
_Upp... | 10 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__UpperCamelCase : Union[str, Any] = '''examples/'''
__UpperCamelCase : str = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_v... | 4 | 0 |
'''simple docstring'''
import numpy as np
def lowerCAmelCase (__A , __A , __A , __A , __A):
"""simple docstring"""
_a = int(np.ceil((x_end - xa) / h))
_a = np.zeros((n + 1,))
_a = ya
_a = x... | 11 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import re... | 4 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
lowerCamelCase__ : int = logging.get_logger(__name__)... | 12 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 4 | 0 |
'''simple docstring'''
from collections.abc import Sequence
from queue import Queue
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_=None , SCREAMING... | 13 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 4 | 0 |
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, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_... | 14 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', ... | 4 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 15 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : ... | 4 | 0 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from... | 16 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipelin... | 4 | 0 |
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
UpperCAmelCase_ : Any = loggin... | 17 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common i... | 4 | 0 |
'''simple docstring'''
def __a(SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ):
'''simple docstring'''
_lowerCAmelCase = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
_lowerCAmelCase ... | 18 |
"""simple docstring"""
from typing import Any
class a :
def __init__( self , _snake_case ):
"""simple docstring"""
lowerCAmelCase = data
lowerCAmelCase = None
def __repr__( self ):
"""simple docstring"""
return F... | 4 | 0 |
"""simple docstring"""
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
_a = datasets.load_iris()
_a = np.array(data["""data"""])
_a = np.array(data["""target"""])
_a ... | 19 |
"""simple docstring"""
from __future__ import annotations
import requests
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
lowerCAmelCase = F'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
return requests.get(_UpperCAmelCase ).json()
def _SCREAMING_SNAKE_C... | 4 | 0 |
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_common import OnnxPipelineT... | 20 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : ... | 4 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.