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'''
from math import pi
def lowerCamelCase ( lowerCamelCase : int , lowerCamelCase : int):
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 665 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase = {
'''configuration_owlvit''': [
... | 119 | 0 |
'''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, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase_ : List[str] = logging.get... | 331 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 119 | 0 |
"""simple docstring"""
def __snake_case ( _lowercase ,_lowercase ):
"""simple docstring"""
return 1 if input_a == input_a else 0
def __snake_case ( ):
"""simple docstring"""
assert xnor_gate(0 ,0 ) == 1
assert xnor_gate(0 ,1 ) == 0
... | 34 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : float, lowercase__ : float, lowercase__ : float ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('One and on... | 119 | 0 |
'''simple docstring'''
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers.utils i... | 384 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : list[int] ):
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
__lowercase =sum(lowercase__ ) / len(lowercase__ ) # Calculate ... | 119 | 0 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from torch i... | 14 |
'''simple docstring'''
import string
def __UpperCamelCase ( lowercase__ : str ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__lowercase =''
for symbol in message:
if symbol in string.ascii_uppercase:
... | 119 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_... | 346 |
'''simple docstring'''
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto... | 119 | 0 |
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_tf_auto import TF_MOD... | 658 |
'''simple docstring'''
class lowerCAmelCase :
def __init__( self : List[Any] , __lowercase : str , __lowercase : Any , __lowercase : str ):
"""simple docstring"""
__lowercase =name
__lowercase ... | 119 | 0 |
from typing import Any
import numpy as np
def UpperCamelCase__ ( lowerCAmelCase__ ):
return np.array_equal(lowercase__ ,matrix.conjugate().T )
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ):
lowercase = v.conjugate().T
lowercase = v... | 428 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils... | 119 | 0 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
A_ = logging.get_logger(__name__)
class __lowercase ( _A ):
def __init__( self : Optional[int] , *__lowerCamelCase : Union[str, Any] ... | 604 |
'''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__)
UpperCAmelCase = {
'''shi-labs/dinat-mini-in1k-224... | 119 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowercase__ ( metaclass=SCREAMING_SNAKE_CASE ):
'''simple docstring'''
UpperCamelCase = ['''torch''', '''scipy''']
def __init__( self : Any , ... | 82 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 119 | 0 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModel... | 145 |
'''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 = logging.get_logger(__name__)
UpperCAmel... | 119 | 0 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : Any):
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6, 8],
... | 665 |
'''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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosit... | 119 | 0 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase (_lowercase ):
"""simple docstring"""
if not nums:
return 0
a__ = nums[0]
a__ = 0
for num in nums[1:]:
a__ , ... | 331 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available... | 119 | 0 |
"""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
SCREAMING_SNAKE_CASE_ = logging.get_logger... | 34 |
'''simple docstring'''
import os
from collections.abc import Iterator
def __UpperCamelCase ( lowercase__ : str = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(lowercase__ ):
__lowercase =[d for d in dir_names if d != 'scripts' a... | 119 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( _lowerCamelCase : str , _lowerCamelCase : str ) -> Tuple:
def get_matched_characters(_lowerCamelCase : str , _lowerCamelCase : str ) -> str:
_lowerCAmelCase : Any = []
_lowerCAmelCas... | 384 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def __UpperCamelCase ( lowercase__ : int = 1_50_00_00 ):
'''simple docstring'''
__lowercase =defaultdict(lowercase__ )
__lowercase =2
while 2 * euclid_m * (euclid_m + 1) <... | 119 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common im... | 14 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def __UpperCamelCase ( lowercase__ : Optional[Any] ):
'''simple docstring'''
for i in range(0, lowercase__ ):
for _ in range(0, n - i - 1 ): # printing spaces
p... | 119 | 0 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
requi... | 346 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils imp... | 119 | 0 |
from math import sqrt
def _A ( SCREAMING_SNAKE_CASE__ : int ):
assert isinstance(lowercase__ , lowercase__ ) and (
number >= 0
), "'number' must been an int and positive"
UpperCamelCase :Optional[int] = True
# 0 and 1 are none primes.
if numbe... | 658 |
'''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 lowerCAmelCase ( A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSO... | 119 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, ... | 428 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if n == 1 or not isinstance(lowercase__, lowercase__ ):
return 0
elif n == 2:
return 1
else:
__lowercase =[0, 1]
for i in r... | 119 | 0 |
from __future__ import annotations
def __UpperCAmelCase ( UpperCAmelCase )-> Tuple:
"""simple docstring"""
create_state_space_tree(lowercase__, [], 0, [0 for i in range(len(lowercase__ ) )] )
def __UpperCAmelC... | 604 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : List[str], lowercase__ : Tuple ):
'''simple docstring'''
__lowercase =[0 for i in range(r + 1 )]
# nc0 = 1
__lowercase =1
for i in range(1, n + 1 ):
# to comput... | 119 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""",
... | 82 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase ( unittest.TestCase ):
... | 119 | 0 |
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,
AutoencoderKL,
... | 145 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
__lowercase =[0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__... | 119 | 0 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def _a ( self : List[Any] ):
'''simple docstr... | 665 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase = {
'''configuration_owlvit''': [
... | 119 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils i... | 331 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 119 | 0 |
"""simple docstring"""
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
SCREAMING_SNAKE_CASE_ = importlib.util.find_spec('s3fs') is not None
if _has_safs:
... | 34 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : float, lowercase__ : float, lowercase__ : float ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('One and on... | 119 | 0 |
'''simple docstring'''
import argparse
import os
import re
UpperCamelCase_ = """src/transformers/models/auto"""
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
UpperCamelCase_ = re.compile(r"""[A-Z_]+_MAPP... | 384 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : list[int] ):
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
__lowercase =sum(lowercase__ ) / len(lowercase__ ) # Calculate ... | 119 | 0 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backb... | 14 |
'''simple docstring'''
import string
def __UpperCamelCase ( lowercase__ : str ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__lowercase =''
for symbol in message:
if symbol in string.ascii_uppercase:
... | 119 | 0 |
"""simple docstring"""
def a__ ( __SCREAMING_SNAKE_CASE ) -> Optional[int]:
__lowerCAmelCase: Dict = set()
# edges = list of graph's edges
__lowerCAmelCase: Any = get_edges(lowercase__ )
# While there are still elements in edges list,... | 346 |
'''simple docstring'''
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto... | 119 | 0 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__snake_case = pytest.mark.integration
@pytest.mark.parametrize('''path''' , ['''paws''', '''c... | 658 |
'''simple docstring'''
class lowerCAmelCase :
def __init__( self : List[Any] , __lowercase : str , __lowercase : Any , __lowercase : str ):
"""simple docstring"""
__lowercase =name
__lowercase ... | 119 | 0 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import DPRCo... | 428 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils... | 119 | 0 |
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def __UpperCAm... | 604 |
'''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__)
UpperCAmelCase = {
'''shi-labs/dinat-mini-in1k-224... | 119 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_deter... | 82 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 119 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_a : Optional[int] = {"""configuration_mmbt""": ["""MMBTConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvaila... | 145 |
'''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 = logging.get_logger(__name__)
UpperCAmel... | 119 | 0 |
'''simple docstring'''
__magic_name__ = [
'Audio',
'Array2D',
'Array3D',
'Array4D',
'Array5D',
'ClassLabel',
'Features',
'Sequence',
'Value',
'Image',
'Translation',
'TranslationVariableLanguages',
]
from .audio import Audio
from .features import ArrayaD, Ar... | 665 |
'''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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosit... | 119 | 0 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set... | 331 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available... | 119 | 0 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Pa... | 34 |
'''simple docstring'''
import os
from collections.abc import Iterator
def __UpperCamelCase ( lowercase__ : str = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(lowercase__ ):
__lowercase =[d for d in dir_names if d != 'scripts' a... | 119 | 0 |
'''simple docstring'''
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state impo... | 384 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def __UpperCamelCase ( lowercase__ : int = 1_50_00_00 ):
'''simple docstring'''
__lowercase =defaultdict(lowercase__ )
__lowercase =2
while 2 * euclid_m * (euclid_m + 1) <... | 119 | 0 |
import string
from math import logaa
def __UpperCAmelCase ( __a : str ,__a : str ) -> Union[str, Any]:
"""simple docstring"""
_a : Any = document.translate(
str.maketrans('''''' ,'''''' ,string.punctuation ) ).r... | 14 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def __UpperCamelCase ( lowercase__ : Optional[Any] ):
'''simple docstring'''
for i in range(0, lowercase__ ):
for _ in range(0, n - i - 1 ): # printing spaces
p... | 119 | 0 |
"""simple docstring"""
import os
import sys
import unittest
__A = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_o... | 346 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils imp... | 119 | 0 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class UpperCAmelCase_ ( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase ( self ) -> Dict:
... | 658 |
'''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 lowerCAmelCase ( A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSO... | 119 | 0 |
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ = False ):
if not isinstance(lowercase__ ,lowercase__ ):
lowercase = f"""Expected string as input, found {type(lowercase__ )}"""
raise ValueError(lowercase__ )
if not isinstance(lowercase__ ... | 428 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if n == 1 or not isinstance(lowercase__, lowercase__ ):
return 0
elif n == 2:
return 1
else:
__lowercase =[0, 1]
for i in r... | 119 | 0 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
... | 604 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : List[str], lowercase__ : Tuple ):
'''simple docstring'''
__lowercase =[0 for i in range(r + 1 )]
# nc0 = 1
__lowercase =1
for i in range(1, n + 1 ):
# to comput... | 119 | 0 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
UpperCamelCase = '''ClapFeatureExtractor'''
UpperCamelCase... | 82 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase ( unittest.TestCase ):
... | 119 | 0 |
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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
_a : O... | 145 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
__lowercase =[0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__... | 119 | 0 |
'''simple docstring'''
from math import factorial
def lowerCamelCase ( lowerCamelCase : int = 100):
return sum(int(lowercase__) for x in str(factorial(lowercase__)))
if __name__ == "__main__":
print(solution(int(input('Enter the Number: ').strip())))
| 665 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase = {
'''configuration_owlvit''': [
... | 119 | 0 |
'''simple docstring'''
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_t... | 331 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 119 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_at... | 34 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : float, lowercase__ : float, lowercase__ : float ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('One and on... | 119 | 0 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,... | 384 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : list[int] ):
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
__lowercase =sum(lowercase__ ) / len(lowercase__ ) # Calculate ... | 119 | 0 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class UpperCAmelCase_ ( unittest.TestCase ):
"""simple docstring"""
... | 14 |
'''simple docstring'''
import string
def __UpperCamelCase ( lowercase__ : str ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__lowercase =''
for symbol in message:
if symbol in string.ascii_uppercase:
... | 119 | 0 |
"""simple docstring"""
from __future__ import annotations
__A = list[tuple[int, int]]
__A = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, 0, 0, 0, 0],
[0, 0, ... | 346 |
'''simple docstring'''
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto... | 119 | 0 |
def _A ( SCREAMING_SNAKE_CASE__ : list , SCREAMING_SNAKE_CASE__ : list , SCREAMING_SNAKE_CASE__ : int ):
if len(lowercase__ ) != len(lowercase__ ):
raise ValueError('''The length of profit and weight must be same.''' )
if max_weight <= 0:
... | 658 |
'''simple docstring'''
class lowerCAmelCase :
def __init__( self : List[Any] , __lowercase : str , __lowercase : Any , __lowercase : str ):
"""simple docstring"""
__lowercase =name
__lowercase ... | 119 | 0 |
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_S... | 428 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils... | 119 | 0 |
def __UpperCAmelCase ( UpperCAmelCase )-> List[Any]:
"""simple docstring"""
lowercase = len(lowercase__ )
lowercase = sum(lowercase__ )
lowercase = [[False for x in range(s + 1 )] for y in range(n + 1 )... | 604 |
'''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__)
UpperCAmelCase = {
'''shi-labs/dinat-mini-in1k-224... | 119 | 0 |
"""simple docstring"""
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""huggingface/autoformer-tourism-monthly""": """https://huggingface.co... | 82 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 119 | 0 |
def snake_case__ ( ):
return [list(range(1_0_0_0 - i , -1_0_0_0 - i , -1 ) ) for i in range(1_0_0_0 )]
_a : Tuple = generate_large_matrix()
_a : Any = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
[[3, 2], ... | 145 |
'''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 = logging.get_logger(__name__)
UpperCAmel... | 119 | 0 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
__... | 665 |
'''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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosit... | 119 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
UpperCamelCase_ : str = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full RobertaForMa... | 331 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available... | 119 | 0 |
"""simple docstring"""
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
SCREAMING_SNAKE_CASE_ = {
'n_samples': 64,
'horizon': 32,
'num_inference_steps': 20,
'n_guide_steps': 2, # can set to 0 for faster sampling, does not use v... | 34 |
'''simple docstring'''
import os
from collections.abc import Iterator
def __UpperCamelCase ( lowercase__ : str = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(lowercase__ ):
__lowercase =[d for d in dir_names if d != 'scripts' a... | 119 | 0 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
UpperCamelCase_ = False
class a_ (unittest.TestCase )... | 384 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def __UpperCamelCase ( lowercase__ : int = 1_50_00_00 ):
'''simple docstring'''
__lowercase =defaultdict(lowercase__ )
__lowercase =2
while 2 * euclid_m * (euclid_m + 1) <... | 119 | 0 |
def __UpperCAmelCase ( __a : list[int] ) -> str:
"""simple docstring"""
_a : str = []
if len(lowercase__ ) == 1:
return [nums.copy()]
for _ in range(len(lowercase__ ) ):
_a : List[Any] = nums... | 14 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def __UpperCamelCase ( lowercase__ : Optional[Any] ):
'''simple docstring'''
for i in range(0, lowercase__ ):
for _ in range(0, n - i - 1 ): # printing spaces
p... | 119 | 0 |
"""simple docstring"""
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmb... | 346 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils imp... | 119 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( lowercase ):
"""simple docstri... | 658 |
'''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 lowerCAmelCase ( A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSO... | 119 | 0 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import torch.nn as n... | 428 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if n == 1 or not isinstance(lowercase__, lowercase__ ):
return 0
elif n == 2:
return 1
else:
__lowercase =[0, 1]
for i in r... | 119 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ = {"configuration_vit_msn": ["VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTMSNConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
... | 604 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : List[str], lowercase__ : Tuple ):
'''simple docstring'''
__lowercase =[0 for i in range(r + 1 )]
# nc0 = 1
__lowercase =1
for i in range(1, n + 1 ):
# to comput... | 119 | 0 |
"""simple docstring"""
class lowercase__ :
'''simple docstring'''
def __init__( self : List[Any] , _UpperCAmelCase : str , _UpperCAmelCase : Any , _UpperCAmelCase : str ) -> Dict:
... | 82 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase ( unittest.TestCase ):
... | 119 | 0 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_util... | 145 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
__lowercase =[0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__... | 119 | 0 |
'''simple docstring'''
from numpy import exp, pi, sqrt
def lowerCamelCase ( lowerCamelCase : Optional[int] , lowerCamelCase : float = 0.0 , lowerCamelCase : float = 1.0):
return 1 / sqrt(2 * pi * sigma**2) * exp(-((x - mu) ** 2) / (2 * sigma**2))
if __name__ == "__main__":
... | 665 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase = {
'''configuration_owlvit''': [
... | 119 | 0 |
'''simple docstring'''
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class lowerCamelCase__ ( __lowerCamelCase ):
"""simple docstring"""
UpperCamelCase__ = '''... | 331 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 119 | 0 |
"""simple docstring"""
import math
def __snake_case ( _lowercase ):
"""simple docstring"""
return math.sqrt(lowercase__ ) * math.sqrt(lowercase__ ) == num
def __snake_case ( _lowercase ):
"""simple docstring"""
UpperCamelCase ... | 34 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : float, lowercase__ : float, lowercase__ : float ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('One and on... | 119 | 0 |
'''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 .toke... | 384 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : list[int] ):
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
__lowercase =sum(lowercase__ ) / len(lowercase__ ) # Calculate ... | 119 | 0 |
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)
from t... | 14 |
'''simple docstring'''
import string
def __UpperCamelCase ( lowercase__ : str ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__lowercase =''
for symbol in message:
if symbol in string.ascii_uppercase:
... | 119 | 0 |
"""simple docstring"""
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class snake_case ( nn.Module ):
SCREAMING_SNAKE_CASE_ : Dict = 4... | 346 |
'''simple docstring'''
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto... | 119 | 0 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_t... | 658 |
'''simple docstring'''
class lowerCAmelCase :
def __init__( self : List[Any] , __lowercase : str , __lowercase : Any , __lowercase : str ):
"""simple docstring"""
__lowercase =name
__lowercase ... | 119 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_... | 428 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils... | 119 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
"distilbert-base-uncased": "https://huggingface.co/distilbert-base-unca... | 604 |
'''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__)
UpperCAmelCase = {
'''shi-labs/dinat-mini-in1k-224... | 119 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def a__ ( lowerCAmelCase__ , lowerCAm... | 82 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 119 | 0 |
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from sklearn.preprocessing import PolynomialF... | 145 |
'''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 = logging.get_logger(__name__)
UpperCAmel... | 119 | 0 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class __lowerCAmelCase ( ... | 665 |
'''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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosit... | 119 | 0 |
'''simple docstring'''
def _lowerCAmelCase (_lowercase = 10_00 ):
"""simple docstring"""
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 331 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available... | 119 | 0 |
"""simple docstring"""
from __future__ import annotations
def __snake_case ( _lowercase ,_lowercase ,_lowercase ,_lowercase ): # noqa: E741
"""simple docstring"""
while r - l > 1:
UpperCamelCase = (l + r) // 2
if v[m] >= key:
U... | 34 |
'''simple docstring'''
import os
from collections.abc import Iterator
def __UpperCamelCase ( lowercase__ : str = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(lowercase__ ):
__lowercase =[d for d in dir_names if d != 'scripts' a... | 119 | 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 import ... | 384 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def __UpperCamelCase ( lowercase__ : int = 1_50_00_00 ):
'''simple docstring'''
__lowercase =defaultdict(lowercase__ )
__lowercase =2
while 2 * euclid_m * (euclid_m + 1) <... | 119 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ = {
'''configuration_blenderbot_small''': [
'''BLENDERBOT_S... | 14 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def __UpperCamelCase ( lowercase__ : Optional[Any] ):
'''simple docstring'''
for i in range(0, lowercase__ ):
for _ in range(0, n - i - 1 ): # printing spaces
p... | 119 | 0 |
"""simple docstring"""
import math
def a__ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE = 0 , __SCREAMING_SNAKE_CASE = 0 ) -> Optional[Any]:
__lowerCAmelCase: Tuple = end or len(lowercase__ )
for i in range(lowercase__ , ... | 346 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils imp... | 119 | 0 |
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxruntime as ort
__snake_case ... | 658 |
'''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 lowerCAmelCase ( A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSO... | 119 | 0 |
class A_ :
def __init__( self : Any , snake_case__ : list[int] ):
lowercase = len(__lowercase )
lowercase = [0] * len_array
if len_array > 0:
lowercase = array[0]
for i in range(1 , __low... | 428 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if n == 1 or not isinstance(lowercase__, lowercase__ ):
return 0
elif n == 2:
return 1
else:
__lowercase =[0, 1]
for i in r... | 119 | 0 |
import os
# Precomputes a list of the 100 first triangular numbers
A_ = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def __UpperCAmelCase ( )-> Dict:
"""simple docstring"""
lowercase = os.path.dirname(os.path.realpath(lowercase__ ... | 604 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : List[str], lowercase__ : Tuple ):
'''simple docstring'''
__lowercase =[0 for i in range(r + 1 )]
# nc0 = 1
__lowercase =1
for i in range(1, n + 1 ):
# to comput... | 119 | 0 |
"""simple docstring"""
import comet # From: unbabel-comet
import torch
import datasets
lowerCamelCase = datasets.logging.get_logger(__name__)
lowerCamelCase = """\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lav... | 82 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase ( unittest.TestCase ):
... | 119 | 0 |
from __future__ import annotations
from collections.abc import Generator
def snake_case__ ( ):
lowerCAmelCase__ :Union[str, Any] = {}
lowerCAmelCase__ :Optional[Any] = 2
while True:
lowerCAmelCase__ :Union[str, Any] = factor_map.pop(lowercase__ ... | 145 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
__lowercase =[0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__... | 119 | 0 |
'''simple docstring'''
import torch
from diffusers import DiffusionPipeline
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self : Any ,_a : List[str] ,_a : Tuple ):
'''simple docstring'''
... | 665 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase = {
'''configuration_owlvit''': [
... | 119 | 0 |
'''simple docstring'''
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import nump... | 331 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 119 | 0 |
"""simple docstring"""
def __snake_case ( _lowercase ):
"""simple docstring"""
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6''') )
def __snake_case ( _lowercase ):
"""simple docstring"""
UpperCamelCa... | 34 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : float, lowercase__ : float, lowercase__ : float ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('One and on... | 119 | 0 |
'''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def _UpperCAmelCase ( _lowerCamelCase : int , _lowerCamelCase : int , _lowerCamelCase : float = 1 / sqrt(2 ) ) -> List[Any]:
_lowerCAmelCase : Optiona... | 384 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : list[int] ):
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
__lowercase =sum(lowercase__ ) / len(lowercase__ ) # Calculate ... | 119 | 0 |
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision.transforms.... | 14 |
'''simple docstring'''
import string
def __UpperCamelCase ( lowercase__ : str ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__lowercase =''
for symbol in message:
if symbol in string.ascii_uppercase:
... | 119 | 0 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class snake_case ( datasets.BuilderConfig ):
SCREAMING_... | 346 |
'''simple docstring'''
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto... | 119 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_te... | 658 |
'''simple docstring'''
class lowerCAmelCase :
def __init__( self : List[Any] , __lowercase : str , __lowercase : Any , __lowercase : str ):
"""simple docstring"""
__lowercase =name
__lowercase ... | 119 | 0 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class A_ :
_A :List[Any] = 42
_A :int = None
_A :int = None
def UpperCamelCase__ ... | 428 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils... | 119 | 0 |
from torch import nn
def __UpperCAmelCase ( UpperCAmelCase )-> Optional[int]:
"""simple docstring"""
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return n... | 604 |
'''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__)
UpperCAmelCase = {
'''shi-labs/dinat-mini-in1k-224... | 119 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny... | 82 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 119 | 0 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
lo... | 145 |
'''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 = logging.get_logger(__name__)
UpperCAmel... | 119 | 0 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_fl... | 665 |
'''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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosit... | 119 | 0 |
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