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 |
|---|---|---|---|---|
_snake_case : str = "\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
_snake_case : Tupl... | 81 | import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, rand... | 10 | 0 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
... | 82 | 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 import TFModelTes... | 10 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionX... | 83 | from __future__ import annotations
_lowerCAmelCase = [True] * 1_000_001
_lowerCAmelCase = 2
while i * i <= 1_000_000:
if seive[i]:
for j in range(i * i, 1_000_001, i):
_lowerCAmelCase = False
i += 1
def _snake_case ( __snake_case ):
return seive[n... | 10 | 0 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
RequestCounter,
... | 84 | import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase = get_tests_dir("fixtures/spiece.model")
@requ... | 10 | 0 |
from ....utils import logging
SCREAMING_SNAKE_CASE__ : List[Any] = logging.get_logger(__name__)
class snake_case ( UpperCamelCase_ ):
def __init__( self : Tuple , a_ : str , a_ : str=None , a_ : int=2048 )-> Union[str, Any]:
... | 85 | import sys
from collections import defaultdict
class lowerCAmelCase_ :
def __init__( self : Optional[int] ):
_UpperCamelCase = []
def UpperCamelCase_ ( self : Any , _A : str ):
return self.node_position[verte... | 10 | 0 |
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def __snake_case ( __UpperCamelCase : Dict[str, torch.Tensor] ):
"""simple docstring"""
A_ = []
A_ ... | 86 | import logging
import os
from .state import PartialState
class lowerCAmelCase_ ( logging.LoggerAdapter ):
@staticmethod
def UpperCamelCase_ ( _A : Any ):
_UpperCamelCase = PartialState()
return not main_process_only or (main_proces... | 10 | 0 |
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 numpy as np
from decord import VideoReader
if i... | 87 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase = "▁"
_lowerCAmelCase ... | 10 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ... | 88 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeline... | 10 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def UpperCamelCase_( lowerCamelCase_ ) -> Tuple:
if "cls_token" in name:
_lowercase : int = name.replace('cls_token' ... | 89 | from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _snake_case ( __snake_case , __snake_case ):
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(__snake_case , __snake_case ) ) )
def _snake_case ( __snake_cas... | 10 | 0 |
'''simple docstring'''
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count... | 90 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 10 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if ver... | 91 | import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
_lowerCAmelCase = HfApi()
_lowerCAmelCase = {}
# fmt: off
_lowerCAmelCase = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433, -1.1743, -3.7467,
1.2342, -2.2485, 0.4636, 0.8076,... | 10 | 0 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def _lowerCAmelCase ( __magic_name__ : str = "https://www.worldometers.info/coronavirus" ) -> dict:
lowercase : List[Any] =BeautifulSoup(requests.get(__magic_name__ ).text , '''html.parser... | 92 | from typing import List
from .keymap import KEYMAP, get_character
def _snake_case ( __snake_case ):
def decorator(__snake_case ):
_UpperCamelCase = getattr(__snake_case , '''handle_key''' , [] )
handle += [key]
setattr(__snake_case , ''... | 10 | 0 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
__A = {"""UserAgent""": UserAgent().random}
def __A (_SCREAMING_SNAKE_CASE ) ->dict:
"""simple docstring"""
lowerCA... | 93 | import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
require_torch,
requi... | 10 | 0 |
'''simple docstring'''
import os
from collections.abc import Iterator
def lowercase_ ( __A : str = "." ) -> Iterator[str]:
"""simple docstring"""
for dir_path, dir_names, filenames in os.walk(__A ):
lowercase : List[Any] =[d for d in dir_names if d... | 94 | def _snake_case ( __snake_case = 100 ):
_UpperCamelCase = (n * (n + 1) // 2) ** 2
_UpperCamelCase = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(f'{solution() = }')
| 10 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
lowerCamelCase_ ... | 95 | 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_STANDAR... | 10 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
'configuration_ctrl': ['CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CTRLConfig'],
'tokenization_c... | 96 | import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_lowerCAmelCase = 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_copies # noqa: E402
# This is the reference code that ... | 10 | 0 |
def a ( snake_case__: str , snake_case__: str = " " ):
'''simple docstring'''
lowercase_ = []
lowercase_ = 0
for index, char in enumerate(snake_case__ ):
if char == separator:
split_words.append(string[last_index:index] )
... | 97 | import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
from transformers import (
... | 10 | 0 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowercase__ : Optional[Any] = logging.get_logger(__nam... | 98 | import math
class lowerCAmelCase_ :
def __init__( self : Tuple , _A : int=0 ): # a graph with Node 0,1,...,N-1
_UpperCamelCase = n
_UpperCamelCase = [
[math.inf for j in range(0 , _A )] for i in range(0 , _A... | 10 | 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.... | 99 | import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
def _snake_case ( __snake_case=None , __snake_case=None ):
return field(default_... | 10 | 0 |
from __future__ import annotations
import requests
def __snake_case ( lowerCAmelCase_ ) -> dict:
SCREAMING_SNAKE_CASE__ = f'''https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'''
return requests.get(lowerCAmelCase_ ).json()
def __snake_... | 100 | import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _snake_case ( *__snake_case , __snake_case = None , __snake_case=True , __snake_case=2 ):
from .. import __version__
_UpperCamelCase = take_from
_UpperCame... | 10 | 0 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class __lowercase :
"""simple docstring"""
_UpperCAmelCase = 42
... | 101 | import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
DataCo... | 10 | 0 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : Union[str, Any] = {
"""en... | 102 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"microsoft/trocr-base-handwritten": (
"https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"
),
# See all T... | 10 | 0 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTest... | 103 | import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, rand... | 10 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder... | 104 | 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 import TFModelTes... | 10 | 0 |
from math import factorial
def __UpperCAmelCase ( lowerCamelCase_ : int = 1_00 ) -> int:
"""simple docstring"""
return sum(int(lowerCamelCase_ ) for x in str(factorial(lowerCamelCase_ ) ) )
if __name__ == "__main__":
print(solution(int(input('''Enter... | 105 | from __future__ import annotations
_lowerCAmelCase = [True] * 1_000_001
_lowerCAmelCase = 2
while i * i <= 1_000_000:
if seive[i]:
for j in range(i * i, 1_000_001, i):
_lowerCAmelCase = False
i += 1
def _snake_case ( __snake_case ):
return seive[n... | 10 | 0 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigT... | 106 | import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase = get_tests_dir("fixtures/spiece.model")
@requ... | 10 | 0 |
'''simple docstring'''
import os
import pytest
from attr import dataclass
_UpperCAmelCase : Optional[Any] = '''us-east-1''' # defaults region
@dataclass
class lowercase_ :
"""simple docstring"""
__lowerCAmelCase = 42
__lowerCAmelCase = "ar... | 107 | import sys
from collections import defaultdict
class lowerCAmelCase_ :
def __init__( self : Optional[int] ):
_UpperCamelCase = []
def UpperCamelCase_ ( self : Any , _A : str ):
return self.node_position[verte... | 10 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class SCREAMING_SNAKE_CASE__ ( UpperCAmelCase ):
'''simple docstring'''
@staticmethod
@abstractmethod
def lowerCamelCase ( lowerCamelCase : ArgumentParser ) -> Union[str, Any]:
"""s... | 108 | import logging
import os
from .state import PartialState
class lowerCAmelCase_ ( logging.LoggerAdapter ):
@staticmethod
def UpperCamelCase_ ( _A : Any ):
_UpperCamelCase = PartialState()
return not main_process_only or (main_proces... | 10 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
... | 109 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase = "▁"
_lowerCAmelCase ... | 10 | 0 |
"""simple docstring"""
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
# TODO Update this
UpperCamelCase__ = {
'facebook/esm-1b': 'https://... | 110 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeline... | 10 | 0 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
_lowerCamelCase = {
'cola'... | 6 | from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _snake_case ( __snake_case , __snake_case ):
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(__snake_case , __snake_case ) ) )
def _snake_case ( __snake_cas... | 10 | 0 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import ... | 312 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 10 | 0 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class UpperCAmelCase_ :
def __init__( self : Union[str, Any] , A : Optional[int] ):
_UpperCAmelCase : int = str(id_ )
_UpperCAmelC... | 289 | import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
_lowerCAmelCase = HfApi()
_lowerCAmelCase = {}
# fmt: off
_lowerCAmelCase = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433, -1.1743, -3.7467,
1.2342, -2.2485, 0.4636, 0.8076,... | 10 | 0 |
from collections.abc import Callable
class snake_case__ :
"""simple docstring"""
def __init__( self , __lowercase = None ) -> Any:
"""simple docstring"""
a__ : str = []
# Stores indexes of each item for suppor... | 136 | from typing import List
from .keymap import KEYMAP, get_character
def _snake_case ( __snake_case ):
def decorator(__snake_case ):
_UpperCamelCase = getattr(__snake_case , '''handle_key''' , [] )
handle += [key]
setattr(__snake_case , ''... | 10 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowercase = logging.get_logger(__name__)
_lowercase... | 443 | import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
require_torch,
requi... | 10 | 0 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils i... | 627 | def _snake_case ( __snake_case = 100 ):
_UpperCamelCase = (n * (n + 1) // 2) ** 2
_UpperCamelCase = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(f'{solution() = }')
| 10 | 0 |
"""simple docstring"""
def lowerCAmelCase_ () -> Optional[int]:
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
UpperCamelCase = generate_large_matrix()
UpperCamelCase = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],... | 473 | 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_STANDAR... | 10 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase = {
"""configuration_git""": ["""GIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GitConfig""", """GitVisionConfig"""],
"""processing_git""": ["""GitProcessor"""]... | 558 | import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_lowerCAmelCase = 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_copies # noqa: E402
# This is the reference code that ... | 10 | 0 |
"""simple docstring"""
from string import ascii_lowercase, ascii_uppercase
def __UpperCAmelCase ( __UpperCamelCase ):
if not sentence:
return ""
__lowercase : List[Any] = dict(zip(__snake_case , __snake_case ) )
return lower_to_upper.get(s... | 76 | import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
from transformers import (
... | 10 | 0 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def lowerCamelCase__ ( ):
__snake_case = HfArgumentParser(__snake_case )
__snake_case = parser.parse_args_into_dataclasses()[0]
__snake_case ... | 356 | import math
class lowerCAmelCase_ :
def __init__( self : Tuple , _A : int=0 ): # a graph with Node 0,1,...,N-1
_UpperCamelCase = n
_UpperCamelCase = [
[math.inf for j in range(0 , _A )] for i in range(0 , _A... | 10 | 0 |
'''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
res... | 274 | import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
def _snake_case ( __snake_case=None , __snake_case=None ):
return field(default_... | 10 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowerCamelCase = {
'configuration_ctrl': ['CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CTRLConfig'],
'tokenization_ctrl': ['CTRLTokenizer'],
}
try:
if not is_tor... | 6 | import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _snake_case ( *__snake_case , __snake_case = None , __snake_case=True , __snake_case=2 ):
from .. import __version__
_UpperCamelCase = take_from
_UpperCame... | 10 | 0 |
def SCREAMING_SNAKE_CASE_ ( snake_case__ ) -> List[str]:
return str(__snake_case ) == str(__snake_case )[::-1]
def SCREAMING_SNAKE_CASE_ ( snake_case__ ) -> Optional[int]:
return int(__snake_case ) + int(str(__snake_case )[::-1] )
def SCREAMING_SNAKE_CASE_ ( ... | 312 | import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
DataCo... | 10 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import TypedDict
class UpperCAmelCase_ ( __lowercase ):
__SCREAMING_SNAKE_CASE : Optional[int] = 4_2
__SCREAMING_SNAKE_CASE : str = 4_2
def __snake_case ( SCREAMING_SNAKE_CASE... | 289 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"microsoft/trocr-base-handwritten": (
"https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"
),
# See all T... | 10 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] ={
"configuration_swinv2": ["SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Swinv2Config"],
}
try:
if not is_torch_available():
raise Op... | 136 | import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, rand... | 10 | 0 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
_lowercase = ... | 443 | 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 import TFModelTes... | 10 | 0 |
'''simple docstring'''
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
import tensorflow as tf
fro... | 627 | from __future__ import annotations
_lowerCAmelCase = [True] * 1_000_001
_lowerCAmelCase = 2
while i * i <= 1_000_000:
if seive[i]:
for j in range(i * i, 1_000_001, i):
_lowerCAmelCase = False
i += 1
def _snake_case ( __snake_case ):
return seive[n... | 10 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}
try:
if not ... | 473 | import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase = get_tests_dir("fixtures/spiece.model")
@requ... | 10 | 0 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_UpperCAmelCase = {
... | 558 | import sys
from collections import defaultdict
class lowerCAmelCase_ :
def __init__( self : Optional[int] ):
_UpperCamelCase = []
def UpperCamelCase_ ( self : Any , _A : str ):
return self.node_position[verte... | 10 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 76 | import logging
import os
from .state import PartialState
class lowerCAmelCase_ ( logging.LoggerAdapter ):
@staticmethod
def UpperCamelCase_ ( _A : Any ):
_UpperCamelCase = PartialState()
return not main_process_only or (main_proces... | 10 | 0 |
'''simple docstring'''
import os
def lowerCamelCase__ ( ):
__snake_case = os.path.join(os.path.dirname(__snake_case ) , 'num.txt' )
with open(__snake_case ) as file_hand:
return str(sum(int(__snake_case ) for line in file_hand ) )[... | 356 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase = "▁"
_lowerCAmelCase ... | 10 | 0 |
'''simple docstring'''
def snake_case_ ( __snake_case : Union[str, Any]) -> Union[str, Any]:
if not isinstance(__snake_case , __snake_case):
lowerCAmelCase_ = F'''Input value of [number={number}] must be an integer'''
raise TypeError(__snake_case)
if number < ... | 274 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeline... | 10 | 0 |
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxLengthCriteria,
MaxNewTokensCrite... | 6 | from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _snake_case ( __snake_case , __snake_case ):
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(__snake_case , __snake_case ) ) )
def _snake_case ( __snake_cas... | 10 | 0 |
import math
class lowercase_ :
"""simple docstring"""
def SCREAMING_SNAKE_CASE_ ( self , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) ->Dict:
lowerCAmelCase = 0.0
lowerCAmelCase = 0.0
... | 312 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 10 | 0 |
"""simple docstring"""
import math
def __snake_case ( SCREAMING_SNAKE_CASE__ : List[Any] ) -> int:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives,... | 289 | import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
_lowerCAmelCase = HfApi()
_lowerCAmelCase = {}
# fmt: off
_lowerCAmelCase = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433, -1.1743, -3.7467,
1.2342, -2.2485, 0.4636, 0.8076,... | 10 | 0 |
class snake_case__ :
"""simple docstring"""
def __init__( self , __lowercase ) -> str:
"""simple docstring"""
a__ : Any = set_counts
a__ : int = max(_A )
a__ : Optional[Any] = len(_... | 136 | from typing import List
from .keymap import KEYMAP, get_character
def _snake_case ( __snake_case ):
def decorator(__snake_case ):
_UpperCamelCase = getattr(__snake_case , '''handle_key''' , [] )
handle += [key]
setattr(__snake_case , ''... | 10 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase = {
"""configuration_rembert""": ["""REMBERT_PRETRAINED_C... | 443 | import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
require_torch,
requi... | 10 | 0 |
'''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def a__ ( a__ , a__ , a__ = 1 / sqrt(2 ) ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = tau * frequency / samplerate
__SCREAMING_SNAKE_CASE = si... | 627 | def _snake_case ( __snake_case = 100 ):
_UpperCamelCase = (n * (n + 1) // 2) ** 2
_UpperCamelCase = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(f'{solution() = }')
| 10 | 0 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class UpperCAmelCase__ ( logging.LoggerAdapter ):
"""simple docstring"""
@staticmethod
def A ( _SCREAMING_SNAKE_CASE ) -> Tuple:
a_ : Dict = PartialState()
... | 473 | 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_STANDAR... | 10 | 0 |
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase ... | 558 | import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_lowerCAmelCase = 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_copies # noqa: E402
# This is the reference code that ... | 10 | 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_ ... | 76 | import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
from transformers import (
... | 10 | 0 |
'''simple docstring'''
import math
def lowerCamelCase__ ( a = 100 ):
__snake_case = sum(i * i for i in range(1 , n + 1 ) )
__snake_case = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return square_of_sum - sum_of_squa... | 356 | import math
class lowerCAmelCase_ :
def __init__( self : Tuple , _A : int=0 ): # a graph with Node 0,1,...,N-1
_UpperCamelCase = n
_UpperCamelCase = [
[math.inf for j in range(0 , _A )] for i in range(0 , _A... | 10 | 0 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
A_ : List[Any] ='''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(... | 274 | import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
def _snake_case ( __snake_case=None , __snake_case=None ):
return field(default_... | 10 | 0 |
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase_ ( __lowercase ):
lowerCamelCase_ = (UnCLIPScheduler,)
def _snake_case ( self :Any , **__A :int ) -> Optional[Any]:
... | 6 | import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _snake_case ( *__snake_case , __snake_case = None , __snake_case=True , __snake_case=2 ):
from .. import __version__
_UpperCamelCase = take_from
_UpperCame... | 10 | 0 |
from torch import nn
def SCREAMING_SNAKE_CASE_ ( snake_case__ ) -> Dict:
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ... | 312 | import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
DataCo... | 10 | 0 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipeline... | 289 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"microsoft/trocr-base-handwritten": (
"https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"
),
# See all T... | 10 | 0 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def lowerCAmelCase_ ( _lowercase : List[Any]) -> Tuple:
"""simple docstring"""
# A local function to see if a dot lands in the circle.
def ... | 136 | import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, rand... | 10 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
... | 443 | 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 import TFModelTes... | 10 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Optional[Any] = {
'configuration_informer': [
'INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 627 | from __future__ import annotations
_lowerCAmelCase = [True] * 1_000_001
_lowerCAmelCase = 2
while i * i <= 1_000_000:
if seive[i]:
for j in range(i * i, 1_000_001, i):
_lowerCAmelCase = False
i += 1
def _snake_case ( __snake_case ):
return seive[n... | 10 | 0 |
"""simple docstring"""
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowerCAmelCase_ (_SCREAMING_SNAKE_CASE :Optional[Any] ) -> List[str]:
a_ : int = prime_factors(__snake_case )
if is_square_free(__snake_case ):
... | 473 | import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase = get_tests_dir("fixtures/spiece.model")
@requ... | 10 | 0 |
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class UpperCAmelCase ( ctypes.Structure ):
'''simple docstring'''
lowerCamelCase_ = [('''size''', ctypes.c_int), ('''visibl... | 558 | import sys
from collections import defaultdict
class lowerCAmelCase_ :
def __init__( self : Optional[int] ):
_UpperCamelCase = []
def UpperCamelCase_ ( self : Any , _A : str ):
return self.node_position[verte... | 10 | 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
a_ = logging.get_logger... | 76 | import logging
import os
from .state import PartialState
class lowerCAmelCase_ ( logging.LoggerAdapter ):
@staticmethod
def UpperCamelCase_ ( _A : Any ):
_UpperCamelCase = PartialState()
return not main_process_only or (main_proces... | 10 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from typing import Any
class a_ :
def __init__( self : str ):
__snake_case = []
__snake_case = 0
__snake_case = 0
def lowercase__ ( self ... | 356 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase = "▁"
_lowerCAmelCase ... | 10 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import Counter
from random import random
class __UpperCAmelCase :
def __init__( self ):
lowerCAmelCase_ = {}
def UpperCAmelCase_ ( self , _lowerCamelCase ):
lowerCAm... | 274 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeline... | 10 | 0 |
_lowerCamelCase = '0.21.0'
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from ... | 6 | from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _snake_case ( __snake_case , __snake_case ):
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(__snake_case , __snake_case ) ) )
def _snake_case ( __snake_cas... | 10 | 0 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowercase__ : Optional[int] = logging.get_logger(__name__)
lowerc... | 312 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 10 | 0 |
"""simple docstring"""
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def... | 289 | import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
_lowerCAmelCase = HfApi()
_lowerCAmelCase = {}
# fmt: off
_lowerCAmelCase = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433, -1.1743, -3.7467,
1.2342, -2.2485, 0.4636, 0.8076,... | 10 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimensi... | 136 | from typing import List
from .keymap import KEYMAP, get_character
def _snake_case ( __snake_case ):
def decorator(__snake_case ):
_UpperCamelCase = getattr(__snake_case , '''handle_key''' , [] )
handle += [key]
setattr(__snake_case , ''... | 10 | 0 |
# flake8: noqa
# Lint as: python3
_lowercase = [
"""VerificationMode""",
"""Version""",
"""disable_progress_bar""",
"""enable_progress_bar""",
"""is_progress_bar_enabled""",
"""experimental""",
]
from .info_utils import VerificationMode
from .logging import disable_pr... | 443 | import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
require_torch,
requi... | 10 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingface.co/facebook/s2t-wav2vec2-large-en... | 627 | def _snake_case ( __snake_case = 100 ):
_UpperCamelCase = (n * (n + 1) // 2) ** 2
_UpperCamelCase = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(f'{solution() = }')
| 10 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/r... | 473 | 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_STANDAR... | 10 | 0 |
from __future__ import annotations
def UpperCamelCase ( __lowercase : Tuple ):
'''simple docstring'''
if not nums:
raise ValueError('List is empty' )
return sum(__snake_case ) / len(__snake_case )
if __name__ == "__main__":
import doctest
doct... | 558 | import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_lowerCAmelCase = 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_copies # noqa: E402
# This is the reference code that ... | 10 | 0 |
"""simple docstring"""
import os
def __UpperCAmelCase ( __UpperCamelCase = "matrix.txt" ):
with open(os.path.join(os.path.dirname(__snake_case ) , __snake_case ) ) as in_file:
__lowercase : int = in_file.read()
__lowercase : Tuple ... | 76 | import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
from transformers import (
... | 10 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase = {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""... | 356 | import math
class lowerCAmelCase_ :
def __init__( self : Tuple , _A : int=0 ): # a graph with Node 0,1,...,N-1
_UpperCamelCase = n
_UpperCamelCase = [
[math.inf for j in range(0 , _A )] for i in range(0 , _A... | 10 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : int =logging.get_logger(__name__)
A_ : Union[str, Any] ={
'''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve/main/config.json''',
... | 274 | import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
def _snake_case ( __snake_case=None , __snake_case=None ):
return field(default_... | 10 | 0 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask... | 6 | import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _snake_case ( *__snake_case , __snake_case = None , __snake_case=True , __snake_case=2 ):
from .. import __version__
_UpperCamelCase = take_from
_UpperCame... | 10 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase__ : List[str] = {'''configuration_vit''': ['''VIT_PRETRAINED_CONF... | 312 | import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
DataCo... | 10 | 0 |
"""simple docstring"""
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
def __snake_case ( SCREAMING_SNAKE_CASE__ : str... | 289 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"microsoft/trocr-base-handwritten": (
"https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"
),
# See all T... | 10 | 0 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class snake_case__ (unittest.TestCase ):
"""s... | 136 | import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, rand... | 10 | 0 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : Optional[Any] , UpperCAmelCase_ : Union[str, Any] , UpperCAmelCase_ : Any ) -> Union[str, Any]:
... | 443 | 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 import TFModelTes... | 10 | 0 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = (boundary[1] - boundary[0]) / steps
__SCREAMING_SNAKE_CASE = boundary[0]
__SCREAMING_SNAKE_CASE = boundary[1]
__SCREAMING_SNAKE_CASE = make_points(__snake_c... | 627 | from __future__ import annotations
_lowerCAmelCase = [True] * 1_000_001
_lowerCAmelCase = 2
while i * i <= 1_000_000:
if seive[i]:
for j in range(i * i, 1_000_001, i):
_lowerCAmelCase = False
i += 1
def _snake_case ( __snake_case ):
return seive[n... | 10 | 0 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRC... | 473 | import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase = get_tests_dir("fixtures/spiece.model")
@requ... | 10 | 0 |
from __future__ import annotations
from typing import Any
def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
if not postfix_notation:
return 0
A_ : str = {'+', '-', '*', '/'}
A_ : Tuple = []
for token in postfi... | 558 | import sys
from collections import defaultdict
class lowerCAmelCase_ :
def __init__( self : Optional[int] ):
_UpperCamelCase = []
def UpperCamelCase_ ( self : Any , _A : str ):
return self.node_position[verte... | 10 | 0 |
"""simple docstring"""
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_smal... | 76 | import logging
import os
from .state import PartialState
class lowerCAmelCase_ ( logging.LoggerAdapter ):
@staticmethod
def UpperCamelCase_ ( _A : Any ):
_UpperCamelCase = PartialState()
return not main_process_only or (main_proces... | 10 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( a , a ):
if discount_rate < 0:
raise ValueError('Discount rate cannot be negative' )
if not cash_flows:
raise ValueError('Cash flows list cannot be empty' )
__snake_case = sum(
... | 356 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase = "▁"
_lowerCAmelCase ... | 10 | 0 |
'''simple docstring'''
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
A_ : List[str] =logging.get_logger(__n... | 274 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeline... | 10 | 0 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test... | 6 | from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _snake_case ( __snake_case , __snake_case ):
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(__snake_case , __snake_case ) ) )
def _snake_case ( __snake_cas... | 10 | 0 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
... | 312 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 10 | 0 |
"""simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..control... | 289 | import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
_lowerCAmelCase = HfApi()
_lowerCAmelCase = {}
# fmt: off
_lowerCAmelCase = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433, -1.1743, -3.7467,
1.2342, -2.2485, 0.4636, 0.8076,... | 10 | 0 |
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
_lowercase : Optional[int] =logg... | 136 | from typing import List
from .keymap import KEYMAP, get_character
def _snake_case ( __snake_case ):
def decorator(__snake_case ):
_UpperCamelCase = getattr(__snake_case , '''handle_key''' , [] )
handle += [key]
setattr(__snake_case , ''... | 10 | 0 |
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