code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from __future__ import annotations
class __UpperCAmelCase :
'''simple docstring'''
def __init__(self : Optional[Any] , _lowerCAmelCase : list[list[int]] ):
A = TypeError(
"""Matrices must be formed from a list ... | 258 |
'''simple docstring'''
def __a ( UpperCAmelCase , UpperCAmelCase ) ->int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def __a ( ) ->None:
"""simple docstring"""
assert or_gate(0 , 0 ) == 0
assert or_gate(0 ... | 258 | 1 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class snake_case__ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCamelCase__ : Optional[int] , UpperCamelCase__ : ... | 83 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(_... | 83 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/config.js... | 65 | import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
UpperCamelCase__ = np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
... | 65 | 1 |
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,
... | 354 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : List[Any] = logging.get_logger(__name__)
A_ : Optional[Any] = {
'YituTech/conv-bert-bas... | 292 | 0 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase_ (a__ ):
"""simple docstring"""
__UpperCamelCase : Optional[Any] = ['''image_processor''... | 25 |
def lowerCAmelCase__ ( lowerCamelCase_ : list[list[float]]):
'''simple docstring'''
lowerCAmelCase__ : list[list[float]] = []
for data in source_data:
for i, el in enumerate(lowerCamelCase_):
if len(lowerCamelCase_) < i + 1:
data_lis... | 129 | 0 |
SCREAMING_SNAKE_CASE_:dict[str, float] = {
"joule": 1.0,
"kilojoule": 1_000,
"megajoule": 1_000_000,
"gigajoule": 1_000_000_000,
"wattsecond": 1.0,
"watthour": 3_600,
"kilowatthour": 3_600_000,
"newtonmeter": 1.0,
"calorie_nutr": 4_186.8,
"kilocalorie_nutr": 4_186_80... | 115 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_:Optional[int] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_:Dict = {
"""BAAI/AltCLIP""": """https://huggingface.co/BAAI/AltCLIP/resol... | 115 | 1 |
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image
from ...image_ut... | 330 |
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def lowerCAmelCase ( lowerCAmelCase... | 262 | 0 |
from manim import *
class SCREAMING_SNAKE_CASE__ ( lowercase__ ):
def SCREAMING_SNAKE_CASE ( self : Any ) -> Union[str, Any]:
a_ : List[Any] = Rectangle(height=0.5 , width=0.5 )
a_ : List[Any] = Rectangle(height=0.46... | 120 |
from __future__ import annotations
UpperCAmelCase_ : Dict = [True] * 100_0001
UpperCAmelCase_ : Any = 2
while i * i <= 100_0000:
if seive[i]:
for j in range(i * i, 100_0001, i):
UpperCAmelCase_ : Tuple = False
i += 1
def SCREAMING_SNAKE_CASE_ ... | 120 | 1 |
"""simple docstring"""
from math import pi, sqrt, tan
def UpperCAmelCase__ ( _UpperCAmelCase ):
"""simple docstring"""
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * side_length**2
def UpperCAmelC... | 286 | import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
__lowerCamelCase : List[Any] = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
... | 219 | 0 |
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class A_ ( __UpperCamelCase ):
'''simple docstring'''
def __init__( self: Tu... | 369 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : str = 0
__lowerCamelCase : Tuple = len(SCREAMING_SNAKE_CASE__ )
for i in range(n - 1 ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE__ ):
if arr[i] > arr[j]:
num_inversions +=... | 194 | 0 |
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class __lowerCamelCase (_a , unittest.TestCase ):
_lowercase = DownBlockaD # noqa F405
... | 310 |
import torch
from transformers import AutoModel
class __lowerCamelCase (torch.nn.Module ):
def __init__( self: Union[str, Any],A_: Tuple="sayef/fsner-bert-base-uncased" ):
'''simple docstring'''
super(A_,self... | 310 | 1 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def a_ ( lowerCAmelCase_ : str ):
if "model" in orig_key:
__lowerCAmelCase = orig_key.replace('model.', '' )
if "norm1" in orig_key:
__lowerCAmelCase = ori... | 207 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils imp... | 207 | 1 |
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,... | 95 | '''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cas... | 145 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__a = logging.get_logger(__name__)
__a = {"vocab_file": "vocab.json", "merges_file":... | 43 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch... | 43 | 1 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class _a ( unittest.TestCase):
def UpperCAmelCase__( s... | 131 | """simple docstring"""
import numpy as np
import qiskit
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 8 ,_lowerCamelCase : int | None = None ) -> str:
_lowerCAmelCase : int = np.random.default_rng(seed=_lowerCamelCase )
# Roughly 25% ... | 44 | 0 |
"""simple docstring"""
from __future__ import annotations
from PIL import Image
# Define glider example
lowercase_ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0... | 11 |
"""simple docstring"""
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from trans... | 11 | 1 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_fla... | 28 |
'''simple docstring'''
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils imp... | 28 | 1 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowerCAmelCase : List[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
im... | 353 |
"""simple docstring"""
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
... | 168 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class UpperCAmelCase ( UpperCamelCase__ ):
def __init__( self :Tuple , lowercase_ :str , lowercase_ :List[Any] )-> List[Any]... | 237 |
'''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 ..controln... | 237 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : int ) -> int:
if len(lowerCAmelCase__ ) < k or k < 0:
raise ValueError('''Invalid Input''' )
__a = __a =... | 11 |
"""simple docstring"""
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
lowercase_ ... | 11 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
fro... | 61 |
"""simple docstring"""
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def __a ( __lowerCamelCase, __lowerCamelCase, __lowerCamelCase = 1 / sqrt(2 ) ):
UpperCAmelCase_ : int = tau * frequency / samplerate
UpperCAmelCase_ : List[... | 61 | 1 |
'''simple docstring'''
from __future__ import annotations
def _snake_case ( _SCREAMING_SNAKE_CASE : list[int | str] ) -> None:
"""simple docstring"""
create_state_space_tree(_SCREAMING_SNAKE_CASE , [] , 0 , [0 for i in range(len(_SCREAMING_SNAKE_CASE ... | 370 |
'''simple docstring'''
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICom... | 187 | 0 |
'''simple docstring'''
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
... | 251 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def lowercase__( __UpperCamelCase: np.ndarray ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : Optional[Any] ... | 251 | 1 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class A :
def __init__( self : str , lowerCAmelCase_ : Any ) -> Union[str, Any]:
"""simple docstring"""
_a ... | 358 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_snake_case : int = {'configuration_yolos': ['YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YolosConfig', 'YolosOnnxConfig... | 179 | 0 |
lowerCAmelCase = [
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
44,
22,
0,
]
lowerCAmelCas... | 110 |
from __future__ import annotations
def _a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowercase__ = 0
lowercase__ = len(SCREAMING_SNAKE_CASE ) - 1
while i < j:
if nums[i] + nums[j] == target:
... | 110 | 1 |
"""simple docstring"""
def __UpperCAmelCase ( lowercase ):
"""simple docstring"""
if number < 0:
raise ValueError("""number must not be negative""" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 361 | """simple docstring"""
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditio... | 30 | 0 |
'''simple docstring'''
def __lowerCAmelCase ( UpperCamelCase__ ) -> int:
assert (
isinstance(UpperCamelCase__ , UpperCamelCase__ ) and number_of_steps > 0
), f"""number_of_steps needs to be positive integer, your input {number_of_steps}"""
if number_of_steps == 1:
retu... | 67 | '''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
__UpperCAmelCase =True
except (ImportError, ModuleNotFoundError):
__UpperCAmelCase =False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.download("punkt", quiet=True)
def __lowerCAme... | 67 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase : str = {
"configuration_dist... | 264 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( lowerCamelCase_ ):
lowerCAmelCase_ = (DDPMScheduler,)
def _snake_case ( ... | 264 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case : Any = logging.get_logger(__name__)
_snake_case : List[str] = {
'BridgeTower/bridgetower-base': 'https://hug... | 292 |
"""simple docstring"""
def A__ ( UpperCamelCase , UpperCamelCase = False ):
if not isinstance(UpperCamelCase , UpperCamelCase ):
A = F"Expected string as input, found {type(UpperCamelCase )}"
raise ValueError(UpperCamelCase )
... | 292 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( a , a , a ) -> float:
if principal <= 0:
raise Exception('''Principal borrowed must be > 0''' )
if rate_per_annum < 0:
raise Exception('''Rate of interest must be >= 0''' )
if years_to_repay <= 0 or not isinstance(a ,... | 351 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers impo... | 301 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeli... | 17 |
from __future__ import annotations
def _UpperCAmelCase ( snake_case ):
"""simple docstring"""
_lowerCAmelCase = str(snake_case )
return n == n[::-1]
def _UpperCAmelCase ( snake_case = 1_00_00_00 ):
"""simple docstring"""
_lowerCAmelCase ... | 82 | 0 |
"""simple docstring"""
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_c... | 364 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKIN... | 53 | 0 |
from __future__ import annotations
from statistics import mean
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
snake_case_ = [0] * no_of_processes
snake_case_ = [0] * no_of_proce... | 285 |
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
snake_case_ ... | 285 | 1 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_snake_case : Union[str, Any] = get_tests_dir('fixtures/test_sentencepiece_wit... | 207 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class _UpperCAmel... | 207 | 1 |
"""simple docstring"""
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
Uppe... | 115 |
"""simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class lowerCamelCase__ ( ctypes.Structure ):
"""simple docstring"""
__a = ... | 115 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = '''▁'''
__UpperCAm... | 42 |
from __future__ import annotations
from math import gcd
def __lowerCamelCase ( __magic_name__ : int , __magic_name__ : int = 2 , __magic_name__ : int = 1 , __magic_name__ : int = 3 , ):
# A value less than 2 can cause an infinite loop in the algorithm.
... | 42 | 1 |
def lowerCAmelCase ( _lowerCAmelCase : Optional[int] ):
"""simple docstring"""
UpperCAmelCase__ = len(_lowerCAmelCase )
for i in range(length - 1 ):
UpperCAmelCase__ = i
for k in range(i + 1 , _lowerCAmelCase ):
if collection[k] < c... | 169 |
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def lowerCAmelCase ( ):
"""simple docstring"""
UpperCAmelCase__ = [randint(-1000 , 1000 ) for i in range(10 )]
UpperCAmelCase__ ... | 169 | 1 |
import sys
_lowerCamelCase : Optional[int] = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'668966489504452445231... | 356 |
from functools import lru_cache
@lru_cache
def a_ ( __lowercase : int ) -> int:
if num < 0:
raise ValueError('Number should not be negative.' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest
doctest.testmod() | 130 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__snake_case =loggi... | 4 |
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class A_ ( SCREAMING_SNAKE_CASE ):
_UpperCAmelCase : Any = ['''image_processor''', '''tokenizer''']
_UpperCAmelCase : List[Any] ... | 73 | 0 |
def _a ( SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
UpperCamelCase__ : List[Any] = int(SCREAMING_SNAKE_CASE )
if n_element < 1:
UpperCamelCase__ : Tuple = ValueError('''a should be a positive number''' )
raise my_error
Upp... | 356 |
def _a ( SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
UpperCamelCase__ : List[str] = generate_pascal_triangle(SCREAMING_SNAKE_CASE )
for row_idx in range(SCREAMING_SNAKE_CASE ):
# Print left spaces
for _ in range(num_rows - row_idx - 1 )... | 51 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase : Tuple = {
"configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
"configura... | 47 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class _lowerCAmelCase :
def __init__( self , _UpperCamelCase=2 , _UpperCamelCase=3 , _UpperCamelCase=64 , _UpperCamelCase=None ) -> ... | 231 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Optional[Any] ={
'configuration_deberta': ['DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DebertaConfig', 'De... | 94 |
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_G... | 94 | 1 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
_a : Union[str, Any] = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to wors... | 44 | """simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 44 | 1 |
"""simple docstring"""
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_con... | 357 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowerCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
__UpperCamelCase = "SpeechT5FeatureExtractor"
__UpperCamelCase = "SpeechT5Tokenizer"
def __init__( ... | 318 | 0 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils impor... | 4 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class UpperCAmelCase_ ( unittest.TestCase ):
def __Upp... | 4 | 1 |
'''simple docstring'''
from collections import deque
from math import floor
from random import random
from time import time
class __UpperCamelCase :
def __init__( self ):
"""simple docstring"""
lowerCamelCase_ ={}
def lowerca... | 6 |
'''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 D... | 6 | 1 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import requi... | 315 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __UpperCAmelCase ( _lowerCamelCase ):
@require_torch
def lowerCamelCase ... | 42 | 0 |
'''simple docstring'''
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def lowerCamelCase__ ( __lowerCamelCase ):
'''simple docstring'''
_UpperCAmelCase : Dict ={}
_UpperCAmelCase : Li... | 358 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax impo... | 242 | 0 |
'''simple docstring'''
def __snake_case ( UpperCAmelCase_ : int = 1000 ):
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 55 |
'''simple docstring'''
from __future__ import annotations
from typing import Generic, TypeVar
a_ : List[str] = TypeVar("""T""")
class snake_case ( Generic[T] ):
"""simple docstring"""
def __init__( self , UpperCamelCase ):
... | 55 | 1 |
def __lowerCamelCase ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
lowerCAmelCase__ , lowerCAmelCase__ = len(lowerCAmelCase__ ), len(grid[0] )
if (
min(lowerCAmelCase__ , lowerCAmelCase__ ) < 0
... | 371 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'facebook/xlm-roberta-xl': 'https://huggingf... | 119 | 0 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
... | 298 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseM... | 298 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmark... | 40 |
"""simple docstring"""
def _UpperCAmelCase ( __lowerCamelCase : List[Any] , __lowerCamelCase : Dict , __lowerCamelCase : Optional[int] , __lowerCamelCase : Tuple ) -> Union[str, Any]:
# Return True if there is node that has not iterated.
_snake_case = [False]... | 40 | 1 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def A_ ( A__ , A__ ) -> List[str]:
a__ : Optional[Any] = tor... | 99 |
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_snake_case = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
parser.add_argument('''--dpm'... | 283 | 0 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
UpperCamelCase_ ="""
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation... | 128 |
"""simple docstring"""
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dens... | 128 | 1 |
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 Vi... | 30 | '''simple docstring'''
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
__a = {
# 1536-bit
5: {
'prime': int(
... | 145 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class __lowerCAmelCase :
'''simple docstring'''
def __init__( self , _a , _a , _a = 0 ):
__a , __a = row, column
__a = [[default_val... | 358 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiec... | 11 | 0 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
_A = TypeVar('KEY')
_A = TypeVar('VAL')
@dataclass(frozen=A_ , slots=A_ )
class UpperCAmelCase__ ( Generic[KEY, VAL] ):
"""simple docst... | 62 | """simple docstring"""
from __future__ import annotations
def lowercase__( __SCREAMING_SNAKE_CASE : list ):
if not nums:
raise ValueError('List is empty' )
return sum(__SCREAMING_SNAKE_CASE ) / len(__SCREAMING_SNAKE_CASE )
if __name__ == "__main__":... | 213 | 0 |
'''simple docstring'''
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism... | 16 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, ... | 16 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
W... | 139 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __lowerCamelCase ( metaclass=A__ ):
'''simple docstring'''
a_ : Union[str, Any] = ["""flax"""]
def __init__( self : Dict , *a_ : Optional[Any] , **a_ ... | 241 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowerCamelCase = version.parse(version.parse(torch.__version__).base_version) < version.parse("""1.11"... | 241 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
UpperCamelCase = ['''image_proce... | 241 | 1 |
def lowerCAmelCase__ ( _SCREAMING_SNAKE_CASE : int = 10 , _SCREAMING_SNAKE_CASE : int = 22 ):
"""simple docstring"""
__a = range(1 , _SCREAMING_SNAKE_CASE )
__a = range(1 , _SCREAMING_SNAKE_CASE )
return sum(
1 for power in powers ... | 302 |
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impo... | 302 | 1 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxMode... | 124 |
import numpy
class UpperCAmelCase :
'''simple docstring'''
def __init__( self : List[str] ,A : numpy.ndarray ,A : numpy.ndarray ):
__A = input_array
# Random initial weights are assigned where first argument is the
# number of nodes in previou... | 124 | 1 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
__UpperCamelCase = [8, 5, 9, 7]
__UpperCamelCase = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
__UpperCamelCase = [
[3, 2, 1, 4],
[0, 2, 5... | 69 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers.uti... | 203 | 0 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case :Dict = logging.get_logger(__name__)
__snake_case :Dict = ... | 360 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load... | 131 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 281 |
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
OpenAIGPTDoubleHeadsMod... | 281 | 1 |
"""simple docstring"""
def _snake_case ( lowercase__ ):
_lowerCamelCase : List[Any] = []
_lowerCamelCase : int = set({'(', '[', '{'} )
_lowerCamelCase : Optional[Any] = set({')', ']', '}'} )
_lowerCamelCase : Opti... | 369 |
"""simple docstring"""
def _snake_case ( lowercase__ = 10 ):
if not isinstance(lowercase__ , lowercase__ ) or n < 0:
raise ValueError('Invalid input' )
_lowerCamelCase : str = 10**n
_lowerCamelCase : Union[str, Any] = 28433... | 12 | 0 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversatio... | 178 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from trans... | 267 | 0 |
from __future__ import annotations
_lowerCamelCase : Optional[int] = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
... | 369 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : Tuple = logging.get_logger(__name__)
_lowerCamelCase : Union[str, Any] = {
'''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.json''',
# See ... | 130 | 0 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
_UpperCAmelCase : Union[str, Any] = """\
@inproceedings{snover-etal-2006-study,
title = \"A Study of Translation Edit Rate with Targeted Human Annotation\",
au... | 174 |
'''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from dataset... | 174 | 1 |
def lowercase__ ( __snake_case : int = 3 , __snake_case : int = 7 , __snake_case : int = 1_000_000 ):
'''simple docstring'''
UpperCAmelCase_ : Dict = 0
UpperCAmelCase_ : int = 1
for current_denomin... | 363 |
def lowercase__ ( __snake_case : List[str] , __snake_case : List[str] , __snake_case : Union[str, Any] , __snake_case : Optional[int] , __snake_case : str , __snake_case : Optional[Any] ):
'''simple docstring'''
... | 145 | 0 |
"""simple docstring"""
import sys
SCREAMING_SNAKE_CASE_ : List[Any] = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295... | 335 |
"""simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
SCREAMING_SNAKE_CASE_ : int = [
'Prosecutor: "No videos were used in the crash investigation" ... | 335 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
... | 228 |
'''simple docstring'''
from __future__ import annotations
class a__ :
'''simple docstring'''
def __init__( self , lowerCamelCase_ ) -> None:
lowerCAmelCase__ = order
# a_{0} ... a_{k}
... | 228 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class ... | 58 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
... | 251 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers impor... | 326 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
if bit_count < 0:
raise ValueError('''The given input must be positive''' )
# get the generated string sequence
_UpperCAmelCase = gray_code_... | 326 | 1 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_available():
... | 67 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase : Union[str, Any] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''... | 18 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : List[str] = logging.get_logger(__name__)
lowercase : List[str] = {
'facebook/dpr-ctx_encoder-single-nq-base': (
'https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/... | 354 |
import numpy as np
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : np.array) -> np.array:
'''simple docstring'''
return (2 / (1 + np.exp(-2 * vector))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod() | 151 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Norm... | 125 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_... | 125 | 1 |
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 134 |
from __future__ import annotations
_snake_case : Union[str, Any] = []
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ):
for i in range(len(__lowerCamelCase ) ):
if board[row][i] == 1:
... | 134 | 1 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from trans... | 13 |
from __future__ import annotations
import math
lowerCamelCase : Optional[int] = '2020.9.26'
lowerCamelCase : int = 'xcodz-dot, cclaus, dhruvmanila'
def SCREAMING_SNAKE_CASE__ ( lowercase ,lowercase ,lowercase ,lowercase ,lowercase ... | 124 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, requir... | 234 |
"""simple docstring"""
_UpperCamelCase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_UpperCamelCase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_UpperCamelCase = {
0: """Sunday""",
1: """Monday""",
2: """Tuesday""",
3: """Wednesday""",
4: """Thursday""",
5: ""... | 234 | 1 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 52 |
"""simple docstring"""
import random
class _UpperCAmelCase :
@staticmethod
def __snake_case ( _A ) -> tuple[list[int], list[int]]:
'''simple docstring'''
_UpperCAmelCase : List[Any] = [ord(_A ) for i in t... | 246 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCAmelCase_ ( snake_case_ ):
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/wiki/CJK_Unified_Ideograph... | 343 |
from __future__ import annotations
from collections.abc import Callable
_snake_case = list[list[float | int]]
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_A : int = len(snake_case_ )
_A : Matrix = [[0 for _ in range(size + 1 ... | 343 | 1 |
"""simple docstring"""
from string import ascii_lowercase, ascii_uppercase
def lowercase_ ( _snake_case ):
if not sentence:
return ""
SCREAMING_SNAKE_CASE__ : int = dict(zip(_snake_case ,_snake_case ) )
return lower_to_upper... | 25 |
"""simple docstring"""
UpperCAmelCase__ : Any = '\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/transform... | 25 | 1 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
_SCREAMING_SNAKE_CASE : ... | 363 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : Optional[Any] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/viv... | 218 | 0 |
'''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property... | 34 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
UpperCamelCase : Union[str, Any] = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def ... | 316 | 0 |
from __future__ import annotations
def UpperCAmelCase ( _lowerCamelCase ): # This function is recursive
A : str = len(_lowerCamelCase )
# If the array contains only one element, we return it (it's the stop condition of
# recursion)
if array_length <= 1:
... | 359 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE = {
"""configuration_electra""": ["""ELECTRA_PRETR... | 256 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=__UpperCAmelCase ):
"""simple docstring"""
snake_case__ = ["note_seq"]
def __init__( self : Optional[Any] ,*lowerCamelCase__ : int ,**lowerCamelCase__ ... | 98 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils import r... | 195 | 0 |
"""simple docstring"""
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow,... | 353 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
_UpperCamelCase: str = '\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer ... | 53 | 0 |
from __future__ import annotations
def __A ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase )-> list:
"""simple docstring"""
_UpperCAmelCase = []
_UpperCAmelCase , _UpperCAmelCase = input_list[low:mid]... | 39 |
from __future__ import annotations
import time
import numpy as np
UpperCAmelCase__ = [8, 5, 9, 7]
UpperCAmelCase__ = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
UpperCAmelCase__ = [
[3, 2, 1, 4],
[0, 2, 5, 2]... | 0 | 0 |
'''simple docstring'''
import string
def _lowerCAmelCase ( lowercase ) -> None:
for key in range(len(string.ascii_uppercase ) ):
__lowerCAmelCase = """"""
for symbol in message:
if symbol in string.ascii_uppercase:
__lowerCAmelC... | 46 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | 46 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta im... | 61 |
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
__magic_name__: str = logging.get_logger(__name__)
__magic_name__: ... | 342 | 0 |
'''simple docstring'''
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class __lowercase ( lowerCAmelCase__ ):
'''simple docstring'''... | 357 |
'''simple docstring'''
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX... | 217 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstrings, add... | 274 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
A : Optional[Any] = logging... | 274 | 1 |
"""simple docstring"""
from manim import *
class lowerCamelCase__ ( snake_case ):
def _UpperCamelCase ( self ):
UpperCAmelCase = Rectangle(height=0.5 ,width=0.5 )
UpperCAmelCase = Rectangle(height=0.25 ,width=0.25 )
Up... | 234 |
"""simple docstring"""
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
... | 234 | 1 |
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
fr... | 48 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, Trai... | 84 | 0 |
'''simple docstring'''
from math import isclose, sqrt
def UpperCamelCase__ ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase ):
"""simple docstring"""
_lowerCAmelCase = point_y / 4 / point_x
_lowerCAmelCase ... | 351 |
'''simple docstring'''
def UpperCamelCase__ ( lowerCAmelCase , lowerCAmelCase ):
"""simple docstring"""
if len(lowerCAmelCase ) != len(lowerCAmelCase ):
raise ValueError("""String lengths must match!""" )
_lowerCAmelCase... | 220 | 0 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
UpperCAmelCase ... | 280 |
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE ( lowerCamelCase__ ):
__lowerCamelCase : Optional[int] =(IPNDMScheduler,)
__lowerCamelCase : int =(('num_inference_steps', 50),)... | 302 | 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
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertMode... | 353 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class snake_case ( unittest.TestCase ... | 303 | 0 |
from statistics import mean, stdev
def A_ ( snake_case : list , snake_case : int = 3 ) -> list:
'''simple docstring'''
__UpperCamelCase = min(snake_case )
__UpperCamelCase = max(snake_case )
# normalize ... | 328 |
from typing import Any
class SCREAMING_SNAKE_CASE__ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE_ )-> Optional[int]:
'''simple docstring'''
__UpperCamelCase = data
__UpperCamelCase = None
... | 328 | 1 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.utils import p... | 197 | from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowerCamelCase_ : Union[str, Any] = {"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXConfig"""... | 197 | 1 |
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