code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked... | 480 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def __snake_case ( ) -> None:
print("""Making key files...""" )
make_key_files("""rsa""" ... | 607 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {"configuration_timm_backbone": ["TimmBackboneConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyN... | 630 |
"""simple docstring"""
from ... import PretrainedConfig
lowerCAmelCase: str ={
"sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}
class lowerCamelCase__ ( __UpperCamelCase ):
__UpperCAmelCase = NEZHA_PRETRAIN... | 607 | 0 |
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
_snake_case : List[Any] = "src/transformers"
_snake_case : Optio... | 81 |
"""simple docstring"""
import tensorflow as tf
from ...tf_utils import shape_list
class lowerCamelCase__ ( tf.keras.layers.Layer ):
def __init__( self , snake_case , snake_case , snake_case , snake_case , snake_case=1 , snake_case=False , **snake_case ) -> ... | 607 | 0 |
from __future__ import annotations
import time
import numpy as np
SCREAMING_SNAKE_CASE : int = [8, 5, 9, 7]
SCREAMING_SNAKE_CASE : Union[str, Any] = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
SCREAMING_SNAKE_CASE : Dict... | 197 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def __snake_case ( __A ,__A = "cpu" ,__A = None ) -> None:
lowercase : Optional[int] = torch.load(__A ,map_location=__A )
for k, v in tqdm(state_... | 607 | 0 |
from PIL import Image
def _UpperCAmelCase ( a : int , a : Union[str, Any] ):
snake_case__ = (259 * (level + 255)) / (255 * (259 - level))
def contrast(a : Optional[Any] ) -> int:
return int(128 + factor * (c - 128) )
retur... | 654 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def __snake_case ( __A ) -> Any:
lowercase : List[str] = os.path.join(args.tf_model_dir ,"""para... | 607 | 0 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class A__ ( __UpperCamelCase , unitte... | 222 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, 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_... | 607 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import Se... | 246 |
"""simple docstring"""
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __snake_case ( __A ) -> Any:
def wrapper(*__A ,**__A ):
lowercase : Tuple ... | 607 | 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,
generate... | 294 |
"""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,
ge... | 607 | 0 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import... | 233 |
"""simple docstring"""
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
... | 607 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
a_ : Tuple = "\\n\n"
a_ : Tuple = "\nPerplexity (PPL) is one of the most common metric... | 676 |
"""simple docstring"""
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowerCAmelCase: Tuple =logging.get_logger(__name__)
lowerCAmelCase: int ... | 607 | 0 |
'''simple docstring'''
from statistics import mean
import numpy as np
def _lowerCAmelCase (_lowercase , _lowercase , _lowercase , _lowercase ):
"""simple docstring"""
a__ = 0
# Number of processes finished
a__ = ... | 331 |
"""simple docstring"""
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowerCAmelCase: List[str] =parse(importlib.metadata.version("torch"))
def __snake_case ( __A ,__A ... | 607 | 0 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_c... | 480 |
"""simple docstring"""
def __snake_case ( ) -> Union[str, Any]:
lowercase : str = 0
for i in range(1 ,1001 ):
total += i**i
return str(__A )[-10:]
if __name__ == "__main__":
print(solution())
| 607 | 0 |
"""simple docstring"""
import math
def _snake_case ( lowercase__ ):
assert isinstance(__A , __A ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return T... | 630 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from tra... | 607 | 0 |
def lowerCAmelCase_ ( ):
__snake_case : str = 0
for i in range(1 , 1_0_0_1 ):
total += i**i
return str(__A )[-1_0:]
if __name__ == "__main__":
print(solution())
| 81 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config i... | 607 | 0 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Co... | 197 |
"""simple docstring"""
from random import shuffle
import tensorflow as tf
from numpy import array
def __snake_case ( __A ,__A ) -> Any:
lowercase : Any = int(__A )
assert noofclusters < len(__A )
# Find out the dimensionality
lower... | 607 | 0 |
import requests
from bsa import BeautifulSoup
def _UpperCAmelCase ( a : Union[str, Any] = "AAPL" ):
snake_case__ = F'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
snake_case__ = BeautifulSoup(requests.get(__A ).text , """html.parser""" ... | 654 |
"""simple docstring"""
import qiskit
def __snake_case ( __A ,__A ) -> qiskit.result.counts.Counts:
lowercase : List[Any] = qiskit.Aer.get_backend("""aer_simulator""" )
lowercase : int = qiskit.QuantumCircuit(4 ,2 )
# encod... | 607 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__lowerCamelCase :int = {"tokenization_wav2vec2_phoneme": ["Wav2Vec2PhonemeCTCTokenizer"]}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
... | 222 |
"""simple docstring"""
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transforme... | 607 | 0 |
def a_ ( UpperCamelCase_ : Optional[int] , UpperCamelCase_ : Tuple ) -> int:
"""simple docstring"""
while b:
lowerCamelCase = b, a % b
return a
def a_ ( UpperCamelCase_ : Any , UpperCamelCase_ : Dict ) -> int:
... | 246 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def __snake_case ( __A ) -> Union[str, Any]:
# This defines a "chinese character" as anything in the C... | 607 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
def _UpperCamelCase ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_C... | 294 |
"""simple docstring"""
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from .... | 607 | 0 |
def _a ( __UpperCamelCase : Tuple ):
lowerCAmelCase__ : List[str] = """"""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def _a ( __UpperCamelCase : List[str] ):
lowerCAmelCase__ : ... | 233 |
"""simple docstring"""
import math
import qiskit
def __snake_case ( __A = 1 ,__A = 1 ,__A = 1 ) -> qiskit.result.counts.Counts:
if (
isinstance(__A ,__A )
or isinstance(__A ,__A )
or isinstance(__A ,__A )
):
raise ... | 607 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig",
... | 608 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling... | 608 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 1 |
"""simple docstring"""
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
__lowerCamelCase = logging.getLog... | 608 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class _snake_case :
'''simple docstring'''
UpperCamelCase__ =42
UpperCamelCase__ =42
class _snake_case ... | 608 |
"""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 import AutoProcessor, Be... | 608 | 1 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"t5-small": "https://huggingface.co/... | 608 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 1 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
__lowerCamelCase = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
__lowerCamelCase = [ord(letter) for letter in str... | 608 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 1 |
"""simple docstring"""
import operator
def a ( __snake_case : list, __snake_case : bool = False, __snake_case : list | None = None ):
'''simple docstring'''
UpperCAmelCase_ :List[Any] = operator.lt if reverse else operator.gt
UpperCAmelCase_ ... | 608 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 1 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"asapp/sew-tiny-100k": "https://huggingface.co/asapp/sew-tiny-100k/resolve/m... | 608 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 1 |
"""simple docstring"""
def a ( __snake_case : int ):
'''simple docstring'''
if not head:
return True
# split the list to two parts
UpperCAmelCase_ ,UpperCAmelCase_ :Optional[Any] = head.next, head
while fast and fast.next:
UpperCAmelC... | 608 |
"""simple docstring"""
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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
Image... | 608 | 1 |
"""simple docstring"""
import qiskit
def a ( __snake_case : int, __snake_case : int ):
'''simple docstring'''
UpperCAmelCase_ :Tuple = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
UpperCAmelCase... | 608 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 1 |
"""simple docstring"""
from cva import destroyAllWindows, imread, imshow, waitKey
def a ( __snake_case : Optional[Any] ):
'''simple docstring'''
UpperCAmelCase_ ,UpperCAmelCase_ :str = img.shape[0], img.shape[1]
# converting each pixel's color to its neg... | 608 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 1 |
"""simple docstring"""
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_dev... | 608 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 1 |
"""simple docstring"""
from __future__ import annotations
__lowerCamelCase = 8.988E9 # units = N * m^s * C^-2
def a ( __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAm... | 608 |
"""simple docstring"""
import os
import sys
import unittest
__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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 1 |
"""simple docstring"""
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 transfo... | 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 1 |
"""simple docstring"""
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
import t... | 608 |
"""simple docstring"""
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 transfo... | 608 | 1 |
"""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 import AutoProcessor, Be... | 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def a ( __snake_case : float, __snake_case : int ):
'''simple docstring'''
UpperCAmelCase_ :List[str] = u
for i in range(1, __snake_case ):
UpperCAmelCase_ :List[... | 608 |
"""simple docstring"""
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 = {
"roberta-base":... | 608 | 1 |
"""simple docstring"""
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers impor... | 608 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 1 |
"""simple docstring"""
import os
__lowerCamelCase = {"I": 1, "V": 5, "X": 10, "L": 50, "C": 1_00, "D": 5_00, "M": 10_00}
def a ( __snake_case : str ):
'''simple docstring'''
UpperCAmelCase_ :str = 0
UpperCAmelCase_ :Tuple = 0
... | 608 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 1 |
"""simple docstring"""
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('''dataset_size''', [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize('''input_in_memory_max_size''', ['''default''', 0, 100 * 2**20, 900 * 2**20] )
def... | 608 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 1 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDepe... | 608 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 1 |
"""simple docstring"""
import string
def a ( __snake_case : str ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
UpperCAmelCase_ :Dict = ''''''
for symbol in message:
if symbol in string.ascii_uppercase:
... | 608 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 1 |
"""simple docstring"""
from collections import namedtuple
import requests
from lxml import html # type: ignore
__lowerCamelCase = namedtuple("covid_data", "cases deaths recovered")
def a ( __snake_case : str = "https://www.worldometers.info/coronavirus/" ):
'''simple docstr... | 608 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 1 |
"""simple docstring"""
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class _snake_case ... | 608 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 1 |
"""simple docstring"""
import baseaa
def a ( __snake_case : str ):
'''simple docstring'''
return baseaa.aaaencode(string.encode('''utf-8''' ) )
def a ( __snake_case : bytes ):
'''simple docstring'''
return baseaa.aaadecode(__snake_case ).decode('... | 608 |
"""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 import AutoProcessor, Be... | 608 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCamelCase = {
"configuration_clap": [
"CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
"ClapAudioConfig",
"ClapConfig",
"ClapT... | 608 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 1 |
"""simple docstring"""
from __future__ import annotations
def a ( __snake_case : float, __snake_case : float, __snake_case : float, ):
'''simple docstring'''
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError('''You cannot supply mo... | 608 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 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_mvp import... | 608 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 1 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as s... | 608 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 1 |
"""simple docstring"""
# Copyright 2023 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
#
#... | 608 |
"""simple docstring"""
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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
Image... | 608 | 1 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"google/umt5-small": "https://huggin... | 608 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"facebook/... | 608 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCamelCase = {
"configuration_rembert": ["REMBERT... | 608 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 1 |
"""simple docstring"""
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils imp... | 608 |
"""simple docstring"""
import os
import sys
import unittest
__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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 1 |
"""simple docstring"""
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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
Image... | 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__lowerCamelCase = {
"configuration_falcon": ["FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP", "FalconConfig"],
}
try:
if not is_torch_avai... | 608 |
"""simple docstring"""
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 transfo... | 608 | 1 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def a ( __snake_case : str ):
'''simple docstring'''
def decorator(__snake_case : List[Any] ):
UpperCAmelCase_ :int = getattr(__snake_case, '''handle_key''',... | 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 1 |
"""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... | 608 |
"""simple docstring"""
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 = {
"roberta-base":... | 608 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTo... | 608 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class ... | 608 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 1 |
"""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... | 608 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 1 |
"""simple docstring"""
import math
def a ( __snake_case : 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, 0, 1, all even numbers, all multiples of 3 a... | 608 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 1 |
"""simple docstring"""
from __future__ import annotations
def a ( __snake_case : list[int] ):
'''simple docstring'''
return len(set(__snake_case ) ) == len(__snake_case )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 608 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 1 |
"""simple docstring"""
def a ( __snake_case : int = 10 ):
'''simple docstring'''
if not isinstance(__snake_case, __snake_case ) or n < 0:
raise ValueError('''Invalid input''' )
UpperCAmelCase_ :int = 10**n
UpperCAmelCase_ :List[str] ... | 608 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
... | 608 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 1 |
"""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 ModelTesterMixin, ids_tensor, ... | 608 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 1 |
"""simple docstring"""
def a ( __snake_case : list ):
'''simple docstring'''
def merge(__snake_case : list, __snake_case : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
... | 608 |
"""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 import AutoProcessor, Be... | 608 | 1 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Any , snake_case : str , snake_case : Any ):
UpperCAmelCa... | 608 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
import random
from typing import Any
class _snake_case :
'''simple docstring'''
def __init__( self : Tuple ):
UpperCAmelCase_ :list[Any] = []
UpperCAmelCase_ :int = 0... | 608 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 1 |
"""simple docstring"""
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =""""""
UpperCamelCase__ =(
... | 608 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 1 |
"""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 ...test_configuration_com... | 608 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=A__ ):
'''simple docstring'''
UpperCamelCase__ =["""flax""", """transformers"""]
def __init__( self : str , *snake_case : Optional[int] , **s... | 608 |
"""simple docstring"""
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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
Image... | 608 | 1 |
"""simple docstring"""
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoencod... | 608 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 1 |
"""simple docstring"""
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...te... | 608 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 1 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 1 |
"""simple docstring"""
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("ignore", category=UserWarning, module="torch.optim.lr_scheduler")
class _snake_case... | 608 |
"""simple docstring"""
import os
import sys
import unittest
__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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 1 |
"""simple docstring"""
# Copyright 2023 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
#
#... | 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 1 |
"""simple docstring"""
import inspect
import unittest
class _snake_case ( unittest.TestCase ):
'''simple docstring'''
def snake_case_ ( self : Tuple ):
try:
import diffusers # noqa: F401
except ImportError:
assert False
... | 608 |
"""simple docstring"""
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 transfo... | 608 | 1 |
"""simple docstring"""
def a ( __snake_case : int = 1000 ):
'''simple docstring'''
UpperCAmelCase_ :int = -1
UpperCAmelCase_ :Any = 0
for a in range(1, n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
... | 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"google/canine-s": "https://huggingface.co/google/canine-s/resolve/main/config.json",
# See all CANINE mod... | 608 |
"""simple docstring"""
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 = {
"roberta-base":... | 608 | 1 |
"""simple docstring"""
from typing import Any
def a ( __snake_case : list, __snake_case : list, __snake_case : dict, __snake_case : dict, __snake_case : dict, ):
'''simple docstring'''
_validation(
__snake_case, __snake_case, ... | 608 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 1 |
"""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... | 608 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 1 |
"""simple docstring"""
def a ( __snake_case : list ):
'''simple docstring'''
if len(__snake_case ) <= 1:
return lst
UpperCAmelCase_ :Union[str, Any] = 1
while i < len(__snake_case ):
if lst[i - 1] <= lst[i]:
i += 1
else:
... | 608 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import pi
def a ( __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError('''On... | 608 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 1 |
"""simple docstring"""
def a ( __snake_case : int ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = [1]
UpperCAmelCase_ ,UpperCAmelCase_ ,UpperCAmelCase_ :str = 0, 0, 0
UpperCAmelCase_ :Optional[int] = ugl... | 608 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
... | 608 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 1 |
"""simple docstring"""
def a ( __snake_case : int = 1000 ):
'''simple docstring'''
return sum(2 * a * ((a - 1) // 2) for a in range(3, n + 1 ) )
if __name__ == "__main__":
print(solution())
| 608 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 1 |
"""simple docstring"""
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 608 |
"""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 import AutoProcessor, Be... | 608 | 1 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCamelCase = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
if not... | 608 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 1 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def a ( __snake_case : str ):
'''simple docstring'''
UpperCAmelCase_ ,UpperCAmelCase_ :int = analyze_text(__snake_case )
... | 608 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 1 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from .... | 608 |
"""simple docstring"""
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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
Image... | 608 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowerCamelCase = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", "M2M100OnnxConfig"],
... | 608 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 1 |
"""simple docstring"""
from math import isqrt
def a ( __snake_case : int ):
'''simple docstring'''
UpperCAmelCase_ :Dict = [True] * max_number
for i in range(2, isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2, __sn... | 608 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 1 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : int ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
UpperCAmelCase_ :int = str(bin(__snake_case ) )[2:] # remove th... | 608 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 1 |
"""simple docstring"""
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def a ( __snake_case : Tuple ):
'''simple docstring'''
return x + 2
class _snake_case ( unittest.TestCase )... | 608 |
"""simple docstring"""
import os
import sys
import unittest
__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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 1 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
fro... | 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 1 |
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