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 |
|---|---|---|---|---|
def a_ ( __lowerCAmelCase ):
if upper_limit < 0:
raise ValueError('''Limit for the Catalan sequence must be ≥ 0''' )
lowerCAmelCase__ = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
lowerCAmelCase__ = 1
if upper_limit > 0:
lowerCAme... | 615 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__magic_name__ : Optional[int] = get_te... | 615 | 1 |
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ (metaclass=_a ):
lowercase_ : Any = ["transformers", "torch", "note_seq"]
def __init__( self : int , *__lowerCamelCase : Optional[Any] , **__lowerCamelCase : int ... | 615 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__magic_name__ : Any = TypeVar("""KEY""")
__magic_name__ : Dict = TypeVar("""VAL""")
@dataclass(frozen=_a , slots=_a )
class SCREAMI... | 615 | 1 |
from __future__ import annotations
def a_ ( __lowerCAmelCase ):
if not nums:
return 0
lowerCAmelCase__ = nums[0]
lowerCAmelCase__ = 0
for num in nums[1:]:
lowerCAmelCase__ , lowerCAmelCase__ = (
max_excluding + num,
... | 615 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 | 1 |
def a_ ( __lowerCAmelCase = 10_00 ):
lowerCAmelCase__ = 2**power
lowerCAmelCase__ = 0
while n:
lowerCAmelCase__ , lowerCAmelCase__ = r + n % 10, n // 10
return r
if __name__ == "__main__":
print(solution(int(str(input())... | 615 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__magic_name__ : List[Any] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input... | 615 | 1 |
from __future__ import annotations
from random import choice
def a_ ( __lowerCAmelCase ):
return choice(__lowerCAmelCase )
def a_ ( __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = random_pivot(__lowerCAmelCase )
# partition based on pivot
... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Optional[int] = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""token... | 615 | 1 |
import os
from collections.abc import Iterator
def a_ ( __lowerCAmelCase = "." ):
for dir_path, dir_names, filenames in os.walk(__lowerCAmelCase ):
lowerCAmelCase__ = [d for d in dir_names if d != '''scripts''' and d[0] not in '''._''']
for filename in filenames:
... | 615 |
import logging
from transformers.configuration_utils import PretrainedConfig
__magic_name__ : Tuple = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
lowercase_ : Tuple = "masked_bert"
def __init__( self : List[Any] , _... | 615 | 1 |
from __future__ import annotations
__magic_name__ : List[Any] = [True] * 1_00_00_01
__magic_name__ : Dict = 2
while i * i <= 1_00_00_00:
if seive[i]:
for j in range(i * i, 1_00_00_01, i):
__magic_name__ : List[str] = False
... | 615 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 615 | 1 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate impor... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Union[str, Any] = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPC... | 615 | 1 |
def a_ ( __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = len(__lowerCAmelCase )
lowerCAmelCase__ = []
for i in range(len(__lowerCAmelCase ) - pat_len + 1 ):
lowerCAmelCase__ = True
for j in range(__lowerCAmelCase )... | 615 |
from __future__ import annotations
def a_ ( __lowerCAmelCase ):
if not nums:
return 0
lowerCAmelCase__ = nums[0]
lowerCAmelCase__ = 0
for num in nums[1:]:
lowerCAmelCase__ , lowerCAmelCase__ = (
max_excluding + num,
... | 615 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils import logg... | 615 |
from __future__ import annotations
def a_ ( __lowerCAmelCase , __lowerCAmelCase = None ):
lowerCAmelCase__ = word_bank or []
# create a table
lowerCAmelCase__ = len(__lowerCAmelCase ) + 1
lowerCAmelCase__ = []
for _ in range(__lowerCA... | 615 | 1 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_availa... | 615 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenize... | 615 | 1 |
def a_ ( __lowerCAmelCase , __lowerCAmelCase ):
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def a_ ( __lowerCAmelCase , __lowerCAmelCase=0 ):
return sorted(__lowerCAmelCase , key=lambda __lowerCAmelCase : x[column] )
def a_ ( __lowerCAme... | 615 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__magic_name__ : List[Any] = logging.get_logger(__name__)
def a_ ( __lowerCAmelCase , __lowerCAmelC... | 615 | 1 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import Iter... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : List[str] = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxCon... | 615 | 1 |
import sys
__magic_name__ : List[str] = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
... | 615 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Any = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_... | 615 | 1 |
import string
from math import logaa
def a_ ( __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = document.translate(
str.maketrans('''''' , '''''' , string.punctuation ) ).replace('''\n''' , '''''' )
lowerCAmelCase__ = document_with... | 615 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : Optional[Any] = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 615 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, D... | 615 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaT... | 615 | 1 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__magic_name__ : List[Any] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input... | 615 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 615 | 1 |
def a_ ( __lowerCAmelCase ):
if isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError('''\'float\' object cannot be interpreted as an integer''' )
if isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError('''\'str\' object cannot be interpreted ... | 615 |
import numpy as np
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = int(np.ceil((x_end - xa) / h ) )
lowerCAmelCase__ = np.zeros((n + 1,) )
lowerCAmelCase__ = ... | 615 | 1 |
def a_ ( __lowerCAmelCase ):
lowerCAmelCase__ = 0
while len(__lowerCAmelCase ) > 1:
lowerCAmelCase__ = 0
# Consider two files with minimum cost to be merged
for _ in range(2 ):
lowerCAmelCase__ = files.index(min(__lowerCAme... | 615 |
from scipy.stats import pearsonr
import datasets
__magic_name__ : Union[str, Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies ... | 615 | 1 |
from __future__ import annotations
__magic_name__ : Union[str, Any] = list[tuple[int, int]]
__magic_name__ : List[Any] = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
... | 615 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__magic_name__ : List[str] = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 615 | 1 |
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastapi... | 615 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transform... | 615 | 1 |
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available... | 615 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from t... | 615 | 1 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__magic_name__ : str = {
"""facebook/mask2former-swin-small-coco-instance""": (
"""https://huggingface.co/... | 615 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__magic_name__ : Optional[int] = get_te... | 615 | 1 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
__magic_name__ : List[str] = """\
"""
__magic_name__ : List[Any] = """
Perplexity (PPL) is one... | 615 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__magic_name__ : Any = TypeVar("""KEY""")
__magic_name__ : Dict = TypeVar("""VAL""")
@dataclass(frozen=_a , slots=_a )
class SCREAMI... | 615 | 1 |
from ....utils import logging
__magic_name__ : Dict = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
def __init__( self : Tuple , __lowerCamelCase : Tuple , __lowerCamelCase : Any=None , __lowerCamelCase : Tup... | 615 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 | 1 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def a_ ( ):
lowerCAmelCase__ = ArgumentParser(
description=(
'''PyTorch TPU distributed training launch ... | 615 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__magic_name__ : List[Any] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input... | 615 | 1 |
def a_ ( __lowerCAmelCase = 1_00 ):
lowerCAmelCase__ = 0
lowerCAmelCase__ = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
if __name__ == "__main__":
print(F"{solution() ... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Optional[int] = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""token... | 615 | 1 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from t... | 615 |
import logging
from transformers.configuration_utils import PretrainedConfig
__magic_name__ : Tuple = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
lowercase_ : Tuple = "masked_bert"
def __init__( self : List[Any] , _... | 615 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Any = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_... | 615 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 615 | 1 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def a_ ( __lowerCAmelCase ):
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/wiki/CJK_U... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Union[str, Any] = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPC... | 615 | 1 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class SCREAMING_SNAKE_CASE__ (_a , unittest.TestCase ):
lowercase_ : int = Phobe... | 615 |
from __future__ import annotations
def a_ ( __lowerCAmelCase ):
if not nums:
return 0
lowerCAmelCase__ = nums[0]
lowerCAmelCase__ = 0
for num in nums[1:]:
lowerCAmelCase__ , lowerCAmelCase__ = (
max_excluding + num,
... | 615 | 1 |
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class SCREAMING_SNAKE_CASE__ (_a ):
def __init__( ... | 615 |
from __future__ import annotations
def a_ ( __lowerCAmelCase , __lowerCAmelCase = None ):
lowerCAmelCase__ = word_bank or []
# create a table
lowerCAmelCase__ = len(__lowerCAmelCase ) + 1
lowerCAmelCase__ = []
for _ in range(__lowerCA... | 615 | 1 |
from __future__ import annotations
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
if len(__lowerCAmelCase ) == 0:
raise ValueError('''find_max() arg is an empty sequence''' )
if (
left >= len(__lowerCAmelCase )
or left < -len(__lowerCAmelCa... | 615 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenize... | 615 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__magic_name__ : Dict = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
... | 615 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__magic_name__ : List[Any] = logging.get_logger(__name__)
def a_ ( __lowerCAmelCase , __lowerCAmelC... | 615 | 1 |
# 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 req... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : List[str] = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxCon... | 615 | 1 |
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for tests
from os.pat... | 615 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Any = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_... | 615 | 1 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils im... | 615 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : Optional[Any] = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 615 | 1 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
__magic_name__ : int = False
try:
__magi... | 615 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaT... | 615 | 1 |
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
__magic_name__ : Optional[Any] = datasets.utils.logging.get_logger(__name__)
@datac... | 615 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 615 | 1 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_availabl... | 615 |
import numpy as np
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = int(np.ceil((x_end - xa) / h ) )
lowerCAmelCase__ = np.zeros((n + 1,) )
lowerCAmelCase__ = ... | 615 | 1 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Optional[Any] , __lowerCamelCase : List[str] , __lowerCamelCase : Union[str, Any] , __lowerCamelCase : Any , ... | 615 |
from scipy.stats import pearsonr
import datasets
__magic_name__ : Union[str, Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies ... | 615 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__magic_name__ : str = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDecoderConfig"... | 615 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__magic_name__ : List[str] = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 615 | 1 |
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` instead."""
)
| 615 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transform... | 615 | 1 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
__magic_name__ : Any = logging.get_logger(__name__)... | 615 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from t... | 615 | 1 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__magic_name__ : Optional[int] = get_te... | 615 | 1 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_availa... | 615 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__magic_name__ : Any = TypeVar("""KEY""")
__magic_name__ : Dict = TypeVar("""VAL""")
@dataclass(frozen=_a , slots=_a )
class SCREAMI... | 615 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
__magic_name__ : List[Any] = {
"""configuration_speech_to_text"""... | 615 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 | 1 |
from __future__ import annotations
from typing import Any
def a_ ( __lowerCAmelCase ):
create_state_space_tree(__lowerCAmelCase , [] , 0 )
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
if index == len(__lowerCAmelCase ):
print(__lowerC... | 615 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__magic_name__ : List[Any] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input... | 615 | 1 |
import requests
from bsa import BeautifulSoup
def a_ ( __lowerCAmelCase = "https://www.worldometers.info/coronavirus" ):
lowerCAmelCase__ = BeautifulSoup(requests.get(__lowerCAmelCase ).text , '''html.parser''' )
lowerCAmelCase__ = soup.findAll('''h1''' ... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Optional[int] = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""token... | 615 | 1 |
from collections import deque
from .hash_table import HashTable
class SCREAMING_SNAKE_CASE__ (_a ):
def __init__( self : List[str] , *__lowerCamelCase : List[str] , **__lowerCamelCase : List[str] ):
"""simple docstring"""
supe... | 615 |
import logging
from transformers.configuration_utils import PretrainedConfig
__magic_name__ : Tuple = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
lowercase_ : Tuple = "masked_bert"
def __init__( self : List[Any] , _... | 615 | 1 |
def a_ ( __lowerCAmelCase = 3 , __lowerCAmelCase = 7 , __lowerCAmelCase = 1_00_00_00 ):
lowerCAmelCase__ = 0
lowerCAmelCase__ = 1
for current_denominator in range(1 , limit + 1 ):
lowerCAmelCase__ = current_denominator * numerator /... | 615 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 615 | 1 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__magic_name__ : Any = logging.get_logger("""transformers.models.speecht5""")
def a_ ( __lowerCAmelCase , __lowerCAmelCase ... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Union[str, Any] = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPC... | 615 | 1 |
def a_ ( __lowerCAmelCase ):
lowerCAmelCase__ = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def a_ ( __lowerCAmelCase = 1_00 ):
lowerCAmelCase__ = 1
lowerCAmelCase__ = 2
for i in range(2 , m... | 615 |
from __future__ import annotations
def a_ ( __lowerCAmelCase ):
if not nums:
return 0
lowerCAmelCase__ = nums[0]
lowerCAmelCase__ = 0
for num in nums[1:]:
lowerCAmelCase__ , lowerCAmelCase__ = (
max_excluding + num,
... | 615 | 1 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
... | 615 |
from __future__ import annotations
def a_ ( __lowerCAmelCase , __lowerCAmelCase = None ):
lowerCAmelCase__ = word_bank or []
# create a table
lowerCAmelCase__ = len(__lowerCAmelCase ) + 1
lowerCAmelCase__ = []
for _ in range(__lowerCA... | 615 | 1 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sent... | 615 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenize... | 615 | 1 |
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, require_vision
from t... | 615 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__magic_name__ : List[Any] = logging.get_logger(__name__)
def a_ ( __lowerCAmelCase , __lowerCAmelC... | 615 | 1 |
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
# Initialise PyTorch model
lowerCAmelCase__ ... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : List[str] = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxCon... | 615 | 1 |
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import ConfigTes... | 615 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Any = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_... | 615 | 1 |
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
__magic_name__ : List[Any] = ... | 615 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : Optional[Any] = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 615 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Dict = logging.get_logger(__name__)
__magic_name__ : Any = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class SCREAMING_SNAKE_CASE__ (_... | 615 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaT... | 615 | 1 |
def a_ ( __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = 0
... | 615 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 615 | 1 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__magic_name__ : Any = TypeVar("""KEY""")
__magic_name__ : Dict = TypeVar("""VAL""")
@dataclass(frozen=_a , slots=_a )
class SCREAMI... | 615 |
import numpy as np
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = int(np.ceil((x_end - xa) / h ) )
lowerCAmelCase__ = np.zeros((n + 1,) )
lowerCAmelCase__ = ... | 615 | 1 |
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase = None ):
if version.parse(hfh.__version__ ).release < version.parse('''0.11.0''' ).release:
... | 615 |
from scipy.stats import pearsonr
import datasets
__magic_name__ : Union[str, Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies ... | 615 | 1 |
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
__magic_name__ : Optional[int] = Mapping[str, np.ndarray]
__magic_name__ : str = Mapping[str, An... | 615 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__magic_name__ : List[str] = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 615 | 1 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__magic_name__ : List[str] = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 615 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transform... | 615 | 1 |
import datasets
__magic_name__ : List[str] = """\
@InProceedings{conneau2018xnli,
author = \"Conneau, Alexis
and Rinott, Ruty
and Lample, Guillaume
and Williams, Adina
and Bowman, Samuel R.
and Schwenk, Hol... | 615 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from t... | 615 | 1 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transform... | 615 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__magic_name__ : Optional[int] = get_te... | 615 | 1 |
from __future__ import annotations
def a_ ( __lowerCAmelCase ):
lowerCAmelCase__ = 0.00
lowerCAmelCase__ = 0
for resistor in resistors:
if resistor <= 0:
lowerCAmelCase__ = F"""Resistor at index {index} has a negative or zero value!"""... | 615 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__magic_name__ : Any = TypeVar("""KEY""")
__magic_name__ : Dict = TypeVar("""VAL""")
@dataclass(frozen=_a , slots=_a )
class SCREAMI... | 615 | 1 |
from __future__ import annotations
__magic_name__ : Any = list[list[int]]
# assigning initial values to the grid
__magic_name__ : Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
... | 615 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 | 1 |
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAme... | 615 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__magic_name__ : List[Any] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input... | 615 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Optional[Any] = {
"""configuration_squeezebert""": [
"""SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Sq... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Optional[int] = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""token... | 615 | 1 |
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.pi... | 615 |
import logging
from transformers.configuration_utils import PretrainedConfig
__magic_name__ : Tuple = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
lowercase_ : Tuple = "masked_bert"
def __init__( self : List[Any] , _... | 615 | 1 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_... | 615 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 615 | 1 |
from __future__ import annotations
from collections import deque
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Dict , __lowerCamelCase : list[str] ):
"""simple docstring"""
lowerCAmelCase__ = []
self.adlist.appen... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Union[str, Any] = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPC... | 615 | 1 |
def a_ ( __lowerCAmelCase = 4_00_00_00 ):
lowerCAmelCase__ = []
lowerCAmelCase__ , lowerCAmelCase__ = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(__lowerCAmelCase )
lowerCAmelCase__ , lowerCAmelCase__ = b,... | 615 |
from __future__ import annotations
def a_ ( __lowerCAmelCase ):
if not nums:
return 0
lowerCAmelCase__ = nums[0]
lowerCAmelCase__ = 0
for num in nums[1:]:
lowerCAmelCase__ , lowerCAmelCase__ = (
max_excluding + num,
... | 615 | 1 |
import requests
from bsa import BeautifulSoup
def a_ ( __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = BeautifulSoup(requests.get(__lowerCAmelCase , params=__lowerCAmelCase ).content , '''html.parser''' )
lowerCAmelCase__ = soup.find('''div'... | 615 |
from __future__ import annotations
def a_ ( __lowerCAmelCase , __lowerCAmelCase = None ):
lowerCAmelCase__ = word_bank or []
# create a table
lowerCAmelCase__ = len(__lowerCAmelCase ) + 1
lowerCAmelCase__ = []
for _ in range(__lowerCA... | 615 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__magic_name__ : List[Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNo... | 615 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenize... | 615 | 1 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
fro... | 615 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__magic_name__ : List[Any] = logging.get_logger(__name__)
def a_ ( __lowerCAmelCase , __lowerCAmelC... | 615 | 1 |
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
from .tokenization_gpta import GPTaTokenizer
... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : List[str] = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxCon... | 615 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Optional[int] = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""token... | 615 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Any = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_... | 615 | 1 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__magic_name__ : str = None
try:
import msvcrt
except ImportError:
__magic_name__ : Dict = None
try:
import fcntl
except ImportError:
... | 615 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : Optional[Any] = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 615 | 1 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import as... | 615 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaT... | 615 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
__magic_name__ : int = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 615 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 615 | 1 |
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ (metaclass=_a ):
lowercase_ : Any = ["torch", "scipy"]
def __init__( self : List[Any] , *__lowerCamelCase : Tuple , **__lowerCamelCase : List[str] ):
... | 615 |
import numpy as np
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = int(np.ceil((x_end - xa) / h ) )
lowerCAmelCase__ = np.zeros((n + 1,) )
lowerCAmelCase__ = ... | 615 | 1 |
import requests
__magic_name__ : Any = """https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="""
def a_ ( __lowerCAmelCase ):
# fetching a list of articles in json format
lowerCAmelCase__ = requests.get(_NEWS_API + bbc_news_api_key ).json()
#... | 615 |
from scipy.stats import pearsonr
import datasets
__magic_name__ : Union[str, Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies ... | 615 | 1 |
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
cla... | 615 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__magic_name__ : List[str] = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 615 | 1 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def a_ ( ):
lowerCAmelCase__ = ArgumentParser(
description=(
'''PyTorch TPU distributed training launch ... | 615 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transform... | 615 | 1 |
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from ac... | 615 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from t... | 615 | 1 |
import warnings
from ..trainer import Trainer
from ..utils import logging
__magic_name__ : Union[str, Any] = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
def __init__( self : Optional[int] , __lowerCamelCase : Dict=None ,... | 615 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__magic_name__ : Optional[int] = get_te... | 615 | 1 |
import re
from filelock import FileLock
try:
import nltk
__magic_name__ : int = True
except (ImportError, ModuleNotFoundError):
__magic_name__ : Tuple = False
if NLTK_AVAILABLE:
with FileLock(""".lock""") as lock:
nltk.download("""... | 615 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__magic_name__ : Any = TypeVar("""KEY""")
__magic_name__ : Dict = TypeVar("""VAL""")
@dataclass(frozen=_a , slots=_a )
class SCREAMI... | 615 | 1 |
from scipy.stats import pearsonr
import datasets
__magic_name__ : Union[str, Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies ... | 615 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 | 1 |
import argparse
import json
from tqdm import tqdm
def a_ ( ):
lowerCAmelCase__ = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'''--src_path''' , type=__lowerCAmelCase , default='''biencoder-nq-dev.json''' , help='''Path to raw DPR trai... | 615 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__magic_name__ : List[Any] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input... | 615 | 1 |
import math
def a_ ( __lowerCAmelCase , __lowerCAmelCase ):
return math.pow(__lowerCAmelCase , 2 ) - a
def a_ ( __lowerCAmelCase ):
return 2 * x
def a_ ( __lowerCAmelCase ):
lowerCAmelCase__ = 2.0
while start <= a:
lowerCAmelCase__ ... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Optional[int] = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""token... | 615 | 1 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
... | 615 |
import logging
from transformers.configuration_utils import PretrainedConfig
__magic_name__ : Tuple = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
lowercase_ : Tuple = "masked_bert"
def __init__( self : List[Any] , _... | 615 | 1 |
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def a_ ( __lowerCAmelCase ):
lowerCAmelCase__ = []
emb... | 615 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 615 | 1 |
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 a_ ( __lowe... | 615 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Union[str, Any] = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPC... | 615 | 1 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentPars... | 615 |
from __future__ import annotations
def a_ ( __lowerCAmelCase ):
if not nums:
return 0
lowerCAmelCase__ = nums[0]
lowerCAmelCase__ = 0
for num in nums[1:]:
lowerCAmelCase__ , lowerCAmelCase__ = (
max_excluding + num,
... | 615 | 1 |
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffusers.utils.t... | 615 |
from __future__ import annotations
def a_ ( __lowerCAmelCase , __lowerCAmelCase = None ):
lowerCAmelCase__ = word_bank or []
# create a table
lowerCAmelCase__ = len(__lowerCAmelCase ) + 1
lowerCAmelCase__ = []
for _ in range(__lowerCA... | 615 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Dict = logging.get_logger(__name__)
__magic_name__ : List[str] = {
"""microsoft/swinv2-tiny-patch4-window8-256""": (
"""https://huggingface.co/microsoft/swinv2-tiny-... | 615 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenize... | 615 | 1 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenize... | 615 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__magic_name__ : List[Any] = logging.get_logger(__name__)
def a_ ( __lowerCAmelCase , __lowerCAmelC... | 615 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.