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 |
|---|---|---|---|---|
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def _lowerCAmelCase ( A__ = 3 ):
if isinstance(A__ , A__ ):
raise TypeError('number of qubits must be a integer.' )
if number_of_qubits <= ... | 622 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import TEXT_GUIDED_IMA... | 622 | 1 |
import inspect
import re
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_config_docstrings.py
a__ : str = "src/transformers"
# This is to make sure the trans... | 622 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 622 | 1 |
import string
import numpy
def _lowerCAmelCase ( A__ , A__ ):
return b if a == 0 else greatest_common_divisor(b % a , A__ )
class UpperCAmelCase__:
'''simple docstring'''
A : List[Any] = string.ascii_uppercase + string.digits
# This cipher takes alp... | 622 |
from math import sqrt
def _lowerCAmelCase ( A__ ):
assert isinstance(A__ , A__ ) and (
number >= 0
), "'number' must been an int and positive"
lowercase__ = True
# 0 and 1 are none primes.
if number <= 1:
lowercase__ = False
for diviso... | 622 | 1 |
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def _lowerCAmelCase ( A__ ):
if "cls_token" in name:
lowercase__ = name.replace('cls_token' , 'vit.embeddings.cls_token' )
... | 622 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression_... | 622 | 1 |
def _lowerCAmelCase ( A__ , A__ = False ):
if not isinstance(A__ , A__ ):
lowercase__ = F'''Expected string as input, found {type(A__ )}'''
raise ValueError(A__ )
if not isinstance(A__ , A__ ):
lowercase__ = F'''Expected boolea... | 622 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 622 | 1 |
def _lowerCAmelCase ( A__ , A__ = 0 ):
lowercase__ = length or len(A__ )
lowercase__ = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:
lowercase__, lowercase__ = list_data[i + 1], list_data[i]
lowe... | 622 |
def _lowerCAmelCase ( A__ = 50_000_000 ):
lowercase__ = set()
lowercase__ = int((limit - 24) ** (1 / 2) )
lowercase__ = set(range(3 , prime_square_limit + 1 , 2 ) )
primes.add(2 )
for p in range(3 , prime_square_limit + 1 , 2 ):
... | 622 | 1 |
from __future__ import annotations
def _lowerCAmelCase ( A__ , A__ = None ):
lowercase__ = word_bank or []
# create a table
lowercase__ = len(A__ ) + 1
lowercase__ = []
for _ in range(A__ ):
table.append([] )
# seed value
lowercas... | 622 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...util... | 622 | 1 |
from __future__ import annotations
from typing import Any
class UpperCAmelCase__( lowerCamelCase ):
'''simple docstring'''
pass
class UpperCAmelCase__:
'''simple docstring'''
def __init__( self : Optional[int] , lowerCAmelCase : Any) -> None:... | 622 |
from sklearn.metrics import matthews_corrcoef
import datasets
a__ : Any = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass classifications. It takes\ninto account true a... | 622 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : int = logging.get_logger(__name__)
a__ : Optional[Any] = {
"facebook/nllb-moe-54B": "https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json",
}
class UpperCAmelCase__(... | 622 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 622 | 1 |
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
a__ : List[Any] = collections.namedtuple("_Datasets", ["train", "v... | 622 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _lowerCAmelCase ( ):
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as original_dirname
from... | 622 | 1 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : str = logging.get_logger(__name__)
a__ : Dict = {
"facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json",
# See... | 622 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class UpperCAmelCase__( lowerCamelCase , un... | 622 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ : Dict = {
"configuration_bigbird_pegasus": [
"BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BigBirdPegasusConfig",
"BigBirdPegasusOnnxConfig",... | 622 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _lowerCAmelCase ( A__ ):
lowercase__ = SwinConfig(image_size=192 )
if "base" in model_name:
lowercase__ = 6
... | 622 | 1 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
a__ : Optional[int] = TypeVar("T")
class UpperCAmelCase__( Generic[T] ):
'''simple docstring'''
def __init__( self : Tuple , lowerCAmelCase : ... | 622 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ : Optional[int] = logging.get_logger(__name__)
a__ : ... | 622 | 1 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoints, we had to include /home/nie... | 622 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import cached_property
fr... | 622 | 1 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
a__ : List[str] = None
try:
import msvcrt
except ImportError:
a__ : List[Any] = None
try:
import fcntl
except ImportError:
a__ : List[A... | 622 |
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)
a__ : Optional[Any] = logging.getLogger()
def _lowe... | 622 | 1 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def _lowerCAmelCase ( A__ ):
lowercase__ = args.pruning_method
lowercase__ = args.threshold
lowercase__ = args.model_name_or_path.rstrip('/' )... | 622 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase__( lowerCamelCase , unittest.TestCase ):
'''simple docstring'''
A : int ... | 622 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : Any = {"voc... | 622 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fro... | 622 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging... | 622 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _lowerCAmelCase ( ):
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
with pytest.ra... | 622 | 1 |
import os
a__ : int = {"I": 1, "V": 5, "X": 10, "L": 50, "C": 1_00, "D": 5_00, "M": 10_00}
def _lowerCAmelCase ( A__ ):
lowercase__ = 0
lowercase__ = 0
while index < len(A__ ) - 1:
lowercase__ = SYMBOLS[numerals[index]]
lowercase__ = SY... | 622 |
def _lowerCAmelCase ( A__ = 600_851_475_143 ):
try:
lowercase__ = int(A__ )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
raise ValueError('Parameter n must be greater than or equa... | 622 | 1 |
a__ : List[str] = "\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
a__ : List[str] ... | 622 |
from __future__ import annotations
def _lowerCAmelCase ( A__ , A__ = None ):
lowercase__ = word_bank or []
# create a table
lowercase__ = len(A__ ) + 1
lowercase__ = []
for _ in range(A__ ):
table.append([] )
# seed value
lowercas... | 622 | 1 |
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse("3.8"):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
a__ : int = ... | 622 |
a__ : Tuple = "Tobias Carryer"
from time import time
class UpperCAmelCase__:
'''simple docstring'''
def __init__( self : str , lowerCAmelCase : List[str] , lowerCAmelCase : Any , lowerCAmelCase : str , lowerCAmelCase : ... | 622 | 1 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class UpperCAmelCase__( lowerCamelCase ):
'''simple docstring'''
... | 622 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a__ : Optional[Any] = logging.get_logger(__name__)
class UpperCAmelCase__( lowerCamelCase ):
'''simple docstring'''
def __init__( self : Optional[Any] , *l... | 622 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
... | 622 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import TEXT_GUIDED_IMA... | 622 | 1 |
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp_space_optuna,
default... | 622 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 622 | 1 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
a__ : int = logging.getLogger(__name__)
class UpperCAmelCase__( lowerCamelCase ):
'''simple docstring'''
def _... | 622 |
from math import sqrt
def _lowerCAmelCase ( A__ ):
assert isinstance(A__ , A__ ) and (
number >= 0
), "'number' must been an int and positive"
lowercase__ = True
# 0 and 1 are none primes.
if number <= 1:
lowercase__ = False
for diviso... | 622 | 1 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _lowerCAmelCase ( A__ ):
if not is_accelerate_available():
return method
lowercase__ = version.parse(accelerate.__version__ ).base_ver... | 622 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression_... | 622 | 1 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
fr... | 622 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 622 | 1 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
a__ : int = ... | 622 |
def _lowerCAmelCase ( A__ = 50_000_000 ):
lowercase__ = set()
lowercase__ = int((limit - 24) ** (1 / 2) )
lowercase__ = set(range(3 , prime_square_limit + 1 , 2 ) )
primes.add(2 )
for p in range(3 , prime_square_limit + 1 , 2 ):
... | 622 | 1 |
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from transformers.file_utils... | 622 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...util... | 622 | 1 |
def _lowerCAmelCase ( A__ ):
lowercase__ = 1
lowercase__ = 2
while i * i <= n:
lowercase__ = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1
if n > 1:
... | 622 |
from sklearn.metrics import matthews_corrcoef
import datasets
a__ : Any = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass classifications. It takes\ninto account true a... | 622 | 1 |
def _lowerCAmelCase ( A__ , A__ ):
return int((input_a, input_a).count(0 ) != 0 )
def _lowerCAmelCase ( ):
assert nand_gate(0 , 0 ) == 1
assert nand_gate(0 , 1 ) == 1
assert nand_gate(1 , 0 ) == 1
assert nand_gate(1 , 1 ) == 0
... | 622 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 622 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : int = logging.get_logger(__name__)
a__ : Dict = {
"sail/poolfo... | 622 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _lowerCAmelCase ( ):
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as original_dirname
from... | 622 | 1 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase__( lowerCamelCase ):
'''simple docstring'''
A : List[str] = (DDPMScheduler,)
def UpperCAmelCase ( self : Dict , **lowerCAm... | 622 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class UpperCAmelCase__( lowerCamelCase , un... | 622 | 1 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerFast
from... | 622 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _lowerCAmelCase ( A__ ):
lowercase__ = SwinConfig(image_size=192 )
if "base" in model_name:
lowercase__ = 6
... | 622 | 1 |
def _lowerCAmelCase ( ):
lowercase__ = []
lowercase__ = 1
while len(A__ ) < 1E6:
constant.append(str(A__ ) )
i += 1
lowercase__ = ''.join(A__ )
return (
int(constant[0] )
* int(constant[9] )
*... | 622 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ : Optional[int] = logging.get_logger(__name__)
a__ : ... | 622 | 1 |
import math
def _lowerCAmelCase ( ):
lowercase__ = input('Enter message: ' )
lowercase__ = int(input(F'''Enter key [2-{len(A__ ) - 1}]: ''' ) )
lowercase__ = input('Encryption/Decryption [e/d]: ' )
if mode.lower().startswith('e' ):
lowercase... | 622 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import cached_property
fr... | 622 | 1 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import TEXT_GUIDED_IMA... | 622 |
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)
a__ : Optional[Any] = logging.getLogger()
def _lowe... | 622 | 1 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_commo... | 622 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase__( lowerCamelCase , unittest.TestCase ):
'''simple docstring'''
A : int ... | 622 | 1 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fro... | 622 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fro... | 622 | 1 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Union[str, Any] = {
"nielsr/canine-s": 20_48,
}
# Unicode defines 1,114,112 to... | 622 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _lowerCAmelCase ( ):
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
with pytest.ra... | 622 | 1 |
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
a__ : Dict = "▁"
a__ :... | 622 |
def _lowerCAmelCase ( A__ = 600_851_475_143 ):
try:
lowercase__ = int(A__ )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
raise ValueError('Parameter n must be greater than or equa... | 622 | 1 |
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
a__ : int = False
class UpperCAmelCase__( unittest.TestCase ):
'''simple d... | 622 |
from __future__ import annotations
def _lowerCAmelCase ( A__ , A__ = None ):
lowercase__ = word_bank or []
# create a table
lowercase__ = len(A__ ) + 1
lowercase__ = []
for _ in range(A__ ):
table.append([] )
# seed value
lowercas... | 622 | 1 |
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def _lowerCAmelCase ( A__ , A__ , A__ ):
# Initialise PyTorch model
lowercase__ = TaConfig.from_json_file(A__ ... | 622 |
a__ : Tuple = "Tobias Carryer"
from time import time
class UpperCAmelCase__:
'''simple docstring'''
def __init__( self : str , lowerCAmelCase : List[str] , lowerCAmelCase : Any , lowerCAmelCase : str , lowerCAmelCase : ... | 622 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
a__ : Optional[int] = {
"configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}
try:
if not is_torch_availabl... | 622 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a__ : Optional[Any] = logging.get_logger(__name__)
class UpperCAmelCase__( lowerCamelCase ):
'''simple docstring'''
def __init__( self : Optional[Any] , *l... | 622 | 1 |
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
a__ : str = {
"sample_size": 32,
"in_channels": 3,
"out_channels": 3,
"layers_per_block": 2,
"num_class_embeds": 10_00,
"bl... | 622 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import TEXT_GUIDED_IMA... | 622 | 1 |
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 import stable_softmax
if... | 622 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 622 | 1 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase__( lowerCamelCase ):
'''simple docst... | 622 |
from math import sqrt
def _lowerCAmelCase ( A__ ):
assert isinstance(A__ , A__ ) and (
number >= 0
), "'number' must been an int and positive"
lowercase__ = True
# 0 and 1 are none primes.
if number <= 1:
lowercase__ = False
for diviso... | 622 | 1 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
a__ : Any = 5_00_00
a__ : List[Any] = 50_00
a__ , a__ : Optional[int] = os.path.split(__file__)
a__ : Optional[int] = os.path.j... | 622 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression_... | 622 | 1 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class UpperCAmelCase__( unittest.TestCase , lowerCamelCase ):
'''simple docstring'''
def UpperCAmelCase ( self : str) -> List[Any]:
"""simple docstrin... | 622 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 622 | 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 AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def _lowerCAmelCase ( A__ ):
lowercase__ = Swinva... | 622 |
def _lowerCAmelCase ( A__ = 50_000_000 ):
lowercase__ = set()
lowercase__ = int((limit - 24) ** (1 / 2) )
lowercase__ = set(range(3 , prime_square_limit + 1 , 2 ) )
primes.add(2 )
for p in range(3 , prime_square_limit + 1 , 2 ):
... | 622 | 1 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...te... | 622 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...util... | 622 | 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 import Accelerator, D... | 622 |
from sklearn.metrics import matthews_corrcoef
import datasets
a__ : Any = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass classifications. It takes\ninto account true a... | 622 | 1 |
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get_up_block
@dataclass
cla... | 622 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 622 | 1 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 622 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _lowerCAmelCase ( ):
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as original_dirname
from... | 622 | 1 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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_comm... | 622 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class UpperCAmelCase__( lowerCamelCase , un... | 622 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ : Tuple = {
"configuration_wav2vec2": ["WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Wav2Vec2Config"],
"f... | 622 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _lowerCAmelCase ( A__ ):
lowercase__ = SwinConfig(image_size=192 )
if "base" in model_name:
lowercase__ = 6
... | 622 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ : str = {
"configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
"tokenization_luke": ["LukeTokenizer"],
}
try:
if not is_torch_available... | 622 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ : Optional[int] = logging.get_logger(__name__)
a__ : ... | 622 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from diffusers.utils import fl... | 622 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import cached_property
fr... | 622 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
a__ : Any = {
"configuration_trocr": ["TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP", "TrOCRConfig"],
"pr... | 622 |
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)
a__ : Optional[Any] = logging.getLogger()
def _lowe... | 622 | 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
a__ : int = Mapping[str, np.ndarray]
a__ : Tuple = Mapping[str, Any] # Is a nested dict.
a__ : i... | 622 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase__( lowerCamelCase , unittest.TestCase ):
'''simple docstring'''
A : int ... | 622 | 1 |
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
OpenAIGPTDoubleHeads... | 622 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fro... | 622 | 1 |
import os
from collections.abc import Iterator
def _lowerCAmelCase ( A__ = "." ):
for dir_path, dir_names, filenames in os.walk(A__ ):
lowercase__ = [d for d in dir_names if d != 'scripts' and d[0] not in '._']
for filename in filenames:
if filename ==... | 622 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _lowerCAmelCase ( ):
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
with pytest.ra... | 622 | 1 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("Googling.....")
a__ : Optional[Any] = "https://www.google.com/search?q=" + " ".join(sys.argv[1:])
a__ : Any = req... | 622 |
def _lowerCAmelCase ( A__ = 600_851_475_143 ):
try:
lowercase__ = int(A__ )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
raise ValueError('Parameter n must be greater than or equa... | 622 | 1 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin... | 622 |
from __future__ import annotations
def _lowerCAmelCase ( A__ , A__ = None ):
lowercase__ = word_bank or []
# create a table
lowercase__ = len(A__ ) + 1
lowercase__ = []
for _ in range(A__ ):
table.append([] )
# seed value
lowercas... | 622 | 1 |
from sklearn.metrics import recall_score
import datasets
a__ : Optional[int] = "\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true positives and FN is the fal... | 622 |
a__ : Tuple = "Tobias Carryer"
from time import time
class UpperCAmelCase__:
'''simple docstring'''
def __init__( self : str , lowerCAmelCase : List[str] , lowerCAmelCase : Any , lowerCAmelCase : str , lowerCAmelCase : ... | 622 | 1 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 622 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a__ : Optional[Any] = logging.get_logger(__name__)
class UpperCAmelCase__( lowerCamelCase ):
'''simple docstring'''
def __init__( self : Optional[Any] , *l... | 622 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : List[Any] = logging.get_logger(__name__)
a__ : Optional[Any] = {
"uclanlp/visualbert-vqa": "https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json",
"uclanlp/visualbert... | 622 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import TEXT_GUIDED_IMA... | 622 | 1 |
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...tes... | 622 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 622 | 1 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class UpperCAmelCase__:
'''simple docstring'''
A : torch.Tensor # [batch_size x 3]
A : torch.Tensor # [batch_size x 3]
A : torch.Tensor # [batch_size x 3]
A : torch.Ten... | 622 |
from math import sqrt
def _lowerCAmelCase ( A__ ):
assert isinstance(A__ , A__ ) and (
number >= 0
), "'number' must been an int and positive"
lowercase__ = True
# 0 and 1 are none primes.
if number <= 1:
lowercase__ = False
for diviso... | 622 | 1 |
# using dfs for finding eulerian path traversal
def _lowerCAmelCase ( A__ , A__ , A__ , A__=None ):
lowercase__ = (path or []) + [u]
for v in graph[u]:
if visited_edge[u][v] is False:
lowercase__, lowercase__ = True, True
lowercas... | 622 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression_... | 622 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM,
AutoTokenizer... | 622 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 622 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ : Tuple = {"configuration_mmbt": ["MMBTConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 622 |
def _lowerCAmelCase ( A__ = 50_000_000 ):
lowercase__ = set()
lowercase__ = int((limit - 24) ** (1 / 2) )
lowercase__ = set(range(3 , prime_square_limit + 1 , 2 ) )
primes.add(2 )
for p in range(3 , prime_square_limit + 1 , 2 ):
... | 622 | 1 |
def _lowerCAmelCase ( A__ = 50_000_000 ):
lowercase__ = set()
lowercase__ = int((limit - 24) ** (1 / 2) )
lowercase__ = set(range(3 , prime_square_limit + 1 , 2 ) )
primes.add(2 )
for p in range(3 , prime_square_limit + 1 , 2 ):
... | 622 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...util... | 622 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
a__ : Optional[int] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 622 |
from sklearn.metrics import matthews_corrcoef
import datasets
a__ : Any = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass classifications. It takes\ninto account true a... | 622 | 1 |
def _lowerCAmelCase ( A__ ):
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print("Program to check whether a number is a Perfect number or not...")
a__ : Tuple = int(input("Enter number: ").str... | 622 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 622 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a__ : int = {
"configuration_efficientformer": [
"EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 622 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _lowerCAmelCase ( ):
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as original_dirname
from... | 622 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a__ : Tuple = logging.get_logger(__name__)
a__ : ... | 622 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class UpperCAmelCase__( lowerCamelCase , un... | 622 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
a__ : Union[str, Any] = logging.get_logger(__name__)
class UpperCAmelCase__( lowerCamelCase ):
'''simple docstring'''
A :... | 622 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _lowerCAmelCase ( A__ ):
lowercase__ = SwinConfig(image_size=192 )
if "base" in model_name:
lowercase__ = 6
... | 622 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : Tuple = logging.get_logger(__name__)
a__ : Union[str, Any] = {
"andreasmadsen/efficient_mlm_m... | 622 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ : Optional[int] = logging.get_logger(__name__)
a__ : ... | 622 | 1 |
from itertools import count
def _lowerCAmelCase ( A__ = 50 ):
lowercase__ = [1] * min_block_length
for n in count(A__ ):
fill_count_functions.append(1 )
for block_length in range(A__ , n + 1 ):
for block_start in range(n - block_le... | 622 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import cached_property
fr... | 622 | 1 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def _lowerCAmelCase ( A__ , A__=() , A__=None , A__="no" , A__="29500" ):
lowercase__ = False
lowercase__... | 622 |
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)
a__ : Optional[Any] = logging.getLogger()
def _lowe... | 622 | 1 |
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STA... | 622 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase__( lowerCamelCase , unittest.TestCase ):
'''simple docstring'''
A : int ... | 622 | 1 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
a__ : Optional[Any] = TypeVar("T")
a__ : List[Any] = TypeVar("U")
class UpperCAmelCase__( Generic[T, U] ):
'''simple docstring'''
def __init__( ... | 622 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fro... | 622 | 1 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
a__ : Optional[int] = ["small", "medium", "large"]
a__ : List[str] = "lm_head.decoder.weight"
a__ : Optional[Any] = "lm_head.weight"
def _lowerCAmelCase ( A__ , A__ ... | 622 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _lowerCAmelCase ( ):
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
with pytest.ra... | 622 | 1 |
def _lowerCAmelCase ( A__ = 10**9 ):
lowercase__ = 1
lowercase__ = 2
lowercase__ = 0
lowercase__ = 0
lowercase__ = 0
while perimeter <= max_perimeter:
perimeters_sum += perimeter
prev_value += 2 * value
value += prev_value
... | 622 |
def _lowerCAmelCase ( A__ = 600_851_475_143 ):
try:
lowercase__ = int(A__ )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
raise ValueError('Parameter n must be greater than or equa... | 622 | 1 |
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
a__ : Tuple = {
# 1536-bit
5: {
"prime": int(
"FFFFFF... | 622 |
from __future__ import annotations
def _lowerCAmelCase ( A__ , A__ = None ):
lowercase__ = word_bank or []
# create a table
lowercase__ = len(A__ ) + 1
lowercase__ = []
for _ in range(A__ ):
table.append([] )
# seed value
lowercas... | 622 | 1 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface import H... | 622 |
a__ : Tuple = "Tobias Carryer"
from time import time
class UpperCAmelCase__:
'''simple docstring'''
def __init__( self : str , lowerCAmelCase : List[str] , lowerCAmelCase : Any , lowerCAmelCase : str , lowerCAmelCase : ... | 622 | 1 |
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_available, logging
from .benchm... | 622 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a__ : Optional[Any] = logging.get_logger(__name__)
class UpperCAmelCase__( lowerCamelCase ):
'''simple docstring'''
def __init__( self : Optional[Any] , *l... | 622 | 1 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _lowerCAmelCase ( A__ ):
lowercase__ = SwinConfig(image_size=192 )
if "base" in model_name:
lowercase__ = 6
... | 622 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import TEXT_GUIDED_IMA... | 622 | 1 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import cached_property
fr... | 622 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 622 | 1 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as Prop... | 622 |
from math import sqrt
def _lowerCAmelCase ( A__ ):
assert isinstance(A__ , A__ ) and (
number >= 0
), "'number' must been an int and positive"
lowercase__ = True
# 0 and 1 are none primes.
if number <= 1:
lowercase__ = False
for diviso... | 622 | 1 |
from math import sqrt
def _lowerCAmelCase ( A__ ):
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 are not primes
return False
... | 622 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression_... | 622 | 1 |
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerT... | 622 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 622 | 1 |
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)
a__ : Optional[Any] = logging.getLogger()
def _lowe... | 622 |
def _lowerCAmelCase ( A__ = 50_000_000 ):
lowercase__ = set()
lowercase__ = int((limit - 24) ** (1 / 2) )
lowercase__ = set(range(3 , prime_square_limit + 1 , 2 ) )
primes.add(2 )
for p in range(3 , prime_square_limit + 1 , 2 ):
... | 622 | 1 |
import torch
from diffusers import StableDiffusionPipeline
a__ : str = "path-to-your-trained-model"
a__ : Optional[Any] = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("cuda")
a__ : List[Any] = "A photo of sks dog in a bucket"
... | 622 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...util... | 622 | 1 |
from __future__ import annotations
from collections.abc import Callable
a__ : Dict = list[list[float | int]]
def _lowerCAmelCase ( A__ , A__ ):
lowercase__ = len(A__ )
lowercase__ = [[0 for _ in range(size + 1 )] for _ in range(A__ )]
lowercase__ =... | 622 |
from sklearn.metrics import matthews_corrcoef
import datasets
a__ : Any = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass classifications. It takes\ninto account true a... | 622 | 1 |
def _lowerCAmelCase ( A__ = 50 ):
lowercase__ = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start in range(row_length - block_length ):
ways_nu... | 622 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 622 | 1 |
def _lowerCAmelCase ( A__ = 50 ):
lowercase__ = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
di... | 622 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _lowerCAmelCase ( ):
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as original_dirname
from... | 622 | 1 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.rob... | 622 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class UpperCAmelCase__( lowerCamelCase , un... | 622 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : List[Any] = logging.get_logger(__name__)
a__ : int = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See all Cvt models at https://huggingfa... | 622 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _lowerCAmelCase ( A__ ):
lowercase__ = SwinConfig(image_size=192 )
if "base" in model_name:
lowercase__ = 6
... | 622 | 1 |
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