code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from dat... | 686 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase :Any = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''Lon... | 686 | 1 |
'''simple docstring'''
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
lowerCamelCase :Optional[i... | 686 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCamelCase :Any = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import LEDConfig, 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
fro... | 686 |
'''simple docstring'''
lowerCamelCase :dict[tuple[int, int, int], int] = {}
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not fail... | 686 | 1 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
lowerCamelCase :Union[str, Any] = '''%20'''.join(argv[1:]) if len(arg... | 686 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
class _lowerCA... | 686 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
lowerCamelCase :List[str] = logging.ge... | 686 |
'''simple docstring'''
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-smal... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : Optional[int] = 0
# if input_string is "aba" than new_input_string become "a|b|a"
A_ : Any = """"""
A_ : Any = """"""
# append each character + "|" in new_string for range(0, le... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Any = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
fr... | 686 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
lowerCamelCase :Optio... | 686 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
lowerCamelCase :int ... | 686 |
'''simple docstring'''
from math import factorial
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
class _lowerCAmelCase :
def __init__(self , lowercase ):
A_ : Optional[Any] = TypeError(
"""Matrices must be formed from a list of zero or more lists containing at """
"""least one and the same number ... | 686 |
'''simple docstring'''
import re
def a ( lowerCamelCase__ ):
'''simple docstring'''
if len(re.findall("""[ATCG]""" , lowerCamelCase__ ) ) != len(lowerCamelCase__ ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans("""ATCG""" , ... | 686 | 1 |
'''simple docstring'''
import torch
from diffusers import StableDiffusionPipeline
lowerCamelCase :List[str] = '''path-to-your-trained-model'''
lowerCamelCase :List[str] = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('''cuda''')
l... | 686 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a ( ):
'''simple docstring'''
with offline(OfflineSimulationMode.CONNECT... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import pi, sqrt
def a ( lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if inductance <= 0:
raise ValueError("""Inductance cannot be 0 or negative""" )
elif capacitance <= 0:
rais... | 686 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
fr... | 686 | 1 |
'''simple docstring'''
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,... | 686 |
'''simple docstring'''
import pytest
lowerCamelCase :Optional[Any] = '''__dummy_dataset1__'''
lowerCamelCase :List[Any] = '''
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = ... | 686 | 1 |
'''simple docstring'''
import torch
from diffusers import DiffusionPipeline
class _lowerCAmelCase ( __UpperCAmelCase ):
def __init__(self , lowercase , lowercase ):
super().__init__()
self.register_modules(unet=lowercase , scheduler=lowercase )
def __call_... | 686 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowerCamelCase :int = datasets.load_iris()
lowerCamelCase :str = np.array(data['''data'''])
lowerCamelCase ... | 686 | 1 |
'''simple docstring'''
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers imp... | 686 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowerCamelCase :List[str] = logging.get_logg... | 686 | 1 |
'''simple docstring'''
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
lowerCamelCase :Optional[int] = logging.get_logger(__name__)
def a ... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :int = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
# flake8: noqa
# Lint as: python3
lowerCamelCase :List[Any] = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import Verific... | 686 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
lowerCamelCase :int = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if depth < 0:
raise ValueError("""Depth cannot be less than 0""" ... | 686 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_... | 686 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
... | 686 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class _lowerCAmelCase ( __UpperCAmelCase , unittest.TestCase ):
__SCREAMING_SNAKE_CAS... | 686 | 1 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def a ( ):
'''simple docstring'''
A_, A_ : Any = 9, 14 # noqa: F841
A_ : int = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
... | 686 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ = None ):
'''simple docstring'''
A_ : List[Any] = word_bank or []
# create a table
A_ : int = len(lowerCamelCase__ ) + 1
A_ : list[list[list[str]]] =... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import pi
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError("""One and only one argument m... | 686 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : int = []
A_ : int = set({"""(""", """[""", """{"""} )
A_ : Union[str, Any] = set({""")""", """]""", """}"""} )
A_ : Tuple = {"""{""": """}""", """[""": """]""", """("""... | 686 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_featur... | 686 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Nest... | 686 | 1 |
'''simple docstring'''
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWithNoAttentio... | 686 |
'''simple docstring'''
import os
import sys
import unittest
lowerCamelCase :Any = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa... | 686 | 1 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class _lowerCAmelCase ( __UpperCAmelCase , unittest.TestCase ):
__SCREAMING_SNAKE_CAS... | 686 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase :Any = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''Lon... | 686 | 1 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transfor... | 686 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCamelCase :Any = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/... | 686 | 1 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 686 |
'''simple docstring'''
lowerCamelCase :dict[tuple[int, int, int], int] = {}
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not fail... | 686 | 1 |
'''simple docstring'''
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
lowerCamelCase :Any = importlib.util.find_spec('''s3fs''') is not None
if _h... | 686 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
class _lowerCA... | 686 | 1 |
'''simple docstring'''
import pytest
lowerCamelCase :Optional[Any] = '''__dummy_dataset1__'''
lowerCamelCase :List[Any] = '''
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = ... | 686 |
'''simple docstring'''
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-smal... | 686 | 1 |
'''simple docstring'''
from statistics import mean, stdev
def a ( lowerCamelCase__ , lowerCamelCase__ = 3 ):
'''simple docstring'''
A_ : Any = min(lowerCamelCase__ )
A_ : int = max(lowerCamelCase__ )
# normalize data
return [round((x - x_min) / (x_max -... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Any = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
lowerCamelCase ... | 686 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
lowerCamelCase :Optio... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : int = []
A_ : int = set({"""(""", """[""", """{"""} )
A_ : Union[str, Any] = set({""")""", """]""", """}"""} )
A_ : Tuple = {"""{""": """}""", """[""": """]""", """("""... | 686 |
'''simple docstring'''
from math import factorial
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
... | 686 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase :int = ... | 686 |
'''simple docstring'''
import re
def a ( lowerCamelCase__ ):
'''simple docstring'''
if len(re.findall("""[ATCG]""" , lowerCamelCase__ ) ) != len(lowerCamelCase__ ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans("""ATCG""" , ... | 686 | 1 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowerCamelCase :List[str] = logging.get_logg... | 686 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a ( ):
'''simple docstring'''
with offline(OfflineSimulationMode.CONNECT... | 686 | 1 |
'''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class _lowerCAmelCase :
def __init__(self , lowercase ):
if isinstance(lowercase , lowercase ... | 686 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
fr... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , ):
'''simple docstring'''
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError("""You cannot supply more or less than 2 values""" ... | 686 |
'''simple docstring'''
import pytest
lowerCamelCase :Optional[Any] = '''__dummy_dataset1__'''
lowerCamelCase :List[Any] = '''
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = ... | 686 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Optional[Any] = logging.get_logger(__name_... | 686 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowerCamelCase :int = datasets.load_iris()
lowerCamelCase :str = np.array(data['''data'''])
lowerCamelCase ... | 686 | 1 |
'''simple docstring'''
from math import factorial
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
... | 686 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowerCamelCase :List[str] = logging.get_logg... | 686 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCamelCase :int = {
'''configuration_groupvit''': [
'''GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Grou... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :int = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
if not isinstance(lowerCamelCase__ , lowerCamelCase__ ):
raise ValueError("""Input must be an integer""" )
if input_num <= 0:
raise ValueError("""Input must be positive""" )
return ... | 686 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
lowerCamelCase :int = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowerCamelCase :Dict = 2_0_0
# Number of elements selected in every generation of evolution. The selection takes
# place from be... | 686 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_... | 686 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import req... | 686 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class _lowerCAmelCase ( __UpperCAmelCase , unittest.TestCase ):
__SCREAMING_SNAKE_CAS... | 686 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta ... | 686 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ = None ):
'''simple docstring'''
A_ : List[Any] = word_bank or []
# create a table
A_ : int = len(lowerCamelCase__ ) + 1
A_ : list[list[list[str]]] =... | 686 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.... | 686 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : int = []
A_ : int = set({"""(""", """[""", """{"""} )
A_ : Union[str, Any] = set({""")""", """]""", """}"""} )
A_ : Tuple = {"""{""": """}""", """[""": """]""", """("""... | 686 | 1 |
'''simple docstring'''
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
imp... | 686 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Nest... | 686 | 1 |
'''simple docstring'''
import os
import sys
import unittest
lowerCamelCase :Any = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa... | 686 |
'''simple docstring'''
import os
import sys
import unittest
lowerCamelCase :Any = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa... | 686 | 1 |
'''simple docstring'''
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import f... | 686 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase :Any = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''Lon... | 686 | 1 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttent... | 686 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCamelCase :Any = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if b == 0:
return (1, 0)
((A_), (A_)) : Union[str, Any] = extended_euclid(lowerCamelCase__ , a % b )
A_ : List[Any] = a... | 686 |
'''simple docstring'''
lowerCamelCase :dict[tuple[int, int, int], int] = {}
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not fail... | 686 | 1 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_availa... | 686 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
class _lowerCA... | 686 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
lowerCamelCase :Optional[int] = logging.get_logger(__name__)
class _lowerCAmelCase ( __UpperCAmelCase ):
def __init__(self , *lowercase , ... | 686 |
'''simple docstring'''
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-smal... | 686 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase :Dict = {
'''configuration_clap''': [
'''CLAP_PRETRAINED_MODEL_ARCHIVE_LIST''',
'''ClapAudioConfig''',
... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Any = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
A_ : List[Any] = s.rsplit(lo... | 686 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
lowerCamelCase :Optio... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
if any(not isinstance(lowerCamelCase__ , lowerCamelCase__ ) or x < 0 for x in sequence ):
raise TypeError("""Sequence must be list of non-negative integers""" )
for _ in range(len(lowerCamel... | 686 |
'''simple docstring'''
from math import factorial
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
... | 686 | 1 |
'''simple docstring'''
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes ... | 686 |
'''simple docstring'''
import re
def a ( lowerCamelCase__ ):
'''simple docstring'''
if len(re.findall("""[ATCG]""" , lowerCamelCase__ ) ) != len(lowerCamelCase__ ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans("""ATCG""" , ... | 686 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. 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-... | 686 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a ( ):
'''simple docstring'''
with offline(OfflineSimulationMode.CONNECT... | 686 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import ... | 686 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
fr... | 686 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
lowerCamelCase :Any = {
'''MIT/ast-finetuned-audioset-10-10-0.4593''': (
'''https://hu... | 686 |
'''simple docstring'''
import pytest
lowerCamelCase :Optional[Any] = '''__dummy_dataset1__'''
lowerCamelCase :List[Any] = '''
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = ... | 686 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase ( metaclass=__UpperCAmelCase ):
__SCREAMING_SNAKE_CASE : Optional[int] = ['transformers', 'torch', 'note_seq']
def __init__(self , *lowercase , **lowercase ):
requ... | 686 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowerCamelCase :int = datasets.load_iris()
lowerCamelCase :str = np.array(data['''data'''])
lowerCamelCase ... | 686 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
... | 686 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowerCamelCase :List[str] = logging.get_logg... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if len(lowerCamelCase__ ) != len(lowerCamelCase__ ):
raise ValueError("""String lengths must match!""" )
A_ : List[str] = 0
for chara, chara in zip(lowerCamelCa... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :int = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
from math import sqrt
def a ( lowerCamelCase__ ):
'''simple docstring'''
assert isinstance(lowerCamelCase__ , lowerCamelCase__ ) and (
number >= 0
), "'number' must been an int and positive"
A_ : int = True
# 0 and 1 are none prime... | 686 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
lowerCamelCase :int = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
A_ : Tuple = len(lowerCamelCase__ ) + 1
A_ : str = len(lowerCamelCase__ ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
# length i of in... | 686 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_... | 686 | 1 |
'''simple docstring'''
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class _lowerCAmelCase ( __UpperCAmelCase ):
__SCREAMING_SNAKE_CASE : int = ['image_processor', 'tokenizer']
__SCREAMING_SNAKE_CASE : Lis... | 686 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class _lowerCAmelCase ( __UpperCAmelCase , unittest.TestCase ):
__SCREAMING_SNAKE_CAS... | 686 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class _lowerCAmelCase ( __Upper... | 686 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ = None ):
'''simple docstring'''
A_ : List[Any] = word_bank or []
# create a table
A_ : int = len(lowerCamelCase__ ) + 1
A_ : list[list[list[str]]] =... | 686 | 1 |
'''simple docstring'''
import math
def a ( lowerCamelCase__ ):
'''simple docstring'''
assert isinstance(lowerCamelCase__ , lowerCamelCase__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return T... | 686 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : int = []
A_ : int = set({"""(""", """[""", """{"""} )
A_ : Union[str, Any] = set({""")""", """]""", """}"""} )
A_ : Tuple = {"""{""": """}""", """[""": """]""", """("""... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : Any = False
while is_sorted is False: # Until all the indices are traversed keep looping
A_ : List[Any] = True
for i in range(0 , len(lowerCamelCase__ ) - 1 , 2 ): # ... | 686 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Nest... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
def count_of_possible_combinations(lowerCamelCase__ ) -> int:
if target < 0:
return 0
if target == 0:
return 1
return sum(count_of... | 686 |
'''simple docstring'''
import os
import sys
import unittest
lowerCamelCase :Any = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa... | 686 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase :Any = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 686 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase :Any = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''Lon... | 686 | 1 |
'''simple docstring'''
import os
import jsonlines
import numpy as np
from tqdm import tqdm
lowerCamelCase :List[str] = 2_0_4_8
lowerCamelCase :Union[str, Any] = 4_0_9_6
lowerCamelCase :List[str] = 4_2
lowerCamelCase :Any = ... | 686 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCamelCase :Any = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ = 10_00 ):
'''simple docstring'''
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution()) | 686 |
'''simple docstring'''
lowerCamelCase :dict[tuple[int, int, int], int] = {}
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not fail... | 686 | 1 |
'''simple docstring'''
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('''>=''', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from t... | 686 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
class _lowerCA... | 686 | 1 |
'''simple docstring'''
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
lowerCamelCase :Optional[Any] = Path(__file__).resolve().parents[3] / '''src'''
sys.path.insert(1, str(git_repo_pat... | 686 |
'''simple docstring'''
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-smal... | 686 | 1 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowerCamelCase :int = datasets.load_iris()
lowerCamelCase :str = np.array(data['''data'''])
lowerCamelCase ... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Any = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
import math
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : Dict = []
A_ : Optional[Any] = 2
A_ : List[str] = int(math.sqrt(lowerCamelCase__ ) ) # Size of every segment
A_ : int = [True] * (end + 1)
A_ : in... | 686 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
lowerCamelCase :Optio... | 686 | 1 |
'''simple docstring'''
import re
def a ( lowerCamelCase__ ):
'''simple docstring'''
if len(re.findall("""[ATCG]""" , lowerCamelCase__ ) ) != len(lowerCamelCase__ ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans("""ATCG""" , ... | 686 |
'''simple docstring'''
from math import factorial
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
... | 686 | 1 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
A_ : List[str] = {
"""en""": """Machine learning is great... | 686 |
'''simple docstring'''
import re
def a ( lowerCamelCase__ ):
'''simple docstring'''
if len(re.findall("""[ATCG]""" , lowerCamelCase__ ) ) != len(lowerCamelCase__ ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans("""ATCG""" , ... | 686 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase :Tuple = logging.get_logger(__name__)
lowerCamelCase :Optional[Any] = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcod... | 686 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a ( ):
'''simple docstring'''
with offline(OfflineSimulationMode.CONNECT... | 686 | 1 |
'''simple docstring'''
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 Batc... | 686 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
fr... | 686 | 1 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
... | 686 |
'''simple docstring'''
import pytest
lowerCamelCase :Optional[Any] = '''__dummy_dataset1__'''
lowerCamelCase :List[Any] = '''
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = ... | 686 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_de... | 686 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowerCamelCase :int = datasets.load_iris()
lowerCamelCase :str = np.array(data['''data'''])
lowerCamelCase ... | 686 | 1 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCamelCase :Any = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/... | 686 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowerCamelCase :List[str] = logging.get_logg... | 686 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Any = logging.get_logger(__name__)
lowerC... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :int = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
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, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.uti... | 686 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
lowerCamelCase :int = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER... | 686 | 1 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
lowerCamelCase :int = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER... | 686 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ = 50 ):
'''simple docstring'''
A_ : List[Any] = [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_... | 686 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class _lowerCAmelCase ( __UpperCAmelCase , unittest.TestCase ):
__SCREAMING_SNAKE_CAS... | 686 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :int = logging.get_logger(__name__)
lowerC... | 686 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ = None ):
'''simple docstring'''
A_ : List[Any] = word_bank or []
# create a table
A_ : int = len(lowerCamelCase__ ) + 1
A_ : list[list[list[str]]] =... | 686 | 1 |
'''simple docstring'''
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
lowerCamelCase :Any = logging.getLogger()
def ... | 686 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : int = []
A_ : int = set({"""(""", """[""", """{"""} )
A_ : Union[str, Any] = set({""")""", """]""", """}"""} )
A_ : Tuple = {"""{""": """}""", """[""": """]""", """("""... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
if not isinstance(lowerCamelCase__ , lowerCamelCase__ ):
raise TypeError("""Input value must be an 'int' type""" )
A_ : str = 0
while number:
position += 1
number >>= 1
... | 686 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Nest... | 686 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 686 |
'''simple docstring'''
import os
import sys
import unittest
lowerCamelCase :Any = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa... | 686 | 1 |
'''simple docstring'''
lowerCamelCase :dict[tuple[int, int, int], int] = {}
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not fail... | 686 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase :Any = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''Lon... | 686 | 1 |
'''simple docstring'''
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def a ( lowerCamelCase__ )... | 686 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCamelCase :Any = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/... | 686 | 1 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( __UpperCAmelCas... | 686 |
'''simple docstring'''
lowerCamelCase :dict[tuple[int, int, int], int] = {}
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not fail... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : Dict = 1
A_ : Any = 2
while i * i <= n:
A_ : List[str] = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1
... | 686 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
class _lowerCA... | 686 | 1 |
'''simple docstring'''
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 accel... | 686 |
'''simple docstring'''
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-smal... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
lowerCamelCase :int = TypeVar('''KT''')
lowerCamelCase :Union[str, Any] = TypeVar('''VT''')
class _lowerCAmelCase ( Generic[KT,... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Any = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pr... | 686 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
lowerCamelCase :Optio... | 686 | 1 |
'''simple docstring'''
from collections import deque
class _lowerCAmelCase :
def __init__(self , lowercase , lowercase , lowercase ):
A_ : Dict = process_name # process name
A_ : Optional[int] = arrival_time # arrival time of the process
# completion time... | 686 |
'''simple docstring'''
from math import factorial
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
... | 686 | 1 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class _lowerCAmelCase ( unittest.TestCase ):
def _a (self ):
A_ : Union[str, Any] = [10, 20, 30, 40, 50, 60]
A_ : Union[str, Any] = [2, 4, 6, 8, 10, 12]
A_ : Any ... | 686 |
'''simple docstring'''
import re
def a ( lowerCamelCase__ ):
'''simple docstring'''
if len(re.findall("""[ATCG]""" , lowerCamelCase__ ) ) != len(lowerCamelCase__ ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans("""ATCG""" , ... | 686 | 1 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
f... | 686 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a ( ):
'''simple docstring'''
with offline(OfflineSimulationMode.CONNECT... | 686 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
lowerCamelCase :int = logging.... | 686 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
fr... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_commo... | 686 |
'''simple docstring'''
import pytest
lowerCamelCase :Optional[Any] = '''__dummy_dataset1__'''
lowerCamelCase :List[Any] = '''
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = ... | 686 | 1 |
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