code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ )-> None:
'''simple docstring'''
_UpperCAmelCase : Tuple = len(lowerCAmelCase_ )
print("""The following activities are selected:""" )
# The first activity is always... | 349 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pi... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowercase :
"""simple docstring"""
UpperCAmelCase = 42
UpperCAmelCase = 42
class ... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : str = {
"""configuration_roberta_prelayernorm""": [
"""ROBERTA_PRELA... | 349 | 1 |
'''simple docstring'''
import argparse
import json
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_se... | 349 |
'''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
A_ : Union[str, Any] = logging.get_logger(__name__)
A_ ... | 349 | 1 |
'''simple docstring'''
import random
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ )-> Tuple:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] = a[left_index]
_UpperCAmelCase : Optional[int] = ... | 349 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class lowercase ( unittest.TestCase ):
"""simple docstring"""
def _snake_case ( self ) -> Optional[Any]:
_UpperCAmelCase : Any = [10, 20, 30, 40, 50, 60]
... | 349 | 1 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class lowercase ( nn.Module ):
"""simple docstring"""
UpperCAmelCase = 42
Uppe... | 349 |
'''simple docstring'''
from __future__ import annotations
import math
def snake_case_ ( lowerCAmelCase_ )-> list[int]:
'''simple docstring'''
if num <= 0:
_UpperCAmelCase : List[Any] = F'''{num}: Invalid input, please enter a positive integer.... | 349 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
... | 349 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase ( _lowerCamelCase ):
"""simple docstring"""
de... | 349 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.tran... | 349 |
'''simple docstring'''
A_ : Optional[Any] = """0.21.0"""
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from ... | 349 | 1 |
'''simple docstring'''
import argparse
import copy
def snake_case_ ( lowerCAmelCase_ )-> Dict:
'''simple docstring'''
_UpperCAmelCase : Dict = {}
with open(lowerCAmelCase_ ) as f:
for line in f:
if line.split()[0] ... | 349 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def snake_case_ ( )-> Union[str, Any]:
'''simple docstring'''
_UpperCAmelCase : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-... | 349 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ : Optional[Any] = {
"""configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}
try:
if not is_torch_avai... | 349 |
'''simple docstring'''
import math
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ )-> int:
'''simple docstring'''
_UpperCAmelCase : str = len(lowerCAmelCase_ )
_UpperCAmelCase : List[str] = int(math.floor(math.sqrt(lowerC... | 349 | 1 |
'''simple docstring'''
from decimal import Decimal, getcontext
from math import ceil, factorial
def snake_case_ ( lowerCAmelCase_ )-> str:
'''simple docstring'''
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise TypeError("""Undefined for non-i... | 349 |
'''simple docstring'''
import argparse
import copy
def snake_case_ ( lowerCAmelCase_ )-> Dict:
'''simple docstring'''
_UpperCAmelCase : Dict = {}
with open(lowerCAmelCase_ ) as f:
for line in f:
if line.split()[0] ... | 349 | 1 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
A_ : int = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_copies # noqa... | 349 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowercase :
"""simple docstring"""
UpperCAmelCase = 42
UpperCAmelCase = 42
class ... | 349 | 1 |
'''simple docstring'''
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 snake_case_ ( lowerCAm... | 349 |
'''simple docstring'''
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from ... | 349 | 1 |
'''simple docstring'''
import pytest
A_ : Optional[int] = """__dummy_dataset1__"""
A_ : Any = """
import json
import os
import datasets
REPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"
URLS = {\"train\": REPO_URL + \"wik... | 349 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import g... | 349 | 1 |
'''simple docstring'''
import math
import qiskit
def snake_case_ ( lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 )-> qiskit.result.counts.Counts:
'''simple docstring'''
if (
isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : List[Any] = logging.get_logger(__name__)
A_ : Union[str, Any] = ... | 349 | 1 |
'''simple docstring'''
import argparse
import collections
import os
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_table.py
A_ : Optional[int] ... | 349 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class ... | 349 | 1 |
'''simple docstring'''
import math
def snake_case_ ( lowerCAmelCase_ )-> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1,... | 349 |
'''simple docstring'''
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
A_ : List[Any] = 637_8137.0
A_ : Dict = 635_6752.31_4245
A_ : int = 6_3_7_8_1_3_7
def snake_case_ ( lowerCAmelCase_ ,... | 349 | 1 |
'''simple docstring'''
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
... | 349 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 100 , )-> float:
'''simple docstring'''
_UpperCAmelCase : str... | 349 | 1 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ )-> int:
'''simple docstring'''
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise TypeError("""only integers accepted as input""" )
else:
_UpperCAmelCase : Dict ... | 349 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def snake_case_ ( )-> int:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] ... | 349 | 1 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
A_ : List[str] = logging.getLogger(__name__)
class lowercase :
"""simple docstring"... | 349 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ )-> int:
'''simple docstring'''
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise TypeError("""only integers accepted as input""" )
else:
_UpperCAmelCase : Dict ... | 349 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
A_ : str = {
"""albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/config.json""",
"""al... | 349 |
'''simple docstring'''
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
A_ : Dict = logging.get_logger(__... | 349 | 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_squeezebert import SqueezeBertTokenizer
A_ : int = logging.get_l... | 349 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 0 , lowerCAmelCase_ = 0 )-> int:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] = right or len(lowerCAmelCase_ ) - 1
if left > right:... | 349 | 1 |
'''simple docstring'''
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, re... | 349 |
'''simple docstring'''
from datetime import datetime
import requests
def snake_case_ ( lowerCAmelCase_ )-> bytes:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
_Upp... | 349 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_c... | 349 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pi... | 349 | 1 |
'''simple docstring'''
from collections import deque
from math import floor
from random import random
from time import time
class lowercase :
"""simple docstring"""
def __init__( self ) -> Dict:
_UpperCAmelCase : int = {}
def _snake_case (... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : str = {
"""configuration_roberta_prelayernorm""": [
"""ROBERTA_PRELA... | 349 | 1 |
'''simple docstring'''
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available()... | 349 |
'''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
A_ : Union[str, Any] = logging.get_logger(__name__)
A_ ... | 349 | 1 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffus... | 349 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class lowercase ( unittest.TestCase ):
"""simple docstring"""
def _snake_case ( self ) -> Optional[Any]:
_UpperCAmelCase : Any = [10, 20, 30, 40, 50, 60]
... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
A_ : Dict = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAme... | 349 |
'''simple docstring'''
from __future__ import annotations
import math
def snake_case_ ( lowerCAmelCase_ )-> list[int]:
'''simple docstring'''
if num <= 0:
_UpperCAmelCase : List[Any] = F'''{num}: Invalid input, please enter a positive integer.... | 349 | 1 |
'''simple docstring'''
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switc... | 349 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase ( _lowerCamelCase ):
"""simple docstring"""
de... | 349 | 1 |
'''simple docstring'''
import numpy as np
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ )-> Optional[Any]:
'''simple docstring'''
_UpperCAmelCase : Tuple = int(np.ceil((x_end... | 349 |
'''simple docstring'''
A_ : Optional[Any] = """0.21.0"""
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from ... | 349 | 1 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_=False )-> Optional[Any]:
'''simple docstring'''
if isinstance(lowerCAmelCase_ , lowerCAmelCase_ ) and isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
... | 349 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def snake_case_ ( )-> Union[str, Any]:
'''simple docstring'''
_UpperCAmelCase : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-... | 349 | 1 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
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 T... | 349 |
'''simple docstring'''
import math
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ )-> int:
'''simple docstring'''
_UpperCAmelCase : str = len(lowerCAmelCase_ )
_UpperCAmelCase : List[str] = int(math.floor(math.sqrt(lowerC... | 349 | 1 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase ( _lowerCamelCase ):
"""simple docstring"""
de... | 349 |
'''simple docstring'''
import argparse
import copy
def snake_case_ ( lowerCAmelCase_ )-> Dict:
'''simple docstring'''
_UpperCAmelCase : Dict = {}
with open(lowerCAmelCase_ ) as f:
for line in f:
if line.split()[0] ... | 349 | 1 |
'''simple docstring'''
from bisect import bisect
from itertools import accumulate
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ )-> Optional[Any]:
'''simple docstring'''
_UpperCAmelCase : Any = sort... | 349 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowercase :
"""simple docstring"""
UpperCAmelCase = 42
UpperCAmelCase = 42
class ... | 349 | 1 |
'''simple docstring'''
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
A_ : str = 4
A_ : List[Any] = 3
class ... | 349 |
'''simple docstring'''
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from ... | 349 | 1 |
'''simple docstring'''
import numpy as np
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 1e-1_2 , lowerCAmelCase_ = 100 , )-> tuple[float, np.ndarray]:
'''simple docstring'''
assert np.shape(lowerCAmelCase_ )[0] == np.shape(low... | 349 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import g... | 349 | 1 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, 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_commo... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : List[Any] = logging.get_logger(__name__)
A_ : Union[str, Any] = ... | 349 | 1 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ )-> list:
'''simple docstring'''
if len(lowerCAmelCase_ ) <= 1:
return lst
_UpperCAmelCase : str = 1
while i < len(lowerCAmelCase_ ):
if lst[i - 1] <= lst[i]:
... | 349 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class ... | 349 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : List[Any] = logging.get_logger(__name__)
A_ : Dict = {
"""tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
"""https://huggingface.co/tanreinama/GPTSA... | 349 |
'''simple docstring'''
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
A_ : List[Any] = 637_8137.0
A_ : Dict = 635_6752.31_4245
A_ : int = 6_3_7_8_1_3_7
def snake_case_ ( lowerCAmelCase_ ,... | 349 | 1 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class lowercase ( _lowerCamelCase ):
"""simple... | 349 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 100 , )-> float:
'''simple docstring'''
_UpperCAmelCase : str... | 349 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def snake_case_ ( lowerCAmelCase_ = None )-> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
_UpperCAmelCase : Union[s... | 349 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def snake_case_ ( )-> int:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] ... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class lowercase :
"""simple docstring"""
UpperCAmelCase = 42
UpperCAmelCase = ... | 349 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ )-> int:
'''simple docstring'''
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise TypeError("""only integers accepted as input""" )
else:
_UpperCAmelCase : Dict ... | 349 | 1 |
'''simple docstring'''
A_ : Tuple = 9.8_0665
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = g )-> float:
'''simple docstring'''
if fluid_density <= 0:
raise ValueError("""Impossible fluid density""" )
... | 349 |
'''simple docstring'''
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
A_ : Dict = logging.get_logger(__... | 349 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_c... | 349 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 0 , lowerCAmelCase_ = 0 )-> int:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] = right or len(lowerCAmelCase_ ) - 1
if left > right:... | 349 | 1 |
'''simple docstring'''
from collections.abc import Generator
from math import sin
def snake_case_ ( lowerCAmelCase_ )-> bytes:
'''simple docstring'''
if len(lowerCAmelCase_ ) != 32:
raise ValueError("""Input must be of length 32""" )
_UpperCAmelCase :... | 349 |
'''simple docstring'''
from datetime import datetime
import requests
def snake_case_ ( lowerCAmelCase_ )-> bytes:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
_Upp... | 349 | 1 |
'''simple docstring'''
import math
def snake_case_ ( lowerCAmelCase_ = 100 )-> int:
'''simple docstring'''
_UpperCAmelCase : int = sum(i * i for i in range(1 , n + 1 ) )
_UpperCAmelCase : List[str] = int(math.pow(sum(range(1 ... | 349 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pi... | 349 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : List[Any] = logging.get_logger(__name__)
A_ : str = {
"""uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/co... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : str = {
"""configuration_roberta_prelayernorm""": [
"""ROBERTA_PRELA... | 349 | 1 |
'''simple docstring'''
import copy
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_ : Optional[Any] ... | 349 |
'''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
A_ : Union[str, Any] = logging.get_logger(__name__)
A_ ... | 349 | 1 |
'''simple docstring'''
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
... | 349 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class lowercase ( unittest.TestCase ):
"""simple docstring"""
def _snake_case ( self ) -> Optional[Any]:
_UpperCAmelCase : Any = [10, 20, 30, 40, 50, 60]
... | 349 | 1 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew... | 349 |
'''simple docstring'''
from __future__ import annotations
import math
def snake_case_ ( lowerCAmelCase_ )-> list[int]:
'''simple docstring'''
if num <= 0:
_UpperCAmelCase : List[Any] = F'''{num}: Invalid input, please enter a positive integer.... | 349 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class lowercase ( metaclass=_lowerCamelCase ):
"""simple docstring"""
UpperCAmelCase = ["""flax"""]
def __init__( self ,*a_ ,**a_ ) -> List[Any]:
requires_backends(self... | 349 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase ( _lowerCamelCase ):
"""simple docstring"""
de... | 349 | 1 |
'''simple docstring'''
# This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenize... | 349 |
'''simple docstring'''
A_ : Optional[Any] = """0.21.0"""
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from ... | 349 | 1 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
A_ : List[str] = """\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and ... | 349 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def snake_case_ ( )-> Union[str, Any]:
'''simple docstring'''
_UpperCAmelCase : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 100 , )-> float:
'''simple docstring'''
_UpperCAmelCase : str... | 349 |
'''simple docstring'''
import math
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ )-> int:
'''simple docstring'''
_UpperCAmelCase : str = len(lowerCAmelCase_ )
_UpperCAmelCase : List[str] = int(math.floor(math.sqrt(lowerC... | 349 | 1 |
'''simple docstring'''
print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
| 349 |
'''simple docstring'''
import argparse
import copy
def snake_case_ ( lowerCAmelCase_ )-> Dict:
'''simple docstring'''
_UpperCAmelCase : Dict = {}
with open(lowerCAmelCase_ ) as f:
for line in f:
if line.split()[0] ... | 349 | 1 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common... | 349 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowercase :
"""simple docstring"""
UpperCAmelCase = 42
UpperCAmelCase = 42
class ... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 349 |
'''simple docstring'''
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from ... | 349 | 1 |
'''simple docstring'''
import requests
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ )-> None:
'''simple docstring'''
_UpperCAmelCase : List[Any] = {"""Content-Type""": """application/json"""}
_UpperCAmelCase : Optional[Any] ... | 349 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import g... | 349 | 1 |
'''simple docstring'''
A_ : Optional[Any] = """0.21.0"""
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from ... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : List[Any] = logging.get_logger(__name__)
A_ : Union[str, Any] = ... | 349 | 1 |
'''simple docstring'''
class lowercase :
"""simple docstring"""
def __init__( self ,a_ ,a_ ,a_ ) -> List[str]:
_UpperCAmelCase : List[Any] = name
_UpperCAmelCase : Dict = value
_UpperCAmelCase : Any ... | 349 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class ... | 349 | 1 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ )-> bool:
'''simple docstring'''
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
_UpperCAmelCase : Any = F'''Input value of [number={number}] must be an integer'''
... | 349 |
'''simple docstring'''
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
A_ : List[Any] = 637_8137.0
A_ : Dict = 635_6752.31_4245
A_ : int = 6_3_7_8_1_3_7
def snake_case_ ( lowerCAmelCase_ ,... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def snake_case_ ( lowerCAmelCase_ )-> list[int]:
'''simple docstring'''
if num <= 0:
_UpperCAmelCase : List[Any] = F'''{num}: Invalid input, please enter a positive integer.... | 349 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 100 , )-> float:
'''simple docstring'''
_UpperCAmelCase : str... | 349 | 1 |
'''simple docstring'''
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from .... | 349 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def snake_case_ ( )-> int:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] ... | 349 | 1 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ = 2000000 )-> int:
'''simple docstring'''
_UpperCAmelCase : int = [0 for i in range(n + 1 )]
_UpperCAmelCase : int = 1
_UpperCAmelCase : Any = 1
f... | 349 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ )-> int:
'''simple docstring'''
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise TypeError("""only integers accepted as input""" )
else:
_UpperCAmelCase : Dict ... | 349 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
A_ : Tuple = logging.get_logger(__name__)
A_ : List[str] = {
"""Intel/dpt-large""": """https://huggingface.co/Intel/dp... | 349 |
'''simple docstring'''
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
A_ : Dict = logging.get_logger(__... | 349 | 1 |
'''simple docstring'''
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def snake_case_ ( lowerCAmelCase_ )-> Dict[str, torch.Tensor]:
'''simple docstring'''
_UpperCAmelCase : ... | 349 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 0 , lowerCAmelCase_ = 0 )-> int:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] = right or len(lowerCAmelCase_ ) - 1
if left > right:... | 349 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : List[Any] = logging.get_logger(__name__)
A_ : Union[str, Any] = ... | 349 |
'''simple docstring'''
from datetime import datetime
import requests
def snake_case_ ( lowerCAmelCase_ )-> bytes:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
_Upp... | 349 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
A_ : int = {
"""configuration_speech_to_text"""... | 349 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pi... | 349 | 1 |
'''simple docstring'''
from math import pi, sqrt
def snake_case_ ( lowerCAmelCase_ )-> float:
'''simple docstring'''
if num <= 0:
raise ValueError("""math domain error""" )
if num > 1_7_1.5:
raise OverflowError("""math range error""" )
... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : str = {
"""configuration_roberta_prelayernorm""": [
"""ROBERTA_PRELA... | 349 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
loggi... | 349 |
'''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
A_ : Union[str, Any] = logging.get_logger(__name__)
A_ ... | 349 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ : Dict = {
"""configuration_layoutlmv3""": [
... | 349 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class lowercase ( unittest.TestCase ):
"""simple docstring"""
def _snake_case ( self ) -> Optional[Any]:
_UpperCAmelCase : Any = [10, 20, 30, 40, 50, 60]
... | 349 | 1 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , )-> float:
'''simple docstring'''
_UpperCAmelCase : Optional[int] = [redshift, radiation_density, matt... | 349 |
'''simple docstring'''
from __future__ import annotations
import math
def snake_case_ ( lowerCAmelCase_ )-> list[int]:
'''simple docstring'''
if num <= 0:
_UpperCAmelCase : List[Any] = F'''{num}: Invalid input, please enter a positive integer.... | 349 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
A_ : int = {
"""configuration_squeezebert""": [
"""SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""S... | 349 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase ( _lowerCamelCase ):
"""simple docstring"""
de... | 349 | 1 |
'''simple docstring'''
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 349 |
'''simple docstring'''
A_ : Optional[Any] = """0.21.0"""
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from ... | 349 | 1 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import g... | 349 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def snake_case_ ( )-> Union[str, Any]:
'''simple docstring'''
_UpperCAmelCase : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-... | 349 | 1 |
'''simple docstring'''
import numpy
# List of input, output pairs
A_ : List[str] = (
((5, 2, 3), 1_5),
((6, 5, 9), 2_5),
((1_1, 1_2, 1_3), 4_1),
((1, 1, 1), 8),
((1_1, 1_2, 1_3), 4_1),
)
A_ : List[Any] = (((5_1_5, 2_2, 1_3), 5_5_5), ((6_1, 3_5, 4_9)... | 349 |
'''simple docstring'''
import math
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ )-> int:
'''simple docstring'''
_UpperCAmelCase : str = len(lowerCAmelCase_ )
_UpperCAmelCase : List[str] = int(math.floor(math.sqrt(lowerC... | 349 | 1 |
'''simple docstring'''
import baseaa
def snake_case_ ( lowerCAmelCase_ )-> bytes:
'''simple docstring'''
return baseaa.baaencode(string.encode("""utf-8""" ) )
def snake_case_ ( lowerCAmelCase_ )-> str:
'''simple docstring'''
return baseaa.b... | 349 |
'''simple docstring'''
import argparse
import copy
def snake_case_ ( lowerCAmelCase_ )-> Dict:
'''simple docstring'''
_UpperCAmelCase : Dict = {}
with open(lowerCAmelCase_ ) as f:
for line in f:
if line.split()[0] ... | 349 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : Dict = logging.get_logger(__name__)
A_ : Any = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encod... | 349 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowercase :
"""simple docstring"""
UpperCAmelCase = 42
UpperCAmelCase = 42
class ... | 349 | 1 |
'''simple docstring'''
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import h... | 349 |
'''simple docstring'''
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from ... | 349 | 1 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
A_ ... | 349 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import g... | 349 | 1 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
A_ : Dict = """docs/source/en/_toctree.yml"""
def snake_case_ ( lowerCAmelCase_ )-> List[Any]:
'''simple docstring'''
_UpperCAmelCase : List[str] = ... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : List[Any] = logging.get_logger(__name__)
A_ : Union[str, Any] = ... | 349 | 1 |
'''simple docstring'''
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
A_ : List[Any] = logging.get_logger(__name__)
def sna... | 349 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class ... | 349 | 1 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def snake_case_ ( lowerCAmelCase_ = "AAPL" )-> str:
'''simple docstring'''
_UpperCAmelCase : Any = F'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
_UpperCAmelCase : ... | 349 |
'''simple docstring'''
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
A_ : List[Any] = 637_8137.0
A_ : Dict = 635_6752.31_4245
A_ : int = 6_3_7_8_1_3_7
def snake_case_ ( lowerCAmelCase_ ,... | 349 | 1 |
'''simple docstring'''
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class lowercase ( _lowerCamelCase ):
"""simple docstring"""
def __init__( self ,a_ ,a_=None ,a_=True ,... | 349 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 100 , )-> float:
'''simple docstring'''
_UpperCAmelCase : str... | 349 | 1 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ )-> Optional[int]:
'''simple docstring'''
_UpperCAmelCase : List[Any] = (boundary[1] - boundary[0]) / steps
_UpperCAmelCase : Tuple = boundary[0]
_Up... | 349 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def snake_case_ ( )-> int:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] ... | 349 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@r... | 349 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ )-> int:
'''simple docstring'''
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise TypeError("""only integers accepted as input""" )
else:
_UpperCAmelCase : Dict ... | 349 | 1 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ )-> bool:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] = len(lowerCAmelCase_ )
_UpperCAmelCase : List[str] = [[False] * (required_sum + 1) for _ ... | 349 |
'''simple docstring'''
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
A_ : Dict = logging.get_logger(__... | 349 | 1 |
'''simple docstring'''
import requests
A_ : str = """https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="""
def snake_case_ ( lowerCAmelCase_ )-> None:
'''simple docstring'''
_UpperCAmelCase : Any = requests.get(_NEWS_API ... | 349 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 0 , lowerCAmelCase_ = 0 )-> int:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] = right or len(lowerCAmelCase_ ) - 1
if left > right:... | 349 | 1 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock impor... | 349 |
'''simple docstring'''
from datetime import datetime
import requests
def snake_case_ ( lowerCAmelCase_ )-> bytes:
'''simple docstring'''
_UpperCAmelCase : Optional[Any] = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
_Upp... | 349 | 1 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_ut... | 349 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pi... | 349 | 1 |
'''simple docstring'''
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : str = {
"""configuration_roberta_prelayernorm""": [
"""ROBERTA_PRELA... | 349 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A_ : Union[str, Any] = logging.get_logger(__name__)
A_ : List[An... | 349 |
'''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
A_ : Union[str, Any] = logging.get_logger(__name__)
A_ ... | 349 | 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
A_ : Union[str, Any] = logging.get_logger(__name__)
A_ ... | 349 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class lowercase ( unittest.TestCase ):
"""simple docstring"""
def _snake_case ( self ) -> Optional[Any]:
_UpperCAmelCase : Any = [10, 20, 30, 40, 50, 60]
... | 349 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.util... | 349 |
'''simple docstring'''
from __future__ import annotations
import math
def snake_case_ ( lowerCAmelCase_ )-> list[int]:
'''simple docstring'''
if num <= 0:
_UpperCAmelCase : List[Any] = F'''{num}: Invalid input, please enter a positive integer.... | 349 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.... | 349 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase ( _lowerCamelCase ):
"""simple docstring"""
de... | 349 | 1 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ )-> list:
'''simple docstring'''
_UpperCAmelCase : Optional[int] = len(lowerCAmelCase_ )
_UpperCAmelCase : Optional[int] = [[0] * n... | 349 |
'''simple docstring'''
A_ : Optional[Any] = """0.21.0"""
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from ... | 349 | 1 |
'''simple docstring'''
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_tor... | 349 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def snake_case_ ( )-> Union[str, Any]:
'''simple docstring'''
_UpperCAmelCase : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-... | 349 | 1 |
'''simple docstring'''
import re
def snake_case_ ( lowerCAmelCase_ )-> list:
'''simple docstring'''
return [char.split() for char in re.split(R"""[^ a-z A-Z 0-9 \s]""" , str_ )]
def snake_case_ ( lowerCAmelCase_ )-> str:
'''simple docstring'''
... | 349 |
'''simple docstring'''
import math
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ )-> int:
'''simple docstring'''
_UpperCAmelCase : str = len(lowerCAmelCase_ )
_UpperCAmelCase : List[str] = int(math.floor(math.sqrt(lowerC... | 349 | 1 |
'''simple docstring'''
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def snake_case_ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_=5 )-> Optional[int]:
'''simple docstring'''
assert masked_input.cou... | 349 |
'''simple docstring'''
import argparse
import copy
def snake_case_ ( lowerCAmelCase_ )-> Dict:
'''simple docstring'''
_UpperCAmelCase : Dict = {}
with open(lowerCAmelCase_ ) as f:
for line in f:
if line.split()[0] ... | 349 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenize... | 349 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowercase :
"""simple docstring"""
UpperCAmelCase = 42
UpperCAmelCase = 42
class ... | 349 | 1 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils impo... | 349 |
'''simple docstring'''
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from ... | 349 | 1 |
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