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'''
from __future__ import annotations
from collections.abc import MutableSequence
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self , snake_case_ , snake_case_ ):
'''simple docstring'''
if len(snake_case_ ... | 368 | '''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : List[Any] = logging.get_logger(__name__)
snake_case__ : Optional[Any] = {
'''huggingface/autoformer-tourism-monthly''':... | 274 | 0 |
'''simple docstring'''
from math import ceil
def _lowerCamelCase ( lowerCamelCase_ : int = 1001 ):
"""simple docstring"""
UpperCAmelCase_ : List[Any] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
UpperCAmelCase_ ... | 369 | '''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
'''simple docstring'''
def _UpperCamelC... | 274 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ):
"""simple docstring"""
return int(input_a == input_a == 0 )
def _lowerCamelCase ( ):
"""simple docstring"""
print('Truth Table of NOR Gate:' ... | 370 | '''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
snake_case__ : str = '''\
'''
snake_case__ : Union[str, Any] = '''
Perplexit... | 274 | 0 |
'''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 BatchFeatu... | 371 | '''simple docstring'''
from sklearn.metrics import fa_score
import datasets
snake_case__ : str = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
snake_case__ : int ... | 274 | 0 |
'''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_bart import Ba... | 350 | '''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, C... | 274 | 0 |
'''simple docstring'''
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
snake_case__ : Optional[int] = logging.getLogger(__name__)
class __SCREAMING_SNAKE_CASE ( lowerC... | 351 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : str ):
"""simple docstring"""
UpperCAmelCase_ : Optional[int] = [0] * len(lowerCamelCase_ )
for i in range(1 , len(lowerCamelCase_ ) ):
# use last results f... | 274 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : int ):
"""simple docstring"""
UpperCAmelCase_ : Dict = [1]
UpperCAmelCase_ : Dict = 0, 0, 0
UpperCAmelCase_ : str = ugly_nums[ia] * 2
UpperC... | 352 | '''simple docstring'''
import os
import time
import numpy as np
import onnxruntime as ort
snake_case__ : Optional[int] = '''1'''
snake_case__ : str = '''0'''
snake_case__ : List[str] = '''1'''
snake_case__ : List[str] = ort.SessionOptions... | 274 | 0 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase_ :Dict = ['''image_processor''', '''tokenizer''... | 353 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ):
"""simple docstring"""
return int(input_a == input_a == 0 )
def _lowerCamelCase ( ):
"""simple docstring"""
print('Truth Table of NOR Gate:' ... | 274 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : int ):
"""simple docstring"""
UpperCAmelCase_ : str = len(lowerCamelCase_ )
while cur > 1:
# Find the maximum number in arr
UpperCAmelCase_ : ... | 354 | '''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ , lowerCamelCase_ ):
'''simp... | 274 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ : Optional[int] = {'''configuration_reformer''': ['''REFORMER_PR... | 355 | '''simple docstring'''
from manim import *
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
def _UpperCamelCase ( self ):
'''simple docstring'''
UpperCAmelCase_ : Dict = Rectangle(height=0.5 , width=0.5 ... | 274 | 0 |
'''simple docstring'''
import unittest
from knapsack import knapsack as k
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
'''simple docstring'''
def _UpperCamelCase ( self ):
'''simple docstring'''
UpperCAmelCase_ : int = 0
... | 356 | '''simple docstring'''
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ , ... | 274 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def _lowerCamelCase ( lowerCamelCase_ : str ):
"""simple docstring"""
UpperCAmelCase_ : int = analyze_text(lowerCamelCase... | 357 | '''simple docstring'''
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers... | 274 | 0 |
def _lowerCamelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ):
"""simple docstring"""
return base * power(lowerCamelCase_ , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print('''Raise base to the power of exponent using recursi... | 358 | '''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase_ :Tuple = ['''image_processor''', '''tokenizer'... | 274 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : Dict ):
"""simple docstring"""
stooge(lowerCamelCase_ , 0 , len(lowerCamelCase_ ) - 1 )
return arr
def _lowerCamelCase ( lowerCamelCase_ : Optional[int] , lowerCame... | 359 | '''simple docstring'''
snake_case__ : str = '''Tobias Carryer'''
from time import time
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self , snake_case_ , snake_case_ , snake_case_ , snake_case_=int(time() ) ): # no... | 274 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import M... | 360 | '''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common impor... | 274 | 0 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
fro... | 361 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : str , lowerCamelCase_ : str = " " ):
"""simple docstring"""
UpperCAmelCase_ : str = []
UpperCAmelCase_ : List[Any] = 0
for index, char in enumerate(lowe... | 274 | 0 |
'''simple docstring'''
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ , ... | 362 | '''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface... | 274 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
snake_case__ : Optional[int] = {'''configuration_gpt_neox''': ['''GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXConfig''']}... | 363 | '''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,
requi... | 274 | 0 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class __SCREAMING_SNAKE_CASE ( datasets.BuilderConfig ):
'''simple docstring'''... | 364 | '''simple docstring'''
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datas... | 274 | 0 |
'''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 --user <user> --host ... | 365 | '''simple docstring'''
snake_case__ : Optional[Any] = tuple[float, float, float]
snake_case__ : Tuple = tuple[float, float, float]
def _lowerCamelCase ( lowerCamelCase_ : Pointad , lowerCamelCase_ : Pointad ):
"""simple docstring"""
... | 274 | 0 |
'''simple docstring'''
snake_case__ : Optional[Any] = tuple[float, float, float]
snake_case__ : Tuple = tuple[float, float, float]
def _lowerCamelCase ( lowerCamelCase_ : Pointad , lowerCamelCase_ : Pointad ):
"""simple docstring"""
... | 366 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
snake_case__ : Dict = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
'''... | 274 | 0 |
'''simple docstring'''
from collections import deque
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self , snake_case_ , snake_case_ , snake_case_ ):
'''simple docstring'''
UpperCAmelCase_ ... | 367 | '''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
lowerCamelCase_ :int
lowerCamelCase_ :int
class ... | 274 | 0 |
'''simple docstring'''
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
snake_case__ : List[Any] = '''scheduler_config.json'''
... | 368 | '''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : List[Any] = logging.get_logger(__name__)
snake_case__ : Optional[Any] = {
'''huggingface/autoformer-tourism-monthly''':... | 274 | 0 |
'''simple docstring'''
import math
import unittest
from transformers import BioGptConfig, 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... | 369 | '''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
'''simple docstring'''
def _UpperCamelC... | 274 | 0 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_dif... | 370 | '''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
snake_case__ : str = '''\
'''
snake_case__ : Union[str, Any] = '''
Perplexit... | 274 | 0 |
'''simple docstring'''
import argparse
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Acc... | 371 | '''simple docstring'''
from sklearn.metrics import fa_score
import datasets
snake_case__ : str = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
snake_case__ : int ... | 274 | 0 |
'''simple docstring'''
snake_case__ : List[str] = {str(digit): digit**5 for digit in range(10)}
def _lowerCamelCase ( lowerCamelCase_ : int ):
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(lowerCamelCase_ ) )
def _l... | 350 | '''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, C... | 274 | 0 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, C... | 351 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : str ):
"""simple docstring"""
UpperCAmelCase_ : Optional[int] = [0] * len(lowerCamelCase_ )
for i in range(1 , len(lowerCamelCase_ ) ):
# use last results f... | 274 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : Any ):
"""simple docstring"""
UpperCAmelCase_ : Optional[Any] = []
UpperCAmelCase_ : str = []
UpperCAmelCase_ : Union[str, Any] = {
'^': ... | 352 | '''simple docstring'''
import os
import time
import numpy as np
import onnxruntime as ort
snake_case__ : Optional[int] = '''1'''
snake_case__ : str = '''0'''
snake_case__ : List[str] = '''1'''
snake_case__ : List[str] = ort.SessionOptions... | 274 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : int ):
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
UpperCAmelCase_ : Union[str, Any] = F'''Input value of [number={number}] must be an integ... | 353 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ):
"""simple docstring"""
return int(input_a == input_a == 0 )
def _lowerCamelCase ( ):
"""simple docstring"""
print('Truth Table of NOR Gate:' ... | 274 | 0 |
'''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 _lowerCamelCase ( lowerCamelCase_ : Dict[str, torch.Tensor] ):
"""simple docstring"""
... | 354 | '''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ , lowerCamelCase_ ):
'''simp... | 274 | 0 |
'''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_mobilebert import MobileBertTokenizer
snake_case__ : Optional[int] = logg... | 355 | '''simple docstring'''
from manim import *
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
def _UpperCamelCase ( self ):
'''simple docstring'''
UpperCAmelCase_ : Dict = Rectangle(height=0.5 , width=0.5 ... | 274 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : List[str] = logging.get_logger(__name__)
snake_case__ : Optional[int] = {
'''tiiuae/falcon-40b''': '''https://huggingface.co/tiiuae/falcon-40b/resolve/mai... | 356 | '''simple docstring'''
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ , ... | 274 | 0 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface... | 357 | '''simple docstring'''
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers... | 274 | 0 |
from math import ceil
def _lowerCamelCase ( lowerCamelCase_ : List[str] , lowerCamelCase_ : Tuple ):
"""simple docstring"""
UpperCAmelCase_ : Optional[int] = list(range(0 , lowerCamelCase_ ) )
UpperCAmelCase_ : ... | 358 | '''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase_ :Tuple = ['''image_processor''', '''tokenizer'... | 274 | 0 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class __SCREAMING_SNAKE_CASE ( datasets.BeamBasedBuilder ):
'''simple docstring... | 359 | '''simple docstring'''
snake_case__ : str = '''Tobias Carryer'''
from time import time
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self , snake_case_ , snake_case_ , snake_case_ , snake_case_=int(time() ) ): # no... | 274 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
snake_case__ : ... | 360 | '''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common impor... | 274 | 0 |
'''simple docstring'''
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
snake_case__ : str = Lock()
def _lowerCamelCase ( lowerCamelCase_ : List[Any] , lowerCamelCase_ : Union[str, Any] , ... | 361 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : str , lowerCamelCase_ : str = " " ):
"""simple docstring"""
UpperCAmelCase_ : str = []
UpperCAmelCase_ : List[Any] = 0
for index, char in enumerate(lowe... | 274 | 0 |
'''simple docstring'''
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase_ :Union[str, Any] ... | 362 | '''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface... | 274 | 0 |
from __future__ import annotations
from PIL import Image
# Define glider example
snake_case__ : str = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0... | 363 | '''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,
requi... | 274 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : list[list[int]] , lowerCamelCase_ : int , lowerCamelCase_ : int , lowerCamelCase_ : set ):
"""simple docstring"""
UpperCAmelCase_ : Union[str, Any] = le... | 364 | '''simple docstring'''
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datas... | 274 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
snake_case__ : Dict = {
'''configuration_swiftformer''': [
'''SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SwiftFo... | 365 | '''simple docstring'''
snake_case__ : Optional[Any] = tuple[float, float, float]
snake_case__ : Tuple = tuple[float, float, float]
def _lowerCamelCase ( lowerCamelCase_ : Pointad , lowerCamelCase_ : Pointad ):
"""simple docstring"""
... | 274 | 0 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
snake_case__ : List[str] = None
try:
import msvcrt
except ImportError:
snake_case__ : Optional[Any] = None
try:
import fcntl
except ImportError:
s... | 366 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
snake_case__ : Dict = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
'''... | 274 | 0 |
'''simple docstring'''
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
snake_case__ : str = '''scheduler_config.json'''
class __SCREAMING_... | 367 | '''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
lowerCamelCase_ :int
lowerCamelCase_ :int
class ... | 274 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : List[Any] = logging.get_logger(__name__)
snake_case__ : int = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santac... | 368 | '''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : List[Any] = logging.get_logger(__name__)
snake_case__ : Optional[Any] = {
'''huggingface/autoformer-tourism-monthly''':... | 274 | 0 |
'''simple docstring'''
import numpy as np
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self ):
'''simple docstring'''
UpperCAmelCase_ : Tuple = (0, 0)
UpperCAmelCase_ : List[str] = None
... | 369 | '''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
'''simple docstring'''
def _UpperCamelC... | 274 | 0 |
'''simple docstring'''
from math import pi
def _lowerCamelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ):
"""simple docstring"""
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 370 | '''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
snake_case__ : str = '''\
'''
snake_case__ : Union[str, Any] = '''
Perplexit... | 274 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase_ :int = '''ClapFeatureExtractor'''
lowerCamelCase_ :Tuple ... | 371 | '''simple docstring'''
from sklearn.metrics import fa_score
import datasets
snake_case__ : str = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
snake_case__ : int ... | 274 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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, ra... | 350 | '''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, C... | 274 | 0 |
'''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
snake_case__ : Optional[Any] = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in... | 351 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : str ):
"""simple docstring"""
UpperCAmelCase_ : Optional[int] = [0] * len(lowerCamelCase_ )
for i in range(1 , len(lowerCamelCase_ ) ):
# use last results f... | 274 | 0 |
'''simple docstring'''
from typing import Union
import fire
import torch
from tqdm import tqdm
def _lowerCamelCase ( lowerCamelCase_ : str , lowerCamelCase_ : str = "cpu" , lowerCamelCase_ : Union[str, None] = None ):
"""simple docstring"""
UpperCAmel... | 352 | '''simple docstring'''
import os
import time
import numpy as np
import onnxruntime as ort
snake_case__ : Optional[int] = '''1'''
snake_case__ : str = '''0'''
snake_case__ : List[str] = '''1'''
snake_case__ : List[str] = ort.SessionOptions... | 274 | 0 |
'''simple docstring'''
import os
import time
import numpy as np
import onnxruntime as ort
snake_case__ : Optional[int] = '''1'''
snake_case__ : str = '''0'''
snake_case__ : List[str] = '''1'''
snake_case__ : List[str] = ort.SessionOpt... | 353 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ):
"""simple docstring"""
return int(input_a == input_a == 0 )
def _lowerCamelCase ( ):
"""simple docstring"""
print('Truth Table of NOR Gate:' ... | 274 | 0 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ... | 354 | '''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ , lowerCamelCase_ ):
'''simp... | 274 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_... | 355 | '''simple docstring'''
from manim import *
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
def _UpperCamelCase ( self ):
'''simple docstring'''
UpperCAmelCase_ : Dict = Rectangle(height=0.5 , width=0.5 ... | 274 | 0 |
'''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 356 | '''simple docstring'''
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ , ... | 274 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
def __init__( self , snake_case_ , snake_case_ ):
... | 357 | '''simple docstring'''
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers... | 274 | 0 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
lowerCamelCase_ :int
lowerCamelCase_ :int
class __SCREAMING_SNAKE_CAS... | 358 | '''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase_ :Tuple = ['''image_processor''', '''tokenizer'... | 274 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : int ):
"""simple docstring"""
UpperCAmelCase_ : Union[str, Any] = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def _lowerCamelCase ( lowerCamelCase_ : int = 5000 ):
... | 359 | '''simple docstring'''
snake_case__ : str = '''Tobias Carryer'''
from time import time
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self , snake_case_ , snake_case_ , snake_case_ , snake_case_=int(time() ) ): # no... | 274 | 0 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,... | 360 | '''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common impor... | 274 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case__ : str = {
'''configuration_table_transformer''': [
'''TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TableTransfor... | 361 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : str , lowerCamelCase_ : str = " " ):
"""simple docstring"""
UpperCAmelCase_ : str = []
UpperCAmelCase_ : List[Any] = 0
for index, char in enumerate(lowe... | 274 | 0 |
'''simple docstring'''
import math
import tensorflow as tf
from packaging import version
def _lowerCamelCase ( lowerCamelCase_ : int ):
"""simple docstring"""
UpperCAmelCase_ : str = tf.convert_to_tensor(lowerCamelCase_ )
UpperCAmelCase_ : ... | 362 | '''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface... | 274 | 0 |
from itertools import permutations
def _lowerCamelCase ( lowerCamelCase_ : tuple ):
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
UpperCAm... | 363 | '''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,
requi... | 274 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : int = logging.get_logger(__name__)
snake_case__ : List[Any] = {
'''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.j... | 364 | '''simple docstring'''
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datas... | 274 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
snake_case__ : str = (3, 9, -11, 0, 7, 5, 1, -1)
snake_case__ : Any = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class __SCREAMING_SN... | 365 | '''simple docstring'''
snake_case__ : Optional[Any] = tuple[float, float, float]
snake_case__ : Tuple = tuple[float, float, float]
def _lowerCamelCase ( lowerCamelCase_ : Pointad , lowerCamelCase_ : Pointad ):
"""simple docstring"""
... | 274 | 0 |
'''simple docstring'''
import math
def _lowerCamelCase ( lowerCamelCase_ : int = 100 ):
"""simple docstring"""
UpperCAmelCase_ : Tuple = sum(i * i for i in range(1 , n + 1 ) )
UpperCAmelCase_ : Union[str, Any] = i... | 366 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
snake_case__ : Dict = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
'''... | 274 | 0 |
'''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,... | 367 | '''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
lowerCamelCase_ :int
lowerCamelCase_ :int
class ... | 274 | 0 |
'''simple docstring'''
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
snake_case__ : Dict = {
'''n_samples''': 64,
'''horizon''': 32,
'''num_inference_steps''': 20,
'''n_guide_steps''': 2, # can set to 0 for faster sampling, do... | 368 | '''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : List[Any] = logging.get_logger(__name__)
snake_case__ : Optional[Any] = {
'''huggingface/autoformer-tourism-monthly''':... | 274 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ... | 369 | '''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
'''simple docstring'''
def _UpperCamelC... | 274 | 0 |
'''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
fr... | 370 | '''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
snake_case__ : str = '''\
'''
snake_case__ : Union[str, Any] = '''
Perplexit... | 274 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : Optional[Any] = logging.get_logger(__name__)
snake_case__ : Optional[Any] = {
'''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve/m... | 371 | '''simple docstring'''
from sklearn.metrics import fa_score
import datasets
snake_case__ : str = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
snake_case__ : int ... | 274 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
snake_case__ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
def __... | 350 | '''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, C... | 274 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : int = 1000000 ):
UpperCAmelCase_ : int = limit + 1
UpperCAmelCase_ : str = [0] * limit
for first_term in range(1 , lowerCamelCase_ ):
for n in range(lowerCa... | 351 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : str ):
"""simple docstring"""
UpperCAmelCase_ : Optional[int] = [0] * len(lowerCamelCase_ )
for i in range(1 , len(lowerCamelCase_ ) ):
# use last results f... | 274 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
snake_case__ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
... | 352 | '''simple docstring'''
import os
import time
import numpy as np
import onnxruntime as ort
snake_case__ : Optional[int] = '''1'''
snake_case__ : str = '''0'''
snake_case__ : List[str] = '''1'''
snake_case__ : List[str] = ort.SessionOptions... | 274 | 0 |
'''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : str = logging.get_logger(__name__)
snake_case__ : List[str] = {
'''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2... | 353 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ):
"""simple docstring"""
return int(input_a == input_a == 0 )
def _lowerCamelCase ( ):
"""simple docstring"""
print('Truth Table of NOR Gate:' ... | 274 | 0 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
snake_case__ : str = '''\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
... | 354 | '''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ , lowerCamelCase_ ):
'''simp... | 274 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstrings,... | 355 | '''simple docstring'''
from manim import *
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
def _UpperCamelCase ( self ):
'''simple docstring'''
UpperCAmelCase_ : Dict = Rectangle(height=0.5 , width=0.5 ... | 274 | 0 |
'''simple docstring'''
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_sub... | 356 | '''simple docstring'''
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ , ... | 274 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : str ):
"""simple docstring"""
if n_term == "":
return []
UpperCAmelCase_ : list = []
for temp in range(int(lowerCamelCase_ ) ):
series.append(F'''1/{temp + ... | 357 | '''simple docstring'''
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers... | 274 | 0 |
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
snake_case__ : Optional[int... | 358 | '''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase_ :Tuple = ['''image_processor''', '''tokenizer'... | 274 | 0 |
'''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
import jax.numpy as... | 359 | '''simple docstring'''
snake_case__ : str = '''Tobias Carryer'''
from time import time
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self , snake_case_ , snake_case_ , snake_case_ , snake_case_=int(time() ) ): # no... | 274 | 0 |
'''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.switch_... | 360 | '''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common impor... | 274 | 0 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,... | 361 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : str , lowerCamelCase_ : str = " " ):
"""simple docstring"""
UpperCAmelCase_ : str = []
UpperCAmelCase_ : List[Any] = 0
for index, char in enumerate(lowe... | 274 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : int = 1000 ):
"""simple docstring"""
return sum(e for e in range(3 , lowerCamelCase_ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f'''{solution() = }''')
| 362 | '''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface... | 274 | 0 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
... | 363 | '''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,
requi... | 274 | 0 |
'''simple docstring'''
import argparse
import os
import re
import zipfile
import torch
from transformers import AutoTokenizer, GPTaConfig
def _lowerCamelCase ( lowerCamelCase_ : Union[str, Any] , lowerCamelCase_ : Optional[int] , lowerCamelCase_ : Optional[int]=0 ... | 364 | '''simple docstring'''
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datas... | 274 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case__ : str = {'''configuration_glpn''': ['''GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GLPNConfig''']}
try:
if not is_vision_... | 365 | '''simple docstring'''
snake_case__ : Optional[Any] = tuple[float, float, float]
snake_case__ : Tuple = tuple[float, float, float]
def _lowerCamelCase ( lowerCamelCase_ : Pointad , lowerCamelCase_ : Pointad ):
"""simple docstring"""
... | 274 | 0 |
'''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 accelerate ... | 366 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
snake_case__ : Dict = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
'''... | 274 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import... | 367 | '''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
lowerCamelCase_ :int
lowerCamelCase_ :int
class ... | 274 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def _lowerCamelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int , lowerCamelCase_ : bool , lowerCamelCase_ : list[int] , lowerCamelCase_ : float ):
"""simple d... | 368 | '''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : List[Any] = logging.get_logger(__name__)
snake_case__ : Optional[Any] = {
'''huggingface/autoformer-tourism-monthly''':... | 274 | 0 |
'''simple docstring'''
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def _lowerCamelCase ( lowerCamelCase_ : Union[str, Any] , lowerCamelCase_ : List[str] , lowerCamelCase_ : List[str] , ... | 369 | '''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
'''simple docstring'''
def _UpperCamelC... | 274 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
snake_case__ : int = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''to... | 370 | '''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
snake_case__ : str = '''\
'''
snake_case__ : Union[str, Any] = '''
Perplexit... | 274 | 0 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def _lowerCamelCase ( lowerCamelCase_ : np.ndarray ):
"""simple docstring"""
UpperCAmelCase_ : str = np.shape(lowerCamelCase_ )
if rows != columns:
UpperCAmelCa... | 371 | '''simple docstring'''
from sklearn.metrics import fa_score
import datasets
snake_case__ : str = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
snake_case__ : int ... | 274 | 0 |
'''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 ..auto import CONFIG_MAPPING
lowerCAmelCase :List[str] = logging... | 275 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow ha... | 275 | 1 |
'''simple docstring'''
lowerCAmelCase :Any = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github... | 275 |
'''simple docstring'''
def lowerCamelCase ( lowerCAmelCase : int ):
"""simple docstring"""
__magic_name__ : Optional[int] = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCamelCase ( lowerCAmelCase : int ):
"""simple ... | 275 | 1 |
'''simple docstring'''
from math import factorial
class _lowerCamelCase :
'''simple docstring'''
def __init__( self : Tuple , _A : List[str] , _A : int ) -> Union[str, Any]:
__magic_name__ : Union[str, Any] = real
if isinstance(_A , _A ... | 275 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DD... | 275 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenizer
... | 275 |
'''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,
logging,
)
... | 275 | 1 |
'''simple docstring'''
def lowerCamelCase ( lowerCAmelCase : Optional[int] , lowerCAmelCase : str ):
"""simple docstring"""
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def lowerCamelCase ( lowerCAmelCase : List[str] , lowerCAmel... | 275 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
lowerCAmelCase :Tuple = logging.get_logger(__name__)
class _lowerCamelCase ( lowercase__ ):
'''simple docstring'''
def __init__( self : Any , ... | 275 | 1 |
'''simple docstring'''
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
lowerCAmelCase :int = WebClient(token=os.environ['''CI_SLACK_BOT_TOKEN'''])
def lowerCamelCase ... | 275 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase :str = {
'''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoder... | 275 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configura... | 275 |
'''simple docstring'''
lowerCAmelCase :Union[str, Any] = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers... | 275 | 1 |
'''simple docstring'''
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
lowerCAmelCase :int = logging.get_logger... | 275 |
'''simple docstring'''
def lowerCamelCase ( lowerCAmelCase : str , lowerCAmelCase : Any , lowerCAmelCase : Any=False ):
"""simple docstring"""
if isinstance(lowerCAmelCase , lowerCAmelCase ) and isinstance(lowerCAmelCase , lowerCAmelCase ):
__magic_name__ : ... | 275 | 1 |
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