code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowerCAmelCase : List[str] = {"""tokenization_byt5""": ["""ByT5Tokenizer"""]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
... | 704 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, l... | 630 | 0 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin, SchedulerOutput
@dataclass
class UpperCamel... | 705 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 630 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class UpperCamelCase__ ( __lowercase ):
"""simple docstring"""
def __init__( self , snake_case__ , ... | 706 |
'''simple docstring'''
import socket
def lowercase ():
"""simple docstring"""
_lowerCAmelCase : Tuple = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowerCAmelCase : Optional[int] ... | 630 | 0 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCAmelCase : Any = "\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and... | 707 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 0 |
'''simple docstring'''
import cva
import numpy as np
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , snake_case__ , snake_case__ ):
'''simple docstring'''
if k in (0.04, 0.06):
_l... | 708 |
'''simple docstring'''
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class UpperCamelCase__ ( tf.keras.layers.Layer ):... | 630 | 0 |
'''simple docstring'''
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_files... | 709 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
... | 630 | 0 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 710 |
'''simple docstring'''
lowerCAmelCase : Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : str = 0
... | 630 | 0 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import F... | 711 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 630 | 0 |
'''simple docstring'''
lowerCAmelCase : str = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowerCAmelCase : List[Any] = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowerCAmelCase : Union[str, Any] = {
0: "Sunday",
1: "Monday",
2: "Tuesday",
3: ... | 712 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import F... | 630 | 0 |
'''simple docstring'''
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_sub... | 713 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 630 | 0 |
import math
def lowercase (_A = 1_0_0 ):
"""simple docstring"""
_lowerCAmelCase : Any = sum(i * i for i in range(1 , n + 1 ) )
_lowerCAmelCase : Optional[int] = int(math.pow(sum(range(... | 714 |
'''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 ...util... | 630 | 0 |
'''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils impo... | 715 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfi... | 630 | 0 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def lowercase (_A ):
"""simple docstring"""
def decorator(_A ):
_lowerCAmelCase : str = getattr(_Uppe... | 716 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = year % 1_9
_lowerCAmelCase : Any = ... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , snake_case__ ):
'''simple docstring'''
_lowerCAmelCase : Union[str, Any] = size
#... | 717 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstring"""
def a ( self ):
'''simple docstring'''
_lowerCAmelCase : Union[str, ... | 630 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Tuple = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
... | 718 |
'''simple docstring'''
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : Optional[int] = (boundary[1] - boundary[0]) / steps
_lowerCAmelCase : Any = boundary[0]
_low... | 630 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase : Optional[A... | 719 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCAmelCase : int = {
"""configuration_trocr""... | 630 | 0 |
'''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, normalize, rescale, resize, to_channel_dimension_format
from ...image_u... | 720 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def lowercase (_A = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values()... | 630 | 0 |
'''simple docstring'''
import numpy as np
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , snake_case__=None , snake_case__=None , snake_case__=None , snake_case__=None , snake_case__=None ):
'''simple docstring'''
... | 721 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase : str = logging.get_logger(__name__)
lowerCAmelCase :... | 630 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
lowerCAmelCase : Optional[int] = {
"""config""": [
"""EXTERNAL_DATA_FORMAT_SIZE_LIMIT""",
"""OnnxConfig""",
"""OnnxConfigWithPast""",
"""OnnxSeq2S... | 700 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase : List[str] = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def lowercase (_A , _A ):
... | 630 | 0 |
from cva import destroyAllWindows, imread, imshow, waitKey
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = img.shape[0], img.shape[1]
# converting each pixel's color to its negative
for i ... | 701 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseMod... | 630 | 0 |
'''simple docstring'''
import numpy as np
lowerCAmelCase : Optional[Any] = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"... | 702 |
'''simple docstring'''
from typing import Any
def lowercase (_A ):
"""simple docstring"""
if not input_list:
return []
_lowerCAmelCase : Optional[int] = [input_list.count(_A ) for value... | 630 | 0 |
'''simple docstring'''
import argparse
from ...utils.dataclasses import (
ComputeEnvironment,
DistributedType,
DynamoBackend,
PrecisionType,
SageMakerDistributedType,
)
from ..menu import BulletMenu
lowerCAmelCase : int = [
"""EAGER""",
"... | 703 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from ... | 630 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
... | 704 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, l... | 630 | 0 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_... | 705 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 630 | 0 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...te... | 706 |
'''simple docstring'''
import socket
def lowercase ():
"""simple docstring"""
_lowerCAmelCase : Tuple = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowerCAmelCase : Optional[int] ... | 630 | 0 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers,... | 707 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCAmelCase : int = {
"""configuration_trocr""... | 708 |
'''simple docstring'''
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class UpperCamelCase__ ( tf.keras.layers.Layer ):... | 630 | 0 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcess... | 709 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : str = u
for i in range(1 , _A ):
_lowerCAmelCase : Optional[... | 710 |
'''simple docstring'''
lowerCAmelCase : Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : str = 0
... | 630 | 0 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
if not isinstance(_A , _A ):
raise ValueError('Input must be an integer' )
if input_num <= 0:
raise ValueError('Input must be... | 711 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 630 | 0 |
'''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 ... | 712 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import F... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : List[str] = 2
_lowerCAmelCase : List[Any] = []
while i *... | 713 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 630 | 0 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
lowerCAmelCase : Union[str, Any] = object()
# For specifying empty leaf dict `{}`
lowerCAmelCase : Any ... | 714 |
'''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 ...util... | 630 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import List, Optional
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
def __init__( self ):
'''simple docstring'''
self.test()
... | 715 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfi... | 630 | 0 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 716 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = year % 1_9
_lowerCAmelCase : Any = ... | 630 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as... | 717 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstring"""
def a ( self ):
'''simple docstring'''
_lowerCAmelCase : Union[str, ... | 630 | 0 |
'''simple docstring'''
lowerCAmelCase : Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : str = 0
... | 718 |
'''simple docstring'''
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : Optional[int] = (boundary[1] - boundary[0]) / steps
_lowerCAmelCase : Any = boundary[0]
_low... | 630 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase : Optional[Any] = {
"""configuration_poolformer""": [
"""POOLFORMER_PRETRAINED_CONFIG_A... | 719 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCAmelCase : int = {
"""configuration_trocr""... | 630 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import... | 720 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def lowercase (_A = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values()... | 630 | 0 |
'''simple docstring'''
from sklearn.metrics import recall_score
import datasets
lowerCAmelCase : Union[str, Any] = """
Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:
Recall = TP / (TP + FN)
Where TP... | 721 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase : str = logging.get_logger(__name__)
lowerCAmelCase :... | 630 | 0 |
'''simple docstring'''
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic... | 700 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase : List[str] = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def lowercase (_A , _A ):
... | 630 | 0 |
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.tes... | 701 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseMod... | 630 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 702 |
'''simple docstring'''
from typing import Any
def lowercase (_A ):
"""simple docstring"""
if not input_list:
return []
_lowerCAmelCase : Optional[int] = [input_list.count(_A ) for value... | 630 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : List[str] = logging.get_logger(__name__)
lowerCAmelCase : Optional[Any] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve... | 703 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from ... | 630 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pip... | 704 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, l... | 630 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop... | 705 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = 4_2
__magic_name__ = 4_2
def lowercase (... | 706 |
'''simple docstring'''
import socket
def lowercase ():
"""simple docstring"""
_lowerCAmelCase : Tuple = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowerCAmelCase : Optional[int] ... | 630 | 0 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def lowercase (_A , _A , _A=None , **_A ):
"""simple docstring"""
_lowerCAmelCase : Tuple = [x.strip() for x in open(_A ... | 707 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 0 |
'''simple docstring'''
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (UnCLIPScheduler,)
... | 708 |
'''simple docstring'''
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class UpperCamelCase__ ( tf.keras.layers.Layer ):... | 630 | 0 |
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pi... | 709 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
... | 630 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowerCAmelCase : Union[str, Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
e... | 710 |
'''simple docstring'''
lowerCAmelCase : Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : str = 0
... | 630 | 0 |
'''simple docstring'''
import qiskit
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = qiskit.Aer.get_backend('aer_simulator' )
# Create a Quantum Circuit acting on... | 711 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 630 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
lowerCAmelCase : Any = """\
"""
lowerCAmelCase : Union[str, A... | 712 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import F... | 630 | 0 |
'''simple docstring'''
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class UpperCamelCase__ :
"""simple docstring"""
pass
| 713 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 630 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvaila... | 714 |
'''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 ...util... | 630 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import ... | 715 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfi... | 630 | 0 |
'''simple docstring'''
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , snake_case__ ):
'''simple docstring'''
_lowerCAmelCase : int = len(snake_case__ )
_lowerCAmelCase ... | 716 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = year % 1_9
_lowerCAmelCase : Any = ... | 630 | 0 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
lowerCAmelCase : st... | 717 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstring"""
def a ( self ):
'''simple docstring'''
_lowerCAmelCase : Union[str, ... | 630 | 0 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase : ... | 718 |
'''simple docstring'''
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : Optional[int] = (boundary[1] - boundary[0]) / steps
_lowerCAmelCase : Any = boundary[0]
_low... | 630 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Dict = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoe... | 719 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCAmelCase : int = {
"""configuration_trocr""... | 630 | 0 |
'''simple docstring'''
def lowercase (_A = 5_0 ):
"""simple docstring"""
_lowerCAmelCase : List[str] = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_leng... | 720 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def lowercase (_A = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values()... | 630 | 0 |
'''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 PegasusToke... | 721 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase : str = logging.get_logger(__name__)
lowerCAmelCase :... | 630 | 0 |
'''simple docstring'''
def lowercase () -> List[Any]:
"""simple docstring"""
return [list(range(1_0_0_0 - i , -1_0_0_0 - i , -1 ) ) for i in range(1_0_0_0 )]
lowerCAmelCase : Union[str, Any] = gen... | 700 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase : List[str] = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def lowercase (_A , _A ):
... | 630 | 0 |
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBertForMa... | 701 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseMod... | 630 | 0 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
lowerCAmelCase : Optional[int] =... | 702 |
'''simple docstring'''
from typing import Any
def lowercase (_A ):
"""simple docstring"""
if not input_list:
return []
_lowerCAmelCase : Optional[int] = [input_list.count(_A ) for value... | 630 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_senten... | 703 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from ... | 630 | 0 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
if edge <= 0 or not isinstance(_A , _A ):
raise ValueError('Length must be a positive.' )
return 3 * ((2_5 + 1_0 * (5 ** (1 / 2))) ** (1... | 704 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, l... | 630 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenizatio... | 705 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 630 | 0 |
'''simple docstring'''
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ..... | 706 |
'''simple docstring'''
import socket
def lowercase ():
"""simple docstring"""
_lowerCAmelCase : Tuple = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowerCAmelCase : Optional[int] ... | 630 | 0 |
'''simple docstring'''
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCAmelCase : Any = input("""Enter image url: """).strip()
print(F'''Downloading image from {url} ...''')
lowerCAmelCase ... | 707 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase : Dict = {
"""configuration_swiftformer""": [
"""SWIFTFORMER_PRETRAINED_CONFIG_ARCHI... | 708 |
'''simple docstring'''
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class UpperCamelCase__ ( tf.keras.layers.Layer ):... | 630 | 0 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Sess... | 709 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
... | 630 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : List[Any] = logging.get_logger(__name__)
lowerCAmelCase : int = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/f... | 710 |
'''simple docstring'''
lowerCAmelCase : Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : str = 0
... | 630 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : List[str] = logging.get_logger(__name__)
lowerCAmelCase : Optional[Any] = {
"""funnel-transformer/small""": """https://huggingface.c... | 711 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
lowerCAmelCase : Tuple = TypeVar("""KT""")
lowerCAmelCase : Dict = TypeVar("""VT""")
class UpperCamelCase__ ( Generic[KT, VT] ):
... | 712 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import F... | 630 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.j... | 713 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 630 | 0 |
lowerCAmelCase : Optional[Any] = [
"""VerificationMode""",
"""Version""",
"""disable_progress_bar""",
"""enable_progress_bar""",
"""is_progress_bar_enabled""",
"""experimental""",
]
from .info_utils import VerificationMode
from .logging import disable_progress_ba... | 714 |
'''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 ...util... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Optional[int] = len(_A )
# We need to create solution object to save path.
... | 715 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfi... | 630 | 0 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowerCAmelCase : int = False... | 716 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = year % 1_9
_lowerCAmelCase : Any = ... | 630 | 0 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
stooge(_A , 0 , len(_A ) - 1 )
return arr
def lowercase (_A , _A , _A ):
"""simple docstring"""
if i >= h:
... | 717 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstring"""
def a ( self ):
'''simple docstring'''
_lowerCAmelCase : Union[str, ... | 630 | 0 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
assert (
isinstance(_A , _A ) and number_of_steps > 0
), f'number_of_steps needs to be positive integer, your input {number_of_steps}'
if n... | 718 |
'''simple docstring'''
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : Optional[int] = (boundary[1] - boundary[0]) / steps
_lowerCAmelCase : Any = boundary[0]
_low... | 630 | 0 |
'''simple docstring'''
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
... | 719 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCAmelCase : int = {
"""configuration_trocr""... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from .... | 720 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def lowercase (_A = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values()... | 630 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
... | 721 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase : str = logging.get_logger(__name__)
lowerCAmelCase :... | 630 | 0 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class Upper... | 700 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase : List[str] = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def lowercase (_A , _A ):
... | 630 | 0 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCAmelCase : Union[str, Any] = version.parse(importlib_metadata.version("""nltk"""))
if NLTK_VERSION >= version.Version("""3.6.4"""):
from nltk ... | 701 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseMod... | 630 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers... | 702 |
'''simple docstring'''
from typing import Any
def lowercase (_A ):
"""simple docstring"""
if not input_list:
return []
_lowerCAmelCase : Optional[int] = [input_list.count(_A ) for value... | 630 | 0 |
'''simple docstring'''
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_ge... | 703 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from ... | 630 | 0 |
'''simple docstring'''
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from di... | 704 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, l... | 630 | 0 |
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_filename,
... | 705 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 630 | 0 |
'''simple docstring'''
def lowercase (_A = 1 , _A = 1_0_0_0 ):
"""simple docstring"""
_lowerCAmelCase : str = 1
_lowerCAmelCase : Optional[Any] = 0
for divide_by_number in range(_A... | 706 |
'''simple docstring'''
import socket
def lowercase ():
"""simple docstring"""
_lowerCAmelCase : Tuple = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowerCAmelCase : Optional[int] ... | 630 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowercase (_A , _A , _A ... | 707 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 0 |
'''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowerCAmelCase : List[str] = argparse.ArgumentParser("""Stable Diffusion script with intel optimizati... | 708 |
'''simple docstring'''
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class UpperCamelCase__ ( tf.keras.layers.Layer ):... | 630 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase : Any = logging.get_logger(__name__)
lowerCAmelCase : Any = {"""vocab_file"... | 709 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
... | 630 | 0 |
'''simple docstring'''
import unittest
from transformers import 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 import Mod... | 710 |
'''simple docstring'''
lowerCAmelCase : Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : str = 0
... | 630 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseMod... | 711 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 630 | 0 |
'''simple docstring'''
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("""ignore""", category=UserWarning, module="""torch.optim.lr_scheduler""")
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self... | 712 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import F... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : List[Any] = [True] * limit
_lowerCAmelCase : Optional[int] = Fal... | 713 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 630 | 0 |
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
lowerCAmelCase ... | 714 |
'''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 ...util... | 630 | 0 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
lowerCAmelCase : Optional[Any] = """
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentat... | 715 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfi... | 630 | 0 |
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