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 collections.abc import Sequence
from queue import Queue
class a__ :
def __init__( self, _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase=None, _UpperCAmelCase=None ):
'''simple docstring'''
lowercase__ = st... | 706 | """simple docstring"""
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
f... | 668 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_: Any = logging.get_logger(__name__)
lowerCAmelCase_: Dict = {
"microsoft/git-base": "https://huggingface.co/microsoft/g... | 707 | """simple docstring"""
from typing import Any
import numpy as np
def __a ( A ):
'''simple docstring'''
return np.array_equal(A , matrix.conjugate().T )
def __a ( A , A ):
'''simple docstring'''
lowercase__ = v.co... | 668 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
from .... | 708 | """simple docstring"""
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_mod... | 668 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
lowerCAmelCase_: Any = {
'google/tapas-base-finetuned-sqa': (
'https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'
),
'google/tapas-base-finetuned-wtq': (
'https://huggingf... | 709 | """simple docstring"""
lowerCAmelCase_: Any = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def __a ( A ):
'''simple docstring'''
if not isinstance(A , A ):
lowercase__ = f'''a bytes-like object is required, not \'{... | 668 | 0 |
"""simple docstring"""
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTR... | 710 | """simple docstring"""
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __a ( A , A , A = "x" , A = 10**-10 , A = 1 , ):
'''simple docstring'''
lowercase__ = symbols(A )
lowercase__ = ... | 668 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_: Union[str, Any] = logging.get_logger(__name__)
lowerCAmelCase_: List[Any] = {
'''tanreinama/GPTSAN-2.8B-spout_is_uniform''': (
'''https://huggingface.co/tanre... | 711 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_: Union[str, Any] = {
"configuration_distilbert": [
... | 668 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
DiffusionPi... | 712 | """simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowerCA... | 668 | 0 |
"""simple docstring"""
def __a ( A ):
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError("List is empty" )
lowercase__ = sum(lowerCamelCase_ ) / len(lowerCamelCase_ ) # Calculate the average
retur... | 713 | """simple docstring"""
from __future__ import annotations
import math
def __a ( A ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even ... | 668 | 0 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokeni... | 714 | """simple docstring"""
import os
import sys
lowerCAmelCase_: Any = os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSeq... | 668 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_: str = {
"configuration_roformer": ["ROFORMER_PRETRA... | 715 | """simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import Flax... | 668 | 0 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class a__ ( unittest.TestCase , _a ):
def snake_case__ ( self ):
'''simple docstring'''
lowercase__ = load_tool("text-classification"... | 716 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_: str = logging.get_logger(__name__)
lowerCAmelCase_: ... | 668 | 0 |
"""simple docstring"""
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def __a ( A ):
'''s... | 717 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_: List[Any] = logging.get_logger(__name__)
lowerCAmelCase_: int = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json"... | 668 | 0 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,... | 718 | """simple docstring"""
lowerCAmelCase_: Union[str, Any] = [
9_9_9,
8_0_0,
7_9_9,
6_0_0,
5_9_9,
5_0_0,
4_0_0,
3_9_9,
3_7_7,
3_5_5,
3_3_3,
3_1_1,
2_8_8,
2_6_6,
2_4_4,
2_2_2,
2_0_0,
1_9_9,
1_7_7,
1_5_5,
1_3_3,
1_1_1,
... | 668 | 0 |
"""simple docstring"""
def __a ( A ):
lowercase__ = min(A ) # min() finds the minimum value
lowercase__ = max(A ) # max() finds the maximum value
lowercase__ = max_val - min_val + 1 # size is difference of max and min values plus one
# list... | 719 | """simple docstring"""
from __future__ import annotations
def __a ( A , A ):
'''simple docstring'''
if partitions <= 0:
raise ValueError("partitions must be a positive number!" )
if partitions > number_of_bytes:
raise ValueError("partitions ca... | 668 | 0 |
"""simple docstring"""
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def __a ( A = True , *A , **A ):
'''simple docstring'''
if not is_tqdm_available():
raise ImportEr... | 720 | """simple docstring"""
from collections import deque
class a__ :
def __init__( self, _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase ):
'''simple docstring'''
lowercase__ = process_name # process name
lowercase__ = arrival_time # arriva... | 668 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class a__ ( ... | 721 | """simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import ... | 668 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType
lowerCAm... | 700 | """simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nes... | 668 | 0 |
"""simple docstring"""
def __a ( A , A , A ):
'''simple docstring'''
if principal <= 0:
raise Exception("Principal borrowed must be > 0" )
if rate_per_annum < 0:
raise Exception("Rate of interest must be >= 0" )
if years_to_repay <= 0... | 701 | """simple docstring"""
import itertools
import math
def __a ( A ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multip... | 668 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_: str = {
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP... | 702 | """simple docstring"""
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class a__ ( _a ):
def __init__( self, _UpperCAmelCase, ... | 668 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.... | 703 | """simple docstring"""
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from... | 668 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_: Optional[Any] = {
"configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
"tokenization_luke": ["LukeTokeni... | 704 | """simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class a__ ( _a ):
snake_case_ = (IPNDMScheduler,)
snake_case_ = (("num_inference_steps", 50),)
def snake_case__ ( self, **... | 668 | 0 |
"""simple docstring"""
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
lowerCAmelCase_: Tuple = re.compile(R"^(?P<major>\d+)" R"\.(?P<minor>\d+)" R"\.(?P<patch>\d+)$")
@total_ordering
@dataclas... | 705 | """simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_t... | 668 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class a__ ( metaclass=__lowercase ):
snake_case_ = ["flax"]
def __init__( self, *_UpperCAmelCase, **_UpperCAmelCase ):
'''simple docstring'''
requires_backends(self, ["flax"] )
... | 706 | """simple docstring"""
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
f... | 668 | 0 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def __a ( A ):
'''simple docstring'''
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch_dump_... | 707 | """simple docstring"""
from typing import Any
import numpy as np
def __a ( A ):
'''simple docstring'''
return np.array_equal(A , matrix.conjugate().T )
def __a ( A , A ):
'''simple docstring'''
lowercase__ = v.co... | 668 | 0 |
from math import asin, atan, cos, radians, sin, sqrt, tan
lowerCAmelCase_: str = 6_3_7_8_1_3_7.0
lowerCAmelCase_: Tuple = 6_3_5_6_7_5_2.3_1_4_2_4_5
lowerCAmelCase_: Tuple = 6_3_7_8_1_3_7
def __a ( A , A , A , A ):
'''simple docstring'... | 708 | """simple docstring"""
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_mod... | 668 | 0 |
"""simple docstring"""
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def __... | 709 | """simple docstring"""
lowerCAmelCase_: Any = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def __a ( A ):
'''simple docstring'''
if not isinstance(A , A ):
lowercase__ = f'''a bytes-like object is required, not \'{... | 668 | 0 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCAmelCase_: Tuple = logging.get_logger(__name__)
class a__ ( a__ ):
snake_case_ ... | 710 | """simple docstring"""
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __a ( A , A , A = "x" , A = 10**-10 , A = 1 , ):
'''simple docstring'''
lowercase__ = symbols(A )
lowercase__ = ... | 668 | 0 |
"""simple docstring"""
def __a ( A , A ):
'''simple docstring'''
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(A , int(b / 2 ) ) * actual_power(A , int(b / 2 ) )
else:
return a * actual_power(A ... | 711 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_: Union[str, Any] = {
"configuration_distilbert": [
... | 668 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
lowerCAmelCase_: Optional[Any] = logging.... | 712 | """simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowerCA... | 668 | 0 |
"""simple docstring"""
from __future__ import annotations
def __a ( A , A = None ):
'''simple docstring'''
lowercase__ = word_bank or []
# create a table
lowercase__ = len(a_ ) + 1
lowercase__ = []
for _ in range(a_ ... | 713 | """simple docstring"""
from __future__ import annotations
import math
def __a ( A ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even ... | 668 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_ut... | 714 | """simple docstring"""
import os
import sys
lowerCAmelCase_: Any = os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSeq... | 668 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase_: Union[str, Any] = {"configuration_deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "D... | 715 | """simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import Flax... | 668 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
lowerCAmelCase_: Union[str, Any] = {"vocab_file": "vocab.txt", "tokenizer_... | 716 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_: str = logging.get_logger(__name__)
lowerCAmelCase_: ... | 668 | 0 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTe... | 717 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_: List[Any] = logging.get_logger(__name__)
lowerCAmelCase_: int = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json"... | 668 | 0 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class a__ ( __lowerCAmelCase ):
def snake_case__ ( self ):
'''simple docstring'''
return [
{"col_1": 3, "col_2": "a"},
... | 718 | """simple docstring"""
lowerCAmelCase_: Union[str, Any] = [
9_9_9,
8_0_0,
7_9_9,
6_0_0,
5_9_9,
5_0_0,
4_0_0,
3_9_9,
3_7_7,
3_5_5,
3_3_3,
3_1_1,
2_8_8,
2_6_6,
2_4_4,
2_2_2,
2_0_0,
1_9_9,
1_7_7,
1_5_5,
1_3_3,
1_1_1,
... | 668 | 0 |
"""simple docstring"""
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def __a ( A , A ):... | 719 | """simple docstring"""
from __future__ import annotations
def __a ( A , A ):
'''simple docstring'''
if partitions <= 0:
raise ValueError("partitions must be a positive number!" )
if partitions > number_of_bytes:
raise ValueError("partitions ca... | 668 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
lowerCAmelCase_: ... | 720 | """simple docstring"""
from collections import deque
class a__ :
def __init__( self, _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase ):
'''simple docstring'''
lowercase__ = process_name # process name
lowercase__ = arrival_time # arriva... | 668 | 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 ImageProcessingSavingTestMix... | 721 | """simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import ... | 668 | 0 |
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
lowerCAmelCase_: List[str] = "src/transformers"
lowerCAmelCase_: Any = ... | 700 | """simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nes... | 668 | 0 |
"""simple docstring"""
def __a ( A ):
'''simple docstring'''
stooge(A , 0 , len(A ) - 1 )
return arr
def __a ( A , A , A ):
'''simple docstring'''
if i >= h:
return
# If first element is small... | 701 | """simple docstring"""
import itertools
import math
def __a ( A ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multip... | 668 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_: List[str] = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],
}
tr... | 702 | """simple docstring"""
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class a__ ( _a ):
def __init__( self, _UpperCAmelCase, ... | 668 | 0 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def __a ( ):
'''simple docstring'''
lowercase__ = ArgumentParser(
description=(
... | 703 | """simple docstring"""
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from... | 668 | 0 |
"""simple docstring"""
import numpy as np
import datasets
lowerCAmelCase_: Any = "\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean dis... | 704 | """simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class a__ ( _a ):
snake_case_ = (IPNDMScheduler,)
snake_case_ = (("num_inference_steps", 50),)
def snake_case__ ( self, **... | 668 | 0 |
"""simple docstring"""
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 n... | 705 | """simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_t... | 668 | 0 |
"""simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nes... | 706 | """simple docstring"""
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
f... | 668 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class a__ ( metaclass=_a ):
snake_case_ = ["torch", "scipy"]
def __init__( self, *_UpperCAmelCase, **_UpperCAmelCase ):
'''simple docstring'''
requires_backends(self, ["torch", "... | 707 | """simple docstring"""
from typing import Any
import numpy as np
def __a ( A ):
'''simple docstring'''
return np.array_equal(A , matrix.conjugate().T )
def __a ( A , A ):
'''simple docstring'''
lowercase__ = v.co... | 668 | 0 |
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 BatchFeature
from ...utils import T... | 708 | """simple docstring"""
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_mod... | 668 | 0 |
"""simple docstring"""
import itertools
import math
def __a ( A ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multip... | 709 | """simple docstring"""
lowerCAmelCase_: Any = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def __a ( A ):
'''simple docstring'''
if not isinstance(A , A ):
lowercase__ = f'''a bytes-like object is required, not \'{... | 668 | 0 |
"""simple docstring"""
def __a ( A ):
'''simple docstring'''
lowercase__ = len(A )
for i in range(1 , A ):
lowercase__ = collection[i]
lowercase__ = 0
lowercase__ = i - 1
while low <= ... | 710 | """simple docstring"""
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __a ( A , A , A = "x" , A = 10**-10 , A = 1 , ):
'''simple docstring'''
lowercase__ = symbols(A )
lowercase__ = ... | 668 | 0 |
"""simple docstring"""
def __a ( A , A ):
'''simple docstring'''
lowercase__ = len(A ) + 1
lowercase__ = len(A ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
# length i of input_string matches with prefix st... | 711 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_: Union[str, Any] = {
"configuration_distilbert": [
... | 668 | 0 |
"""simple docstring"""
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
lowerCAmelCase_: List[Any] = Mapping[str, np.ndarray]
lowerCAmelCase_: Tuple = Mapping[str, ... | 712 | """simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowerCA... | 668 | 0 |
"""simple docstring"""
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteSchedule... | 713 | """simple docstring"""
from __future__ import annotations
import math
def __a ( A ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even ... | 668 | 0 |
"""simple docstring"""
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf imp... | 714 | """simple docstring"""
import os
import sys
lowerCAmelCase_: Any = os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSeq... | 668 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_t... | 715 | """simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import Flax... | 668 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_pro... | 716 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_: str = logging.get_logger(__name__)
lowerCAmelCase_: ... | 668 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def __a ( A , A , A ):
'''simple docstring'''
... | 717 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_: List[Any] = logging.get_logger(__name__)
lowerCAmelCase_: int = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json"... | 668 | 0 |
"""simple docstring"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
lowerCAmelCase_: Optional[Any] = numpy.array([0, 0])
lowerCAmelCase_: Optional[Any] = numpy.array([0.5, 0.8_660_254])
lowerCAmelCase_: Lis... | 718 | """simple docstring"""
lowerCAmelCase_: Union[str, Any] = [
9_9_9,
8_0_0,
7_9_9,
6_0_0,
5_9_9,
5_0_0,
4_0_0,
3_9_9,
3_7_7,
3_5_5,
3_3_3,
3_1_1,
2_8_8,
2_6_6,
2_4_4,
2_2_2,
2_0_0,
1_9_9,
1_7_7,
1_5_5,
1_3_3,
1_1_1,
... | 668 | 0 |
"""simple docstring"""
def __a ( A ):
lowercase__ = [0] * len(A )
for i in range(1 , len(A ) ):
# use last results for better performance - dynamic programming
lowercase__ = prefix_result[i - 1]
while j > 0 and input_string... | 719 | """simple docstring"""
from __future__ import annotations
def __a ( A , A ):
'''simple docstring'''
if partitions <= 0:
raise ValueError("partitions must be a positive number!" )
if partitions > number_of_bytes:
raise ValueError("partitions ca... | 668 | 0 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class a__ ( _a ):
snake_case_ = ... | 720 | """simple docstring"""
from collections import deque
class a__ :
def __init__( self, _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase ):
'''simple docstring'''
lowercase__ = process_name # process name
lowercase__ = arrival_time # arriva... | 668 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_: Union[str, Any] = {"configuration_mra": ["MRA_PRETRAINED_CONFIG_ARCHIVE_MA... | 721 | """simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import ... | 668 | 0 |
def __a ( A ):
'''simple docstring'''
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 700 | """simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nes... | 668 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_: int = logging.get_logger(__name__)
lowerCAmelCase_: Optional[Any] = {
"google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
"goo... | 701 | """simple docstring"""
import itertools
import math
def __a ( A ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multip... | 668 | 0 |
"""simple docstring"""
def __a ( A , A ):
'''simple docstring'''
while b:
lowercase__ , lowercase__ = b, a % b
return a
def __a ( A , A ):
'''simple docstring'''
return a if b == 0 else euclidean_gcd_recur... | 702 | """simple docstring"""
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class a__ ( _a ):
def __init__( self, _UpperCAmelCase, ... | 668 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigT... | 703 | """simple docstring"""
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from... | 668 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_: List[Any] = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCT... | 704 | """simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class a__ ( _a ):
snake_case_ = (IPNDMScheduler,)
snake_case_ = (("num_inference_steps", 50),)
def snake_case__ ( self, **... | 668 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
... | 705 | """simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_t... | 668 | 0 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceCla... | 706 | """simple docstring"""
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
f... | 668 | 0 |
"""simple docstring"""
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_f... | 707 | """simple docstring"""
from typing import Any
import numpy as np
def __a ( A ):
'''simple docstring'''
return np.array_equal(A , matrix.conjugate().T )
def __a ( A , A ):
'''simple docstring'''
lowercase__ = v.co... | 668 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class a__ ( _a ):
snake_case_ = 42
snake_cas... | 708 | """simple docstring"""
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_mod... | 668 | 0 |
"""simple docstring"""
def __a ( A = 1_00_00_00 ):
'''simple docstring'''
lowercase__ = limit + 1
lowercase__ = [0] * limit
for first_term in range(1 , A ):
for n in range(A , A , A ):
lowercase__ = ... | 709 | """simple docstring"""
lowerCAmelCase_: Any = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def __a ( A ):
'''simple docstring'''
if not isinstance(A , A ):
lowercase__ = f'''a bytes-like object is required, not \'{... | 668 | 0 |
"""simple docstring"""
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class a__ ( _a ):
snake_case_ = (PNDMScheduler,)
snake_case_ = (("num_inference_steps", 50),)
def snake_case__ ( self, **_U... | 710 | """simple docstring"""
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __a ( A , A , A = "x" , A = 10**-10 , A = 1 , ):
'''simple docstring'''
lowercase__ = symbols(A )
lowercase__ = ... | 668 | 0 |
"""simple docstring"""
import numpy as np
def __a ( A , A , A , A , A ):
'''simple docstring'''
lowercase__ = int(np.ceil((x_end - xa) / h ) )
lowercase__ = np.zeros((n + 1,) )
lowercase__ = ya
l... | 711 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_: Union[str, Any] = {
"configuration_distilbert": [
... | 668 | 0 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_: Optional[int] = logging.get_logger(__name__)
lowerCAmelCase_: List[Any] = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main... | 712 | """simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowerCA... | 668 | 0 |
"""simple docstring"""
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)
f... | 713 | """simple docstring"""
from __future__ import annotations
import math
def __a ( A ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even ... | 668 | 0 |
"""simple docstring"""
def __a ( A ):
'''simple docstring'''
lowercase__ = False
while is_sorted is False: # Until all the indices are traversed keep looping
lowercase__ = True
for i in range(0 , len(A ) - 1 , 2 ): # ... | 714 | """simple docstring"""
import os
import sys
lowerCAmelCase_: Any = os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSeq... | 668 | 0 |
"""simple docstring"""
from math import factorial
def __a ( A , A ):
'''simple docstring'''
if n < k or k < 0:
raise ValueError("Please enter positive integers for n and k where n >= k" )
return factorial(A ) // (factorial(A ) * factorial(n - ... | 715 | """simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import Flax... | 668 | 0 |
"""simple docstring"""
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils i... | 716 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_: str = logging.get_logger(__name__)
lowerCAmelCase_: ... | 668 | 0 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")
def __a ( A ):
'''simple docstring'''
lowercase__ = test_file.split(os.... | 717 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_: List[Any] = logging.get_logger(__name__)
lowerCAmelCase_: int = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json"... | 668 | 0 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def __a ( A , A ... | 718 | """simple docstring"""
lowerCAmelCase_: Union[str, Any] = [
9_9_9,
8_0_0,
7_9_9,
6_0_0,
5_9_9,
5_0_0,
4_0_0,
3_9_9,
3_7_7,
3_5_5,
3_3_3,
3_1_1,
2_8_8,
2_6_6,
2_4_4,
2_2_2,
2_0_0,
1_9_9,
1_7_7,
1_5_5,
1_3_3,
1_1_1,
... | 668 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCAmelCase_: int = logging.get_logger(__name__)
lowerCAmelCase_: Tuple = {
"shi... | 719 | """simple docstring"""
from __future__ import annotations
def __a ( A , A ):
'''simple docstring'''
if partitions <= 0:
raise ValueError("partitions must be a positive number!" )
if partitions > number_of_bytes:
raise ValueError("partitions ca... | 668 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_: List[str] = {
"configuration_deberta": ["DEBERTA_PRETRAINED_CONFIG_ARCHIVE... | 720 | """simple docstring"""
from collections import deque
class a__ :
def __init__( self, _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase ):
'''simple docstring'''
lowercase__ = process_name # process name
lowercase__ = arrival_time # arriva... | 668 | 0 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
lowerCAmelCase_: str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
lowerCAmelCase_: list[int] = [ord(let... | 721 | """simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import ... | 668 | 0 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def __a ( A ):
'''simple docstring'''
return (data["da... | 700 | """simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nes... | 668 | 0 |
"""simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class a__ ( nn.Module ):
def __init__( self, _UpperCAmelCase = 16, _UpperCAmelCase = 88, _UpperCAmelCase = None, _UpperCAmelCase = 1, ... | 701 | """simple docstring"""
import itertools
import math
def __a ( A ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multip... | 668 | 0 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTe... | 702 | """simple docstring"""
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class a__ ( _a ):
def __init__( self, _UpperCAmelCase, ... | 668 | 0 |
"""simple docstring"""
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
lowerCAmelCase_: int = abspath(join(dirname(dirname... | 703 | """simple docstring"""
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from... | 668 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipe... | 704 | """simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class a__ ( _a ):
snake_case_ = (IPNDMScheduler,)
snake_case_ = (("num_inference_steps", 50),)
def snake_case__ ( self, **... | 668 | 0 |
"""simple docstring"""
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def __a ( A , A ):
... | 705 | """simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_t... | 668 | 0 |
"""simple docstring"""
from functools import lru_cache
def __a ( A ):
'''simple docstring'''
lowercase__ = 2
lowercase__ = set()
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factor... | 706 | """simple docstring"""
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
f... | 668 | 0 |
"""simple docstring"""
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowerCAmelCase_: List[Any] = parse(importlib.metadata.version("torch"))
def __a ( A , A , A ):
... | 707 | """simple docstring"""
from typing import Any
import numpy as np
def __a ( A ):
'''simple docstring'''
return np.array_equal(A , matrix.conjugate().T )
def __a ( A , A ):
'''simple docstring'''
lowercase__ = v.co... | 668 | 0 |
from __future__ import annotations
def __a ( A , A , A ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError("One and only one argument must be 0" )
if resistance < 0:
raise ValueError("Resistanc... | 708 | """simple docstring"""
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_mod... | 668 | 0 |
"""simple docstring"""
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def __a ( A , A , A ):
'''simple docstring'''
lowercase__ = OmegaConf.load(A )
lowercase__ = t... | 709 | """simple docstring"""
lowerCAmelCase_: Any = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def __a ( A ):
'''simple docstring'''
if not isinstance(A , A ):
lowercase__ = f'''a bytes-like object is required, not \'{... | 668 | 0 |
"""simple docstring"""
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
lowerCAmelCase_: Optional[int] = logging.get_logger(__name__)
lowerCAmelCase_: Union[str, Any] = R"\... | 710 | """simple docstring"""
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __a ( A , A , A = "x" , A = 10**-10 , A = 1 , ):
'''simple docstring'''
lowercase__ = symbols(A )
lowercase__ = ... | 668 | 0 |
"""simple docstring"""
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax import jit
... | 711 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_: Union[str, Any] = {
"configuration_distilbert": [
... | 668 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_: List[Any] = logging.get_logger(__name__)
lowerCAmelCase_: int = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json"... | 712 | """simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowerCA... | 668 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_availa... | 713 | """simple docstring"""
from __future__ import annotations
import math
def __a ( A ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even ... | 668 | 0 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class a__ :
def __init__( self, _UpperCAmelCase ):
'''simple docstring'''
lowercase__ = str(id_ )
lowercase__ = None
lowercase__ = None
... | 714 | """simple docstring"""
import os
import sys
lowerCAmelCase_: Any = os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSeq... | 668 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
UpperCAmelCase_: Tuple = {
"configuration_speecht5": [
"SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 715 | """simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import Flax... | 668 | 0 |
"""simple docstring"""
class a__ :
def __init__( self ):
'''simple docstring'''
lowercase__ = {}
def snake_case__ ( self ):
'''simple docstring'''
print(self.vertex )
for i in self.vertex:
print(_UpperCAmelCase, " -> "... | 716 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_: str = logging.get_logger(__name__)
lowerCAmelCase_: ... | 668 | 0 |
"""simple docstring"""
import os
import sys
lowerCAmelCase_: Any = os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSeq... | 717 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_: List[Any] = logging.get_logger(__name__)
lowerCAmelCase_: int = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json"... | 668 | 0 |
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