code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCamelCase = {
"configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
"tokenization_roc_bert": ["RoCBertTok... | 351 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
_UpperCamelCase = Lock()
def UpperCamelCase_( snake_case__: Optional[Any] , snake_case__: Optional[int] , snake_case__: Tuple , snake_case__: Tuple ... | 335 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
_UpperCamelCase = {'''configuration_speech_encoder_decoder''': ['''SpeechEncoderDecoderConfig''']}
try:
if not is_torch_available():
raise OptionalDe... | 352 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowercase :
'''simple docstring'''
def __init__(self ) -> str:
"""simple docstring"""
UpperCAmelCase__ = ''
UpperCAmelCase__ = ... | 335 | 0 |
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_d... | 353 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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 ... | 335 | 0 |
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
im... | 354 |
from collections import deque
def UpperCamelCase_( snake_case__: Tuple ) -> Tuple:
UpperCAmelCase__ = len(snake_case__ )
UpperCAmelCase__ = deque()
UpperCAmelCase__ = [False for _ in range(snake_case__ )]
UpperCAmelCase__ = [-1... | 335 | 0 |
_UpperCamelCase = 9.8_0_6_6_5
def UpperCamelCase_( snake_case__: Any , snake_case__: Union[str, Any] , snake_case__: Optional[int] = g ) -> List[str]:
if fluid_density <= 0:
raise ValueError('Impossible fluid density' )
if volume < 0:
raise ValueError(... | 355 |
from ...configuration_utils import PretrainedConfig
_UpperCamelCase = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-finetuned-wtq''': (
'''https://huggingface.c... | 335 | 0 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
... | 356 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCamelCase = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBertConfig''',
... | 335 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():... | 357 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisionConfig,
... | 335 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.set_verbo... | 358 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def UpperCamelCase_( snake_case__: Optional[int] , snake_case__: List[Any] , snake_case__: Union[str, Any] ) -> Tuple:
UpperCAmelCase__ = OmegaConf.... | 335 | 0 |
import numpy as np
import datasets
_UpperCamelCase = "\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 distance.\nIt was introduced by P... | 359 |
# flake8: noqa
# Lint as: python3
_UpperCamelCase = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disab... | 335 | 0 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def UpperCamelCase_( snake_case__: Optional[int] ) -> Any:
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch_dump_output , args.confi... | 360 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/confi... | 335 | 0 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase ( lowerCamelCase__ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE : str = (EulerDiscreteScheduler,)
... | 361 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_spe... | 335 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase = {
'''configuration_funnel''': ['''FUNNEL_PRETRAINED... | 362 |
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 TFModelTesterMixin, ... | 335 | 0 |
def UpperCamelCase_( snake_case__: str = 10_00 ) -> int:
UpperCAmelCase__ = -1
UpperCAmelCase__ = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
UpperCAmelCase__ = (n * n - 2 * a * n) //... | 363 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch... | 335 | 0 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_... | 364 |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class lowercase :
'''simple docstring'''
__SCREAMING_SNAKE_CASE = field(
default="""codeparrot/codeparrot""" , metadata={"""help""": """Model name or path of model to be trained."""} )... | 335 | 0 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
_UpperCamelCase = 0B101_100_111_110_110_010_010_000_011_110_111_011_000_110_... | 365 |
import unittest
import numpy as np
from transformers import RobertaConfig, 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
if is_flax_available():
from transfo... | 335 | 0 |
def UpperCamelCase_( snake_case__: int = 1_00 ) -> int:
"""simple docstring"""
UpperCAmelCase__ = set()
UpperCAmelCase__ = 0
UpperCAmelCase__ = n + 1 # maximum limit
for a in range(2 , lowerCAmelCase__ ):
for b ... | 366 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
_UpperCamelCase = logging.get_logger(__name__)
class lowercase ( _UpperCamelCase ):
'''simple docstring'''
def __init__(self , *__a , **__a ) -> None:
... | 335 | 0 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
i... | 367 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
raise O... | 335 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class lowercase ( UpperCamelCase__ ):
'''simple docstring'''
def __init__(self , __a , __a , __a ) -> Optional[int]:
"""simple docstring"... | 368 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 335 | 0 |
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
_UpperCamelCase = {
# 1536-bit
5: {
'''prime''': int(
... | 369 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
Compu... | 335 | 0 |
def UpperCamelCase_( snake_case__: Optional[int] , snake_case__: Tuple ) -> int:
return int((input_a, input_a).count(0 ) != 0 )
def UpperCamelCase_( ) -> None:
assert nand_gate(0 , 0 ) == 1
assert nand_gate(0 , 1 ) == 1
assert nand_gate(1 ... | 370 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowercase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
@register_to_config
def __init__(self , *,
__a = 4 , __a ... | 335 | 0 |
_UpperCamelCase = 0 # The first color of the flag.
_UpperCamelCase = 1 # The second color of the flag.
_UpperCamelCase = 2 # The third color of the flag.
_UpperCamelCase = (red, white, blue)
def UpperCamelCase_( snake_case__: list ) -> List[Any]... | 371 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase ( _UpperCamelCase , unittest.TestC... | 335 | 0 |
import os
from pathlib import Path
def UpperCamelCase_( ) -> List[Any]:
from torch.utils.cpp_extension import load
UpperCAmelCase__ = Path(snake_case__ ).resolve().parent.parent.parent / 'kernels' / 'deformable_detr'
UpperCAmelCase__ = [
root / filename
... | 350 |
class lowercase : # Public class to implement a graph
'''simple docstring'''
def __init__(self , __a , __a , __a ) -> None:
"""simple docstring"""
UpperCAmelCase__ = row
UpperCAmelCase__ = col
UpperCAmelCase__ = graph
... | 335 | 0 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common imp... | 351 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
_UpperCamelCase = Lock()
def UpperCamelCase_( snake_case__: Optional[Any] , snake_case__: Optional[int] , snake_case__: Tuple , snake_case__: Tuple ... | 335 | 0 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowercase ( _UpperCamelCase ):
'''simple docstring'''
@require_torch
def UpperCamelCase__ (self ... | 352 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowercase :
'''simple docstring'''
def __init__(self ) -> str:
"""simple docstring"""
UpperCAmelCase__ = ''
UpperCAmelCase__ = ... | 335 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def UpperCamelCase_( snake_case__: str ) -> str:
UpperCAmelCase__ = SwinConfig(image_size=1_92 )
if "base" in mod... | 353 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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 ... | 335 | 0 |
from __future__ import annotations
import math
class lowercase :
'''simple docstring'''
def __init__(self , __a ) -> None:
"""simple docstring"""
UpperCAmelCase__ = size
# approximate the overall size of segment tree with given value
... | 354 |
from collections import deque
def UpperCamelCase_( snake_case__: Tuple ) -> Tuple:
UpperCAmelCase__ = len(snake_case__ )
UpperCAmelCase__ = deque()
UpperCAmelCase__ = [False for _ in range(snake_case__ )]
UpperCAmelCase__ = [-1... | 335 | 0 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowercase ( _UpperCamelCase ):
'''simple docstring'''
def __init__(self , __a , __a = None , __a = None , __a... | 355 |
from ...configuration_utils import PretrainedConfig
_UpperCamelCase = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-finetuned-wtq''': (
'''https://huggingface.c... | 335 | 0 |
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
_UpperCamelCase = '''src/diffusers'''
# Matches is_xxx_available()
_UpperCamelCase = re.compile(R'''is\... | 356 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCamelCase = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBertConfig''',
... | 335 | 0 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs... | 357 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisionConfig,
... | 335 | 0 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
_UpperCamelCase = logging.getLogger(__name__)
class lowercase :
'''simple docstring'''
def __ini... | 358 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def UpperCamelCase_( snake_case__: Optional[int] , snake_case__: List[Any] , snake_case__: Union[str, Any] ) -> Tuple:
UpperCAmelCase__ = OmegaConf.... | 335 | 0 |
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils imp... | 359 |
# flake8: noqa
# Lint as: python3
_UpperCamelCase = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disab... | 335 | 0 |
from ...configuration_utils import PretrainedConfig
_UpperCamelCase = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-finetuned-wtq''': (
'''https://huggingface.c... | 360 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/confi... | 335 | 0 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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 ... | 361 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_spe... | 335 | 0 |
"""simple docstring"""
def UpperCamelCase_( snake_case__: int , snake_case__: int ) -> str:
if number < 0 or shift_amount < 0:
raise ValueError('both inputs must be positive integers' )
UpperCAmelCase__ = str(bin(snake_case__ ) )
binary_numbe... | 362 |
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 TFModelTesterMixin, ... | 335 | 0 |
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_UpperCamelCase = '''\
@inproceedings{popovic-2015-chrf,
title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",
author = "Popovi{\'c}, Maja",
booktitle = "Proceeding... | 363 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch... | 335 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
'''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolv... | 364 |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class lowercase :
'''simple docstring'''
__SCREAMING_SNAKE_CASE = field(
default="""codeparrot/codeparrot""" , metadata={"""help""": """Model name or path of model to be trained."""} )... | 335 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''facebook/xmod-base''': '''http... | 365 |
import unittest
import numpy as np
from transformers import RobertaConfig, 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
if is_flax_available():
from transfo... | 335 | 0 |
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('''hub/hopper-medium-v2/unet/hor32''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/unet/hor128''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/value_function''', exist_ok=True)
def UpperCamelCase_( ... | 366 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
_UpperCamelCase = logging.get_logger(__name__)
class lowercase ( _UpperCamelCase ):
'''simple docstring'''
def __init__(self , *__a , **__a ) -> None:
... | 335 | 0 |
def UpperCamelCase_( snake_case__: int , snake_case__: int ) -> int:
while b:
UpperCAmelCase__ , UpperCAmelCase__ = b, a % b
return a
def UpperCamelCase_( snake_case__: int , snake_case__: int ) -> int:
return a if b == 0 else euclidean_gcd_... | 367 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
raise O... | 335 | 0 |
import inspect
import unittest
from transformers import BitConfig
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_backbone_common import BackboneTesterMixin
from ..... | 368 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 335 | 0 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def UpperCamelCase_( snake_case__: List[str] , snake_case__: List[Any]=7 ) -> Union[str, Any]:
UpperCAmelCase__ = None
if token is not None:
UpperCAmel... | 369 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
Compu... | 335 | 0 |
class lowercase :
'''simple docstring'''
def __init__(self , __a ) -> Tuple:
"""simple docstring"""
UpperCAmelCase__ = val
UpperCAmelCase__ = None
UpperCAmelCase__ = None
def UpperCamelCase__ (self , __... | 370 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowercase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
@register_to_config
def __init__(self , *,
__a = 4 , __a ... | 335 | 0 |
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 ConfigTester
from ..... | 371 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase ( _UpperCamelCase , unittest.TestC... | 335 | 0 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class lowercase ( _UpperCamelCase , _UpperCam... | 350 |
class lowercase : # Public class to implement a graph
'''simple docstring'''
def __init__(self , __a , __a , __a ) -> None:
"""simple docstring"""
UpperCAmelCase__ = row
UpperCAmelCase__ = col
UpperCAmelCase__ = graph
... | 335 | 0 |
import requests
from bsa import BeautifulSoup
def UpperCamelCase_( snake_case__: str = "AAPL" ) -> str:
UpperCAmelCase__ = f"https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"
UpperCAmelCase__ = BeautifulSoup(requests.get(snake_case__ ).text , 'html.pa... | 351 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
_UpperCamelCase = Lock()
def UpperCamelCase_( snake_case__: Optional[Any] , snake_case__: Optional[int] , snake_case__: Tuple , snake_case__: Tuple ... | 335 | 0 |
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''kakaobrain/align-base''':... | 352 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowercase :
'''simple docstring'''
def __init__(self ) -> str:
"""simple docstring"""
UpperCAmelCase__ = ''
UpperCAmelCase__ = ... | 335 | 0 |
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes
from unilm.wav... | 353 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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 ... | 335 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requ... | 354 |
from collections import deque
def UpperCamelCase_( snake_case__: Tuple ) -> Tuple:
UpperCAmelCase__ = len(snake_case__ )
UpperCAmelCase__ = deque()
UpperCAmelCase__ = [False for _ in range(snake_case__ )]
UpperCAmelCase__ = [-1... | 335 | 0 |
# flake8: noqa
# Lint as: python3
_UpperCamelCase = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disab... | 355 |
from ...configuration_utils import PretrainedConfig
_UpperCamelCase = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-finetuned-wtq''': (
'''https://huggingface.c... | 335 | 0 |
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jn... | 356 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCamelCase = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBertConfig''',
... | 335 | 0 |
from math import sqrt
def UpperCamelCase_( snake_case__: int ) -> bool:
assert isinstance(snake_case__ , snake_case__ ) and (
number >= 0
), "'number' must been an int and positive"
UpperCAmelCase__ = True
# 0 and 1 are none primes.
if number <= 1:
Up... | 357 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisionConfig,
... | 335 | 0 |
from math import pi
def UpperCamelCase_( snake_case__: int , snake_case__: int ) -> float:
return 2 * pi * radius * (angle / 3_60)
if __name__ == "__main__":
print(arc_length(90, 10))
| 358 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def UpperCamelCase_( snake_case__: Optional[int] , snake_case__: List[Any] , snake_case__: Union[str, Any] ) -> Tuple:
UpperCAmelCase__ = OmegaConf.... | 335 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
raise O... | 359 |
# flake8: noqa
# Lint as: python3
_UpperCamelCase = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disab... | 335 | 0 |
import os
def UpperCamelCase_( snake_case__: str = "matrix.txt" ) -> int:
with open(os.path.join(os.path.dirname(snake_case__ ) , snake_case__ ) ) as in_file:
UpperCAmelCase__ = in_file.read()
UpperCAmelCase__ = [[int(snake_case__ ) fo... | 360 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/confi... | 335 | 0 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowercase :
'''simple docstring'''
def __init__(self ) -> str:
"""simple docstring"""
UpperCAmelCase__ = ''
UpperCAmelCase__ = ... | 361 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_spe... | 335 | 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.pipelines.conver... | 362 |
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 TFModelTesterMixin, ... | 335 | 0 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''google/umt5-small''': '''https://huggingface.co/goog... | 363 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch... | 335 | 0 |
import unittest
import numpy as np
from transformers import RobertaConfig, 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
if is_flax_available():
from trans... | 364 |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class lowercase :
'''simple docstring'''
__SCREAMING_SNAKE_CASE = field(
default="""codeparrot/codeparrot""" , metadata={"""help""": """Model name or path of model to be trained."""} )... | 335 | 0 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def UpperCamelCase_( ) -> Tuple:
UpperCAmelCase__ = HfArgumentParser(snake_case__ )
UpperCAmelCase__ = parser.parse_args_into_dataclasses()[0]
UpperCAmelCase__ = ... | 365 |
import unittest
import numpy as np
from transformers import RobertaConfig, 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
if is_flax_available():
from transfo... | 335 | 0 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
_UpperCamelCase = False
class lowercase ( unittest.TestCase ):
'''simple docstring'... | 366 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
_UpperCamelCase = logging.get_logger(__name__)
class lowercase ( _UpperCamelCase ):
'''simple docstring'''
def __init__(self , *__a , **__a ) -> None:
... | 335 | 0 |
_UpperCamelCase = tuple[float, float, float]
_UpperCamelCase = tuple[float, float, float]
def UpperCamelCase_( snake_case__: Pointad , snake_case__: Pointad ) -> Vectorad:
UpperCAmelCase__ = end_pointa[0] - end_pointa[0]
UpperCAmelCase__ = ... | 367 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
raise O... | 335 | 0 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
_UpperCamelCase = logging.get_logger(__name__)
class lowercase ( _UpperCamelCase ):
'''simple docstring'''
def __init__(self , *__a , **__a ) -> None:
... | 368 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 335 | 0 |
import heapq
def UpperCamelCase_( snake_case__: dict ) -> set[int]:
UpperCAmelCase__ = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like a Priority Queue
# heapq works with a min priority... | 369 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
Compu... | 335 | 0 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def UpperCamelCase_( snake_case__: int ) -> List[str]: # picklable for mu... | 370 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowercase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
@register_to_config
def __init__(self , *,
__a = 4 , __a ... | 335 | 0 |
def UpperCamelCase_( snake_case__: str , snake_case__: str ) -> int:
if len(snake_case__ ) != len(snake_case__ ):
raise ValueError('String lengths must match!' )
UpperCAmelCase__ = 0
for chara, chara in zip(snake_case__ , snak... | 371 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase ( _UpperCamelCase , unittest.TestC... | 335 | 0 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''huggingface/informer-tourism-monthly''': (
'''https://huggingface.co/hugging... | 350 |
class lowercase : # Public class to implement a graph
'''simple docstring'''
def __init__(self , __a , __a , __a ) -> None:
"""simple docstring"""
UpperCAmelCase__ = row
UpperCAmelCase__ = col
UpperCAmelCase__ = graph
... | 335 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requ... | 351 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
_UpperCamelCase = Lock()
def UpperCamelCase_( snake_case__: Optional[Any] , snake_case__: Optional[int] , snake_case__: Tuple , snake_case__: Tuple ... | 335 | 0 |
def UpperCamelCase_( snake_case__: list ) -> float:
UpperCAmelCase__ = 0
while len(snake_case__ ) > 1:
UpperCAmelCase__ = 0
# Consider two files with minimum cost to be merged
for _ in range(2 ):
UpperCAmelCase__ = files.index(min(... | 352 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowercase :
'''simple docstring'''
def __init__(self ) -> str:
"""simple docstring"""
UpperCAmelCase__ = ''
UpperCAmelCase__ = ... | 335 | 0 |
import torch
from torch import nn
class lowercase ( nn.Module ):
'''simple docstring'''
def __init__(self , __a , __a , __a , __a , __a=1 , __a=False ) -> Optional[Any]:
"""simple docstring"""
super().__init__()
UpperCAmelCase__ = n_toke... | 353 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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 ... | 335 | 0 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def UpperCamelCase_( snake_case__: Optional[int] ) -> Dict:
if not is_accelerate_available():
return method
UpperCAmelCase__ = version.par... | 354 |
from collections import deque
def UpperCamelCase_( snake_case__: Tuple ) -> Tuple:
UpperCAmelCase__ = len(snake_case__ )
UpperCAmelCase__ = deque()
UpperCAmelCase__ = [False for _ in range(snake_case__ )]
UpperCAmelCase__ = [-1... | 335 | 0 |
def UpperCamelCase_( snake_case__: int = 2_00 ) -> int:
UpperCAmelCase__ = [1, 2, 5, 10, 20, 50, 1_00, 2_00]
UpperCAmelCase__ = [0] * (pence + 1)
UpperCAmelCase__ = 1 # base case: 1 way to make 0 pence
for coin in coins:
for i in range(snake_case... | 355 |
from ...configuration_utils import PretrainedConfig
_UpperCamelCase = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-finetuned-wtq''': (
'''https://huggingface.c... | 335 | 0 |
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_compute_m... | 356 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCamelCase = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBertConfig''',
... | 335 | 0 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_UpperCamelCase = get_tests_dir('''fixtures/test_sentencepiece_with_bytef... | 357 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisionConfig,
... | 335 | 0 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentParser, Tr... | 358 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def UpperCamelCase_( snake_case__: Optional[int] , snake_case__: List[Any] , snake_case__: Union[str, Any] ) -> Tuple:
UpperCAmelCase__ = OmegaConf.... | 335 | 0 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCamelCase_( snake_case__: Union[str, Any] , snake_case__: int , snake_case__: Dict )... | 359 |
# flake8: noqa
# Lint as: python3
_UpperCamelCase = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disab... | 335 | 0 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = [
['''attention''', '''attn'''],
... | 360 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/confi... | 335 | 0 |
def UpperCamelCase_( snake_case__: list[list[int]] , snake_case__: int , snake_case__: int , snake_case__: set ) -> int:
UpperCAmelCase__ , UpperCAmelCase__ = len(snake_case__ ), len(grid[0] )
if (
min(snake_case__ , snake_case__ ) < 0
... | 361 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_spe... | 335 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def UpperCamelCase_( snake_case__: str , snake_case__: str , snake_case__: str , snake_case__: Path , ... | 362 |
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 TFModelTesterMixin, ... | 335 | 0 |
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
_UpperCamelCase = 3
def UpperCamelCase_( snake_case__: int ) -> int:
print('Generating primitive root of p' )
while True:
UpperCAmelCase__ = r... | 363 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch... | 335 | 0 |
from __future__ import annotations
from fractions import Fraction
def UpperCamelCase_( snake_case__: int , snake_case__: int ) -> bool:
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def UpperCamelCase_( snake_case__: int ... | 364 |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class lowercase :
'''simple docstring'''
__SCREAMING_SNAKE_CASE = field(
default="""codeparrot/codeparrot""" , metadata={"""help""": """Model name or path of model to be trained."""} )... | 335 | 0 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import... | 365 |
import unittest
import numpy as np
from transformers import RobertaConfig, 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
if is_flax_available():
from transfo... | 335 | 0 |
def UpperCamelCase_( snake_case__: int ) -> int:
"""simple docstring"""
UpperCAmelCase__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def UpperCamelCase_( snake_case__: int ) -> int:
"""simple docst... | 366 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
_UpperCamelCase = logging.get_logger(__name__)
class lowercase ( _UpperCamelCase ):
'''simple docstring'''
def __init__(self , *__a , **__a ) -> None:
... | 335 | 0 |
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_available():
im... | 367 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
raise O... | 335 | 0 |
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def UpperCamelCase_( snake_case__: Optional[int] ) -> Dict:
for param in module.parameters():
UpperCAmelCase__ = False
def UpperCamelCase_( ) -> List[str]:
UpperCAmelCase__ =... | 368 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 335 | 0 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.... | 369 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
Compu... | 335 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
_UpperCamelCase = {'''configuration_dpt''': ['''DPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPTConfig''']}
try:
... | 370 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowercase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
@register_to_config
def __init__(self , *,
__a = 4 , __a ... | 335 | 0 |
from collections import deque
def UpperCamelCase_( snake_case__: Tuple ) -> Tuple:
UpperCAmelCase__ = len(snake_case__ )
UpperCAmelCase__ = deque()
UpperCAmelCase__ = [False for _ in range(snake_case__ )]
UpperCAmelCase__ ... | 371 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase ( _UpperCamelCase , unittest.TestC... | 335 | 0 |
import numpy as np
import datasets
_UpperCamelCase = '''
Compute the Mahalanobis Distance
Mahalonobis distance is the distance between a point and a distribution.
And not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.
It was introduced by Prof... | 350 |
class lowercase : # Public class to implement a graph
'''simple docstring'''
def __init__(self , __a , __a , __a ) -> None:
"""simple docstring"""
UpperCAmelCase__ = row
UpperCAmelCase__ = col
UpperCAmelCase__ = graph
... | 335 | 0 |
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def UpperCamelCase_( snake_case__: List[Any] , snake_case__: List[str] , snake_case__: Dict , snake_case__: Optional[int] ) -> Optional[int]:
UpperCAmelCase__ = {
'en': 'Machine learni... | 351 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
_UpperCamelCase = Lock()
def UpperCamelCase_( snake_case__: Optional[Any] , snake_case__: Optional[int] , snake_case__: Tuple , snake_case__: Tuple ... | 335 | 0 |
from __future__ import annotations
import queue
class lowercase :
'''simple docstring'''
def __init__(self , __a ) -> int:
"""simple docstring"""
UpperCAmelCase__ = data
UpperCAmelCase__ = None
UpperCAmelCase__ = ... | 352 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowercase :
'''simple docstring'''
def __init__(self ) -> str:
"""simple docstring"""
UpperCAmelCase__ = ''
UpperCAmelCase__ = ... | 335 | 0 |
import torch
from diffusers import DiffusionPipeline
class lowercase ( _UpperCamelCase ):
'''simple docstring'''
def __init__(self , __a , __a ) -> List[Any]:
"""simple docstring"""
super().__init__()
self.register_modules(unet=__a , scheduler=__a... | 353 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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 ... | 335 | 0 |
from __future__ import annotations
_UpperCamelCase = []
def UpperCamelCase_( snake_case__: list[list[int]] , snake_case__: int , snake_case__: int ) -> bool:
for i in range(len(snake_case__ ) ):
if board[row][i] == 1:
return False
for i in range(len(... | 354 |
from collections import deque
def UpperCamelCase_( snake_case__: Tuple ) -> Tuple:
UpperCAmelCase__ = len(snake_case__ )
UpperCAmelCase__ = deque()
UpperCAmelCase__ = [False for _ in range(snake_case__ )]
UpperCAmelCase__ = [-1... | 335 | 0 |
from __future__ import annotations
import pandas as pd
def UpperCamelCase_( snake_case__: list[int] , snake_case__: list[int] , snake_case__: int ) -> list[int]:
UpperCAmelCase__ = [0] * no_of_processes
UpperCAmelCase__ = [0] * no_of_processes
# Copy the... | 355 |
from ...configuration_utils import PretrainedConfig
_UpperCamelCase = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-finetuned-wtq''': (
'''https://huggingface.c... | 335 | 0 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def UpperCamelCase_( snake_case__: str , snake_case__: str , **snake_case__: Tuple ) -> Optional[Any]:
UpperCAmelCase__ = AutoConfig.from_pretrained(snake_case__ , **snake_case_... | 356 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCamelCase = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBertConfig''',
... | 335 | 0 |
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
_UpperCamelCase = TypeVar('''T''')
class lowercase ( Generic[T] ):
'''simple d... | 357 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisionConfig,
... | 335 | 0 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowercase ( _UpperCamelCase , unittest.TestCas... | 358 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def UpperCamelCase_( snake_case__: Optional[int] , snake_case__: List[Any] , snake_case__: Union[str, Any] ) -> Tuple:
UpperCAmelCase__ = OmegaConf.... | 335 | 0 |
import os
import numpy
import onnx
def UpperCamelCase_( snake_case__: str , snake_case__: Dict ) -> str:
UpperCAmelCase__ = a.name
UpperCAmelCase__ = b.name
UpperCAmelCase__ = ''
UpperCAmelCase__ = ''
UpperCAmelCase__ ... | 359 |
# flake8: noqa
# Lint as: python3
_UpperCamelCase = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disab... | 335 | 0 |
import os
_UpperCamelCase = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def UpperCamelCase_( snake_case__: str ) -> int:
UpperCAmelCase__ = 0
UpperCAmelCase__ = 0
while index < len(snake_case__ ... | 360 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/confi... | 335 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from diffusers.utils... | 361 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_spe... | 335 | 0 |
"""simple docstring"""
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
_UpperCamelCase = parse(importlib.metadata.version('''torch'''))
def UpperCamelCase_( snake_case__: Union[s... | 362 |
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 TFModelTesterMixin, ... | 335 | 0 |
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