code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
def _A ( snake_case = 60_08_51_47_51_43 ) -> int:
try:
_lowercase : List[str] = int(snake_case )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
raise ValueError("Parameter n m... | 245 |
'''simple docstring'''
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMI... | 245 | 1 |
import os
from collections.abc import Iterator
def UpperCamelCase ( _A : str = "." )-> Iterator[str]:
"""simple docstring"""
for dir_path, dir_names, filenames in os.walk(_A ):
A__ = [d for d in dir_names if d != "scripts" and d[0] not in "._"]... | 716 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError("To use the rich extension, install rich with `pip install rich`")
| 232 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 368 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class __snake_case ( SCREAMING_SNAKE_CASE ):
def __init__( self ,a_="" ,a_="train" ):
"""simple docstring"""
assert os.path.isdir(a_ )
lowerCAmelCase__ = []
low... | 193 | 0 |
'''simple docstring'''
def A__ ( __lowerCAmelCase : Tuple ):
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
raise TypeError("""only integers accepted as input""" )
else:
lowerCamelCase__ = str(abs(__UpperCamelCase ... | 707 |
'''simple docstring'''
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 : Optional[Any] = 'src/diffusers'
# Matches is_xxx_available()
UpperCamelCase ... | 9 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx i... | 369 |
def UpperCamelCase ( snake_case__ : List[str] , snake_case__ : Any ) -> Union[str, Any]:
UpperCamelCase : int = [1]
for i in range(2 , snake_case__ ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1] * n, "k... | 40 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
__lowerCamelCase = {
"configuration_audio_spectrogram_transformer": [
"AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONF... | 536 | """simple docstring"""
import unittest
import torch
from torch import nn
from diffusers.models.activations import get_activation
class UpperCamelCase__( unittest.TestCase ):
def snake_case__ ( self ) -> str:
A__ = get_activation('swis... | 536 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
... | 29 |
'''simple docstring'''
import pickle
import numpy as np
from matplotlib import pyplot as plt
class snake_case__ :
def __init__( self : List[Any] , __a : str , __a : Dict , __a : List[Any] , __a : str , ... | 286 | 0 |
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class SC... | 707 |
"""simple docstring"""
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
... | 150 | 0 |
'''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class ... | 267 |
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = 256
# Modulus to hash a string
SCREAMING_SNAKE_CASE__ = 100_0003
def lowerCamelCase ( _snake_case : str ,_snake_case : str ):
'''simple docstring'''
lowercase__ = ... | 267 | 1 |
# Copyright 2021 The HuggingFace 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 required by a... | 584 | def UpperCAmelCase_ ( _UpperCAmelCase ):
lowerCamelCase_: List[str] = len(_UpperCAmelCase )
for i in range(1 , _UpperCAmelCase ):
lowerCamelCase_: str = collection[i]
lowerCamelCase_: str = 0
lowerCam... | 584 | 1 |
"""simple docstring"""
import requests
__lowercase : Optional[int] = "YOUR API KEY"
def SCREAMING_SNAKE_CASE ( snake_case, snake_case = giphy_api_key):
__snake_case = '''+'''.join(query.split())
__snake_case = f"https://api.giphy.com/v1/gifs/search?q={f... | 564 | """simple docstring"""
import sys
__lowercase : Union[str, Any] = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557... | 564 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.se... | 54 |
from __future__ import annotations
class lowercase :
def __init__( self , _a = 0 ) -> str:
_A : Any = key
def a__ ( self , _a , _a ) -> list[str]:
assert isinstance(_a , _a ) and isinstance(_a , _a ... | 54 | 1 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepInverseS... | 475 |
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
SCREAMING_SNAKE_CASE__ : List[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_... | 311 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {'''configuration_reformer''': ['''REFORMER_PRETRAINED_CONFIG_ARCHIVE_... | 280 |
'''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 ) -> Optional[... | 280 | 1 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import TensorType... | 9 |
'''simple docstring'''
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
_lowerCAmelCase = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
... | 161 | 0 |
from typing import Any
def _lowerCAmelCase(a : list , a : list , a : dict , a : dict , a : dict , ) -> list:
_validation(
a , a , a , a , a , )
# Creates data structures and fill initial step
_SCREAMING_SNAKE_CASE ... | 714 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class __UpperCAmelCase :
'''simple docstring'''
def __init__( self , _A ):
'''simple docstring'''
_SCREAMING_SNAKE_CASE =[]
self.adlist.append(
{'''value''': '''''', '''nex... | 165 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'CLIPSegVisionConfig',
],
'proc... | 25 | import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
A__ = logging.get_logger(__name__)
A__ = {
"""Intel/dpt-large""": """https://huggingface.co/Intel/dpt-large/resolve/main/config.json""",
# See all DPT models at h... | 166 | 0 |
from math import factorial
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : Optional[Any] , lowerCAmelCase : int , lowerCAmelCase : List[Any] ) -> int:
"""simple docstring"""
__... | 711 |
def snake_case_ (__A : int ) -> int:
assert (
isinstance(__A , __A ) and number_of_steps > 0
), f'''number_of_steps needs to be positive integer, your input {number_of_steps}'''
if number_of_steps == 1:
return 1
__lowerCAmelCase ,__lowerCAmelCase : L... | 218 | 0 |
'''simple docstring'''
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
... | 69 |
'''simple docstring'''
def UpperCamelCase ( ) -> int:
'''simple docstring'''
return 1
def UpperCamelCase ( lowercase_ : int ) -> int:
'''simple docstring'''
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def UpperCamelCase ( lowercase_ : ... | 72 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
__snake_case = version.parse(version.parse(torch.__version__).base_version) < version.parse("""1.11""")
def __lo... | 117 |
"""simple docstring"""
from __future__ import annotations
from cmath import sqrt
def __lowerCAmelCase ( lowercase : int , lowercase : int , lowercase : int ) -> tuple[complex, complex]:
"""simple docstring"""
if a == 0:
raise... | 117 | 1 |
'''simple docstring'''
from PIL import Image
def lowercase_ ( _lowercase , _lowercase ) -> Image:
'''simple docstring'''
lowerCamelCase_ : List[Any] = (259 * (level + 255)) / (255 * (259 - level))
def contrast(_lowercase ) -> int:
return int(128 + ... | 422 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : Optional[int] = logging.get_logger(__name__)
__lowercase : Optional[int] = {
'''studio-ousia/luke-base''': '''https://huggingface.co/studio-ousia/luke-base/resolve/... | 422 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : Optional[Any] =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : List[Any] ={
"""microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/ma... | 706 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmel... | 72 | 0 |
'''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 imp... | 476 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : bool , _SCREAMING_SNAKE_CASE : list[int] , _SCREAMING_SNAKE_CASE : float ):
if depth < 0:
raise Valu... | 476 | 1 |
"""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 _lowerCAmelCase ( ... | 498 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ = {'''configuration_sew''': ['''SEW_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SEWConfig''']}
try:
if not is_torch_available():
raise Optiona... | 498 | 1 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_at... | 24 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils ... | 438 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_t... | 721 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, loggi... | 5 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__... | 96 |
'''simple docstring'''
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
Albe... | 400 | 0 |
def SCREAMING_SNAKE_CASE ( lowerCAmelCase , lowerCAmelCase ):
if not (isinstance(lowerCAmelCase , lowerCAmelCase ) and isinstance(lowerCAmelCase , lowerCAmelCase )):
raise ValueError('''longest_common_substring() takes two strings for inputs'... | 711 |
def SCREAMING_SNAKE_CASE ( lowerCAmelCase ):
_UpperCamelCase = 0
for ch in input_str:
_UpperCamelCase = ord(lowerCAmelCase )
_UpperCamelCase = pow(2 , lowerCAmelCase )
# I... | 105 | 0 |
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class _SCREAMING_SNAKE_CASE ( A , unittest.TestCase ):
... | 643 |
from __future__ import annotations
def a__ ( snake_case__ : list[int] ):
if len(snake_case__ ) == 0:
return array
_UpperCAmelCase,_UpperCAmelCase : List[str] = min(snake_case__ ), max(snake_case__ )
# Compute the variables
_UpperCAmelCase : T... | 643 | 1 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
_U... | 711 | import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback... | 70 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ : List[str] = {'''configuration_glpn''': ['''GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GLPNConfig''']}
try:
if not is_v... | 33 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCamelCase__ : int = 1_0_0 ) -> int:
_SCREAMING_SNAKE_CASE : Any = set()
_SCREAMING_SNAKE_CASE : Any = 0
_SCREAMING_SNAKE_CASE : Tuple = n + 1 # maximum limit
for a in range(2, lowerCa... | 572 | 0 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, 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_... | 709 |
import random
def lowerCamelCase__ ( UpperCamelCase__ : list , UpperCamelCase__ : List[Any] ) -> tuple:
'''simple docstring'''
_snake_case , _snake_case , _snake_case = [], [], []
for element in data:
... | 541 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class snake_case__ ( __SCREAMING_SNAKE_CASE ... | 638 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
... | 638 | 1 |
from __future__ import annotations
import requests
a__ = set(
'''approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories created_utc downs
edited gilded... | 578 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCAmelCase ( __a : Tuple ,__a : Dict ,__a : ... | 578 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTMSNConfig
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 Confi... | 664 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 664 | 1 |
"""simple docstring"""
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __snake_case( unittest.TestCase ):
_A = JukeboxTokenizer
_A = {
'''artist''': '''Zac Brown Band''',
... | 168 |
"""simple docstring"""
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class __snake_case( __A ):
def __lt__( self , A_ ):
'''simp... | 168 | 1 |
'''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_identi... | 418 |
"""simple docstring"""
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def ... | 677 | 0 |
'''simple docstring'''
import math
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : str , UpperCAmelCase : int=0 ) -> List[str]: # a graph with Node 0,1,...,N-1
'''simple docstring'''
lowercase : str =n
lowercase ... | 8 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 1 |
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()... | 234 |
'''simple docstring'''
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to... | 41 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCamelCase = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():
raise OptionalDepend... | 307 |
__lowerCamelCase = '0.21.0'
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launc... | 307 | 1 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
__lowercase : Optional[int] = logging.get_logger(__name__)
def lowercase ( __A : Union[str, Any] ) -> Tup... | 36 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError('''To use the rich extension, install rich with `pip install rich`''')
| 36 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set... | 681 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 681 | 1 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
_lowerCAmelCase: Optional[int] = None
try:
import msvcrt
except ImportError:
_lowerCAmelCase: List[str] = None
try:
import fcntl
except ImportError:
_lowerCAmelCase: Dict ... | 20 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def SCREAMING_SNAKE_CASE_ ( __A : float ) -> float:
if num <= 0:
raise ValueError("math domain error" )
return quad(__A , 0 , __A , args=(__A) )[0]
def SCREAM... | 418 | 0 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
... | 713 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( A : list ) -> list:
"""simple docstring"""
__snake_case : Tuple = False
while is_sorted is False: # Until all the indices are traversed keep looping
__snake_case : ... | 61 | 0 |
'''simple docstring'''
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import Gradient... | 320 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
'junnyu/roformer_chinese_smal... | 320 | 1 |
"""simple docstring"""
import os
import numpy
import onnx
def A_ ( __lowercase , __lowercase ):
UpperCamelCase_ : Dict =a.name
UpperCamelCase_ : str =b.name
UpperCamelCase_ : Optional[int] =''
UpperCamelCase_ : str =''
UpperCamelCase_... | 395 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as ... | 395 | 1 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class _lowercase :
lowercase = 42
lowercase = 42
class _lowercase :
def __init__( self : Tuple , snake_case : ... | 417 | # Copyright 2021 The HuggingFace 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 required by applicabl... | 417 | 1 |
'''simple docstring'''
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():
impor... | 617 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Tuple = logging.get_logger(__name__)
class UpperCAmelCase ( UpperCAmelCase_ ):
_A : List[Any] = """timm_backbone"""
def __init__( self ,... | 617 | 1 |
"""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 snake... | 346 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : Any = {"""configuration_xlnet""": ["""XLNET_PRETRAINED_CONFI... | 87 | 0 |
'''simple docstring'''
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class Upp... | 428 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, rand... | 428 | 1 |
from random import randint, random
def SCREAMING_SNAKE_CASE_ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ = False , UpperCamelCase__ = False , UpperCamelCase__ = 5 , ):
UpperCamelCase__ : int = [[-1] * number_of_cells] # Create a hi... | 285 |
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
deprecate... | 285 | 1 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __lowerCAmelCase ( a__ ):
@staticmethod
@abstractmethod
def lowerCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
raise NotImplementedError()
@abstractmethod
def lowerCame... | 710 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rouge, chunks, p... | 622 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
... | 477 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json''',
# See all GLPN models ... | 351 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase__ = {
'configuration_mobilevit': ['MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MobileViTConf... | 217 | """simple docstring"""
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = '▁'
lowercase__ ... | 217 | 1 |
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen
from ..table import ... | 17 |
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def __SCREAMING_SNAKE_CASE ( a__ : Optional[Any] ,a__ : Union[str, Any] ,a__ : Optiona... | 17 | 1 |
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse('''3.8'''):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
UpperCamelCase__ : ... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE_ : Tuple = 0
... | 685 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'''configuration_clipseg''': [
'''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''CLIPSegConfig''',
'''CLIPSegT... | 642 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
__UpperCAmelCase = loggi... | 642 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCamelCase : Any = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}
try:
if not... | 316 | from __future__ import annotations
import math
import random
from typing import Any
class a__ :
def __init__( self : Dict ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : list[Any] = []
SCREAMING_SNAKE_CASE_ : int = 0
... | 316 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_)
class UpperCamelCase_ ( SCREAMING_SNAKE_CASE_):
"""simple docstring"""
sna... | 682 |
"""simple docstring"""
from collections import deque
class _a :
def __init__( self : Tuple , SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
lowerCamelCase__ ... | 510 | 0 |
'''simple docstring'''
def UpperCAmelCase_ ( lowercase__ , lowercase__ ):
'''simple docstring'''
a_ =[1]
for i in range(2 , lowercase__ ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1]... | 41 |
'''simple docstring'''
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
lowercase = logging.getLogger()
... | 41 | 1 |
import math
def lowercase ( ):
UpperCAmelCase__ = input("""Enter message: """ )
UpperCAmelCase__ = int(input(F'''Enter key [2-{len(_lowerCAmelCase ) - 1}]: ''' ) )
UpperCAmelCase__ = input("""Encryption/Decryption [e/d]: """ )
if mode.lower().startswi... | 392 |
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=_snake_case ):
'''simple docstring'''
UpperCamelCase__ : Any = ["onnx"]
def __init__( self : Tuple , *lowerCamelCase_ : List[str]... | 392 | 1 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDa... | 586 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_uti... | 586 | 1 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class __snake_case :
_a : Union[str, Any]= None
def _SCREAMING_SNAKE_CASE ( self ):
'''simple docstring'''
lowercase : Union[str, Any] ... | 336 |
__A : Dict = "Alexander Joslin"
import operator as op
from .stack import Stack
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
_A = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
... | 27 | 0 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers... | 709 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def snake_case (A_ :int = 8 ):
'''simple docstring'''
a : Tuple = ascii_letters + digits + punctuation
return "".... | 118 | 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 (
HfArgumentPa... | 98 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__magic_name__ ):
"""simple docstring"""
_snake_case : Dict = ['transformers', 'torch', 'note_seq']
def __init__( self : Tuple ... | 98 | 1 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def UpperCAmelCase__ ( UpperCAmelCase__ ) -> int:
A_ = FileLock(str(tmpdir / """foo.lock""" ) )
A_ = FileLock(str(tmpdir / """foo.lock"... | 667 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaP... | 667 | 1 |
'''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 lowerCAmelCase (__A):
"... | 11 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
f... | 153 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_I... | 712 |
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx_utils import OnnxRuntimeMod... | 99 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
... | 572 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.uti... | 164 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffus... | 374 |
"""simple docstring"""
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision impor... | 374 | 1 |
"""simple docstring"""
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: ... | 473 | """simple docstring"""
import inspect
import unittest
from transformers import ViTMSNConfig
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 Co... | 473 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from ... | 703 |
'''simple docstring'''
def A_ ( snake_case , snake_case ):
SCREAMING_SNAKE_CASE:Optional[int] = word.split()
def justify(snake_case , snake_case , snake_case ) -> str:
SCREAMING_SNAKE_CASE:str = max_width - width
SCREAMING_SNAKE... | 465 | 0 |
"""simple docstring"""
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modelin... | 389 |
"""simple docstring"""
import argparse
import json
from tqdm import tqdm
def lowerCAmelCase__ ( ):
'''simple docstring'''
_a : Tuple = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"""--src_path""" , type=UpperCamelCase__... | 389 | 1 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _A ( __UpperCamelCase ):
SCREAMING_SNAKE_CASE_ : Any =(EulerDiscreteScheduler,)
SCREAMING_SNAKE_CASE_ : List[str] =10
... | 469 | import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
__magic_name__ =pd.read_csv('''sample_data.csv''', header=None)
__magic_name__ ... | 469 | 1 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowercase : int =logging.get_logger(__name__)
_lowercase : Any ={'''... | 305 | def A__ ( lowercase: str ) -> str:
if not all(char in '01' for char in bin_string ):
raise ValueError('Non-binary value was passed to the function' )
if not bin_string:
raise ValueError('Empty string was passed to the function' )
A... | 305 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__snake_case ={
"""configuration_mega""": ["""MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegaConfig""", """MegaOnnxConfig"""]... | 513 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from to... | 513 | 1 |
"""simple docstring"""
import math
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if initial_intensity < 0:
raise ValueError("""The value of intensity cannot be negati... | 58 |
UpperCAmelCase_ = 8.31_44_62 # Unit - J mol-1 K-1
def __magic_name__ ( lowercase , lowercase , lowercase ) -> float:
"""simple docstring"""
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError("""Invalid inputs. E... | 458 | 0 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, sl... | 610 | '''simple docstring'''
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
... | 610 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__snake_case : List[Any] = {
'configuration_ctrl': ['CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CTRLConfig'],
... | 571 |
"""simple docstring"""
from collections import namedtuple
__snake_case : Optional[int] = namedtuple('from_to', 'from_ to')
__snake_case : Union[str, Any] = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.001, 1_000),
'kilolitre': fr... | 571 | 1 |
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,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_ch... | 476 | from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowerCAmelCase :
_SCREAMING_SNAKE_CASE : torch.Tensor # [batch_size x 3]
_SCREAMING_SNAKE_CASE : torch.Tensor # [batch_size x 3]
_SCREAMING_SNAKE_CAS... | 476 | 1 |
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension,
ImageInput,
... | 84 |
import os
import jsonlines
import numpy as np
from tqdm import tqdm
_lowercase = 2_048
_lowercase = 4_096
_lowercase = 42
_lowercase = os.environ.pop('PROCESS_TRAIN', 'false')
_lowercase = {'null': 0, 'short': 1, 'long': 2, 'yes': 3, 'no': 4}
def __lowerC... | 306 | 0 |
'''simple docstring'''
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
__lowerCamelCase : int = get_tests_d... | 271 |
'''simple docstring'''
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWater... | 271 | 1 |
'''simple docstring'''
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __UpperCAmelCase ( SCREAMING_SNAKE_CASE__: str, SCREAMING_SNAKE_CASE__: complex, SCREAMING_SNAKE_CASE__: str = "x", SCREAMING_SNAKE_CAS... | 448 |
'''simple docstring'''
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
__UpperCamelCase : Optional[int] = Lock()
def __UpperCAmelCase ( SCREAMING_SNAKE_CASE__: Tuple, SCR... | 448 | 1 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pip... | 720 |
def _lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
A_ = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def _lowerCamelCase ... | 563 | 0 |
from __future__ import annotations
import bisect
def UpperCAmelCase__ ( lowerCamelCase_ : list[int] , lowerCamelCase_ : int , lowerCamelCase_ : int = 0 , lowerCamelCase_ : int = -1 ):
if hi < 0:
__a : Optional[... | 47 |
import re
import string
import numpy as np
import datasets
__UpperCamelCase = '\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n'
__UpperCamelCase = '\nArgs:\n predictions: List o... | 551 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def SCREAMING_SNAKE_CASE__ ( snake_case : str ) -> None:
"""simple docstring"""
a , a : Optional[int] ... | 610 | '''simple docstring'''
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration... | 610 | 1 |
def lowerCamelCase ( UpperCamelCase : int , UpperCamelCase : int ) -> float:
return base * power(UpperCamelCase , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print('Raise base to the power of exponent using recursion...')
A = ... | 544 |
"""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... | 373 | 0 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def A__ ( UpperCamelCase ):
A = args.pruning_method
A = args.threshold
A = args.model_name_or_pa... | 524 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get_u... | 524 | 1 |
'''simple docstring'''
import re
def _a (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
return [char.split() for char in re.split(r'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def _a (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCamelCase =split_input(str_ )
... | 404 |
'''simple docstring'''
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class UpperCAmelCase ( lowercase_):
"""simple docstring"""
def UpperCamelCase__ ( self : str , UpperCamelCase__ : str )... | 404 | 1 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sentencepiec... | 703 |
import string
import numpy
def a_ ( __magic_name__ , __magic_name__ ) -> int:
"""simple docstring"""
return b if a == 0 else greatest_common_divisor(b % a , __magic_name__ )
class a_ :
A__ : List[Any] = string.asc... | 84 | 0 |
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[Any] = logging.get_logger(__name__)
a : int ... | 613 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | 1 |
'''simple docstring'''
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.... | 706 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : Optional[Any] , A__ : list[int] ) -> None:
'''simple docstring'''
a__ : Union[str, Any] = len(A__ )
a__ : Tuple = [0] * len_array
... | 340 | 0 |
"""simple docstring"""
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import... | 83 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizer... | 449 | 0 |
'''simple docstring'''
UpperCamelCase__ : List[str] = {
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '... | 385 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _lowerCAmelCase ( __A ):
"""simple docstring"""
lowerCamelCase = ''''''
lowerC... | 385 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( _SCREAMING_SNAKE_CASE : list[list[int]] ):
"""simple docstring"""
__a = len(_SCREAMING_SNAKE_CASE )
# We need to create solution object to save path.
__a = [[0 for _ in range(_SCREAMING_SNAKE_CASE )... | 225 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowerCamelCase__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
... | 225 | 1 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_utils imp... | 721 |
import pytest
import datasets
# Import fixture modules as plugins
UpperCamelCase__ : Union[str, Any] = ["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]
def _UpperCAmelCase ( _SCREAMING_SNAKE_CASE : Optional[Any] , _SCREAMING_SNAKE_CASE : Dict ):
... | 620 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase : int = logging.get_logger(__name__)
lowerCAmelCase : Any = {'''voca... | 214 |
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
lowerCAmelCase : Union[str, Any] = logging.getLogger()
def _lowercase... | 214 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {
"google/realm-cc-news-pretrained-embedder": (
"https://huggingface.co/google/realm-cc-news-pret... | 604 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils import logging
logging.se... | 604 | 1 |
'''simple docstring'''
from math import factorial
__a: dict[str, int] = {str(digit): factorial(digit) for digit in range(10)}
def __UpperCamelCase ( UpperCAmelCase ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise TypeError('''Parameter number must be int''' )
if... | 152 |
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,
EulerAncestralDiscreteScheduler,
EulerDiscreteSche... | 336 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=lowercase ):
"""simple docstring"""
_lowerCamelCase = ["note_seq"]
def __init__( self , *UpperCamelCase , **UpperCa... | 445 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a_ : List[Any] = ... | 445 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.