code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import unittest
import numpy as np
from transformers import AlbertConfig, 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... | 66 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowercase : Union[str, Any] = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupVi... | 66 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : Union[str, Any] = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
"""google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config... | 66 |
"""simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 66 | 1 |
"""simple docstring"""
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
__lowercase : Union[str, Any] = logging.get_logger(__name__)
def lowerCamelCase_ ( _lowerCamelCase : Di... | 66 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowercase : Optional[Any] = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-At... | 66 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowercase : List[Any] = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""tokenization_ct... | 66 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase ( tf.keras.layers.Layer ):
"""simpl... | 66 | 1 |
"""simple docstring"""
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaTo... | 66 |
"""simple docstring"""
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
__lowercase :Tuple = JukeboxTokenizer
__lowercase :Optional... | 66 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : list[int] , _lowerCamelCase : list[int] ):
# Check if the input is valid
if not len(_lowerCamelCase ) == len(_lowerCamelCase ) == 3:
raise ValueError('''Please enter a valid equation.'''... | 66 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_i... | 66 | 1 |
"""simple docstring"""
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 ... | 66 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
__lowercase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , *UpperCamel... | 66 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__lowercase : int = logging.get_logger(__name__)
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , *UpperCamelCase__... | 66 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowercase : Tuple = {
"""configuration_squeezebert""": [
"""SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Squ... | 66 | 1 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__lowercase : Any = logging.get_logger(__name__)
__lowercase : int = {
"""t5-small""": """https://hugging... | 66 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_availabl... | 66 | 1 |
"""simple docstring"""
from math import isqrt
def lowerCamelCase_ ( _lowerCamelCase : int ):
return all(number % divisor != 0 for divisor in range(2 , isqrt(_lowerCamelCase ) + 1 ) )
def lowerCamelCase_ ( _lowerCamelCase : int = 1_0**6 ):
... | 66 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class lowerCA... | 66 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase : list , _lowerCamelCase : int , _lowerCamelCase : int , _lowerCamelCase : int ):
lowerCamelCase_ = []
lowerCamelCase_ , lowerCamelCas... | 66 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class l... | 66 | 1 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
... | 66 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , UpperCamelCase__ , UpperCamelCase__ ) -> Dict:
'''simple docstring'''
super... | 66 | 1 |
"""simple docstring"""
import random
def lowerCamelCase_ ( _lowerCamelCase : int , _lowerCamelCase : float , _lowerCamelCase : bool = False ):
lowerCamelCase_ = {i: [] for i in range(_lowerCamelCase )}
# if probability is greater or equal than 1... | 66 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowerCamelCase_ ( _lowerCamelCase : int = 8 ):
lowerCamelCase_ = ascii_letters + digits + punctuation
return "".joi... | 66 | 1 |
"""simple docstring"""
from __future__ import annotations
import requests
__lowercase : Tuple = 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 cont... | 66 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class lowerCAmelCase :
"""simple docstring"""
def __init__( self , UpperCamelCase__ ) -> str:
'''simple docstring'''
lowerCamelCase_ =... | 66 | 1 |
"""simple docstring"""
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
__lowercase : Union[str, Any] = logging.getLogger(__name__)
__lowe... | 66 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCAmelCase :
"""simple docstring"""
def __init__( self ) -> Dict:
'''simple docstring'''
lowerCamelCase_ ... | 66 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : int = 3 , _lowerCamelCase : int = 7 , _lowerCamelCase : int = 1_0_0_0_0_0_0 ):
lowerCamelCase_ = 0
lowerCamelCase_ = 1
for current_denominator in range(1 , limit ... | 66 |
"""simple docstring"""
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCamelCase_ ( _lowerCamelCase : str , _l... | 66 | 1 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class lowerCA... | 66 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase : Tuple = {
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""Jukebox... | 66 | 1 |
"""simple docstring"""
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
class ... | 66 |
"""simple docstring"""
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 ... | 66 | 1 |
"""simple docstring"""
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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosi... | 66 |
"""simple docstring"""
import argparse
import os
import re
__lowercase : Optional[int] = """src/diffusers"""
# Pattern that looks at the indentation in a line.
__lowercase : Dict = re.compile(r"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
__lowercase : in... | 66 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def lowerCamelCase_ ( _lowerCamelCase : float , _lowerCamelCase : float ):
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacit... | 66 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import ... | 66 | 1 |
"""simple docstring"""
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 (
ChannelDim... | 66 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 66 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : int = 5_0 ):
lowerCamelCase_ = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for til... | 66 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require... | 66 | 1 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowercase : Optional[Any] = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-At... | 66 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowercase : Union[str, Any] = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupVi... | 66 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowercase : int = {
"""configuration_pix2struct""": [
"""PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Pix2StructC... | 66 |
"""simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 66 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def lowerCamelCase_ ( _lowerCamelCase : int ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, ... | 66 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowercase : Optional[Any] = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-At... | 66 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, FalconConfig, 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_mod... | 66 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase ( tf.keras.layers.Layer ):
"""simpl... | 66 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.co... | 66 |
"""simple docstring"""
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
__lowercase :Tuple = JukeboxTokenizer
__lowercase :Optional... | 66 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_co... | 66 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_i... | 66 | 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 transformers import TFXL... | 66 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
__lowercase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , *UpperCamel... | 66 | 1 |
"""simple docstring"""
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
__lowercase : str = """http://ww... | 66 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowercase : Tuple = {
"""configuration_squeezebert""": [
"""SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Squ... | 66 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowerCAmelCase ( metaclass=a ):
"""simple docstring"""
__lowercase :Optional[Any] = ["torch"]
def __init__( self , *UpperCamelCase__ , **UpperCamelCase__ ) -> ... | 66 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_availabl... | 66 | 1 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
__lowercase : Dict = TypeVar("""T""")
__lowercase : Optional[int] = Union[List[T], Tuple[T, ...]]
__lowercase : str = Union[T, List[T], Dict[str, T]]
__lowercase : str = Union... | 66 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class lowerCA... | 66 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : int = 1_0_0_0_0_0_0 ):
lowerCamelCase_ = set(range(3 , _lowerCamelCase , 2 ) )
primes.add(2 )
for p in range(3 , _lowerCamelCase , 2 ):
... | 66 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class l... | 66 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def lowerCamelCase_ ( _lowerCamelCase : int ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, ... | 66 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , UpperCamelCase__ , UpperCamelCase__ ) -> Dict:
'''simple docstring'''
super... | 66 | 1 |
"""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 diffusers.utils.testing_utils imp... | 66 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowerCamelCase_ ( _lowerCamelCase : int = 8 ):
lowerCamelCase_ = ascii_letters + digits + punctuation
return "".joi... | 66 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase : int ):
lowerCamelCase_ = str(_lowerCamelCase )
return len(_lowerCamelCase ) == 9 and set(_lowerCamelCase ) == set('''123456789''' )
def lowerCamelCa... | 66 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class lowerCAmelCase :
"""simple docstring"""
def __init__( self , UpperCamelCase__ ) -> str:
'''simple docstring'''
lowerCamelCase_ =... | 66 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, 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_... | 66 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCAmelCase :
"""simple docstring"""
def __init__( self ) -> Dict:
'''simple docstring'''
lowerCamelCase_ ... | 66 | 1 |
"""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():
from .tokeni... | 66 |
"""simple docstring"""
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCamelCase_ ( _lowerCamelCase : str , _l... | 66 | 1 |
"""simple docstring"""
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
__lowercase : str ... | 66 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase : Tuple = {
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""Jukebox... | 66 | 1 |
"""simple docstring"""
class lowerCAmelCase :
"""simple docstring"""
def __init__( self , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ) -> int:
'''simple docstring'''
lowerCamelCase_ = name
lowerCamel... | 66 |
"""simple docstring"""
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 ... | 66 | 1 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(""".""")
def lowerCamelCase_ ( _lowerCamelCase : List[Any] ):
lowerCamelCase_ = test_f... | 66 |
"""simple docstring"""
import argparse
import os
import re
__lowercase : Optional[int] = """src/diffusers"""
# Pattern that looks at the indentation in a line.
__lowercase : Dict = re.compile(r"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
__lowercase : in... | 66 | 1 |
"""simple docstring"""
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class lowerCAmelCase :
"""simple docstring"""
__lowercase :int = None
def _lowerCAmelCase ( self ) -> Dict:
... | 66 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import ... | 66 | 1 |
"""simple docstring"""
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def lowerCamelCase_ ( _lowerCamelCase : str , _lowerCamelCase : str=1 ):
if n_shave_prefix_segments >= 0:
return ".".join(path.spl... | 66 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 66 | 1 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowercase : List[Any] = logging.get_logger(__name__)
__lowercase : List[Any] = {
"""CarlCochet/trajectory-transformer-halfcheetah-medium-v2""": (
"""https://huggingfac... | 66 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require... | 66 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : int , _lowerCamelCase : Optional[int] , _lowerCamelCase : int , _lowerCamelCase : Union[str, Any] ):
if height >= 1:
move_tower(height - 1 , _lowerCamelCase , _lowerCam... | 66 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowercase : Union[str, Any] = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupVi... | 66 | 1 |
"""simple docstring"""
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoencoder... | 66 |
"""simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 66 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase : Any = {
"""configuration_mobilebert""": [
"""MOBILEBERT_PRETRAINED... | 66 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowercase : Optional[Any] = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-At... | 66 | 1 |
"""simple docstring"""
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
__lowercase : List[Any] = 4
__lowercase : List[Any] = 3
class ... | 66 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase ( tf.keras.layers.Layer ):
"""simpl... | 66 | 1 |
"""simple docstring"""
import os
import unittest
from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin... | 66 |
"""simple docstring"""
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
__lowercase :Tuple = JukeboxTokenizer
__lowercase :Optional... | 66 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowerCAmelCase ( metaclass=a ):
"""simple docstring"""
__lowercase :Tuple = ["torch", "scipy"]
def __init__( self , *UpperCamelCase__ , **UpperCamelCase__ ) -> ... | 66 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_i... | 66 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : str = logging.get_logger(__name__)
__lowercase : Dict = {
"""facebook/s2t-small-librispeech-asr""": (
"""https://huggingface.co/facebook/s2t-small-librispeec... | 66 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
__lowercase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , *UpperCamel... | 66 | 1 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
... | 66 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowercase : Tuple = {
"""configuration_squeezebert""": [
"""SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Squ... | 66 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : List[str] = logging.get_logger(__name__)
__lowercase : List[str] = {
"""huggingface/informer-tourism-monthly""": (
... | 66 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_availabl... | 66 | 1 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowerCamelCase_ ( _lowerCamelCase : int = 8 ):
lowerCamelCase_ = ascii_letters + digits + punctuation
return "".joi... | 66 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class lowerCA... | 66 | 1 |
"""simple docstring"""
import argparse
import os
import re
__lowercase : Optional[int] = """src/diffusers"""
# Pattern that looks at the indentation in a line.
__lowercase : Dict = re.compile(r"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
__lowercase : in... | 66 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class l... | 66 | 1 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__lowercase : str = """"""
__lowercase : Optional[int] = """"""
__lowercase : List[Any] = """"""
__lowercase : Dict = 1 # (0 is vertical, 1 is horizo... | 66 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , UpperCamelCase__ , UpperCamelCase__ ) -> Dict:
'''simple docstring'''
super... | 66 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 66 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowerCamelCase_ ( _lowerCamelCase : int = 8 ):
lowerCamelCase_ = ascii_letters + digits + punctuation
return "".joi... | 66 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_availabl... | 66 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class lowerCAmelCase :
"""simple docstring"""
def __init__( self , UpperCamelCase__ ) -> str:
'''simple docstring'''
lowerCamelCase_ =... | 66 | 1 |
"""simple docstring"""
import unittest
from knapsack import greedy_knapsack as kp
class lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def _lowerCAmelCase ( self ) -> Optional[int]:
'''simple docstring'''
low... | 66 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCAmelCase :
"""simple docstring"""
def __init__( self ) -> Dict:
'''simple docstring'''
lowerCamelCase_ ... | 66 | 1 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def... | 700 |
"""simple docstring"""
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCamelCase_ ( _lowerCamelCase : str , _l... | 66 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase : Any , _lowerCamelCase : Optional[Any] ):
lowerCamelCase_ = []
lowerCamelCase_ = []
lowerCamelCase_ = 0
lowerCamelCase_ ... | 701 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase : Tuple = {
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""Jukebox... | 66 | 0 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__lowercase : Dict = pytest.mark.integration
@pytest.mark.parametrize('''path''' , ['''paw... | 702 |
"""simple docstring"""
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 ... | 66 | 0 |
"""simple docstring"""
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.... | 703 |
"""simple docstring"""
import argparse
import os
import re
__lowercase : Optional[int] = """src/diffusers"""
# Pattern that looks at the indentation in a line.
__lowercase : Dict = re.compile(r"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
__lowercase : in... | 66 | 0 |
"""simple docstring"""
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone impor... | 704 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import ... | 66 | 0 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowercase : Tuple = logging.get_logger(__name__)
# TODO: upload to AWS
__lowercase : List[Any] = {
"yjernite/retribert-base-uncased": (
"https://huggingface.co/yjernit... | 705 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 66 | 0 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__lowercase : Union[str, Any] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__lowercase : List[Any] = [file for file... | 706 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require... | 66 | 0 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.... | 707 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowercase : Union[str, Any] = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupVi... | 66 | 0 |
"""simple docstring"""
from __future__ import annotations
__lowercase : Any = 8.9_88E9 # units = N * m^s * C^-2
def lowerCamelCase_ ( _lowerCamelCase : float , _lowerCamelCase : float , _lowerCamelCase : float , _lowerCamelCase : float ):
lowerCa... | 708 |
"""simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 66 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase : list[int] , _lowerCamelCase : list[int] , _lowerCamelCase : int ):
lowerCamelCase_ = list(range(len(__lowerCAmelCase ) ) )
lowerCamelCas... | 709 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowercase : Optional[Any] = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-At... | 66 | 0 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : Optional[Any] ):
lowerCamelCase_ = 0
for ch in input_str:
lowerCamelCase_ = ord(lowerCamelCase__ )
lowerCamelCase_ = pow(2 , lowerCamel... | 710 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase ( tf.keras.layers.Layer ):
"""simpl... | 66 | 0 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : float ):
return 1_0 - x * x
def lowerCamelCase_ ( _lowerCamelCase : float , _lowerCamelCase : float ):
if equation(_lowerCAmelCase ) * equation(_lowerCAmelCase ) >= 0:
... | 711 |
"""simple docstring"""
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
__lowercase :Tuple = JukeboxTokenizer
__lowercase :Optional... | 66 | 0 |
"""simple docstring"""
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for tests
from os.path import join # noqa: this is just for tests
from os.path impor... | 712 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_i... | 66 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : str = logging.get_logger(__name__)
__lowercase : int = {
"""huggingface/time-series-transformer-tourism-monthly""": (
... | 713 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
__lowercase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , *UpperCamel... | 66 | 0 |
"""simple docstring"""
import os
from datetime import datetime as dt
from github import Github
__lowercase : Dict = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
... | 714 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowercase : Tuple = {
"""configuration_squeezebert""": [
"""SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Squ... | 66 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
... | 715 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_availabl... | 66 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : List[str] = logging.get_logger(__name__)
__lowercase : Union[str, Any] = {
"""microsoft/trocr-base-handwritten""": (
"""https://huggingface.co/microsof... | 716 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class lowerCA... | 66 | 0 |
def lowerCamelCase_ ( _lowerCamelCase : Dict , _lowerCamelCase : List[str] ):
while a != 0:
lowerCamelCase_ = b % a, a
return b
def lowerCamelCase_ ( _lowerCamelCase : List[str] , _lowerCamelCase : Dict ):
if gcd(_l... | 717 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class l... | 66 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowercase : int = logging.get_logger(__name__)
__lowercase : List[Any] = {
"distil... | 718 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , UpperCamelCase__ , UpperCamelCase__ ) -> Dict:
'''simple docstring'''
super... | 66 | 0 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : Any , _lowerCamelCase : List[Any] , _lowerCamelCase : Tuple ):
def update_area_of_max_square(_lowerCamelCase : Union[str, Any] , _lowerCamelCase : List[str] ) -> int:
# BASE ... | 719 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowerCamelCase_ ( _lowerCamelCase : int = 8 ):
lowerCamelCase_ = ascii_letters + digits + punctuation
return "".joi... | 66 | 0 |
"""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_COM... | 720 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class lowerCAmelCase :
"""simple docstring"""
def __init__( self , UpperCamelCase__ ) -> str:
'''simple docstring'''
lowerCamelCase_ =... | 66 | 0 |
"""simple docstring"""
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : Optional[int] = logging.get_logger(__name__)
__lowercase : str = {
'''huggingface/autoformer-tourism-monthly''': '''https://huggin... | 721 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCAmelCase :
"""simple docstring"""
def __init__( self ) -> Dict:
'''simple docstring'''
lowerCamelCase_ ... | 66 | 0 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : int = 2_0_0_0_0_0_0 ):
lowerCamelCase_ = [0 for i in range(n + 1 )]
lowerCamelCase_ = 1
lowerCamelCase_ = 1
for i in range(2 , int(n**0.5 ) + 1 )... | 700 |
"""simple docstring"""
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCamelCase_ ( _lowerCamelCase : str , _l... | 66 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common im... | 701 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase : Tuple = {
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""Jukebox... | 66 | 0 |
import sys
__lowercase : List[Any] = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""668966489504452... | 702 |
"""simple docstring"""
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 ... | 66 | 0 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : str ):
lowerCamelCase_ = 0
for ch in input_str:
lowerCamelCase_ = ord(snake_case_ )
lowerCamelCase_ = pow(2 , snake_case_ )
... | 703 |
"""simple docstring"""
import argparse
import os
import re
__lowercase : Optional[int] = """src/diffusers"""
# Pattern that looks at the indentation in a line.
__lowercase : Dict = re.compile(r"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
__lowercase : in... | 66 | 0 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase ( lowercase__ ):
"""simple docstring"""
__lowercase :Optional[int] ... | 704 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import ... | 66 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
def lowerCamelCase_ ( _lowerCamelCase : int ):
if num <= 0:
lowerCamelCase_ = F"""{num}: Invalid input, please enter a positive integer."""
raise ValueError(_lowerCamelCase ... | 705 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 66 | 0 |
import os
import sys
import transformers
__lowercase : str = """3"""
print("""Python version:""", sys.version)
print("""transformers version:""", transformers.__version__)
try:
import torch
print("""Torch version:""", torch.__version__)
print("""Cuda available:""", torch.cuda.is_available())
pri... | 706 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require... | 66 | 0 |
"""simple docstring"""
import math
def lowerCamelCase_ ( _lowerCamelCase : Optional[int] ):
lowerCamelCase_ = [True] * n
lowerCamelCase_ = False
lowerCamelCase_ = False
lowerCamelCase_ = True
for i in range(3 , ... | 707 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowercase : Union[str, Any] = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupVi... | 66 | 0 |
"""simple docstring"""
import unittest
from transformers import BigBirdConfig, 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
from transformers.mode... | 708 |
"""simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 66 | 0 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : str , _lowerCamelCase : int ):
lowerCamelCase_ = word.split()
def justify(_lowerCamelCase : list , _lowerCamelCase : int , _lowerCamelCase : int ) -> str:
lowe... | 709 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowercase : Optional[Any] = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-At... | 66 | 0 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : Optional[int] , _lowerCamelCase : int ):
lowerCamelCase_ = [0 for i in range(r + 1 )]
# nc0 = 1
lowerCamelCase_ = 1
for i in range(1 , n + 1 ):
... | 710 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase ( tf.keras.layers.Layer ):
"""simpl... | 66 | 0 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params... | 711 |
"""simple docstring"""
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
__lowercase :Tuple = JukeboxTokenizer
__lowercase :Optional... | 66 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision... | 712 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_i... | 66 | 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
__lowercase : Optional[int] = logging.get_logger(__name__)
__lowercase... | 713 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
__lowercase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , *UpperCamel... | 66 | 0 |
"""simple docstring"""
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def lowerCamelCase_ ( _lowerCamelCase : Optional[int] , _lowerCamelCase : Optional[Any] , **_lowerCamelCase : List[Any] ):
lowerCamelCase_ = AutoConf... | 714 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowercase : Tuple = {
"""configuration_squeezebert""": [
"""SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Squ... | 66 | 0 |
"""simple docstring"""
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoToke... | 715 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_availabl... | 66 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase : Optional[Any] = {
... | 716 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class lowerCA... | 66 | 0 |
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test... | 717 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class l... | 66 | 0 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase : Any ):
if isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError('''\'float\' object cannot be interpreted as an integer''' )
if isinstance(__lowerCAmelCase , __lowerC... | 718 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , UpperCamelCase__ , UpperCamelCase__ ) -> Dict:
'''simple docstring'''
super... | 66 | 0 |
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