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 BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
fro... | 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"""
def lowerCamelCase_ ( _lowerCamelCase : int ):
lowerCamelCase_ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCamelCase_ ( _lowerCamelCase : int ):
lowerCamelCase_ ... | 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 re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
__lowercase : Any = object()
# For specifying empty leaf dict `{}`
__lowercase : str = objec... | 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 heapq as hq
import math
from collections.abc import Iterator
class lowerCAmelCase :
"""simple docstring"""
def __init__( self , UpperCamelCase__ ) -> str:
'''simple docstring'''
lowerCamelCase_ =... | 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 gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandin... | 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 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 |
"""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 json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
f... | 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 json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common imp... | 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 tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...test... | 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 typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__lowercase : List[Any] = {
"""configuration_efficientformer""": [
"""EFFICIENTFORME... | 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 os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
__lowercase : Optional[int] = {
"""sample_size""": 3_2,
"""in_channels""": 3,
"""out_channels""": 3,
"""layers_p... | 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"""
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
... | 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 math import ceil, sqrt
def lowerCamelCase_ ( _lowerCamelCase : int = 1_0_0_0_0_0_0 ):
lowerCamelCase_ = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
lowerCamelC... | 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"""
def lowerCamelCase_ ( _lowerCamelCase : float , _lowerCamelCase : float ):
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'''{price_plus_tax(1_0_0, 0.2_5) = }''')
print(f'''{price_plus_tax(1_2_5.5_0, 0.0_5) = }''') | 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 unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
__lowercase :Tuple = JukeboxTokenizer
__lowercase :Optional... | 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_torch_available, is_vision_available
__lowercase : Dict = {
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Chines... | 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 torch
from diffusers import DiffusionPipeline
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , UpperCamelCase__ , UpperCamelCase__ ) -> Dict:
'''simple docstring'''
super... | 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 : int = 2_0_0 ):
lowerCamelCase_ = [1, 2, 5, 1_0, 2_0, 5_0, 1_0_0, 2_0_0]
lowerCamelCase_ = [0] * (pence + 1)
lowerCamelCase_ = 1 # base case: 1 way to make 0 pence
for coin... | 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 math
def lowerCamelCase_ ( _lowerCamelCase : int ):
lowerCamelCase_ = []
lowerCamelCase_ = 2
lowerCamelCase_ = int(math.sqrt(_lowerCamelCase ) ) # Size of every segment
lowerCamelCase_ ... | 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"""
from collections import deque
from math import floor
from random import random
from time import time
class lowerCAmelCase :
"""simple docstring"""
def __init__( self ) -> int:
'''simple docstring'''
lowerCamelCase_ ... | 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"""
def lowerCamelCase_ ( _lowerCamelCase : str ):
assert column_title.isupper()
lowerCamelCase_ = 0
lowerCamelCase_ = len(_lowerCamelCase ) - 1
lowerCamelCase_ = 0
while index >= 0:
lowerC... | 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 logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowercase : List[str] = None
try:
import msvcrt
except ImportError:
__lowercase : Optional[Any] = None
try:
import fcntl
except ImportError:
__lowercase : Li... | 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 typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel... | 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"""
# Copyright 2022 The HuggingFace Team and The OpenBMB 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/licen... | 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"""
__lowercase : str = frozenset(
[
"""prompt""",
"""height""",
"""width""",
"""guidance_scale""",
"""negative_prompt""",
"""prompt_embeds""",
"""negative_prompt_embeds""",
"""cross_attention_kwargs""",
]
)
__l... | 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 gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.util... | 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 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 |
"""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"""
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 ... | 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"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowercase : str = {
"""configuration_poolformer""": [
"""POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""PoolFormerC... | 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"""
def lowerCamelCase_ ( _lowerCamelCase : int ):
if p < 2:
raise ValueError('''p should not be less than 2!''' )
elif p == 2:
return True
lowerCamelCase_ = 4
lowerCamelCase_ = (1 << p) - 1
... | 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 os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
__lowercase : Tuple = HUGGINGFACE_HUB_CACHE
__lowercase : Tuple = """config.json"""
__lowercase : Any = """diffusion_pytorch_model.bin"""
__lowercase : str ... | 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
__lowercase : Optional[Any] = list[list[int]]
# assigning initial values to the grid
__lowercase : Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0... | 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"""
def lowerCamelCase_ ( _lowerCamelCase : list[list] ):
lowerCamelCase_ = current_set.copy()
for row_index, row in enumerate(_lowerCamelCase ):
lowerCamelCase_ = row[0]
for column_index, column in enumerate(... | 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 : float , _lowerCamelCase : float , _lowerCamelCase : int ):
if principal <= 0:
raise Exception('''Principal borrowed must be > 0''' )
if rate_per_annum < 0:
raise Excepti... | 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 typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
... | 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 fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def lowerCamelCase_ ( _lowerCamelCase : str , _lowerCamelCase : Union[str, Any] , _lowerCamelCase : U... | 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 PIL import Image
def lowerCamelCase_ ( _lowerCamelCase : Image , _lowerCamelCase : float ):
def brightness(_lowerCamelCase : int ) -> float:
return 1_2_8 + level + (c - 1_2_8)
if not -2_55.0 <= level <= 2_55.0:
... | 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"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__lowercase : Union[str, Any] = {
"""configuration_gpt_neo""": ["""GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoConfig""", """GPTN... | 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"""
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 |
"""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"""
# Copyright 2023 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
#
# U... | 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"""
def lowerCamelCase_ ( _lowerCamelCase : bytes ):
return "".join([hex(_lowerCamelCase )[2:].zfill(2 ).upper() for byte in list(_lowerCamelCase )] )
def lowerCamelCase_ ( _lowerCamelCase : str ):
# Check data validity, foll... | 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"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def lowerCamelCase_ ( _lowerCamelCase : list[list[float]] ):
lowerCamelCase_ = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since t... | 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"""
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
__lowercase : Dict = logging.get_logger(__name__)
def lowerCamelCase_ ( _lowerCamelCase : Any ):
l... | 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 argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def lowerCamelCase_ ( _lowerCamelCase : Optional[int] ):
lowerCamelCase_ = args.pruning_method
lowerCamelCase_ ... | 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 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 GradientState
from accelerat... | 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 torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowerCamelCase_ ( _lowerCamelCase : List[Any] ):
lowerCamelCase_ = [
'''encoder.version''',
'''decoder.versi... | 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"""
def lowerCamelCase_ ( _lowerCamelCase : int , _lowerCamelCase : int ):
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
lowerCamelCase_ = str(bin(_lowerCamelCase ) )[2:] ... | 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 typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class lowerCAmelCase ( a ):
"""simple docstring"""
... | 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 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,
... | 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
import hashlib # hashlib is only used inside the Test class
import struct
class lowerCAmelCase :
"""simple docstring"""
def __init__( self , UpperCamelCase__ ) -> str:
'''simple docstring'''
lower... | 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 os
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 logging
__lowercase : Tuple = logging.get_logger(__name__)
__lowercase... | 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"""
from collections import defaultdict
def lowerCamelCase_ ( _lowerCamelCase : str , _lowerCamelCase : str ):
lowerCamelCase_ = first_str.lower().strip()
lowerCamelCase_ = second_str.lower().strip()
# Remove whitespace
... | 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 gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
... | 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"""
def lowerCamelCase_ ( _lowerCamelCase : int ):
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
lowerCamelCase_ = 1
lowerCamelCase_ = 1
while repunit:
lowerCamelCase_ = (1_0 * repunit ... | 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 inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_availa... | 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 typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowercase : List[Any] = {"""configuration_van""": ["""VAN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """VanConfig"""]}
try:
if not is_torch_a... | 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"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.util... | 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 os
from datetime import datetime as dt
from github import Github
__lowercase : int = [
"""good first issue""",
"""feature request""",
"""wip""",
]
def lowerCamelCase_ ( ):
lowerCamelCase_ = Github(os.environ['''GITHUB_TOKEN'''] ... | 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 Any
def lowerCamelCase_ ( _lowerCamelCase : list ):
if not input_list:
return []
lowerCamelCase_ = [input_list.count(_lowerCamelCase ) for value in input_list]
lowerCamelCase_ = max(_lowerCam... | 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 copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__lowercase : Union[str, Any] = {
"""facebook/mask2former-swin-small-coco-instance""": (
"""https:... | 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"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__lowercase : Union[str, Any] = {
"""configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_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"""
def lowerCamelCase_ ( _lowerCamelCase : list , _lowerCamelCase : list , _lowerCamelCase : int ):
lowerCamelCase_ = len(_lowerCamelCase )
lowerCamelCase_ = [[0] * n for i in range(_lowerCamelCase )]
fo... | 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 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__":
__lowercase : List[Any] = pd.read_csv("""sample_data.csv""", header=No... | 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 unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase : str = ... | 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 Dict
from .base import GenericTensor, Pipeline
class lowerCAmelCase ( a ):
"""simple docstring"""
def _lowerCAmelCase ( self , UpperCamelCase__=None , UpperCamelCase__=None , UpperCamelCase__=None , **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 argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if ve... | 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 gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.testing_... | 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 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 |
"""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 sys
__lowercase : Tuple = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
... | 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
__lowercase : List[str] = tuple[int, int, int]
__lowercase : List[Any] = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
__lowercase : int = """ABCDEFGHIJKLMNOPQRSTUVWXYZ... | 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 gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@requi... | 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 json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepar... | 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 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 |
"""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 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 |
"""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"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.dumm... | 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 pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def ... | 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 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... | 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 = 1_0_0_0_0_0_0 ):
lowerCamelCase_ = limit + 1
lowerCamelCase_ = [0] * limit
for first_term in range(1 , _lowerCamelCase ):
for n in range(_lowerCamelCase ,... | 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"""
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 |
"""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 collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_co... | 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_torch_available
__lowercase : Tuple = {
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""Jukebox... | 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 __future__ import annotations
from typing import Any
class lowerCAmelCase ( a ):
"""simple docstring"""
pass
class lowerCAmelCase :
"""simple docstring"""
def __init__( self , UpperCamelCase__ ) -> None:
... | 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"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase : str , _lowerCamelCase : list[str] | None = None ):
lowerCamelCase_ = word_bank or []
# create a table
lowerCamelCase_ = len(_lowerCamelCase ... | 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 scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
__lowercase : int = """\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},
author... | 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 collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_o... | 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"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase ( a ):
"""simple docstring"""
__lowercase :Optional[int] = ["image_processor", "tokenizer"]
__lowercase :List[str] ... | 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"""
import numpy as np
__lowercase : Optional[int] = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", "... | 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 random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
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_par... | 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 typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
__lowercase : Tuple = datasets.utils.logging.get_logger(__name__)
class lowerCAmelCase ( folder_based_builder.FolderBa... | 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 random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin... | 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"""
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 |
"""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"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configur... | 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 transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase : Un... | 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"""
from functools import lru_cache
def lowerCamelCase_ ( _lowerCamelCase : int ):
lowerCamelCase_ = 2
lowerCamelCase_ = set()
while i * i <= n:
if n % i:
i += 1
else:
... | 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 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 : Optional[int] = logging.get_logger(__name__)
__lowe... | 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 sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
__lowercase : Union[str, Any] = """\
@inproceedings{snover-etal-2006-study,
title = \"A Study of Translation Edit Rate with Targeted Human Annotation\",
author = \"Snover, M... | 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"""
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_u... | 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 os
import pytest
from attr import dataclass
__lowercase : Optional[int] = """us-east-1""" # defaults region
@dataclass
class lowerCAmelCase :
"""simple docstring"""
__lowercase :str
__lowercase :Any = "arn:aws:iam::55810514... | 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 gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_imag... | 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 __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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,... | 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 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.