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 |
|---|---|---|---|---|
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_comm... | 33 |
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
ca... | 33 | 1 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to h... | 33 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
... | 33 | 1 |
print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
| 33 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def UpperCAmelCase ( _snake_case = 3 ):
if isinstance(_snake_case , _snake_case ):
raise TypeError('''number of q... | 33 | 1 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __UpperCamelCase ( __UpperCAmelCase ):
... | 33 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
cl... | 33 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""google/vivit-b-16x2-kinetics400""": (
"""https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"""
... | 33 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __UpperCamelCase ( yaml.SafeLoader ):
'''simple docstring'''
def __snake_case ( self , UpperCAmelCase_ ):
lowerCAmelCase =... | 33 | 1 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __UpperCamelCase ( unittest.TestCase ):
... | 33 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_sim... | 33 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_availabl... | 33 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_te... | 33 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ... | 33 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = args.pruning_method
lowerCAmelCase = args.threshold
lo... | 33 | 1 |
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
@require_to... | 33 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""vocab_file""": """vocab.txt""",
"""... | 33 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""CarlCochet/trajectory-transformer-halfcheetah-medium-v2""": (
"""https://huggingface.co/CarlCochet/trajectory-transformer-half... | 33 |
from __future__ import annotations
from typing import Generic, TypeVar
UpperCAmelCase_ =TypeVar("""T""")
class __UpperCamelCase ( Generic[T] ):
'''simple docstring'''
def __init__( self , UpperCAmelCase_ ):
lowerCAmelCase = data
... | 33 | 1 |
import collections
import importlib.util
import os
import re
from pathlib import Path
UpperCAmelCase_ ="""src/transformers"""
# Matches is_xxx_available()
UpperCAmelCase_ =re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
UpperCAmelCase_ =... | 33 |
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case ):
def count_of_possible_combinations(_snake_case ) -> int:
if target < 0:
return 0
if target == 0:
return 1
ret... | 33 | 1 |
from collections.abc import Sequence
def UpperCAmelCase ( _snake_case , _snake_case = False ):
if not arr:
return 0
lowerCAmelCase = 0 if allow_empty_subarrays else float('''-inf''' )
lowerCAmelCase = 0.0
for num in... | 33 |
import torch
from diffusers import StableDiffusionPipeline
UpperCAmelCase_ ="""path-to-your-trained-model"""
UpperCAmelCase_ =StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")
UpperCAmelCase_ ="""A photo of sks dog in a bucket"""
UpperCAmel... | 33 | 1 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def UpperCAmelCase ( _snake_case = "laptop" ):
lowerCAmelCase = F"""https://www.amazon.in/laptop/s?k={product}"""
lowerCAmelCase = {
... | 33 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ ={
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""JukeboxPriorConfig""",
... | 33 | 1 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_sim... | 33 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from tra... | 33 | 1 |
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
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""faceb... | 33 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""google/switch-base-8""": """https://huggingface.co/google/switch-base-8/blob/main/config.json""",
}
class __UpperCamelCase ... | 33 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, ra... | 33 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase , lowerCAmelCase = analyze_text(_snake_case )
lowerCAmelCase = list(''' ''' +... | 33 | 1 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase ( __UpperCAmelCase ):
... | 33 |
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_params imp... | 33 | 1 |
class __UpperCamelCase :
'''simple docstring'''
def __init__( self ):
lowerCAmelCase = {} # Mapping from char to TrieNode
lowerCAmelCase = False
def __snake_case ( self , UpperCAmelCase_ ):
for word... | 33 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase_ ={
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_A... | 33 | 1 |
from copy import deepcopy
class __UpperCamelCase :
'''simple docstring'''
def __init__( self , UpperCAmelCase_ = None , UpperCAmelCase_ = None ):
if arr is None and size is not None:
lowerCAmelCase = size
... | 33 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
UpperCAmelCase_ =datasets.utils.loggi... | 33 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""google/switch-base-8""": """https://huggingface.co/google/switch-base-8/blob/main/config.json""",
}
class __UpperCamelCase ... | 33 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase_ =logging.get_logger(__name__)
class __UpperCamelCase ( __UpperCAmelCase , __Upp... | 33 | 1 |
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = [1]
lowerCAmelCase , lowerCAmelCase , lowerCAmelCase = 0, 0, 0
lowerCAmelCase = ugly_nums[ia] * 2
lowerCAmelCase = ugly_nums[ia] * 3
lowerCAmelCase = ugly_nums[ia] * ... | 33 |
from collections.abc import Sequence
def UpperCAmelCase ( _snake_case , _snake_case = False ):
if not arr:
return 0
lowerCAmelCase = 0 if allow_empty_subarrays else float('''-inf''' )
lowerCAmelCase = 0.0
for num in... | 33 | 1 |
def UpperCAmelCase ( ):
lowerCAmelCase = 0
for i in range(1 , 1001 ):
total += i**i
return str(_snake_case )[-10:]
if __name__ == "__main__":
print(solution())
| 33 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
... | 33 | 1 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
UpperCAmelCase_ =logging.get_logger(__name__)
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
def __init__( self , *UpperCAmelCa... | 33 |
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
ca... | 33 | 1 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __UpperC... | 33 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
... | 33 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ ={"""configuration_xlnet""": ["""XLNET_PRETRAINED_CONFIG_... | 33 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def UpperCAmelCase ( _snake_case = 3 ):
if isinstance(_snake_case , _snake_case ):
raise TypeError('''number of q... | 33 | 1 |
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'''kwargs, expected''' , [
({'''num_shards''': 0, '''max_num_jobs''': 1}, []),
({'''num_shards''': 10, '''max_num_jobs''': 1}... | 33 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
cl... | 33 | 1 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase , lowerCAmelCase = analyze_text(_snake_case )
lowerCAmelCase = list(''' ''' +... | 33 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __UpperCamelCase ( yaml.SafeLoader ):
'''simple docstring'''
def __snake_case ( self , UpperCAmelCase_ ):
lowerCAmelCase =... | 33 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""microsoft/trocr-base-handwritten""": (
"""https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"""
... | 33 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_sim... | 33 | 1 |
import torch
from diffusers import StableDiffusionPipeline
UpperCAmelCase_ ="""path-to-your-trained-model"""
UpperCAmelCase_ =StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")
UpperCAmelCase_ ="""A photo of sks dog in a bucket"""
UpperCAmel... | 33 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_te... | 33 | 1 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common... | 33 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = args.pruning_method
lowerCAmelCase = args.threshold
lo... | 33 | 1 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def UpperCAmelCase ( _snake_case = 3 ):
if isinstance(_snake_case , _snake_case ):
raise TypeError('''number of q... | 33 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""vocab_file""": """vocab.txt""",
"""... | 33 | 1 |
from __future__ import annotations
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case , _snake_case ):
lowerCAmelCase = []
lowerCAmelCase , lowerCAmelCase = input_list[low:mid], input_list[mid : high + 1]
while left and ... | 33 |
from __future__ import annotations
from typing import Generic, TypeVar
UpperCAmelCase_ =TypeVar("""T""")
class __UpperCamelCase ( Generic[T] ):
'''simple docstring'''
def __init__( self , UpperCAmelCase_ ):
lowerCAmelCase = data
... | 33 | 1 |
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def UpperCAmelCase ( _snake_case ):
lowerCA... | 33 |
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case ):
def count_of_possible_combinations(_snake_case ) -> int:
if target < 0:
return 0
if target == 0:
return 1
ret... | 33 | 1 |
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from transfor... | 33 |
import torch
from diffusers import StableDiffusionPipeline
UpperCAmelCase_ ="""path-to-your-trained-model"""
UpperCAmelCase_ =StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")
UpperCAmelCase_ ="""A photo of sks dog in a bucket"""
UpperCAmel... | 33 | 1 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTok... | 33 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ ={
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""JukeboxPriorConfig""",
... | 33 | 1 |
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered... | 33 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from tra... | 33 | 1 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
UpperCAmelCase_ ={
... | 33 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""google/switch-base-8""": """https://huggingface.co/google/switch-base-8/blob/main/config.json""",
}
class __UpperCamelCase ... | 33 | 1 |
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Conf... | 33 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase , lowerCAmelCase = analyze_text(_snake_case )
lowerCAmelCase = list(''' ''' +... | 33 | 1 |
from __future__ import annotations
def UpperCAmelCase ( _snake_case , _snake_case ):
if len(_snake_case ) < k or k < 0:
raise ValueError('''Invalid Input''' )
lowerCAmelCase = lowerCAmelCase = sum(array[:k] )
for ... | 33 |
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_params imp... | 33 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCAmelCase_ ={"""processing_wav2vec2_with_lm""": ["""Wav2Vec2ProcessorWithLM"""]}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
UpperCAmelCase_ =_LazyM... | 33 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase_ ={
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_A... | 33 | 1 |
from __future__ import annotations
from typing import Any
class __UpperCamelCase :
'''simple docstring'''
def __init__( self , UpperCAmelCase_ ):
lowerCAmelCase = num_of_nodes
lowerCAmelCase = []
lowerCAmelCase =... | 33 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
UpperCAmelCase_ =datasets.utils.loggi... | 33 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimen... | 33 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase_ =logging.get_logger(__name__)
class __UpperCamelCase ( __UpperCAmelCase , __Upp... | 33 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPano... | 33 |
from collections.abc import Sequence
def UpperCAmelCase ( _snake_case , _snake_case = False ):
if not arr:
return 0
lowerCAmelCase = 0 if allow_empty_subarrays else float('''-inf''' )
lowerCAmelCase = 0.0
for num in... | 33 | 1 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUE... | 33 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
... | 33 | 1 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class __UpperCamelCase ( enum.... | 33 |
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
ca... | 33 | 1 |
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vis... | 33 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
... | 33 | 1 |
def UpperCAmelCase ( _snake_case = 100 ):
lowerCAmelCase = (n * (n + 1) // 2) ** 2
lowerCAmelCase = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(F'''{solution() = }''')
| 33 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def UpperCAmelCase ( _snake_case = 3 ):
if isinstance(_snake_case , _snake_case ):
raise TypeError('''number of q... | 33 | 1 |
import numpy as np
def UpperCAmelCase ( _snake_case ):
return 1 / (1 + np.exp(-vector ))
def UpperCAmelCase ( _snake_case ):
return vector * sigmoid(_snake_case )
if __name__ == "__main__":
import doctest
doctes... | 33 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
cl... | 33 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
cl... | 33 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __UpperCamelCase ( yaml.SafeLoader ):
'''simple docstring'''
def __snake_case ( self , UpperCAmelCase_ ):
lowerCAmelCase =... | 33 | 1 |
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBertF... | 33 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_sim... | 33 | 1 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case ):... | 33 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_te... | 33 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipe... | 33 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = args.pruning_method
lowerCAmelCase = args.threshold
lo... | 33 | 1 |
from math import factorial
def UpperCAmelCase ( _snake_case , _snake_case ):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
... | 33 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""vocab_file""": """vocab.txt""",
"""... | 33 | 1 |
def UpperCAmelCase ( _snake_case ):
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''' )
for cell_n in range(1 , len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_... | 33 |
from __future__ import annotations
from typing import Generic, TypeVar
UpperCAmelCase_ =TypeVar("""T""")
class __UpperCamelCase ( Generic[T] ):
'''simple docstring'''
def __init__( self , UpperCAmelCase_ ):
lowerCAmelCase = data
... | 33 | 1 |
import os
from datetime import datetime as dt
from github import Github
UpperCAmelCase_ =[
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
]
def ... | 33 |
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case ):
def count_of_possible_combinations(_snake_case ) -> int:
if target < 0:
return 0
if target == 0:
return 1
ret... | 33 | 1 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
__a : Union[str, Any] =(CMStochasticIterativeScheduler,)
__a... | 33 |
import torch
from diffusers import StableDiffusionPipeline
UpperCAmelCase_ ="""path-to-your-trained-model"""
UpperCAmelCase_ =StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")
UpperCAmelCase_ ="""A photo of sks dog in a bucket"""
UpperCAmel... | 33 | 1 |
def UpperCAmelCase ( _snake_case ):
if not isinstance(_snake_case , _snake_case ):
lowerCAmelCase = F"""Input value of [number={number}] must be an integer"""
raise TypeError(_snake_case )
if number < 1:
... | 33 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ ={
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""JukeboxPriorConfig""",
... | 33 | 1 |
from __future__ import annotations
from statistics import mean
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case ):
lowerCAmelCase = [0] * no_of_processes
lowerCAmelCase = [0] * no_of_processes
# Initialize remaining_time to ... | 33 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from tra... | 33 | 1 |
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
... | 33 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""google/switch-base-8""": """https://huggingface.co/google/switch-base-8/blob/main/config.json""",
}
class __UpperCamelCase ... | 33 | 1 |
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,
)
... | 33 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase , lowerCAmelCase = analyze_text(_snake_case )
lowerCAmelCase = list(''' ''' +... | 33 | 1 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_te... | 33 |
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_params imp... | 33 | 1 |
from collections.abc import Sequence
from queue import Queue
class __UpperCamelCase :
'''simple docstring'''
def __init__( self , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_=None , UpperCAmelCase_=None ):
... | 33 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase_ ={
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_A... | 33 | 1 |
import os
import sys
UpperCAmelCase_ =os.path.join(os.path.dirname(__file__), """src""")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSequenceClassi... | 33 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
UpperCAmelCase_ =datasets.utils.loggi... | 33 | 1 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
... | 33 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase_ =logging.get_logger(__name__)
class __UpperCamelCase ( __UpperCAmelCase , __Upp... | 33 | 1 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __UpperCamelCase ( unittest.TestCase ):
'''simple docstring'... | 33 |
from collections.abc import Sequence
def UpperCAmelCase ( _snake_case , _snake_case = False ):
if not arr:
return 0
lowerCAmelCase = 0 if allow_empty_subarrays else float('''-inf''' )
lowerCAmelCase = 0.0
for num in... | 33 | 1 |
UpperCAmelCase_ ={
"""meter""": """m""",
"""kilometer""": """km""",
"""megametre""": """Mm""",
"""gigametre""": """Gm""",
"""terametre""": """Tm""",
"""petametre""": """Pm""",
"""exametre""": """Em""",
"""zettametre""": """Zm""",
"""yottametre""": """Ym""",
}... | 33 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
... | 33 | 1 |
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
UpperCAmelCase_ =logging.get_logger(__name__)
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
def __init__( self , *Uppe... | 33 |
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
ca... | 33 | 1 |
import os
import jsonlines
import numpy as np
from tqdm import tqdm
UpperCAmelCase_ =2048
UpperCAmelCase_ =4096
UpperCAmelCase_ =42
UpperCAmelCase_ =os.environ.pop("""PROCESS_TRAIN""", """false""")
UpperCAmelCase_ ={"""null""": 0, """short""": 1, """long""": 2, """yes"""... | 33 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
... | 33 | 1 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class __UpperCamelCase :
'''simple docstring'''
def __init__( self , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , U... | 33 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def UpperCAmelCase ( _snake_case = 3 ):
if isinstance(_snake_case , _snake_case ):
raise TypeError('''number of q... | 33 | 1 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=__UpperCAmelCase )
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring''... | 33 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
cl... | 33 | 1 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
UpperCAmelCase_ =np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (trapmf(), g... | 33 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __UpperCamelCase ( yaml.SafeLoader ):
'''simple docstring'''
def __snake_case ( self , UpperCAmelCase_ ):
lowerCAmelCase =... | 33 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase_ ={"""configuration_unispeech""": ["""UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP""", """UniSpeechCon... | 33 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_sim... | 33 | 1 |
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
B... | 33 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_te... | 33 | 1 |
import numpy as np
def UpperCAmelCase ( _snake_case , _snake_case ):
return np.where(vector > 0 , _snake_case , (alpha * (np.exp(_snake_case ) - 1)) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 33 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = args.pruning_method
lowerCAmelCase = args.threshold
lo... | 33 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ ={
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""JukeboxPriorConfig""",
... | 33 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""vocab_file""": """vocab.txt""",
"""... | 33 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ ={
"""configuration_rag""": ["""RagConfig"""],
"""retrieval_rag""": ["""RagRetriever"""],
"""tokenization_rag""": ["""RagTokenizer"... | 33 |
from __future__ import annotations
from typing import Generic, TypeVar
UpperCAmelCase_ =TypeVar("""T""")
class __UpperCamelCase ( Generic[T] ):
'''simple docstring'''
def __init__( self , UpperCAmelCase_ ):
lowerCAmelCase = data
... | 33 | 1 |
UpperCAmelCase_ ="""Alexander Joslin"""
import operator as op
from .stack import Stack
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = {'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-''': op.sub}
lowerCAmelCase = Stack()
... | 33 |
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case ):
def count_of_possible_combinations(_snake_case ) -> int:
if target < 0:
return 0
if target == 0:
return 1
ret... | 33 | 1 |
from __future__ import annotations
from fractions import Fraction
def UpperCAmelCase ( _snake_case , _snake_case ):
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def UpperCAmelCase (... | 33 |
import torch
from diffusers import StableDiffusionPipeline
UpperCAmelCase_ ="""path-to-your-trained-model"""
UpperCAmelCase_ =StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")
UpperCAmelCase_ ="""A photo of sks dog in a bucket"""
UpperCAmel... | 33 | 1 |
import datasets
from .evaluate import evaluate
UpperCAmelCase_ ="""\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint arXiv:2103.06... | 33 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ ={
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""JukeboxPriorConfig""",
... | 33 | 1 |
import itertools
import string
from collections.abc import Generator, Iterable
def UpperCAmelCase ( _snake_case , _snake_case ):
lowerCAmelCase = iter(_snake_case )
while True:
lowerCAmelCase = tuple(itertools.islice(_snake_case ... | 33 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from tra... | 33 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
__a : List[Any] ="""encoder-decod... | 33 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""google/switch-base-8""": """https://huggingface.co/google/switch-base-8/blob/main/config.json""",
}
class __UpperCamelCase ... | 33 | 1 |
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class __UpperCamelCase ( __UpperCAmelCase ):
... | 33 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase , lowerCAmelCase = analyze_text(_snake_case )
lowerCAmelCase = list(''' ''' +... | 33 | 1 |
from ..utils import DummyObject, requires_backends
class __UpperCamelCase ( metaclass=__UpperCAmelCase ):
'''simple docstring'''
__a : str =["""flax"""]
def __init__( self , *UpperCAmelCase_ , **UpperCAmelCase_ ):
... | 33 |
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_params imp... | 33 | 1 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transforme... | 33 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase_ ={
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_A... | 33 | 1 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # ... | 33 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
UpperCAmelCase_ =datasets.utils.loggi... | 33 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase_ =logging.get_logger(__name__)
class __UpperCamelCase ( __UpperCAmelCase , __Upp... | 33 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase_ =logging.get_logger(__name__)
class __UpperCamelCase ( __UpperCAmelCase , __Upp... | 33 | 1 |
UpperCAmelCase_ ="""0.18.2"""
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_librosa_av... | 33 |
from collections.abc import Sequence
def UpperCAmelCase ( _snake_case , _snake_case = False ):
if not arr:
return 0
lowerCAmelCase = 0 if allow_empty_subarrays else float('''-inf''' )
lowerCAmelCase = 0.0
for num in... | 33 | 1 |
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration,
... | 33 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
... | 33 | 1 |
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""vocab_file""": """vocab.json""",
... | 33 |
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
ca... | 33 | 1 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
UpperCAmelCase_ =datasets.utils.loggi... | 33 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
... | 33 | 1 |
from cva import destroyAllWindows, imread, imshow, waitKey
def UpperCAmelCase ( _snake_case ):
# getting number of pixels in the image
lowerCAmelCase , lowerCAmelCase = img.shape[0], img.shape[1]
# converting each pixel's color to its negative
... | 33 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def UpperCAmelCase ( _snake_case = 3 ):
if isinstance(_snake_case , _snake_case ):
raise TypeError('''number of q... | 33 | 1 |
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case , _snake_case ):
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
lowerCAmelCase = mf_knapsack(i - 1 , _snake_case , _... | 33 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
cl... | 33 | 1 |
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def UpperCAmelCase ( _snake_case , _snake_case , _sna... | 33 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __UpperCamelCase ( yaml.SafeLoader ):
'''simple docstring'''
def __snake_case ( self , UpperCAmelCase_ ):
lowerCAmelCase =... | 33 | 1 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def UpperCAmelCase ( _snake_case = "" ):
lowerCAmelCase = url or '''https://www.imdb.com/chart/top/?ref_=nv_mv_250'''
lowerCAmelCase = BeautifulSoup(requests.ge... | 33 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_sim... | 33 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""microsoft/unispeech-large-1500h-cv""": (
"""https://huggingface.co/microsoft/unispeech-larg... | 33 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_te... | 33 | 1 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __UpperCamelCase ( yaml.SafeLoader ):
'''simple docstring'''
def __snake_case ( self , UpperCAmelCase_ ):
lowerCAmelCase =... | 33 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = args.pruning_method
lowerCAmelCase = args.threshold
lo... | 33 | 1 |
from __future__ import annotations
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case , ):
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError('''You cannot supply more or less than 2 values''' )
elif s... | 33 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""vocab_file""": """vocab.txt""",
"""... | 33 | 1 |
import functools
def UpperCAmelCase ( _snake_case , _snake_case ):
# Validation
if not isinstance(_snake_case , _snake_case ) or not all(isinstance(_snake_case , _snake_case ) for day in days ):
raise ValueError('''... | 33 |
from __future__ import annotations
from typing import Generic, TypeVar
UpperCAmelCase_ =TypeVar("""T""")
class __UpperCamelCase ( Generic[T] ):
'''simple docstring'''
def __init__( self , UpperCAmelCase_ ):
lowerCAmelCase = data
... | 33 | 1 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__UpperCAmelCase )
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
__a : ... | 33 |
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case ):
def count_of_possible_combinations(_snake_case ) -> int:
if target < 0:
return 0
if target == 0:
return 1
ret... | 33 | 1 |
from __future__ import annotations
def UpperCAmelCase ( _snake_case , _snake_case = None , _snake_case = None ):
if start is None:
lowerCAmelCase = 0
if end is None:
lowerCAmelCase = len(_snake_case ) - 1
... | 33 |
import torch
from diffusers import StableDiffusionPipeline
UpperCAmelCase_ ="""path-to-your-trained-model"""
UpperCAmelCase_ =StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")
UpperCAmelCase_ ="""A photo of sks dog in a bucket"""
UpperCAmel... | 33 | 1 |
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