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 pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_... | 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 importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase_ ="""src/transformers"""
# This is to make sure the transformers module imp... | 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 functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""asapp/sew-tiny-100k""": """https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json""",
... | 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 math import isqrt
def UpperCAmelCase ( _snake_case ):
return all(number % divisor != 0 for divisor in range(2 , isqrt(_snake_case ) + 1 ) )
def UpperCAmelCase ( _snake_case = 10**6 ):
lowerCAmelCase = 0
... | 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 |
# Imports
import numpy as np
class __UpperCamelCase :
'''simple docstring'''
def __init__( self , UpperCAmelCase_=None , UpperCAmelCase_=None , UpperCAmelCase_=None , UpperCAmelCase_=None , UpperCAmelCase_=None ):
self.set... | 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 |
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
UpperCAmelCase_ ="""<<<<<<< This should probably be modified because it mentions: """
UpperCAmelCase_ =""... | 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 |
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case ):
lowerCAmelCase = len(_snake_case )
lowerCAmelCase = [[0] * n for i in range(_snake_case )]
for i in range(_snake_case ):
lowerCAmelCase = y_points[i... | 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 json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer
... | 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 argparse
import os
import re
UpperCAmelCase_ ="""src/transformers/models/auto"""
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
UpperCAmelCase_ =re.compile(R"""[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s... | 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 |
from __future__ import annotations
import math
from collections.abc import Callable
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case , _snake_case = 100 , ):
lowerCAmelCase = x_start
lowerCAmelCase = fnc(_snake_case )
... | 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 datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers... | 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 TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ ={
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfig""",
"""XCLIPTextConfig""",
"""X... | 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 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 |
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 warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
UpperCAmelCase_ =logging.get_logger(__name__)
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
def __init__( self , *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 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoIm... | 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 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having... | 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 unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMix... | 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 Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""camembert-base""": """https://huggingf... | 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 |
def UpperCAmelCase ( _snake_case , _snake_case ):
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
lowerCAmelCase = str(bin(_snake_case ) )[2:] # remove the leading "0b"
lowerCAmelCas... | 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 collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, Patchin... | 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 unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_... | 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 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 |
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 argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = [
'''encoder.version''',
'''decoder.version''',
'''mod... | 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 |
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - generate model_... | 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 os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCAmelCase_ ="""
import os
"""
UpperCAmelCase_ ="""
def foo():
import os
return False
"""
UpperCAmelCase_ ="""
def foo():
def bar():
if True:
import os
... | 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 bisect import bisect
from itertools import accumulate
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case , _snake_case ):
lowerCAmelCase = sorted(zip(_snake_case , _snake_case ) , key=lambda _snake_case : x[0] / x[1] ... | 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
from typing import Any
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
pass
class __UpperCamelCase :
'''simple docstring'''
def __init__( self , 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 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCAmelCase_ ... | 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
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ="""▁"""
UpperCAm... | 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 warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCAmelCase_ =logging.get_logger(__name__)
class __UpperCamelCase ( __UpperCAmelCase ):
'''simple docstring'''
def __init__( self , *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 |
UpperCAmelCase_ =[sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_0000)]
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = 0
while number:
# Increased Speed Slightly by checking every 5 digits together.
sum_of_di... | 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 ( _snake_case , _snake_case , _snake_case , _snake_case ):
if height >= 1:
move_tower(height - 1 , _snake_case , _snake_case , _snake_case )
move_disk(_snake_case , _snake_case )
... | 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 math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.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 unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available()... | 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 numpy as np
def UpperCAmelCase ( _snake_case ):
return 1 / (1 + np.exp(-vector ))
def UpperCAmelCase ( _snake_case ):
return vector * sigmoid(1.702 * vector )
if __name__ == "__main__":
import doctest
doc... | 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 json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
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... | 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 |
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = int(_snake_case )
if n_element < 1:
lowerCAmelCase = ValueError('''a should be a positive number''' )
raise my_error
lowerCAmelCase = [1]
lowerCAmelCa... | 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_tf_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase_ ={
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_A... | 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 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ ={
"""configuration_roberta""": ["""ROBERTA_PRETRAINED_CONFIG... | 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 sys
UpperCAmelCase_ =(
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856403... | 700 |
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 | 0 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import TEXT_GUIDED_IM... | 701 |
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 | 0 |
def UpperCAmelCase ( _snake_case ):
return "".join([hex(_SCREAMING_SNAKE_CASE )[2:].zfill(2 ).upper() for byte in list(_SCREAMING_SNAKE_CASE )] )
def UpperCAmelCase ( _snake_case ):
# Check data validity, following RFC3548
... | 702 |
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 | 0 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateP... | 703 |
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 | 0 |
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResampling,... | 704 |
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 | 0 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ... | 705 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ ={
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""JukeboxPriorConfig""",
... | 33 | 0 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
UpperCAmelCase_ =list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
UpperCAmelCase_ =[file for file in filepaths if fi... | 706 |
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 | 0 |
import itertools
import os
import re
UpperCAmelCase_ =re.compile(R"""([A-Z]+)([A-Z][a-z])""")
UpperCAmelCase_ =re.compile(R"""([a-z\d])([A-Z])""")
UpperCAmelCase_ =re.compile(R"""(?<!_)_(?!_)""")
UpperCAmelCase_ =re.compile(R"""(_{2,})""")
UpperCAmelCase_ =r"^\w+(\.\w+)*$"
Upp... | 707 |
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 | 0 |
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import arra... | 708 |
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 | 0 |
UpperCAmelCase_ =[
'DownloadConfig',
'DownloadManager',
'DownloadMode',
'StreamingDownloadManager',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager
| 709 |
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 | 0 |
def UpperCAmelCase ( ):
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(lowerCamelCase__ , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name__ == "__main__":
print... | 710 |
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 | 0 |
'''simple docstring'''
from typing import Any
class __UpperCamelCase :
'''simple docstring'''
def __init__( self , UpperCAmelCase_ ):
lowerCAmelCase = data
lowerCAmelCase = None
def __repr__( self ... | 711 |
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 | 0 |
from pathlib import Path
import torch
from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter
UpperCAmelCase_ ="Create a default config file for Accelerate with only a few flags set."
... | 712 |
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 | 0 |
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = [
'''encoder.version''',
'''decoder.version''',
... | 713 |
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 | 0 |
from __future__ import annotations
def UpperCAmelCase ( _snake_case , _snake_case ):
lowerCAmelCase = []
lowerCAmelCase = []
lowerCAmelCase = 0
lowerCAmelCase = sum(lowerCAmelCase__ )
create_state_space_tree(lowerCAmel... | 714 |
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 | 0 |
def UpperCAmelCase ( _snake_case ):
'''simple docstring'''
lowerCAmelCase = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def UpperCAmelCase ( _snake_case ):
'''simple ... | 715 |
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 | 0 |
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case ):
def update_area_of_max_square(_snake_case , _snake_case ) -> int:
# BASE CASE
if row >= rows or col >= cols:
return 0
lowe... | 716 |
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 | 0 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
# TODO Update this
UpperCAmelCase_ ={
"""facebook/esm-1b""": """https://huggingface.... | 717 |
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 | 0 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case , _snak... | 718 |
# 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 | 0 |
def UpperCAmelCase ( _snake_case , _snake_case ):
lowerCAmelCase = ''''''
for i in table:
res += inp[i - 1]
return res
def UpperCAmelCase ( _snake_case ):
return data[1:] + data[0]
def UpperCAmelCa... | 719 |
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 | 0 |
def UpperCAmelCase ( _snake_case , _snake_case ):
if density <= 0:
raise ValueError('''Impossible fluid density''' )
if bulk_modulus <= 0:
raise ValueError('''Impossible bulk modulus''' )
return (bulk_modulus / de... | 720 |
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 | 0 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copi... | 721 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_te... | 33 | 0 |
print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
| 700 |
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 | 0 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def UpperCAmelCase ( _snake_case , _snake_case=() , _snake_case=None , _snake_case="no" , _snake_cas... | 701 |
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 | 0 |
from __future__ import annotations
from cmath import sqrt
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case ):
if a == 0:
raise ValueError('''Coefficient \'a\' must not be zero.''' )
lowerCAmelCase = b * b - 4 * a * c
low... | 702 |
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 | 0 |
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acc... | 703 |
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 | 0 |
from math import factorial
def UpperCAmelCase ( _snake_case , _snake_case , _snake_case ):
if successes > trials:
raise ValueError('''successes must be lower or equal to trials''' )
if trials < 0 or successes < 0:
r... | 704 |
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 | 0 |
'''simple docstring'''
from __future__ import annotations
import time
import numpy as np
UpperCAmelCase_ =[8, 5, 9, 7]
UpperCAmelCase_ =[
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
UpperCAmelCase_ =[
[3, 2, 1, 4],... | 705 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ ={
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""JukeboxPriorConfig""",
... | 33 | 0 |
from math import ceil
def UpperCAmelCase ( _snake_case = 1001 ):
lowerCAmelCase = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowerCAmelCase = 2 * i + 1
lowerCAmelCase = 2 * i
lowerCAme... | 706 |
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 | 0 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import require_elasticsear... | 707 |
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 | 0 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
UpperCAmelCase_ =False
class __UpperCamelCase ( unittest.Te... | 708 |
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 | 0 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
... | 709 |
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 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ ={
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''',
... | 710 |
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 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
'facebo... | 711 |
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 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""google/bigbird-roberta-base""": """https://huggi... | 712 |
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 | 0 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common ... | 713 |
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 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params ... | 714 |
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 | 0 |
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... | 715 |
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 | 0 |
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
UpperCAmelCase_ =logging.get_logger(__name__)
class __UpperCamelCase ( UpperCamelCase__ ):
'''simple docstring'''
def __init__( self , *U... | 716 |
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 | 0 |
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet import StableDiffusionControlNetPipeline # noqa: F401
deprecate(
"""stable diffusion controlnet""",
"""0.22.0""",
"""Importing `StableDiffusio... | 717 |
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 | 0 |
from __future__ import annotations
from PIL import Image
# Define glider example
UpperCAmelCase_ =[
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, ... | 718 |
# 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 | 0 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
... | 719 |
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 | 0 |
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decord import Vi... | 720 |
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 | 0 |
import math
import sys
def UpperCAmelCase ( _snake_case ):
lowerCAmelCase = ''''''
try:
with open(_snake_case , '''rb''' ) as binary_file:
lowerCAmelCase = binary_file.read()
for dat in data:
... | 721 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_te... | 33 | 0 |
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 , *UpperCAmel... | 700 |
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 | 0 |
from __future__ import annotations
def UpperCAmelCase ( _snake_case ):
# preprocessing the first row
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
for i in range(1 , ... | 701 |
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 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ ={
'configuration_nllb_moe': [
'NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP',
'NllbMoeConfig',
]
}
try:
if not is_torch_available():
raise Optional... | 702 |
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 | 0 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common i... | 703 |
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 | 0 |
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class __UpperCamelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self , UpperC... | 704 |
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 | 0 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_co... | 705 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ ={
"""configuration_jukebox""": [
"""JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""JukeboxConfig""",
"""JukeboxPriorConfig""",
... | 33 | 0 |
def UpperCAmelCase ( _snake_case ):
if not all(char in '''01''' for char in bin_string ):
raise ValueError('''Non-binary value was passed to the function''' )
if not bin_string:
raise ValueError('''Empty string was passed to the... | 706 |
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 | 0 |
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
UpperCAmelCase_ ={
"""kakaobrain/align-base""": """https://huggin... | 707 |
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 | 0 |
import numpy
# List of input, output pairs
UpperCAmelCase_ =(
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
UpperCAmelCase_ =(((515, 22, 13), 555), ((61, 35, 49), 150))
UpperCAmelCase_ =[2, 4, 1, 5]
UpperCAmelCase_ ... | 708 |
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 | 0 |
from __future__ import annotations
class __UpperCamelCase :
'''simple docstring'''
def __init__( self , UpperCAmelCase_ ):
lowerCAmelCase = order
# a_{0} ... a_{k}
lowerCAmelCase = [1.0] + [0.0] * order
... | 709 |
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 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcessor,
... | 710 |
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 | 0 |
'''simple docstring'''
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
UpperCAmelCase_ =logging.get_logger(__name__)
... | 711 |
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 | 0 |
def UpperCAmelCase ( _snake_case = 1000 ):
lowerCAmelCase = 3
lowerCAmelCase = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
... | 712 |
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 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
UpperCAmelCase_ ={
"""configuration_ernie""": ["""ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ErnieConfig""", """ErnieOnnxConfig"""],
}
try:
... | 713 |
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 | 0 |
import inspect
import unittest
class __UpperCamelCase ( unittest.TestCase ):
'''simple docstring'''
def __snake_case ( self ):
try:
import diffusers # noqa: F401
except ImportError:
assert ... | 714 |
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 | 0 |
import tensorflow as tf
from ...tf_utils import shape_list
class __UpperCamelCase ( tf.keras.layers.Layer ):
'''simple docstring'''
def __init__( self , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelC... | 715 |
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 | 0 |
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.toke... | 716 |
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 | 0 |
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