code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils impor... | 673 |
"""simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessin... | 673 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
lowerCAmelCase_ : Optional[Any] = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithP... | 673 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import c... | 673 | 1 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
lowerCAmelCase_ : str = (7_2_0, 1_2_8_0) # Height, Width
lowerCAmelCase_ : Optional[int] = (0.4, 0.6) # if height or w... | 673 |
"""simple docstring"""
import socket
def _lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
UpperCAmelCase = socket.gethostname()
UpperCAmelCase ... | 673 | 1 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCAmelCase_ : D... | 673 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
return math.sqrt(lowerCAmelCase ) * math.sqrt(lowerCAmelCase ) == num
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
... | 673 | 1 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import T... | 673 |
"""simple docstring"""
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def _lowerCAmelCase ( *lowerCAmelCase ):
'''simple docstring'''
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
... | 673 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ : Dict = {
'''configuration_bigbird_pegasus''': [
'''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''B... | 673 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase = 100 ):
'''simple docstring'''
UpperCAmelCase = sum(i * i for i in range(1 , n + 1 ) )
UpperCAmelCase = int(math.pow(sum(range(1 , n + 1 ) ... | 673 | 1 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
... | 673 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase = [0] * len(lowerCAmelCase )
UpperCAmelCase = []
UpperCAmelCase = [1] * len(lowerCAmelCase )
for values... | 673 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
lowerCAmelCase_ : List[str] = {'''vocab_file''': '''vocab.... | 673 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | 673 | 1 |
"""simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from... | 673 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class UpperCamelCase_ ( a_ )... | 673 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase_ ( a_ , unittest.TestCase ):
_A : str ... | 673 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase_ : Any = {
'''configuration_encodec''': [
'''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''E... | 673 | 1 |
"""simple docstring"""
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutpu... | 673 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyN... | 673 | 1 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def _lowerCAmelCase ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase = False ):
'''simple docstring'''
... | 673 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import flo... | 673 | 1 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diff... | 673 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : int = logging.get_logger(__name__)
lowerCAmelCase_ : Any = {
'''facebook/wav2vec2-base-960h''': '''https:... | 673 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
req... | 673 |
"""simple docstring"""
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Itera... | 673 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
if number < 0:
raise ValueError("""number must not be negative""" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod(... | 673 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
lowerCAmelCase_ : List[str] = False
class UpperCamelCase_ ( ... | 673 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase = len(lowerCAmelCase )
UpperCAmelCase = len(matrix[0] )
UpperCAmelCase = min(lowerCAmelCase , lowerCAmel... | 673 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class UpperCamelCase_ :
def __init__( self , snake_case__=2 , snake_case__=3 , snake_case__=64 , snake_case__=None ) ... | 673 | 1 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives,... | 673 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class UpperCamelCase_ ( nn.Module ):
_A : int
_A : jnp.dtype = jnp.floataa
def UpperCamelCase_ ( self ) -> Dict:
"""simple docstring""... | 673 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import... | 673 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configura... | 673 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase = [0] * len(lowerCAmelCase )
UpperCAmelCase = []
UpperCAmelCase = [1] * len(lowerCAmelCase )
for values... | 673 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, NystromformerConfig, 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_... | 673 | 1 |
"""simple docstring"""
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import Pa... | 673 |
"""simple docstring"""
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLIComman... | 673 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
lowerCAmelCase_ : List[Any] ... | 673 |
"""simple docstring"""
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class UpperCamelCase_ :
def __init__( self , snake_case__ , s... | 673 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase = 100 ):
'''simple docstring'''
UpperCAmelCase = 0
UpperCAmelCase = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints ... | 673 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils im... | 673 | 1 |
"""simple docstring"""
import sys
lowerCAmelCase_ : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''125406987471585238630507156932909632... | 673 |
"""simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessin... | 673 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase = int(lowerCAmelCase )
if n_element < 1:
UpperCAmelCase = ValueError("""a should be a positive number""" )
... | 673 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import c... | 673 | 1 |
"""simple docstring"""
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def _lowerCAmelCase ( ):
'''simple docstring'''
raise RuntimeError(... | 673 |
"""simple docstring"""
import socket
def _lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
UpperCAmelCase = socket.gethostname()
UpperCAmelCase ... | 673 | 1 |
"""simple docstring"""
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCamelCase_ ( a_ ):
@require_torch
def UpperCamelCase_ ( self ) ->... | 673 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
return math.sqrt(lowerCAmelCase ) * math.sqrt(lowerCAmelCase ) == num
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
... | 673 | 1 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configurat... | 673 |
"""simple docstring"""
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def _lowerCAmelCase ( *lowerCAmelCase ):
'''simple docstring'''
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
... | 673 | 1 |
"""simple docstring"""
#
# This a `torch.distributed` diagnostics script that checks that all GPUs in the cluster (one or
# many nodes) can talk to each other via nccl and allocate gpu memory.
#
# To run first adjust the number of processes and nodes:
#
# python -m torch.distributed.run --nproc_per_node 2... | 673 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase = 100 ):
'''simple docstring'''
UpperCAmelCase = sum(i * i for i in range(1 , n + 1 ) )
UpperCAmelCase = int(math.pow(sum(range(1 , n + 1 ) ... | 673 | 1 |
"""simple docstring"""
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import... | 673 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase = [0] * len(lowerCAmelCase )
UpperCAmelCase = []
UpperCAmelCase = [1] * len(lowerCAmelCase )
for values... | 673 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ : List[Any] ... | 673 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | 673 | 1 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
return math.sqrt(lowerCAmelCase ) * math.sqrt(lowerCAmelCase ) == num
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
... | 673 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class UpperCamelCase_ ( a_ )... | 673 | 1 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def _lowerCAmelCase ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase = None ):
'''simple docstring'''
if ver... | 673 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase_ : Any = {
'''configuration_encodec''': [
'''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''E... | 673 | 1 |
"""simple docstring"""
import operator
def _lowerCAmelCase ( lowerCAmelCase , lowerCAmelCase = False , lowerCAmelCase = None ):
'''simple docstring'''
UpperCAmelCase = operator.lt if reverse else operator.gt
UpperCAmelCase ... | 673 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyN... | 673 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase = 1000 ):
'''simple docstring'''
UpperCAmelCase = 2**power
UpperCAmelCase = str(lowerCAmelCase )
UpperCAmelCase = list(lowerCAmelCase )
UpperCAme... | 673 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import flo... | 673 | 1 |
"""simple docstring"""
from __future__ import annotations
import os
from typing import Any
import requests
lowerCAmelCase_ : Optional[int] = '''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowerCAmelCase_... | 673 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : int = logging.get_logger(__name__)
lowerCAmelCase_ : Any = {
'''facebook/wav2vec2-base-960h''': '''https:... | 673 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 673 |
"""simple docstring"""
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Itera... | 673 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformer... | 673 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
lowerCAmelCase_ : List[str] = False
class UpperCamelCase_ ( ... | 673 | 1 |
"""simple docstring"""
# 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 con... | 673 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class UpperCamelCase_ :
def __init__( self , snake_case__=2 , snake_case__=3 , snake_case__=64 , snake_case__=None ) ... | 673 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase , lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase = len(lowerCAmelCase ) + 1
UpperCAmelCase = len(lowerCAmelCase ) + 1
# dp is a 2d matrix where dp[i][... | 673 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class UpperCamelCase_ ( nn.Module ):
_A : int
_A : jnp.dtype = jnp.floataa
def UpperCamelCase_ ( self ) -> Dict:
"""simple docstring""... | 673 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
fr... | 673 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configura... | 673 | 1 |
def __lowercase ( snake_case, snake_case, snake_case ):
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def __lowercase ( snake_case, snake_case, snake_case ):
"""simple docstring"""
return round(float((moles * 0.0821 *... | 0 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, NystromformerConfig, 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_... | 673 | 0 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is... | 1 |
"""simple docstring"""
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLIComman... | 673 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class lowerCamelCase__ ( _A):
"""simple docstring"""... | 2 |
"""simple docstring"""
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class UpperCamelCase_ :
def __init__( self , snake_case__ , s... | 673 | 0 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def A_( A... | 3 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils im... | 673 | 0 |
"""simple docstring"""
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to... | 4 |
"""simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessin... | 673 | 0 |
'''simple docstring'''
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
_lowercase = logging.get_log... | 5 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import c... | 673 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 6 |
"""simple docstring"""
import socket
def _lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
UpperCAmelCase = socket.gethostname()
UpperCAmelCase ... | 673 | 0 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class lowercase_ ( unittest.TestCase , __lowerCAmelCase ):
'''simple docstring'''
def lowerCAmelCase_ ( self : Optional[Any] ):
_A ... | 7 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
return math.sqrt(lowerCAmelCase ) * math.sqrt(lowerCAmelCase ) == num
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
... | 673 | 0 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import req... | 8 |
"""simple docstring"""
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def _lowerCAmelCase ( *lowerCAmelCase ):
'''simple docstring'''
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
... | 673 | 0 |
import os
import string
import sys
SCREAMING_SNAKE_CASE__ = 1 << 8
SCREAMING_SNAKE_CASE__ = {
'''tab''': ord('''\t'''),
'''newline''': ord('''\r'''),
'''esc''': 2_7,
'''up''': 6_5 + ARROW_KEY_FLAG,
'''down''': 6_6 + ARROW_KEY_FLAG,
'''right''': 6_7 + ARROW_KEY_FLAG,
'''l... | 9 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase = 100 ):
'''simple docstring'''
UpperCAmelCase = sum(i * i for i in range(1 , n + 1 ) )
UpperCAmelCase = int(math.pow(sum(range(1 , n + 1 ) ... | 673 | 0 |
import sys
from collections import defaultdict
class lowerCAmelCase_ :
def __init__( self : Optional[int] ):
_UpperCamelCase = []
def UpperCamelCase_ ( self : Any , _A : str ):
return self.node_position[verte... | 10 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase = [0] * len(lowerCAmelCase )
UpperCAmelCase = []
UpperCAmelCase = [1] * len(lowerCAmelCase )
for values... | 673 | 0 |
'''simple docstring'''
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPP... | 11 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | 673 | 0 |
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 _snake_case ( unittest.TestCase ):
def lowercase__ ( self):
... | 12 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class UpperCamelCase_ ( a_ )... | 673 | 0 |
'''simple docstring'''
def UpperCAmelCase__ ( UpperCAmelCase_ : int , UpperCAmelCase_ : int ) -> str:
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
__lowerCamelCase : int = str(bin... | 13 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase_ : Any = {
'''configuration_encodec''': [
'''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''E... | 673 | 0 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def __UpperCAmelCase ( ) -> None:
"""simple docstring"""
print('''Making key files...''' )
make_key_files('''r... | 14 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyN... | 673 | 0 |
def UpperCamelCase ( __magic_name__ : int , __magic_name__ : int ) -> str:
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
lowercase__ = str(bin(__magic_name__ ) )[2:] # remove the lea... | 15 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import flo... | 673 | 0 |
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 _SCREAMING_SNAKE_CASE ( unittest.TestCase ):
... | 16 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : int = logging.get_logger(__name__)
lowerCAmelCase_ : Any = {
'''facebook/wav2vec2-base-960h''': '''https:... | 673 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ : Any = {
'''configuration_data2vec_audio''': ['''DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Data2VecAudioConfig'''],
'''configuratio... | 17 |
"""simple docstring"""
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Itera... | 673 | 0 |
'''simple docstring'''
from __future__ import annotations
class lowerCAmelCase_ :
def __init__( self , _lowerCAmelCase ) -> None:
_lowerCAmelCase = data
_lowerCAmelCase = None
_lowerCAmelCase = None
def __a(SCREAMING_S... | 18 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
lowerCAmelCase_ : List[str] = False
class UpperCamelCase_ ( ... | 673 | 0 |
"""simple docstring"""
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils impo... | 19 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class UpperCamelCase_ :
def __init__( self , snake_case__=2 , snake_case__=3 , snake_case__=64 , snake_case__=None ) ... | 673 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase: Union[str, Any] = {
'configuration_roformer': ['ROFORMER_PRETRAINED_... | 20 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class UpperCamelCase_ ( nn.Module ):
_A : int
_A : jnp.dtype = jnp.floataa
def UpperCamelCase_ ( self ) -> Dict:
"""simple docstring""... | 673 | 0 |
from __future__ import annotations
def lowerCAmelCase_ ( lowerCamelCase , lowerCamelCase ):
__magic_name__ : Tuple =sorted(numsa + numsa )
__magic_name__ , __magic_name__ : Optional[Any] =divmod(len(lowerCamelCase ) , 2 )
i... | 21 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configura... | 673 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case : Union[str, Any] = logging.get_logger(__name__)
_snake_case : Optional[int] = {
'asapp/sew-d-tiny-100k': 'https://hug... | 22 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, NystromformerConfig, 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_... | 673 | 0 |
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING:
... | 23 |
"""simple docstring"""
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLIComman... | 673 | 0 |
'''simple docstring'''
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
clas... | 24 |
"""simple docstring"""
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class UpperCamelCase_ :
def __init__( self , snake_case__ , s... | 673 | 0 |
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowerCamelCase__ ( _a):
SCREAMING_SNAKE_CASE : Optional[Any] = [
"encoder.version",
"decoder.version",
"model.encoder.version",
"model.decoder.vers... | 25 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils im... | 673 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
__UpperCamelCa... | 26 |
"""simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessin... | 673 | 0 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
__A : Union[str, Any] = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, ... | 27 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import c... | 673 | 0 |
'''simple docstring'''
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
UpperCamelCase_ = logging.getLogger(__name__)
... | 28 |
"""simple docstring"""
import socket
def _lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
UpperCAmelCase = socket.gethostname()
UpperCAmelCase ... | 673 | 0 |
"""simple docstring"""
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMM... | 29 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
return math.sqrt(lowerCAmelCase ) * math.sqrt(lowerCAmelCase ) == num
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
... | 673 | 0 |
import colorsys
from PIL import Image # type: ignore
def lowerCamelCase__ ( _lowercase , _lowercase , _lowercase ):
'''simple docstring'''
UpperCAmelCase_ : Union[str, Any] = x
UpperCAmelCase_ : List[str] = y
for step in range(_lowercase ): # ... | 30 |
"""simple docstring"""
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def _lowerCAmelCase ( *lowerCAmelCase ):
'''simple docstring'''
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
... | 673 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
... | 31 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase = 100 ):
'''simple docstring'''
UpperCAmelCase = sum(i * i for i in range(1 , n + 1 ) )
UpperCAmelCase = int(math.pow(sum(range(1 , n + 1 ) ... | 673 | 0 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils im... | 32 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase = [0] * len(lowerCAmelCase )
UpperCAmelCase = []
UpperCAmelCase = [1] * len(lowerCAmelCase )
for values... | 673 | 0 |
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
fr... | 33 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | 673 | 0 |
"""simple docstring"""
import random
class snake_case_ :
"""simple docstring"""
@staticmethod
def UpperCAmelCase__ ( lowerCamelCase_) -> tuple[list[int], list[int]]:
UpperCamelCase = [ord(lowerCamelCase_) for i in text]
UpperCamelCase ... | 34 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class UpperCamelCase_ ( a_ )... | 673 | 0 |
from __future__ import annotations
def a ( A__ ) -> bool:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Union[str, Any] = str(A__ )
return len(A__ ) == 9 and set(A__ ) == set('''123456789''' )
def a ( ) -> int | No... | 35 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase_ : Any = {
'''configuration_encodec''': [
'''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''E... | 673 | 0 |
from __future__ import annotations
import math
class _A :
'''simple docstring'''
def __init__( self ,SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case : Dict = size
# approximate the overall size of segment tree with given value
snake_ca... | 36 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyN... | 673 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
i... | 37 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import flo... | 673 | 0 |
'''simple docstring'''
import math
def UpperCamelCase__ ( __magic_name__ : int ) -> int:
'''simple docstring'''
if not isinstance(__magic_name__ , __magic_name__ ):
snake_case__ : Union[str, Any] = f"Input value of [number={number}] must be an i... | 38 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : int = logging.get_logger(__name__)
lowerCAmelCase_ : Any = {
'''facebook/wav2vec2-base-960h''': '''https:... | 673 | 0 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
lowerCAmelCase_ = '''sshleifer/bart-tiny-rando... | 39 |
"""simple docstring"""
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Itera... | 673 | 0 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, requi... | 40 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
lowerCAmelCase_ : List[str] = False
class UpperCamelCase_ ( ... | 673 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase_ (lowerCamelCase__ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Dict = (DDPMScheduler,)
def SCREAMING_SNAK... | 41 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class UpperCamelCase_ :
def __init__( self , snake_case__=2 , snake_case__=3 , snake_case__=64 , snake_case__=None ) ... | 673 | 0 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 42 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class UpperCamelCase_ ( nn.Module ):
_A : int
_A : jnp.dtype = jnp.floataa
def UpperCamelCase_ ( self ) -> Dict:
"""simple docstring""... | 673 | 0 |
def _a ( SCREAMING_SNAKE_CASE = 10_00 ):
"""simple docstring"""
lowercase__ = 2**power
lowercase__ = str(SCREAMING_SNAKE_CASE )
lowercase__ = list(SCREAMING_SNAKE_CASE )
lowercase__ = 0
for i in list_num:
sum_of_num += int(SCREAMING_SNAKE_CASE )
retur... | 43 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configura... | 673 | 0 |
'''simple docstring'''
def A_ ( _lowerCAmelCase : Optional[int] ):
"""simple docstring"""
_lowerCamelCase : int = len(_lowerCAmelCase )
_lowerCamelCase : Dict = sum(_lowerCAmelCase )
_lowerCamelCase : List[Any] = [[False for x i... | 44 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, NystromformerConfig, 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_... | 673 | 0 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
UpperCamelCase = get_tests_dir("fixtures/test_sentencepiece_with_bytefallback.m... | 45 |
"""simple docstring"""
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLIComman... | 673 | 0 |
"""simple docstring"""
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def lowerCamelCase_( _lowerCamelCase ) -> Tuple:
'''simple docstring'''
def is_in_circle(_lowerCamelCase , _lowerCamelCase ... | 46 |
"""simple docstring"""
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class UpperCamelCase_ :
def __init__( self , snake_case__ , s... | 673 | 0 |
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class _UpperCamelCase( __lowerCamelCase ):
__SCREAMING_SNAKE_CASE : Any = '''MCTCTFeatureExtractor'''
__SCREAMING_SNAKE_CASE : Tuple = ... | 47 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils im... | 673 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, r... | 48 |
"""simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessin... | 673 | 0 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def lowercase__ ( snake_case_ :Tuple ):
__UpperCAmelCase = args.pruning_method
__UpperCAmelCase ... | 49 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import c... | 673 | 0 |
'''simple docstring'''
from collections.abc import Generator
def A__ ( ):
lowerCamelCase__ , lowerCamelCase__ = 0, 1
while True:
lowerCamelCase__ , lowerCamelCase__ = b, a + b
yield b
def A__ ( __lowerCAmelCa... | 50 |
"""simple docstring"""
import socket
def _lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
UpperCAmelCase = socket.gethostname()
UpperCAmelCase ... | 673 | 0 |
'''simple docstring'''
def __snake_case ( SCREAMING_SNAKE_CASE_ : str ) -> bool:
"""simple docstring"""
UpperCAmelCase = [int(SCREAMING_SNAKE_CASE_ ) for i in ip_va_address.split('''.''' ) if i.isdigit()]
return len(SCREAMING_SNAKE_CASE_ ) == 4 and all(0 <= int(S... | 51 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
return math.sqrt(lowerCAmelCase ) * math.sqrt(lowerCAmelCase ) == num
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
... | 673 | 0 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE... | 52 |
"""simple docstring"""
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def _lowerCAmelCase ( *lowerCAmelCase ):
'''simple docstring'''
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
... | 673 | 0 |
import requests
_snake_case : Tuple = '' # <-- Put your OpenWeatherMap appid here!
_snake_case : Dict = 'https://api.openweathermap.org/data/2.5/'
def a_ ( lowerCAmelCase_ : str = "Chicago", lowerCAmelCase_ : str = APPID ):
return reque... | 53 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCAmelCase = 100 ):
'''simple docstring'''
UpperCAmelCase = sum(i * i for i in range(1 , n + 1 ) )
UpperCAmelCase = int(math.pow(sum(range(1 , n + 1 ) ... | 673 | 0 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def a__ ( lowercase__ ):
'''simple docstring'''
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
class A ... | 54 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase = [0] * len(lowerCAmelCase )
UpperCAmelCase = []
UpperCAmelCase = [1] * len(lowerCAmelCase )
for values... | 673 | 0 |
def UpperCAmelCase ( a_ ) -> list:
"""simple docstring"""
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(a_ ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__('doctest').testmod()
| 55 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | 673 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
def _a (lowercase__ : list ) -> int:
"""simple docstring"""
if not postfix_notation:
return 0
__snake_case = {'+', '-', '*', '/'}
__snake_case = ... | 56 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class UpperCamelCase_ ( a_ )... | 673 | 0 |
def snake_case (UpperCAmelCase__ ) -> str:
if isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise TypeError('\'float\' object cannot be interpreted as an integer' )
if isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise TypeError('\... | 57 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase_ : Any = {
'''configuration_encodec''': [
'''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''E... | 673 | 0 |
"""simple docstring"""
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 __lowerCAmelCase ( __UpperCamelCase :... | 58 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyN... | 673 | 0 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
__A = logging.get_logger(__name__)
class _SCREAMING_SNAKE_CA... | 59 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import flo... | 673 | 0 |
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