code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
_UpperCamelCase = TypeVar("""T""")
class lowerCamelCase__ ( Generic[T] ):
def __init__( self ,A ):
UpperCAmelCas... | 711 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class lowerCamelCase__ :
def __init__( self ,A ,A ):
if len(A ) != degree + 1:
raise ValueError(
"""The number o... | 74 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers impor... | 712 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common imp... | 74 | 0 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class lowerCamelCase__ ( snake_case ):
def __init__( self ):
# test for the above condition
self.test()
def _UpperCamelCase ( se... | 713 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
_Up... | 74 | 0 |
"""simple docstring"""
_UpperCamelCase = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("""3.7"""):
raise ImportWarning(
"""To use `datasets`, Python>=3.7 is required, and the current version of Py... | 714 |
"""simple docstring"""
def _a ( _snake_case ): # noqa: E741
"""simple docstring"""
UpperCAmelCase = len(_snake_case )
UpperCAmelCase = 0
UpperCAmelCase = [0] * n
UpperCAmelCase = [False] * n
UpperCAmel... | 74 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)... | 715 |
"""simple docstring"""
_UpperCamelCase = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_... | 74 | 0 |
"""simple docstring"""
def _a ( _snake_case ):
"""simple docstring"""
UpperCAmelCase = [0] * len(_snake_case )
for i in range(1 , len(_snake_case ) ):
# use last results for better performance - dynamic programming
... | 716 |
"""simple docstring"""
import argparse
import struct
import unittest
class lowerCamelCase__ :
def __init__( self ,A ):
UpperCAmelCase = data
# Initialize hash values
UpperCAmelCase = [
0x6A_09_E6_67,
... | 74 | 0 |
"""simple docstring"""
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 Accele... | 717 |
"""simple docstring"""
def _a ( _snake_case = 10 , _snake_case = 22 ):
"""simple docstring"""
UpperCAmelCase = range(1 , _snake_case )
UpperCAmelCase = range(1 , _snake_case )
return sum(
1 for power in powers fo... | 74 | 0 |
"""simple docstring"""
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_... | 718 |
"""simple docstring"""
from __future__ import annotations
def _a ( _snake_case ):
"""simple docstring"""
return len(set(_snake_case ) ) == len(_snake_case )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 74 | 0 |
"""simple docstring"""
from __future__ import annotations
from statistics import mean
def _a ( _snake_case , _snake_case , _snake_case ):
"""simple docstring"""
UpperCAmelCase = [0] * no_of_processes
UpperCAmelCase = [0] * no_of_processes
... | 719 |
"""simple docstring"""
import math
def _a ( _snake_case ):
"""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, 0, 1, all even numbers, all... | 74 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffuser... | 720 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase__ ( snake_case ):
SCREAMING_SNAKE_CASE = ['''image_processor''', '''tokenizer''']
SCREAMING_SNAKE_CASE = '''CL... | 74 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
_UpperCamelCase = TypeVar("""T""")
class lowerCamelCase__ ( Generic[T] ):
def __init__( self ,A ):
UpperCAmelCase = data
Up... | 721 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_UpperCamelCase = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def _a ( _snake_case = "mumbai" ):
"""simple d... | 74 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase = {"""configuration_fnet""": ["""FNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FNetConfig"""... | 700 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class lowerCamelCase__ ( unittest.TestCase ):
def _UpperCamelCase ( ... | 74 | 0 |
"""simple docstring"""
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
_UpperCamelCase = mod... | 701 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class lowerCamelCase__ :
def __init__( self ,A = 6 ):
UpperCAmelCase = None
UpperCAmelCase = None
self.create_linked_list(A )
... | 74 | 0 |
"""simple docstring"""
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_UpperCamelCase = get_test... | 702 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_UpperCamelCase = logging.get_logger("""transformers.models.speecht5""")
def _a ( _snake_case , _snake_case , _... | 74 | 0 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 703 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_UpperCamelCase = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < v... | 74 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase ... | 704 |
"""simple docstring"""
def _a ( _snake_case ):
"""simple docstring"""
if not isinstance(_snake_case , _snake_case ):
raise ValueError("""Input must be an integer""" )
if input_num <= 0:
raise ValueError("""Input must be positive... | 74 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_UpperCamelCase = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Lay... | 705 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTenso... | 74 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_UpperCamelCase = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER... | 706 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArg... | 74 | 0 |
"""simple docstring"""
import os
import sys
import unittest
_UpperCamelCase : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_dummies # noqa: E402
from check_dummies impo... | 707 |
"""simple docstring"""
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelT... | 74 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase ... | 708 |
"""simple docstring"""
from math import sqrt
def _a ( _snake_case = 100_0000 ):
"""simple docstring"""
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
... | 74 | 0 |
"""simple docstring"""
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
_UpperCamelCase = yaml.safe_load(
"""\
name: \"\"
allow_empty: fals... | 709 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
_UpperCamelCase = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
"""attn""... | 74 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vi... | 710 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[de... | 74 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {}
class lowerCamelCase__ ( snake_case ):
SCREAMING_SNAKE_CASE = '''llama'''
SCREA... | 711 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class lowerCamelCase__ :
def __init__( self ,A ,A ):
if len(A ) != degree + 1:
raise ValueError(
"""The number o... | 74 | 0 |
"""simple docstring"""
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version(""">=""", FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.dist... | 712 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common imp... | 74 | 0 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def _a ( _snake_case , _snake_case , _snake_case = None ) -> str:
"""simple docstring"""
if version.parse(hfh.__versio... | 713 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
_Up... | 74 | 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__)
if is_torc... | 714 |
"""simple docstring"""
def _a ( _snake_case ): # noqa: E741
"""simple docstring"""
UpperCAmelCase = len(_snake_case )
UpperCAmelCase = 0
UpperCAmelCase = [0] * n
UpperCAmelCase = [False] * n
UpperCAmel... | 74 | 0 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, ... | 715 |
"""simple docstring"""
_UpperCamelCase = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_... | 74 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffus... | 716 |
"""simple docstring"""
import argparse
import struct
import unittest
class lowerCamelCase__ :
def __init__( self ,A ):
UpperCAmelCase = data
# Initialize hash values
UpperCAmelCase = [
0x6A_09_E6_67,
... | 74 | 0 |
"""simple docstring"""
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_config... | 717 |
"""simple docstring"""
def _a ( _snake_case = 10 , _snake_case = 22 ):
"""simple docstring"""
UpperCAmelCase = range(1 , _snake_case )
UpperCAmelCase = range(1 , _snake_case )
return sum(
1 for power in powers fo... | 74 | 0 |
"""simple docstring"""
from math import isclose, sqrt
def _a ( _snake_case , _snake_case , _snake_case ):
"""simple docstring"""
UpperCAmelCase = point_y / 4 / point_x
UpperCAmelCase = 2 * normal_gradient / (1 + normal_gradient * normal_grad... | 718 |
"""simple docstring"""
from __future__ import annotations
def _a ( _snake_case ):
"""simple docstring"""
return len(set(_snake_case ) ) == len(_snake_case )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 74 | 0 |
"""simple docstring"""
from math import sqrt
def _a ( _snake_case = 100_0000 ):
"""simple docstring"""
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
... | 719 |
"""simple docstring"""
import math
def _a ( _snake_case ):
"""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, 0, 1, all even numbers, all... | 74 | 0 |
"""simple docstring"""
import re
from ..models.auto import AutoProcessor
from ..models.vision_encoder_decoder import VisionEncoderDecoderModel
from ..utils import is_vision_available
from .base import PipelineTool
if is_vision_available():
from PIL import Image
class lowerCamelCase__ ( ... | 720 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase__ ( snake_case ):
SCREAMING_SNAKE_CASE = ['''image_processor''', '''tokenizer''']
SCREAMING_SNAKE_CASE = '''CL... | 74 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common imp... | 721 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_UpperCamelCase = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def _a ( _snake_case = "mumbai" ):
"""simple d... | 74 | 0 |
from __future__ import annotations
def _a ( _snake_case ):
"""simple docstring"""
UpperCAmelCase = [True] * limit
UpperCAmelCase = False
UpperCAmelCase = False
UpperCAmelCase = True
for i in range(3 , int(limit*... | 700 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class lowerCamelCase__ ( unittest.TestCase ):
def _UpperCamelCase ( ... | 74 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 701 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class lowerCamelCase__ :
def __init__( self ,A = 6 ):
UpperCAmelCase = None
UpperCAmelCase = None
self.create_linked_list(A )
... | 74 | 0 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_visio... | 702 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_UpperCamelCase = logging.get_logger("""transformers.models.speecht5""")
def _a ( _snake_case , _snake_case , _... | 74 | 0 |
"""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... | 703 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_UpperCamelCase = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < v... | 74 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
"""vinvino02/glpn-kitti""": """https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json""",
... | 704 |
"""simple docstring"""
def _a ( _snake_case ):
"""simple docstring"""
if not isinstance(_snake_case , _snake_case ):
raise ValueError("""Input must be an integer""" )
if input_num <= 0:
raise ValueError("""Input must be positive... | 74 | 0 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisionConfig,
)
def _a ... | 705 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTenso... | 74 | 0 |
"""simple docstring"""
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_... | 706 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArg... | 74 | 0 |
"""simple docstring"""
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import ... | 707 |
"""simple docstring"""
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelT... | 74 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
"""uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.jso... | 708 |
"""simple docstring"""
from math import sqrt
def _a ( _snake_case = 100_0000 ):
"""simple docstring"""
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
... | 74 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from... | 709 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
_UpperCamelCase = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
"""attn""... | 74 | 0 |
"""simple docstring"""
_UpperCamelCase = """Input must be a string of 8 numbers plus letter"""
_UpperCamelCase = """TRWAGMYFPDXBNJZSQVHLCKE"""
def _a ( _snake_case ):
"""simple docstring"""
if not isinstance(_snake_case , _snake_case ):
... | 710 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[de... | 74 | 0 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_... | 711 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class lowerCamelCase__ :
def __init__( self ,A ,A ):
if len(A ) != degree + 1:
raise ValueError(
"""The number o... | 74 | 0 |
"""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
_UpperCamelCase = {"""vocab_file""": """vocab.txt""", """tokenizer_file"""... | 712 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common imp... | 74 | 0 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTenso... | 713 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
_Up... | 74 | 0 |
"""simple docstring"""
def _a ( _snake_case , _snake_case ):
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
UpperCAmelCase = str(bin(_snake_case ) )[2:] # remov... | 714 |
"""simple docstring"""
def _a ( _snake_case ): # noqa: E741
"""simple docstring"""
UpperCAmelCase = len(_snake_case )
UpperCAmelCase = 0
UpperCAmelCase = [0] * n
UpperCAmelCase = [False] * n
UpperCAmel... | 74 | 0 |
"""simple docstring"""
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from da... | 715 |
"""simple docstring"""
_UpperCamelCase = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_... | 74 | 0 |
"""simple docstring"""
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class lowerCamelCas... | 716 |
"""simple docstring"""
import argparse
import struct
import unittest
class lowerCamelCase__ :
def __init__( self ,A ):
UpperCAmelCase = data
# Initialize hash values
UpperCAmelCase = [
0x6A_09_E6_67,
... | 74 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common im... | 717 |
"""simple docstring"""
def _a ( _snake_case = 10 , _snake_case = 22 ):
"""simple docstring"""
UpperCAmelCase = range(1 , _snake_case )
UpperCAmelCase = range(1 , _snake_case )
return sum(
1 for power in powers fo... | 74 | 0 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Imag... | 718 |
"""simple docstring"""
from __future__ import annotations
def _a ( _snake_case ):
"""simple docstring"""
return len(set(_snake_case ) ) == len(_snake_case )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 74 | 0 |
"""simple docstring"""
def _a ( _snake_case , _snake_case , _snake_case = 0 , _snake_case = 0 ):
"""simple docstring"""
UpperCAmelCase = right or len(_snake_case ) - 1
if left > right:
return -1
elif list_data[left] == key:
... | 719 |
"""simple docstring"""
import math
def _a ( _snake_case ):
"""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, 0, 1, all even numbers, all... | 74 | 0 |
"""simple docstring"""
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils ... | 720 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase__ ( snake_case ):
SCREAMING_SNAKE_CASE = ['''image_processor''', '''tokenizer''']
SCREAMING_SNAKE_CASE = '''CL... | 74 | 0 |
"""simple docstring"""
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
r... | 721 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_UpperCamelCase = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def _a ( _snake_case = "mumbai" ):
"""simple d... | 74 | 0 |
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
_UpperCamelCase = abspath(join(dirname(dirname(__file__)), """src"""))
... | 700 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class lowerCamelCase__ ( unittest.TestCase ):
def _UpperCamelCase ( ... | 74 | 0 |
"""simple docstring"""
def _a ( _snake_case ):
"""simple docstring"""
return "".join([hex(_snake_case )[2:].zfill(2 ).upper() for byte in list(_snake_case )] )
def _a ( _snake_case ):
"""simple docstring"""
if (le... | 701 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class lowerCamelCase__ :
def __init__( self ,A = 6 ):
UpperCAmelCase = None
UpperCAmelCase = None
self.create_linked_list(A )
... | 74 | 0 |
"""simple docstring"""
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
_UpperCamelCase = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow(""""... | 702 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_UpperCamelCase = logging.get_logger("""transformers.models.speecht5""")
def _a ( _snake_case , _snake_case , _... | 74 | 0 |
"""simple docstring"""
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from to... | 703 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_UpperCamelCase = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < v... | 74 | 0 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
_Up... | 704 |
"""simple docstring"""
def _a ( _snake_case ):
"""simple docstring"""
if not isinstance(_snake_case , _snake_case ):
raise ValueError("""Input must be an integer""" )
if input_num <= 0:
raise ValueError("""Input must be positive... | 74 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, sl... | 705 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTenso... | 74 | 0 |
"""simple docstring"""
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 lowerCamelCase__ ( unittest.TestCase ):
'''sim... | 706 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArg... | 74 | 0 |
"""simple docstring"""
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock i... | 707 |
"""simple docstring"""
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelT... | 74 | 0 |
"""simple docstring"""
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 ... | 708 |
"""simple docstring"""
from math import sqrt
def _a ( _snake_case = 100_0000 ):
"""simple docstring"""
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
... | 74 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
"""s-JoL/Open-Llama-V1""": """https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/con... | 709 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
_UpperCamelCase = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
"""attn""... | 74 | 0 |
"""simple docstring"""
from __future__ import annotations
_UpperCamelCase = tuple[int, int, int]
_UpperCamelCase = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
_UpperCamelCase = """ABCDEFGHIJKLMNOPQRSTUVWXYZ"""
# ----------... | 710 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[de... | 74 | 0 |
"""simple docstring"""
def _a ( _snake_case , _snake_case ):
"""simple docstring"""
UpperCAmelCase = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def _a ( _snake_case ... | 711 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class lowerCamelCase__ :
def __init__( self ,A ,A ):
if len(A ) != degree + 1:
raise ValueError(
"""The number o... | 74 | 0 |
"""simple docstring"""
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... | 712 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common imp... | 74 | 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 require_torch, requir... | 713 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
_Up... | 74 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
_UpperCamelCase = {
"""susnato/ernie-m-base_pytorch""": """https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json""",
"""susnato/er... | 714 |
"""simple docstring"""
def _a ( _snake_case ): # noqa: E741
"""simple docstring"""
UpperCAmelCase = len(_snake_case )
UpperCAmelCase = 0
UpperCAmelCase = [0] * n
UpperCAmelCase = [False] * n
UpperCAmel... | 74 | 0 |
"""simple docstring"""
class lowerCamelCase__ :
def __init__( self ):
UpperCAmelCase = {} # Mapping from char to TrieNode
UpperCAmelCase = False
def _UpperCamelCase ( self ,A ... | 715 |
"""simple docstring"""
_UpperCamelCase = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_... | 74 | 0 |
"""simple docstring"""
def _a ( _snake_case ):
"""simple docstring"""
if not isinstance(_snake_case , _snake_case ):
raise ValueError("""Input must be an integer""" )
if input_num <= 0:
raise ValueError("""Input must be positive... | 716 |
"""simple docstring"""
import argparse
import struct
import unittest
class lowerCamelCase__ :
def __init__( self ,A ):
UpperCAmelCase = data
# Initialize hash values
UpperCAmelCase = [
0x6A_09_E6_67,
... | 74 | 0 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArg... | 717 |
"""simple docstring"""
def _a ( _snake_case = 10 , _snake_case = 22 ):
"""simple docstring"""
UpperCAmelCase = range(1 , _snake_case )
UpperCAmelCase = range(1 , _snake_case )
return sum(
1 for power in powers fo... | 74 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_UpperCamelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailab... | 718 |
"""simple docstring"""
from __future__ import annotations
def _a ( _snake_case ):
"""simple docstring"""
return len(set(_snake_case ) ) == len(_snake_case )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 74 | 0 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils im... | 719 |
"""simple docstring"""
import math
def _a ( _snake_case ):
"""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, 0, 1, all even numbers, all... | 74 | 0 |
"""simple docstring"""
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowerCamelCase__ :
def __init__( self ,A ,A ,A ):
if dst_width < 0 or dst_height < 0:
raise ValueError("""Destination width/height shou... | 720 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase__ ( snake_case ):
SCREAMING_SNAKE_CASE = ['''image_processor''', '''tokenizer''']
SCREAMING_SNAKE_CASE = '''CL... | 74 | 0 |
"""simple docstring"""
import os
import sys
import unittest
_UpperCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
... | 721 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_UpperCamelCase = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def _a ( _snake_case = "mumbai" ):
"""simple d... | 74 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _a ( _snake_case ):
"""simple docstring"""
UpperCAmelCase = SwinConfig(image_size=192 )
if "base" i... | 700 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class lowerCamelCase__ ( unittest.TestCase ):
def _UpperCamelCase ( ... | 74 | 0 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr imp... | 701 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class lowerCamelCase__ :
def __init__( self ,A = 6 ):
UpperCAmelCase = None
UpperCAmelCase = None
self.create_linked_list(A )
... | 74 | 0 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
_UpperCamelCase = """examples/"""
_UpperCamelCase = {
"""examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""": ... | 702 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_UpperCamelCase = logging.get_logger("""transformers.models.speecht5""")
def _a ( _snake_case , _snake_case , _... | 74 | 0 |
"""simple docstring"""
def _a ( _snake_case ):
"""simple docstring"""
UpperCAmelCase = [0 for i in range(len(_snake_case ) )]
# initialize interval's left pointer and right pointer
UpperCAmelCase , UpperCAmelCase = ... | 703 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_UpperCamelCase = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < v... | 74 | 0 |
"""simple docstring"""
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _a ( _snake_case , _snake_case , **_snake_case ):
"""simple docstring"""
UpperCAmelCase = AutoConfig.from_pretrained(_snake_case , **_snake_c... | 704 |
"""simple docstring"""
def _a ( _snake_case ):
"""simple docstring"""
if not isinstance(_snake_case , _snake_case ):
raise ValueError("""Input must be an integer""" )
if input_num <= 0:
raise ValueError("""Input must be positive... | 74 | 0 |
def _a ( _snake_case ):
"""simple docstring"""
if n == 1 or not isinstance(_snake_case , _snake_case ):
return 0
elif n == 2:
return 1
else:
UpperCAmelCase = [0, 1]
for i in range(2 , n + 1 ):
... | 705 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTenso... | 74 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig""... | 706 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArg... | 74 | 0 |
"""simple docstring"""
class lowerCamelCase__ :
def __init__( self ,A ):
# we need a list not a string, so do something to change the type
UpperCAmelCase = arr.split(""",""" )
def _UpperCamelCase ( self ):
... | 707 |
"""simple docstring"""
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelT... | 74 | 0 |
"""simple docstring"""
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 ..... | 708 |
"""simple docstring"""
from math import sqrt
def _a ( _snake_case = 100_0000 ):
"""simple docstring"""
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
... | 74 | 0 |
"""simple docstring"""
import math
def _a ( _snake_case ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Ne... | 709 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
_UpperCamelCase = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
"""attn""... | 74 | 0 |
"""simple docstring"""
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class lowerCamelCase__ ( snake_case ):
def __init__( self ,A="" ,A="train" ):
assert os.path.isdir(A )
UpperCAmelCase ... | 710 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[de... | 74 | 0 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline... | 711 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class lowerCamelCase__ :
def __init__( self ,A ,A ):
if len(A ) != degree + 1:
raise ValueError(
"""The number o... | 74 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class lowerCamelCase__ :
def __init__( self ,A ,A ):
if len(A ) != degree + 1:
raise ValueError(
"""The number of coeff... | 712 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common imp... | 74 | 0 |
"""simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class lowerCamelCase__ :
def __init__( self ,A ,A ,A ,A ,A ,A=0.2 ,A=0.2 ):
UpperCAmelCase = bp_numa
UpperCAmelCase = bp_n... | 713 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
_Up... | 74 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_... | 714 |
"""simple docstring"""
def _a ( _snake_case ): # noqa: E741
"""simple docstring"""
UpperCAmelCase = len(_snake_case )
UpperCAmelCase = 0
UpperCAmelCase = [0] * n
UpperCAmelCase = [False] * n
UpperCAmel... | 74 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_UpperCamelCase = {"""configuration_swin""": ["""SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SwinConfig""", """SwinOn... | 715 |
"""simple docstring"""
_UpperCamelCase = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_... | 74 | 0 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
"""ut/deta""": """https://huggingface.co/ut/deta/resolve/main... | 716 |
"""simple docstring"""
import argparse
import struct
import unittest
class lowerCamelCase__ :
def __init__( self ,A ):
UpperCAmelCase = data
# Initialize hash values
UpperCAmelCase = [
0x6A_09_E6_67,
... | 74 | 0 |
"""simple docstring"""
import argparse
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... | 717 |
"""simple docstring"""
def _a ( _snake_case = 10 , _snake_case = 22 ):
"""simple docstring"""
UpperCAmelCase = range(1 , _snake_case )
UpperCAmelCase = range(1 , _snake_case )
return sum(
1 for power in powers fo... | 74 | 0 |
"""simple docstring"""
import argparse
import struct
import unittest
class lowerCamelCase__ :
def __init__( self ,A ):
UpperCAmelCase = data
# Initialize hash values
UpperCAmelCase = [
0x6A_09_E6_67,
... | 718 |
"""simple docstring"""
from __future__ import annotations
def _a ( _snake_case ):
"""simple docstring"""
return len(set(_snake_case ) ) == len(_snake_case )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 74 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_... | 719 |
"""simple docstring"""
import math
def _a ( _snake_case ):
"""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, 0, 1, all even numbers, all... | 74 | 0 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
_UpperCamelCase = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
"""attn""": "... | 720 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase__ ( snake_case ):
SCREAMING_SNAKE_CASE = ['''image_processor''', '''tokenizer''']
SCREAMING_SNAKE_CASE = '''CL... | 74 | 0 |
"""simple docstring"""
def _a ( _snake_case ):
"""simple docstring"""
if edge <= 0 or not isinstance(_snake_case , _snake_case ):
raise ValueError("""Length must be a positive.""" )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge... | 721 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_UpperCamelCase = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def _a ( _snake_case = "mumbai" ):
"""simple d... | 74 | 0 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__A : int = '%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('Search: ')))
print('Googling.....')
__A... | 75 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A : Union[str, Any] = logging.get_logger(__name__)
__A : Optional[Any] = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
class _SCRE... | 75 | 1 |
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