code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import sys
_snake_case = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'66896648950445244523161731856403098711121722383113'
... | 353 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ ):
_A : Tuple = 0
if start < end:
_A : Tuple = randint(snake_case_,snake_case_ )
... | 343 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case = {
'''configuration_clap''': [
'''CLAP_PRETRAINED_MODEL_ARCHIVE_LIST''',
'''ClapAudioConfig''',
'''ClapConfig''',
'''ClapTextConfig''',
],
... | 354 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json"
),
}
class ... | 343 | 0 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class lowercase ( UpperCamelCase__ ):
... | 355 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
_snake_case = logging.getLogger()
def lowerCAmelCase_ ... | 343 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer
_sna... | 356 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_... | 343 | 0 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def lowerCAmelCase_ ( snake_case_ ):
monkeypatch.setattr("""datasets.utils.deprecation_utils._emitted_deprecation_warnings""",set() )
@pytest.fixture
def lowerCAmelCase_ ( ... | 357 |
def lowerCAmelCase_ ( snake_case_ = 1000 ):
_A : List[Any] = 3
_A : Tuple = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
... | 343 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class lowercase ( a_ ):
_a ... | 358 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...t... | 343 | 0 |
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForImageClassification,
MobileViTVaF... | 359 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
"configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
"tokenization_roc_bert": ["RoCBertTokenizer"],
}
try:
... | 343 | 0 |
"""simple docstring"""
import baseaa
def lowerCAmelCase_ ( snake_case_ ):
return baseaa.aaaencode(string.encode("""utf-8""" ) )
def lowerCAmelCase_ ( snake_case_ ):
return baseaa.aaadecode(snake_case_ ).decode("""utf-8""" )
if __name__... | 360 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
... | 343 | 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
_snake_case = logging.get_logger(__name__)
class lowercase ( ... | 361 |
# Copyright (c) 2021-, NVIDIA CORPORATION. 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
#
# Unless required by... | 343 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
_snake_case = {
"configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}
try:
if not is_torch_available():
... | 362 |
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 import BertTokenizer
_snake_case = logging.get_logger(__name__)
_snake_case = {"voc... | 343 | 0 |
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
_A : Optional[int] = str(bin(_lowercase ) )[2:] # remove the leading "0b"
_A : Optional[A... | 363 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as ort... | 343 | 0 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_ ):
# Initialise PyTo... | 364 |
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ ):
create_state_space_tree(snake_case_,[],0,[0 for i in range(len(snake_case_ ) )] )
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_,):
if index == len(snake... | 343 | 0 |
"""simple docstring"""
from PIL import Image
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_A : Dict = (259 * (level + 255)) / (255 * (259 - level))
def contrast(snake_case_ ) -> int:
return int(128 + factor * (c - 128) )
ret... | 365 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def lowerCAmelCase_ ( snake_case_ ... | 343 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
_snake_case = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
_snake_case = {
'vocab_f... | 366 |
from __future__ import annotations
from collections.abc import Callable
_snake_case = list[list[float | int]]
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_A : int = len(snake_case_ )
_A : Matrix = [[0 for _ in range(size + 1 ... | 343 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def lowerCAmelCase_ ( snake_case_ ):
_A : s... | 367 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_snake_case = "https://www.indeed.co.in/jobs?q=mobile+app+development&l="
def lowerCAmelCase_ ( snake_case_ = "mumbai" ):
_A : Optional[Any] = ... | 343 | 0 |
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
_snake_case = 1.054571817e-34 # unit of ℏ : J * s
_snake_case = 3e8 # unit of c : m * s^-1
def lowerCAmelCase_ ( snake_case_,snake_case_,... | 368 |
from __future__ import annotations
from decimal import Decimal
from numpy import array
def lowerCAmelCase_ ( snake_case_ ):
_A : Tuple = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementation only works for 2x2 mat... | 343 | 0 |
"""simple docstring"""
from maths.prime_factors import prime_factors
def lowerCAmelCase_ ( snake_case_ ):
if not isinstance(__UpperCamelCase,__UpperCamelCase ):
_A : str = f'''Input value of [number={number}] must be an integer'''
r... | 369 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor impo... | 343 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {'configuration_mra': ['MRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MraConfig']}
try:
if not is_torch_available():
... | 370 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def lowerCAmelCase_ ( snake_case_,snake_case_=None ):
_A : Any = None
if token is not None:
_A : ... | 343 | 0 |
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
_snake_case = logging.get_logger(__name__)
_snake_case = r"\n Args:\n input_ids (`torch.LongTensor` of shape `(batch_size, sequence_... | 371 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase ( unittest.TestCase ):
def a__ ( self ) -> List[str]:
debug_launcher(test_script.main )
... | 343 | 0 |
import math
import flax.linen as nn
import jax.numpy as jnp
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ = 1,snake_case_ = 1,snake_case_ = 1.0e4,snake_case_ = False,snake_case_ = 1.0,):
assert timesteps.ndim == 1, "Timesteps should be a 1d-array"
assert embedding_dim % ... | 350 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake... | 343 | 0 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def lowerCAmelCase_ ( snake_case_ = True,*snake_case_,**snake_case_ ):
if not is_tqdm_available():
raise ImportError("""Accelerate's ... | 351 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
# Load checkp... | 343 | 0 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModelForSequenc... | 352 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase (... | 343 | 0 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import is_xformers_avail... | 353 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ ):
_A : Tuple = 0
if start < end:
_A : Tuple = randint(snake_case_,snake_case_ )
... | 343 | 0 |
import unittest
from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_te... | 354 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json"
),
}
class ... | 343 | 0 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_snake_case = False
try:
_snake_case = _is_package_available("google.c... | 355 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
_snake_case = logging.getLogger()
def lowerCAmelCase_ ... | 343 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
_snake_case = {'configuration_speech_encoder_decoder': ['SpeechEncoderDecoderConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
excep... | 356 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_... | 343 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
f... | 357 |
def lowerCAmelCase_ ( snake_case_ = 1000 ):
_A : List[Any] = 3
_A : Tuple = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
... | 343 | 0 |
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_ ):
if height >= 1:
move_tower(height - 1,_A,_A,_A )
move_disk(_A,_A )
move_tower(height - 1,_A,_A,_A )
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
... | 358 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...t... | 343 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_snake_case = {
"configuration_mobilebert": [
"MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"MobileBertConfi... | 359 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
"configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
"tokenization_roc_bert": ["RoCBertTokenizer"],
}
try:
... | 343 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__a )
class lowercase ( __a ):
# `task` is not a ClassVar since we want it to be part of the... | 360 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
... | 343 | 0 |
from string import ascii_lowercase, ascii_uppercase
def lowerCAmelCase_ ( snake_case_ ):
if not sentence:
return ""
_A : Tuple = dict(zip(snake_case_,snake_case_ ) )
return lower_to_upper.get(sentence[0],sentence[0] ) + sentence[1... | 361 |
# Copyright (c) 2021-, NVIDIA CORPORATION. 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
#
# Unless required by... | 343 | 0 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerForObjectDetection
fr... | 362 |
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 import BertTokenizer
_snake_case = logging.get_logger(__name__)
_snake_case = {"voc... | 343 | 0 |
class lowercase :
def __init__( self ) -> None:
_A : List[str] = {} # Mapping from char to TrieNode
_A : List[str] = False
def a__ ( self , _a ) -> None:
for word in words:
... | 363 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as ort... | 343 | 0 |
from timeit import timeit
_snake_case = {
"MALAYALAM": True,
"String": False,
"rotor": True,
"level": True,
"A": True,
"BB": True,
"ABC": False,
"amanaplanacanalpanama": True, # "a man a plan a canal panama"
}
# Ensure our test data is valid
assert all((key == key[::-1]) is value... | 364 |
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ ):
create_state_space_tree(snake_case_,[],0,[0 for i in range(len(snake_case_ ) )] )
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_,):
if index == len(snake... | 343 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case... | 365 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def lowerCAmelCase_ ( snake_case_ ... | 343 | 0 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowercase :
@property
def a__ ( self ) -> int... | 366 |
from __future__ import annotations
from collections.abc import Callable
_snake_case = list[list[float | int]]
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_A : int = len(snake_case_ )
_A : Matrix = [[0 for _ in range(size + 1 ... | 343 | 0 |
import sys
_snake_case = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856403098711121722383113"
... | 367 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_snake_case = "https://www.indeed.co.in/jobs?q=mobile+app+development&l="
def lowerCAmelCase_ ( snake_case_ = "mumbai" ):
_A : Optional[Any] = ... | 343 | 0 |
import os
# Precomputes a list of the 100 first triangular numbers
_snake_case = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def lowerCAmelCase_ ( ):
_A : List[str] = os.path.dirname(os.path.realpath(snake_case_ ) )
_A : List[Any] = ... | 368 |
from __future__ import annotations
from decimal import Decimal
from numpy import array
def lowerCAmelCase_ ( snake_case_ ):
_A : Tuple = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementation only works for 2x2 mat... | 343 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"facebook/data2vec-text-base": "https://hugg... | 369 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor impo... | 343 | 0 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoToken... | 370 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def lowerCAmelCase_ ( snake_case_,snake_case_=None ):
_A : Any = None
if token is not None:
_A : ... | 343 | 0 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as ort... | 371 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase ( unittest.TestCase ):
def a__ ( self ) -> List[str]:
debug_launcher(test_script.main )
... | 343 | 0 |
from __future__ import annotations
import numpy as np
def lowerCAmelCase_ ( snake_case_ ):
_A : Any = np.shape(snake_case_ )
if rows != columns:
_A : Optional[Any] = (
"""'table' has to be of square shaped a... | 350 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake... | 343 | 0 |
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
PixaStructTextConfig,
... | 351 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
# Load checkp... | 343 | 0 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_snake_case = "https://www.indeed.co.in/jobs?q=mobile+app+development&l="
def lowerCAmelCase_ ( snake_case_ = "mumbai" ):
_A : Optional[Any] = ... | 352 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase (... | 343 | 0 |
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark import (
BarkCoarseConfig,
... | 353 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ ):
_A : Tuple = 0
if start < end:
_A : Tuple = randint(snake_case_,snake_case_ )
... | 343 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case = {
"configuration_swinv2": ["SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Swinv2Config"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except O... | 354 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json"
),
}
class ... | 343 | 0 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/config.json",
"xlnet-large-cased": "https://huggingface.co/xlnet-large-... | 355 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
_snake_case = logging.getLogger()
def lowerCAmelCase_ ... | 343 | 0 |
# Copyright (c) 2021-, NVIDIA CORPORATION. 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
#
# Unless required ... | 356 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_... | 343 | 0 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def lowerCAmelCase_ ( snake_case_ ):
_A : Any = int(snake_case_ )
_A ... | 357 |
def lowerCAmelCase_ ( snake_case_ = 1000 ):
_A : List[Any] = 3
_A : Tuple = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
... | 343 | 0 |
def lowerCAmelCase_ ( snake_case_ ):
if not isinstance(snake_case_,snake_case_ ):
_A : List[str] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(snake_case_ )
if number < 1:
_A : Dic... | 358 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...t... | 343 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"asapp/sew-d-tiny-100k": "https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json",
# See all SEW-D models at http... | 359 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
"configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
"tokenization_roc_bert": ["RoCBertTokenizer"],
}
try:
... | 343 | 0 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
_snake_case = logging.get_logger(... | 360 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
... | 343 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_snake_case = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm": ["XLMTokenizer"],
}
try:
if not is_torc... | 361 |
# Copyright (c) 2021-, NVIDIA CORPORATION. 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
#
# Unless required by... | 343 | 0 |
from collections.abc import Callable
class lowercase :
def __init__( self , _a = None ) -> None:
# Stores actual heap items.
_A : list = []
# Stores indexes of each item for supporting updates and deletion.
... | 362 |
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 import BertTokenizer
_snake_case = logging.get_logger(__name__)
_snake_case = {"voc... | 343 | 0 |
def lowerCAmelCase_ ( snake_case_ ):
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 363 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as ort... | 343 | 0 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
_snake_case = pd.read_csv("sample_data.csv", header=None)
_snake_case = df.shape[:1][0]
# If you'r... | 364 |
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ ):
create_state_space_tree(snake_case_,[],0,[0 for i in range(len(snake_case_ ) )] )
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_,):
if index == len(snake... | 343 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ ):
if len(snake_case_ ) == 0:
return array
_A : Optional[Any] = min(snake_case_ ), max(snake_case_ )
# Compute the variables
_... | 365 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def lowerCAmelCase_ ( snake_case_ ... | 343 | 0 |
def lowerCAmelCase_ ( snake_case_ ):
if num <= 0:
raise ValueError("""Input must be a positive integer""" )
_A : Union[str, Any] = [True] * (num + 1)
_A : Optional[Any] = 2
while p * p <= num:
if primes[p... | 366 |
from __future__ import annotations
from collections.abc import Callable
_snake_case = list[list[float | int]]
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_A : int = len(snake_case_ )
_A : Matrix = [[0 for _ in range(size + 1 ... | 343 | 0 |
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
_snake_case = {
# 1536-bit
5: {
"prime": int(
"FFFFFFFFFFFFFFFFC90FD... | 367 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_snake_case = "https://www.indeed.co.in/jobs?q=mobile+app+development&l="
def lowerCAmelCase_ ( snake_case_ = "mumbai" ):
_A : Optional[Any] = ... | 343 | 0 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor impo... | 368 |
from __future__ import annotations
from decimal import Decimal
from numpy import array
def lowerCAmelCase_ ( snake_case_ ):
_A : Tuple = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementation only works for 2x2 mat... | 343 | 0 |
"""simple docstring"""
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,... | 369 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor impo... | 343 | 0 |
from collections.abc import Callable
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ ):
_A : float = a
_A : float = b
if function(snake_case_ ) == 0: # one of the a or b is a root for the function
return a... | 370 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def lowerCAmelCase_ ( snake_case_,snake_case_=None ):
_A : Any = None
if token is not None:
_A : ... | 343 | 0 |
def lowerCAmelCase_ ( snake_case_ ):
_A : str = [0] * len(snake_case_ )
_A : Optional[int] = []
_A : List[Any] = []
_A : Dict = 0
for values in graph.values():
for i in val... | 371 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase ( unittest.TestCase ):
def a__ ( self ) -> List[str]:
debug_launcher(test_script.main )
... | 343 | 0 |
def lowerCAmelCase_ ( snake_case_ ):
return sum(i for i in range(1,number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print("Program to check whether a number is a Perfect number or not...")
_snake_case = int(input("Enter number: ").strip())
print(f""... | 350 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake... | 343 | 0 |
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
assert x is not None
assert y is not None
_A : Tuple = len(snake_case_ )
_A : int = len(snake_case_ )
# declaring the array for storing the dp values
_A : ... | 351 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
# Load checkp... | 343 | 0 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_... | 352 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase (... | 343 | 0 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, i... | 353 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ ):
_A : Tuple = 0
if start < end:
_A : Tuple = randint(snake_case_,snake_case_ )
... | 343 | 0 |
from math import ceil
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_A : List[str] = list(range(0,snake_case_ ) )
_A : int = [item for sublist in list(device_map.values() ) for item in sublist]
# Duplicate check
... | 354 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json"
),
}
class ... | 343 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
RandomHorizontalFlip... | 355 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
_snake_case = logging.getLogger()
def lowerCAmelCase_ ... | 343 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable()
except Op... | 356 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_... | 343 | 0 |
from math import isclose, sqrt
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ ):
_A : Optional[int] = point_y / 4 / point_x
_A : Optional[Any] = 2 * normal_gradient / (1 + normal_gradient * normal_gradient)
_A : T... | 357 |
def lowerCAmelCase_ ( snake_case_ = 1000 ):
_A : List[Any] = 3
_A : Tuple = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
... | 343 | 0 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase (... | 358 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...t... | 343 | 0 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
_snake... | 359 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
"configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
"tokenization_roc_bert": ["RoCBertTokenizer"],
}
try:
... | 343 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from... | 360 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
... | 343 | 0 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_pytess... | 361 |
# Copyright (c) 2021-, NVIDIA CORPORATION. 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
#
# Unless required by... | 343 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class lowercase ( UpperCamelCase__ ):
_a = ... | 362 |
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 import BertTokenizer
_snake_case = logging.get_logger(__name__)
_snake_case = {"voc... | 343 | 0 |
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
_snake_case = logging.get_logger(__name__)
def lowerCAmelCase_ ... | 363 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as ort... | 343 | 0 |
def lowerCAmelCase_ ( snake_case_ ):
_A : List[str] = [0] * len(snake_case_ )
for i in range(1,len(snake_case_ ) ):
# use last results for better performance - dynamic programming
_A : Union[str, Any] = prefix_... | 364 |
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ ):
create_state_space_tree(snake_case_,[],0,[0 for i in range(len(snake_case_ ) )] )
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_,):
if index == len(snake... | 343 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json",
# See all GPTNeoX models at https... | 365 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def lowerCAmelCase_ ( snake_case_ ... | 343 | 0 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from... | 366 |
from __future__ import annotations
from collections.abc import Callable
_snake_case = list[list[float | int]]
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_A : int = len(snake_case_ )
_A : Matrix = [[0 for _ in range(size + 1 ... | 343 | 0 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...tes... | 367 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_snake_case = "https://www.indeed.co.in/jobs?q=mobile+app+development&l="
def lowerCAmelCase_ ( snake_case_ = "mumbai" ):
_A : Optional[Any] = ... | 343 | 0 |
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ ):
# Initialise PyTorch model
_A :... | 368 |
from __future__ import annotations
from decimal import Decimal
from numpy import array
def lowerCAmelCase_ ( snake_case_ ):
_A : Tuple = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementation only works for 2x2 mat... | 343 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
_snake_case = 1.054571817e-34 # unit of ℏ : J * s
_snake_case = 3e8 # unit of c : m * s^-1
def lowerCAmelCase_ ( ... | 369 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor impo... | 343 | 0 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
_snake_case = logging.get_logger(__name__)
def lowerCAmelCase_ ( snake_case_ ):
_A : List[Any] = ... | 370 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def lowerCAmelCase_ ( snake_case_,snake_case_=None ):
_A : Any = None
if token is not None:
_A : ... | 343 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torch_device
from... | 371 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase ( unittest.TestCase ):
def a__ ( self ) -> List[str]:
debug_launcher(test_script.main )
... | 343 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake... | 350 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake... | 343 | 0 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegmentation,
... | 351 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
# Load checkp... | 343 | 0 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rouge, chunks, ... | 352 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase (... | 343 | 0 |
import requests
_snake_case = "" # <-- Put your OpenWeatherMap appid here!
_snake_case = "https://api.openweathermap.org/data/2.5/"
def lowerCAmelCase_ ( snake_case_ = "Chicago",snake_case_ = APPID ):
return requests.get(URL_BASE + """weather""",params=locals() ).json()
... | 353 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ ):
_A : Tuple = 0
if start < end:
_A : Tuple = randint(snake_case_,snake_case_ )
... | 343 | 0 |
from jiwer import compute_measures
import datasets
_snake_case = "\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL to MER and WIL: improved evaluation measures for connecte... | 354 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json"
),
}
class ... | 343 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_snake_case = {
"configuration_convbert": ["CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvBertConfig", "ConvBertOnnxConfig... | 355 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
_snake_case = logging.getLogger()
def lowerCAmelCase_ ... | 343 | 0 |
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_ ):
_A : List[Any] = []
_A : List[str] = input_list[low:mid], input_list[mid : high + 1]
while left and right:
resul... | 356 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_... | 343 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@r... | 357 |
def lowerCAmelCase_ ( snake_case_ = 1000 ):
_A : List[Any] = 3
_A : Tuple = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
... | 343 | 0 |
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch_available():
import ... | 358 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...t... | 343 | 0 |
from typing import Any
import numpy as np
def lowerCAmelCase_ ( snake_case_ ):
return np.array_equal(snake_case_,matrix.conjugate().T )
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_A : Tuple = v.conjugate().T
_A : ... | 359 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
"configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
"tokenization_roc_bert": ["RoCBertTokenizer"],
}
try:
... | 343 | 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 import BertTokenizer
_snake_case = logging.get_logger(__na... | 360 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
... | 343 | 0 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constant_sc... | 361 |
# Copyright (c) 2021-, NVIDIA CORPORATION. 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
#
# Unless required by... | 343 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface import Hu... | 362 |
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 import BertTokenizer
_snake_case = logging.get_logger(__name__)
_snake_case = {"voc... | 343 | 0 |
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lo... | 363 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as ort... | 343 | 0 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
fr... | 364 |
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ ):
create_state_space_tree(snake_case_,[],0,[0 for i in range(len(snake_case_ ) )] )
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_,):
if index == len(snake... | 343 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.