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 argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ ):
# Initialise PyTorch mode... | 343 |
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 | 1 |
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... | 343 |
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 | 1 |
from collections.abc import Sequence
def lowerCAmelCase_ ( snake_case_ = None ):
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
_A : str = nums[0]
for i in range(1,len(snake_case_ ) ):
... | 343 |
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 | 1 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase (... | 343 |
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 | 1 |
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,
... | 343 |
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 | 1 |
def lowerCAmelCase_ ( snake_case_ ):
return " ".join(
"""""".join(word[::-1] ) if len(snake_case_ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words("Hey wollef sroirraw"))
| 343 |
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 | 1 |
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)
_snake_case = models.Sequential()
# Step 1 - Convolution
# Here 64,64... | 343 |
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 | 1 |
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def lowerCAmelCase_ ( snake_case_ ):
ran... | 343 |
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 | 1 |
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()
... | 343 |
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 | 1 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerFast
fro... | 343 |
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 | 1 |
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 |
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 | 1 |
def lowerCAmelCase_ ( snake_case_ ):
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 343 |
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 | 1 |
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
return number | (1 << position)
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
return number & ~(1 << position)
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
return number ^ (1 << p... | 343 |
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 | 1 |
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_... | 343 |
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 | 1 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart i... | 343 |
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 | 1 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_vision_available
f... | 343 |
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 | 1 |
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_A : int = sorted(numsa + numsa )
_A , _A : Optional[int] = divmod(len(snake_case_ ),2 )
if mod == 1:
return all_nu... | 343 |
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 | 1 |
import argparse
from collections import defaultdict
import yaml
_snake_case = "docs/source/en/_toctree.yml"
def lowerCAmelCase_ ( snake_case_ ):
_A : Any = defaultdict(snake_case_ )
_A : Optional[Any] = []
_A : List[... | 343 |
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 | 1 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowercase ( UpperCamelCase__ ):
_a = "M-CLIP"
def __init__( self , _a=1024 , _a=768 , **_a ) -> Optional[int]:
_A : st... | 343 |
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 | 1 |
# 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 |
# 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 | 1 |
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 : ... | 343 |
# 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 | 1 |
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"The `inpainting.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionInpaintPipeline` instead."
)
| 343 |
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 | 1 |
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_ ):
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
_A : List[str] = mf_knapsack(i - 1,snake_case_,snake_case_,snake_case_ )
... | 343 |
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 | 1 |
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 |
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 | 1 |
import unittest
from knapsack import greedy_knapsack as kp
class lowercase ( unittest.TestCase ):
def a__ ( self ) -> Dict:
_A : Optional[Any] = [10, 20, 30, 40, 50, 60]
_A : Tuple = [2, 4, 6, 8, 10, ... | 343 |
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 | 1 |
from __future__ import annotations
import os
from collections.abc import Mapping
_snake_case = tuple[int, int]
class lowercase :
def __init__( self , _a , _a ) -> None:
_A : set[int] = vertices
_A : dict[EdgeT,... | 343 |
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 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
_snake_case = logging.get_logger(__name__)
_snake_case = {
"Intel/dpt-large": "https://huggingface.co/Intel/dpt-large/resolve/main/config.json",
# See all DPT models at https://hug... | 343 |
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 | 1 |
import colorsys
from PIL import Image # type: ignore
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ ):
_A : Dict = x
_A : Optional[Any] = y
for step in range(snake_case_ ): # noqa: B007
_A : Lis... | 343 |
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 | 1 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, vali... | 343 |
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 | 1 |
import inspect
import unittest
from transformers import BitConfig
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 ...test_c... | 343 |
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 | 1 |
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 lowerCAmelCas... | 343 |
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 | 1 |
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def lowerCAmelCase_ ( *snake_case_ ):
if not isinstance(_UpperCAmelCase,_UpperCAmelCase ):
_A : str = list(_UpperCAmelCase )
fo... | 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 json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {"vocab_file": "vocab.json", "merges_file"... | 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 typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, F... | 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 logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS
log... | 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 __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...test_pipeline_mixin i... | 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 argparse
from collections import defaultdict
import yaml
_snake_case = "docs/source/en/_toctree.yml"
def lowerCAmelCase_ ( snake_case_ ):
_A : Any = defaultdict(__a )
for doc in model_doc:
counts[doc["local"]] += 1
_A : ... | 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
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_vision
from transformers.utils i... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
"google/fnet-large": "https://huggingface.co/google/fnet-large/resolve/mai... | 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 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
class lowercase ( lowercase__ ):
_a = 'encoder-decoder'
_a = True
def __init__( self , **_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 json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
_snake_case = """."""
# Internal TensorFlow ops that can be safely igno... | 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 string
import numpy
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
return b if a == 0 else greatest_common_divisor(b % a,__lowerCamelCase )
class lowercase :
_a = string.ascii_uppercase + string.digits
... | 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 load_tool
from .test_tools_common import ToolTesterMixin
_snake_case = "\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After op... | 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
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
_snake_case = logging.get_logger(__... | 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 |
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_ ): # noqa: E741
while r - l > 1:
_A : List[str] = (l + r) // 2
if v[m] >= key:
_A : Any = m
... | 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 time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxLengthCriteria,
MaxNewTokensCr... | 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"""
class lowercase :
def __init__( self ) -> None:
_A : dict[str, TrieNode] = {} # Mapping from char to TrieNode
_A : Optional[int] = False
def a__ ( self , _a ) -> ... | 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 datasets
_snake_case = "\\n@InProceedings{conneau2018xnli,\n author = \"Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk, Holger\n and Sto... | 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 ..utils import DummyObject, requires_backends
class lowercase ( metaclass=UpperCamelCase__ ):
_a = ['''keras_nlp''']
def __init__( self , *_a , **_a ) -> List[str]:
requires_backends(self , ["""keras_nlp"""] )
| 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 glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback, get_ea... | 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 copy
import random
from transformers import CLIPTokenizer
class lowercase ( a__ ):
def __init__( self , *_a , **_a ) -> List[Any]:
super().__init__(*_lowerCamelCase , **_lowerCamelCase )
_A ... | 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 unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import to... | 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 random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
... | 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_ = 100 ):
_A : Optional[Any] = set()
_A : int = 0
_A : str = n + 1 # maximum limit
for a in range(2,__a ):
for b in range(2,__a ):
_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 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"microsoft/trocr-base-handwritten": (
"https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"
),
# See all TrOCR models at h... | 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 typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
_snake_case = {"""configuration_beit""": ["""BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BeitConfig""", """BeitOnnxConfig"""]}
tr... | 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 inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion import Stable... | 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 |
def lowerCAmelCase_ ( snake_case_ ):
_A : Any = []
_A : Any = []
_A : List[str] = {
"""^""": 3,
"""*""": 2,
"""/""": 2,
"""%""": 2,
"""+""": 1,
"""-""": 1,
... | 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 Any
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_,snake_case_,):
_validation(
snake_case_,snake_case_,snake_case_,snake_case_,snake_case_,)
# Creates data structures and fill initial step
_A : dict = {}
... | 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 unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenizer, FlaxM... | 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 ....configuration_utils import PretrainedConfig
from ....utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"CarlCochet/trajectory-transformer-halfcheetah-medium-v2": (
"https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/co... | 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 |
import logging
from transformers.configuration_utils import PretrainedConfig
_snake_case = logging.getLogger(__name__)
class lowercase ( lowerCAmelCase_ ):
_a = 'masked_bert'
def __init__( self , _a=3_0522 , _a=768 , _a=12 , _a=12 , _... | 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 |
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
def get_matched_characters(snake_case_,snake_case_ ) -> str:
_A : Optional[Any] = []
_A : Tuple = min(len(_stra ),len(_stra ) ) // 2
for i, l in ... | 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 ..utils import DummyObject, requires_backends
class lowercase ( metaclass=UpperCamelCase__ ):
_a = ['transformers', 'torch', 'note_seq']
def __init__( self , *_a , **_a ) -> Tuple:
requires_backen... | 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 json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase ( UpperCamelCase__,unittest.TestCase ):
_a = CTRLTokenizer
_... | 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 gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
from diffusers.u... | 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 inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
_snake_case = "src/transformers"
# This is to make sure the transformers module imp... | 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 torch
from torch.utils.data import Dataset
from utils import logger
class lowercase ( SCREAMING_SNAKE_CASE__ ):
def __init__( self , _a , _a ) -> Optional[int]:
_A : Any = params
_A ... | 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 argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenizatio... | 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 |
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... | 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 typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_availab... | 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
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
@require_torch
clas... | 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 argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load... | 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 unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if 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 |
def lowerCAmelCase_ ( snake_case_ ):
if not grid or not grid[0]:
raise TypeError("""The grid does not contain the appropriate information""" )
for cell_n in range(1,len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_n - 1]
_A : Any ... | 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 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 Image
from ..image_utils import l... | 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 __future__ import annotations
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_,snake_case_,snake_case_,):
_A : Optional[Any] = len(_UpperCAmelCase )
# If row is equal to the size of the board it means there are a queen in each row in
# the ... | 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 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 ):
debug_launcher(test_script.main )
def a__ ( self ... | 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 |
from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import AttentionProcessor, AttnProcessor
from .modeli... | 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 math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied from diffu... | 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 faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here to ... | 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 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 = {
"andreasmadsen/efficient_mlm_m0.40": (
"https://huggingface.c... | 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 |
def lowerCAmelCase_ ( snake_case_ ):
_A : List[str] = generate_pascal_triangle(snake_case_ )
for row_idx in range(snake_case_ ):
# Print left spaces
for _ in range(num_rows - row_idx - 1 ):
print(end=""" """ )... | 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 |
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... | 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 |
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 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"""
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
_A : Tuple = (boundary[1] - boundary[0]) / steps
_A : Optional[Any] = boundary[0]
_... | 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 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... | 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 |
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
if not isinstance(__lowerCAmelCase,__lowerCAmelCase ):
raise ValueError("""iterations must be defined as integers""" )
if not isinstance(__lowerCAmelCase,__lowerCAmelCase ) or not number >= 1:
raise Val... | 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 unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class lowercase ( unittest.TestCase ):
@require_torch
def 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 |
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_cpmant': ['CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CpmAntConfig'],
'tokenization_cpmant': ['... | 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 re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
_snake_case = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for Text Simplification},\n a... | 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 argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from transformers.file_util... | 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 |
def lowerCAmelCase_ ( snake_case_ ):
_A : Optional[Any] = int(SCREAMING_SNAKE_CASE__ )
if n_element < 1:
_A : Optional[int] = ValueError("""a should be a positive number""" )
raise my_error
_A : Optional[Any] = [1]
... | 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 doctest
from collections import deque
import numpy as np
class lowercase :
def __init__( self ) -> Optional[Any]:
_A : Optional[int] = [2, 1, 2, -1]
_A : List[str] = [1, 2, 3, 4]
def a__ ( se... | 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 collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class lowercase :
_a = 4_2
_a = None
_a = ... | 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
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
... | 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 |
from __future__ import annotations
from collections import namedtuple
def lowerCAmelCase_ ( snake_case_,snake_case_,snake_case_ ):
_A : Optional[Any] = namedtuple("""result""","""name value""" )
if (voltage, current, power).count(0 ) != 1:
... | 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 typing import TYPE_CHECKING
from ...utils import _LazyModule
_snake_case = {"tokenization_byt5": ["ByT5Tokenizer"]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
_snake_case = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
... | 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 transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class lowercase ( __SCREAMING_SNAKE_CASE ):
_a = CustomTokenizer
pass
| 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 |
_snake_case = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
_snake_case = [{'type': 'code', 'content': I... | 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 |
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