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 unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class lowerCamelCase_ ( UpperCAmelCase_ ):
... | 105 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase = '''▁'''
__lowercase ... | 105 | 1 |
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
__lowerc... | 105 | import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as ProphetN... | 105 | 1 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
@require_torch
def UpperCamelCase__ ... | 105 | from __future__ import annotations
from math import pi
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError('''One and only one argume... | 105 | 1 |
__lowercase = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
__... | 105 | from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ):
'''simple docstring'''
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError('''You cannot supply more or less than 2 valu... | 105 | 1 |
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCamelCase_ ( ... | 105 | from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
print(f"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(SCREAMING_SNAKE_CASE ):
print(f"""{i}\t\t{d}""" )
d... | 105 | 1 |
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowerCamelCase ( SCREAMING_SNAKE_CASE = 8 ):
'''simple docstring'''
__UpperCamelCase :Tuple = ascii_letters + digits + punctuation
return "".... | 105 | import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ( UpperCAmelCase_ , unittest.TestCase ):
'''simple docstring'''
... | 105 | 1 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from trans... | 105 | import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, Partial... | 105 | 1 |
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
__lowercase = datasets.utils.logging.get_logger(__name__)
@dataclass
class lowerCamelCase_ ( datasets... | 105 | 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 import... | 105 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 105 | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 105 | 1 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('''socket.socket''' )
@patch('''builtins.open''' )
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Any = Mock()
... | 105 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__lowercase = {
'''configuration_layoutlmv3''': [
'''LAYOUTLMV3_PRETRAINED_CONFIG_ARCH... | 105 | 1 |
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
a__ : str
a__ : int
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if not isin... | 105 | from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, r... | 105 | 1 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__lowercase = logging.get_logger(__name__) # pylint: disable=invalid-name
class lowerCamelCase_ ( UpperCAmelCas... | 105 | def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
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]
... | 105 | 1 |
import qiskit
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :List[str] = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
__UpperCamelCase :str ... | 105 | import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Optional[int] = [
'''encoder.version''',
'''decoder.ver... | 105 | 1 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__lowercase = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__lowercase = [file for file in filepaths if file != file.low... | 105 | from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.... | 105 | 1 |
from math import factorial
def lowerCamelCase ( SCREAMING_SNAKE_CASE = 100 ):
'''simple docstring'''
return sum(map(SCREAMING_SNAKE_CASE , str(factorial(SCREAMING_SNAKE_CASE ) ) ) )
if __name__ == "__main__":
print(solution(int(input('''Enter the Number: ''').str... | 105 | from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__lowercase = logging.get_logger(__name__)
__lowercase = {'''vocab_file''': '''vocab.json''', '''merges_file''': '... | 105 | 1 |
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()
ex... | 105 | import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFI... | 105 | 1 |
import heapq as hq
import math
from collections.abc import Iterator
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self , __lowercase) -> Optional[Any]:
__UpperCamelCase :List[str] = str(id_)
__UpperCamelCase :Union[str, Any] ... | 105 | import os
import pytest
from transformers.dynamic_module_utils import get_imports
__lowercase = '''
import os
'''
__lowercase = '''
def foo():
import os
return False
'''
__lowercase = '''
def foo():
def bar():
if True:
import os
return False
r... | 105 | 1 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowerCamelCase_ ( UpperCAmelCase_ , unittest.TestCas... | 105 | from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__lowercase = logging.... | 105 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase = {
'''configuration_git''': ['''GIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GitConfig''', '''GitVisionConfig'''],
'''processing_git''': ['''GitProcessor'''],
}
try:
if... | 105 | import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from to... | 105 | 1 |
from __future__ import annotations
from typing import Any
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self , __lowercase) -> None:
__UpperCamelCase :List[Any] = num_of_nodes
__UpperCamelCase :list[list[int]] = []
... | 105 | import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCamelCase ( ):
'''simple docstring'''
__UpperCamelCase :int = ArgumentParser(
description=(
'''Py... | 105 | 1 |
import unittest
import numpy as np
import requests
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():
... | 105 | from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils import PreTrain... | 105 | 1 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
raise TypeError('''Undefined for non-integers''' )
elif pre... | 105 | import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
__lowercase = {
'''tiny.en''': '''https://openaipublic.azureedge.net/main/whisper/models/d3dd57d32accea0... | 105 | 1 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if (
(cp >= 0X4_e_0_0 and cp <= 0X9_f_f_f)
or (cp >= 0X3_4_0_0 a... | 105 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase = '''▁'''
__lowercase ... | 105 | 1 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFI... | 105 | import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as ProphetN... | 105 | 1 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoImageProcessor, ResNetCon... | 105 | from __future__ import annotations
from math import pi
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError('''One and only one argume... | 105 | 1 |
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class lowerCamelCase_ :
'''simple docstring'''
a__ : List[str]
a__ ... | 105 | from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ):
'''simple docstring'''
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError('''You cannot supply more or less than 2 valu... | 105 | 1 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F'{price_plus_tax(100, 0.2_5) = }')
print(F'{price_plus_tax(1_2_5.5_0, 0.0_5) = }')
| 105 | from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
print(f"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(SCREAMING_SNAKE_CASE ):
print(f"""{i}\t\t{d}""" )
d... | 105 | 1 |
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase = '''▁'''
__lowercase ... | 105 | import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ( UpperCAmelCase_ , unittest.TestCase ):
'''simple docstring'''
... | 105 | 1 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :List[Any] = {
'''en''': '''Machine learning is grea... | 105 | import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, Partial... | 105 | 1 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
return " ".join(
''''''.join(word[::-1] ) if len(SCREAMING_SNAKE_CASE ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_... | 105 | 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 import... | 105 | 1 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE = 1_000 ):
'''simple docstring'''
__UpperCamelCase , __UpperCamelCase :Tuple = 1, 1
__UpperCamelCase :Tuple = []
for i in range(1 , n + 1 ):
__UpperCamelCase :List[str] = prev_numerator + 2... | 105 | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 105 | 1 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__lowercase = logging.get_logger(__name__)
__lowercase = {'''vocab_file''': '''vocab.json''', '''merges_file''': '... | 105 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__lowercase = {
'''configuration_layoutlmv3''': [
'''LAYOUTLMV3_PRETRAINED_CONFIG_ARCH... | 105 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__lowercase = {'''processing_layoutxlm''': ['''LayoutXLMProcessor''']}
try:
if not... | 105 | from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, r... | 105 | 1 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Prophet... | 105 | def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
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]
... | 105 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.set_verbosity_info()
__lowercase... | 105 | import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Optional[int] = [
'''encoder.version''',
'''decoder.ver... | 105 | 1 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import T... | 105 | from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.... | 105 | 1 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch_dump_output... | 105 | from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__lowercase = logging.get_logger(__name__)
__lowercase = {'''vocab_file''': '''vocab.json''', '''merges_file''': '... | 105 | 1 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if "model" in orig_key:
__UpperCamelCase :str = orig_key.replace('''model.''' , '''''' )
if "norm1" in or... | 105 | import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFI... | 105 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''CarlCochet/trajectory-transformer-halfcheetah-medium-v2''': (
'''https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v... | 105 | import os
import pytest
from transformers.dynamic_module_utils import get_imports
__lowercase = '''
import os
'''
__lowercase = '''
def foo():
import os
return False
'''
__lowercase = '''
def foo():
def bar():
if True:
import os
return False
r... | 105 | 1 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ( UpperCAmelCase_ , unittest.TestCase ):
'''simple docstring'''
... | 105 | from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__lowercase = logging.... | 105 | 1 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__lowercase = '''\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksachat... | 105 | import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from to... | 105 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase = {
'''configuration_deberta''': ['''DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DebertaConfig''', '''Debe... | 105 | import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCamelCase ( ):
'''simple docstring'''
__UpperCamelCase :int = ArgumentParser(
description=(
'''Py... | 105 | 1 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def lowerCamelCase ( SCRE... | 105 | from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils import PreTrain... | 105 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''microsoft/git-base''': '''https://huggingface.co/microsoft/git-base/resolve/main/config.json''',
}
cla... | 105 | import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
__lowercase = {
'''tiny.en''': '''https://openaipublic.azureedge.net/main/whisper/models/d3dd57d32accea0... | 105 | 1 |
import os
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 logging
__lowercase = logging.get_logger(__name__)
__lowercase = {'''vocab_file''': '''sente... | 105 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase = '''▁'''
__lowercase ... | 105 | 1 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if is_vision_availabl... | 105 | import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as ProphetN... | 105 | 1 |
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, FlaxTi... | 105 | from __future__ import annotations
from math import pi
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError('''One and only one argume... | 105 | 1 |
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
__lowercase = (
'''This metric will be removed from the library soon, metrics should be ha... | 105 | from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ):
'''simple docstring'''
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError('''You cannot supply more or less than 2 valu... | 105 | 1 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ... | 105 | from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
print(f"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(SCREAMING_SNAKE_CASE ):
print(f"""{i}\t\t{d}""" )
d... | 105 | 1 |
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(UpperCAmelCase_ ) , """Tatoeba di... | 105 | import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ( UpperCAmelCase_ , unittest.TestCase ):
'''simple docstring'''
... | 105 | 1 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Optional[int] = 1
__UpperCamelCase :Optional[Any] = 2
while i * i <= n:
__UpperCamelCase :str = 0
while n % i == 0:
n //= i
... | 105 | import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, Partial... | 105 | 1 |
import copy
import re
class lowerCamelCase_ :
'''simple docstring'''
a__ : Optional[int] = """hp"""
a__ : Any = {}
a__ : List[str] = None
@classmethod
def UpperCamelCase__ ( cls , __lowercase ,... | 105 | 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 import... | 105 | 1 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from to... | 105 | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 105 | 1 |
__lowercase = frozenset(
[
'''prompt''',
'''height''',
'''width''',
'''guidance_scale''',
'''negative_prompt''',
'''prompt_embeds''',
'''negative_prompt_embeds''',
'''cross_attention_kwargs''',
]
)
__lowercase = frozenset(['''pro... | 105 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__lowercase = {
'''configuration_layoutlmv3''': [
'''LAYOUTLMV3_PRETRAINED_CONFIG_ARCH... | 105 | 1 |
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for tests
from os.path import join #... | 105 | from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, r... | 105 | 1 |
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Optional[int] = os.path.join(args.tf_model_dir , '''para... | 105 | def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
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]
... | 105 | 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 import... | 105 | import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Optional[int] = [
'''encoder.version''',
'''decoder.ver... | 105 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowercase = {'''configuration_yolos''': ['''YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''YolosConfig''', '''YolosOnnxConfig''']}
try:
if not is_vision_available():
... | 105 | from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.... | 105 | 1 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
return 10 - x * x
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if equation(SCREAMING_SNAKE_CASE ) * equation(SCREAMING_SNAKE_CASE ) >= 0:... | 105 | from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__lowercase = logging.get_logger(__name__)
__lowercase = {'''vocab_file''': '''vocab.json''', '''merges_file''': '... | 105 | 1 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCamelCase ( ):
'''simple docstring'''
__UpperCamelCase :int = ArgumentParser(
description=(
'''Py... | 105 | import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFI... | 105 | 1 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as ProphetN... | 105 | import os
import pytest
from transformers.dynamic_module_utils import get_imports
__lowercase = '''
import os
'''
__lowercase = '''
def foo():
import os
return False
'''
__lowercase = '''
def foo():
def bar():
if True:
import os
return False
r... | 105 | 1 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Optional[int] = [
'''encoder.version''',
'''decoder.ver... | 105 | from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__lowercase = logging.... | 105 | 1 |
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class lowerCamelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
... | 105 | import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from to... | 105 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''kssteven/ibert-roberta-base''': '''https://huggingface.co... | 105 | import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCamelCase ( ):
'''simple docstring'''
__UpperCamelCase :int = ArgumentParser(
description=(
'''Py... | 105 | 1 |
import sys
__lowercase = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557'''
'''66896648950445244523161731856403... | 105 | from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils import PreTrain... | 105 | 1 |
from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Tuple = list(range(len(SCREAMING_SNAKE_CASE ) ) )
__UpperCamelCase :Dict ... | 105 | import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
__lowercase = {
'''tiny.en''': '''https://openaipublic.azureedge.net/main/whisper/models/d3dd57d32accea0... | 105 | 1 |
from __future__ import annotations
import math
import random
from typing import Any
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self) -> None:
__UpperCamelCase :list[Any] = []
__UpperCamelCase :int = 0
__UpperCamelC... | 105 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase = '''▁'''
__lowercase ... | 105 | 1 |
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
__lowercase = '''<<<<<<< This should probably be modified because it mentions: '''
__lowercase = '''=======
>>>>>>>
''... | 105 | import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as ProphetN... | 105 | 1 |
import os
import jsonlines
import numpy as np
from tqdm import tqdm
__lowercase = 2048
__lowercase = 4096
__lowercase = 42
__lowercase = os.environ.pop('''PROCESS_TRAIN''', '''false''')
__lowercase = {'''null''': 0, '''short''': 1, '''long''': 2, '''yes''': 3, '''no''': 4... | 105 | from __future__ import annotations
from math import pi
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError('''One and only one argume... | 105 | 1 |
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
__lowercase = 0
__lowercase = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0,... | 105 | from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ):
'''simple docstring'''
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError('''You cannot supply more or less than 2 valu... | 105 | 1 |
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.... | 105 | from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
print(f"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(SCREAMING_SNAKE_CASE ):
print(f"""{i}\t\t{d}""" )
d... | 105 | 1 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :List[str] = int(np.c... | 105 | import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ( UpperCAmelCase_ , unittest.TestCase ):
'''simple docstring'''
... | 105 | 1 |
from __future__ import annotations
from math import ceil, floor, sqrt
def lowerCamelCase ( SCREAMING_SNAKE_CASE = 2_000_000 ):
'''simple docstring'''
__UpperCamelCase :list[int] = [0]
__UpperCamelCase :int
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1... | 105 | import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, Partial... | 105 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from diffusers.utils import floats... | 105 | 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 import... | 105 | 1 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase ... | 105 | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 105 | 1 |
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
return sum(param.float().sum(... | 105 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__lowercase = {
'''configuration_layoutlmv3''': [
'''LAYOUTLMV3_PRETRAINED_CONFIG_ARCH... | 105 | 1 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
__UpperCamelCase :Optional[Any] = str(bin(SCREAMING_SNAKE_CASE ) )[2:] # ... | 105 | from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, r... | 105 | 1 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Tuple = 0
__UpperCamelCase :Tuple = len(SCREAMING_SNAKE_CASE ) - 1
while left <= right:
# avoid divided by 0 during interpolation
... | 105 | def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
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]
... | 105 | 1 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteSched... | 105 | import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Optional[int] = [
'''encoder.version''',
'''decoder.ver... | 105 | 1 |
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
__lowercase = parse(importlib.metadata.version('''torch'''))
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_... | 105 | from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.... | 105 | 1 |
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 lowerCamelCase_ ( UpperCAmelCase_ ):
... | 105 | from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__lowercase = logging.get_logger(__name__)
__lowercase = {'''vocab_file''': '''vocab.json''', '''merges_file''': '... | 105 | 1 |
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
from transf... | 105 | import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFI... | 105 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 105 | import os
import pytest
from transformers.dynamic_module_utils import get_imports
__lowercase = '''
import os
'''
__lowercase = '''
def foo():
import os
return False
'''
__lowercase = '''
def foo():
def bar():
if True:
import os
return False
r... | 105 | 1 |
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse('''3.8'''):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
__lowercase = ''''''
... | 105 | from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__lowercase = logging.... | 105 | 1 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE = 50 ):
'''simple docstring'''
__UpperCamelCase :Optional[Any] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start in ra... | 105 | import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from to... | 105 | 1 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase_ ( UpperCAmelCase_ ):
'''simple docstring'''
a__ : Optional[Any] = (DDIMParallelScheduler,)
a__ : List[Any] = ((""... | 105 | import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCamelCase ( ):
'''simple docstring'''
__UpperCamelCase :int = ArgumentParser(
description=(
'''Py... | 105 | 1 |
import unittest
import numpy as np
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = None , ):
'''simple docstring'''
__UpperCamelCase :int = np.shape(SCREAMING_SNAKE_CASE )
__UpperCamelC... | 105 | from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils import PreTrain... | 105 | 1 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE = 1_000_000 ):
'''simple docstring'''
__UpperCamelCase :Optional[Any] = set(range(3 , SCREAMING_SNAKE_CASE , 2 ) )
primes.add(2 )
for p in range(3 , SCREAMING_SNAKE_CASE , 2 ):
if p no... | 105 | import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
__lowercase = {
'''tiny.en''': '''https://openaipublic.azureedge.net/main/whisper/models/d3dd57d32accea0... | 105 | 1 |
from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if len(SCREAMING_SNAKE_CASE ) < k or k < 0:
raise ValueError('''Invalid Input''' )
__UpperCamelCase :List[str] = sum(array[:k] ... | 105 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase = '''▁'''
__lowercase ... | 105 | 1 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.utils import logging
... | 105 | import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as ProphetN... | 105 | 1 |
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class lowerCamelCase_ ( UpperCAmelCase_ , unittest.TestCase ):
'''simple docstring'''
a__ : ... | 105 | from __future__ import annotations
from math import pi
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError('''One and only one argume... | 105 | 1 |
import math
import sys
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if number != int(SCREAMING_SNAKE_CASE ):
raise ValueError('''the value of input must be a natural number''' )
if number < 0:
raise ValueError('''the value of input must not... | 105 | from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ):
'''simple docstring'''
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError('''You cannot supply more or less than 2 valu... | 105 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...utils im... | 105 | from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
print(f"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(SCREAMING_SNAKE_CASE ):
print(f"""{i}\t\t{d}""" )
d... | 105 | 1 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
__lowercase = logging.g... | 105 | import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ( UpperCAmelCase_ , unittest.TestCase ):
'''simple docstring'''
... | 105 | 1 |
from timeit import timeit
__lowercase = {
'''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
ass... | 105 | import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, Partial... | 105 | 1 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def lowerCamelCase ( SCREAMING_SNAKE_CASE = "" ):
'''simple docstring'''
__UpperCamelCase :Dict = url or '''https://www.imdb.com/chart/top/?ref_=nv_mv_250'''
__UpperCamelCase :A... | 105 | 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 import... | 105 | 1 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .dataclasses import BnbQua... | 105 | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 105 | 1 |
def lowerCamelCase ( SCREAMING_SNAKE_CASE = 2_000_000 ):
'''simple docstring'''
__UpperCamelCase :str = [0 for i in range(n + 1 )]
__UpperCamelCase :Union[str, Any] = 1
__UpperCamelCase :Union[str, Any] = 1
for i in range(2 , int(n**0.... | 105 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__lowercase = {
'''configuration_layoutlmv3''': [
'''LAYOUTLMV3_PRETRAINED_CONFIG_ARCH... | 105 | 1 |
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...uti... | 105 | from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, r... | 105 | 1 |
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.utils.... | 105 | def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
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]
... | 105 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.