code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import os
import sys
import unittest
lowercase : Any = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find... | 20 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _A :
UpperCamelCase__ : Optional[Union[str, Path]] = None
UpperCamelCase__ : bool = False
UpperCamelCase__ : bool... | 49 | 0 |
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE : List[Any] = logging.get_logger(__name__)
def UpperCamelCase_( lowerC... | 21 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Union[str, Any] = logging.get_logger(__name__)
__snake_case :Any = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class ... | 49 | 0 |
'''simple docstring'''
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git... | 22 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
__snake_case :List[Any] = logging.getLogger(__name__)
class _A :
def __init__( self : List[str]):... | 49 | 0 |
'''simple docstring'''
import random
from .binary_exp_mod import bin_exp_mod
def snake_case_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[Any]=1000 ) -> int:
if n < 2:
return False
if n % 2 == 0:
r... | 23 |
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ... | 49 | 0 |
def lowerCamelCase__ ( snake_case_ : List[Any] ) -> Optional[Any]:
__snake_case = 1
__snake_case = 2
while i * i <= n:
__snake_case = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divi... | 24 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __snak... | 49 | 0 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=a__ )
class lowerCAmelCase_ (a__ ):
"""simple docstring"""
... | 25 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def __snake_case ( ):
__a , __a = 9, 14 # noqa: F841
__a = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, ... | 49 | 0 |
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_enforce_args(snake_case_,snake_case_ )
if n == 0:
return 0
_A : Tuple = float("""-inf""" )
for i in range(1,n + 1 ):
_A : str = max(
snake_case... | 26 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _A ( unittest.TestCase ):
def _lowerCamelCase ( self : List[Any]):
'''simple docstring'''
__a = [
'''safety_checker/pytorch_mo... | 49 | 0 |
'''simple docstring'''
from collections import defaultdict
class __UpperCamelCase :
def __init__( self , __a , __a ):
'''simple docstring'''
__a : Dict = total # total no of tasks (N)
# DP table will have a dimension of (2^M)*N... | 27 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers i... | 49 | 0 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tenso... | 28 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_mo... | 49 | 0 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import C... | 29 |
from __future__ import annotations
from typing import Any
def __snake_case ( _UpperCAmelCase ):
if not postfix_notation:
return 0
__a = {'''+''', '''-''', '''*''', '''/'''}
__a = []
for token in postfix_notation:
if token in operations:... | 49 | 0 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def a ( snake_case__: Tuple ):
'''simple docstring'''
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
class lowercase_... | 30 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
__snake_case :Optional[int] = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generati... | 49 | 0 |
'''simple docstring'''
def UpperCamelCase_ ( _UpperCAmelCase : list ) -> list:
"""simple docstring"""
_UpperCAmelCase : List[Any] = len(_UpperCAmelCase )
for _ in range(_UpperCAmelCase ):
for i in range(_ % 2 , arr_siz... | 31 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ):
# Initialise PyTorch model
... | 49 | 0 |
import math
def SCREAMING_SNAKE_CASE_ ( __A : int ) -> bool:
"""simple docstring"""
a_ : Dict = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(__A )
def SCREAMING_SNAKE_... | 32 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def __snake_case ( _UpperCAmelCase = "isbn/0140328726" ):
__a = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashes
if new_olid.count('''/''' )... | 49 | 0 |
"""simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from data... | 33 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class _A ( __UpperCAmelCase ):
def __init__( self : Optional[int] ... | 49 | 0 |
'''simple docstring'''
def snake_case_ (_a : int ):
if not isinstance(_a , _a ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must be positive''' )
return sum(
divisor for divisor in ... | 34 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 49 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__a = {"configuration_deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeiTConfig", "DeiTOnnxCon... | 35 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _A ( __UpperCAmelCase ):
UpperCamelCase__ : Tuple = (DDPMParallelScheduler,)
def _lowerCamelCase ( self : int , **__SCREAMING_SNAKE_... | 49 | 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 UpperCAmelCase_ ( unittest.TestCase):
@require_torch
... | 36 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch
from ..mode... | 49 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from tran... | 37 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
__snake_case :str = logging.get_logger(__name__)
__snake_case ... | 49 | 0 |
import re
import string
import numpy as np
import datasets
UpperCAmelCase_ : Dict = '''
Returns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.
'''
UpperCAmelCase_ : Any = '''
Args:
... | 38 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers import (
Effic... | 49 | 0 |
def __A ( __lowerCAmelCase , __lowerCAmelCase )-> float:
"""simple docstring"""
return base * power(__lowerCAmelCase , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print('''Raise base to the power of exponent using recursion...''')
_a ... | 39 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__snake_case :Optional[Any] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__snake_case :Any = [file for fil... | 49 | 0 |
"""simple docstring"""
def lowercase ( A_ , A_ , A_ , A_ )-> bool:
'''simple docstring'''
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
# 2. Validate that next vertex is not already in path
return not any(vertex == next_ver ... | 40 |
from collections import defaultdict
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase ):
__a = first_str.lower().strip()
__a = second_str.lower().strip()
# Remove whitespace
__a = first_str.replace(''' ''' , '''''' )
__a ... | 49 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import To... | 41 |
import logging
from transformers.configuration_utils import PretrainedConfig
__snake_case :Any = logging.getLogger(__name__)
class _A ( __UpperCAmelCase ):
UpperCamelCase__ : Optional[Any] = '''masked_bert'''
def __init__( self : str ... | 49 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( __A = 1_000_000 ) -> int:
_snake_case = limit + 1
_snake_case = [0] * limit
for first_term in range(1 , __A ):
for n in range(__A , __A , __A ):
_snake_case = first_term + n / first_term
if commo... | 42 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _A :
UpperCamelCase__ : Optional[Union[str, Path]] = None
UpperCamelCase__ : bool = False
UpperCamelCase__ : bool... | 49 | 0 |
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_S... | 43 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Union[str, Any] = logging.get_logger(__name__)
__snake_case :Any = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class ... | 49 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 1000 ) -> int:
_lowerCAmelCase , _lowerCAmelCase : Tuple = 1, 1
_lowerCAmelCase : Optional[Any] = 2
while True:
_lowerCAmelCase : Any = 0
... | 44 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
__snake_case :List[Any] = logging.getLogger(__name__)
class _A :
def __init__( self : List[str]):... | 49 | 0 |
"""simple docstring"""
import fire
from utils import calculate_rouge, save_json
def lowercase ( lowerCAmelCase__ : Tuple , lowerCAmelCase__ : str , lowerCAmelCase__ : List[str]=None , **lowerCAmelCase__ : Dict ) -> int:
__a = ... | 45 |
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ... | 49 | 0 |
"""simple docstring"""
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_... | 46 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __snak... | 49 | 0 |
'''simple docstring'''
from collections import defaultdict
def _lowerCAmelCase ( _UpperCamelCase : str , _UpperCamelCase : str ) -> bool:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =first_str.lower().strip()
_SCREAMING_SNAKE_CASE ... | 47 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def __snake_case ( ):
__a , __a = 9, 14 # noqa: F841
__a = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, ... | 49 | 0 |
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark import (
BarkC... | 48 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _A ( unittest.TestCase ):
def _lowerCamelCase ( self : List[Any]):
'''simple docstring'''
__a = [
'''safety_checker/pytorch_mo... | 49 | 0 |
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_col... | 50 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers i... | 49 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenizati... | 51 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_mo... | 49 | 0 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A__ ( __snake_case ):
_UpperCAmelCase :List[Any] = (DDIMParallelScheduler,)
_UpperCAmelCase :Any = (('eta', 0.0), ('num_inference_steps', 5_0))
... | 52 |
from __future__ import annotations
from typing import Any
def __snake_case ( _UpperCAmelCase ):
if not postfix_notation:
return 0
__a = {'''+''', '''-''', '''*''', '''/'''}
__a = []
for token in postfix_notation:
if token in operations:... | 49 | 0 |
'''simple docstring'''
def lowercase__ ( __lowercase : Union[str, Any] , __lowercase : List[Any] , __lowercase : Optional[int] ) -> Any:
"""simple docstring"""
if n == 0:
return 1
elif n % 2 == 1:
return (binary_... | 53 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
__snake_case :Optional[int] = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generati... | 49 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMSche... | 54 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ):
# Initialise PyTorch model
... | 49 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( UpperCAmelCase_ : Dict , UpperCAmelC... | 55 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def __snake_case ( _UpperCAmelCase = "isbn/0140328726" ):
__a = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashes
if new_olid.count('''/''' )... | 49 | 0 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
... | 56 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class _A ( __UpperCAmelCase ):
def __init__( self : Optional[int] ... | 49 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils i... | 57 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 49 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class a_ :
'''simple docstring'''
def __init__( self , A = 6 ) -> None:
_SCREAMING_SNAKE_CASE = None
_SCREAMING_SNAKE_CASE = None
self.create_linked_list(... | 58 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _A ( __UpperCAmelCase ):
UpperCamelCase__ : Tuple = (DDPMParallelScheduler,)
def _lowerCamelCase ( self : int , **__SCREAMING_SNAKE_... | 49 | 0 |
import math
import unittest
def UpperCamelCase ( __lowerCamelCase : int ):
assert isinstance(__lowerCamelCase , __lowerCamelCase ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes... | 59 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch
from ..mode... | 49 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
snake_case__ : Optional[int] = {
'''configuration_altclip''': [
'''ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''A... | 60 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
__snake_case :str = logging.get_logger(__name__)
__snake_case ... | 49 | 0 |
"""simple docstring"""
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 ... | 61 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers import (
Effic... | 49 | 0 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
'nielsr/canine-s': 2048,
}
# Unicode defines 1,114,112 total “codepoints”
_A = 111_4112
# B... | 62 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__snake_case :Optional[Any] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__snake_case :Any = [file for fil... | 49 | 0 |
'''simple docstring'''
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
cla... | 63 |
from collections import defaultdict
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase ):
__a = first_str.lower().strip()
__a = second_str.lower().strip()
# Remove whitespace
__a = first_str.replace(''' ''' , '''''' )
__a ... | 49 | 0 |
"""simple docstring"""
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def UpperCAmelCase__ (snake_case__ : Optional[int] , snake_case__ : str , snake_case__ : Optional[Any] , snake_case__ : str ):
"""si... | 64 |
import logging
from transformers.configuration_utils import PretrainedConfig
__snake_case :Any = logging.getLogger(__name__)
class _A ( __UpperCAmelCase ):
UpperCamelCase__ : Optional[Any] = '''masked_bert'''
def __init__( self : str ... | 49 | 0 |
UpperCamelCase__ = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
def lowerCAmelCase_ ( ) -> None:
'''simple docstring'''
UpperCAmelCase__ = input("Enter message: " )
UpperCAmelCase__ = input("Enter key [alphanumeric]: " )
Uppe... | 65 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _A :
UpperCamelCase__ : Optional[Union[str, Path]] = None
UpperCamelCase__ : bool = False
UpperCamelCase__ : bool... | 49 | 0 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
__a = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False)
parser.add_argument("--dpm", action="... | 66 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Union[str, Any] = logging.get_logger(__name__)
__snake_case :Any = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class ... | 49 | 0 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
__UpperCAmelCase =log... | 67 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
__snake_case :List[Any] = logging.getLogger(__name__)
class _A :
def __init__( self : List[str]):... | 49 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""google/switch-base-8""": """https://huggingface.co/google/switch-base-8/blob/main/config.json""",
}
class a__ ( snake_case ... | 68 |
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ... | 49 | 0 |
"""simple docstring"""
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,... | 69 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __snak... | 49 | 0 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def UpperCamelCase__ ( lowerCAmelCase = 1_50_00_00 ):
"""simple docstring"""
_lowerCAmelCase = defaultdict(lowerCAmelCase )
_lowerCAmelCase ... | 70 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def __snake_case ( ):
__a , __a = 9, 14 # noqa: F841
__a = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, ... | 49 | 0 |
def A ( a_ = 1_000 ) -> int:
__UpperCamelCase , __UpperCamelCase : Optional[Any] =1, 1
__UpperCamelCase : Optional[Any] =[]
for i in range(1 ,n + 1 ):
__UpperCamelCase : int =prev_nu... | 71 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _A ( unittest.TestCase ):
def _lowerCamelCase ( self : List[Any]):
'''simple docstring'''
__a = [
'''safety_checker/pytorch_mo... | 49 | 0 |
"""simple docstring"""
lowerCAmelCase__ = [0, 2, 4, 6, 8]
lowerCAmelCase__ = [1, 3, 5, 7, 9]
def snake_case_ ( A_ : int, A_ : int, A_ : list[int], A_ : int ):
'''simple docstring'''
if remaining_length == 0:
... | 72 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers i... | 49 | 0 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ ) -> None:
__lowerCamelCase , __lowerCamelCase : Dict = analyze_text(lowerCamelCase__ )
__lo... | 73 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_mo... | 49 | 0 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class lowerCAm... | 74 |
from __future__ import annotations
from typing import Any
def __snake_case ( _UpperCAmelCase ):
if not postfix_notation:
return 0
__a = {'''+''', '''-''', '''*''', '''/'''}
__a = []
for token in postfix_notation:
if token in operations:... | 49 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
a_ : Optional[int] = {
"""configuration_gpt_neo""": ["""GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoConfig""", ""... | 75 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
__snake_case :Optional[int] = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generati... | 49 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_perceiver': ['PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PerceiverConfig', 'PerceiverOnnxConfi... | 76 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ):
# Initialise PyTorch model
... | 49 | 0 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def a_ ( ):
'''simple docstring'''
lowercase__ : Any = ArgumentParser(
descri... | 77 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def __snake_case ( _UpperCAmelCase = "isbn/0140328726" ):
__a = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashes
if new_olid.count('''/''' )... | 49 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_config... | 78 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class _A ( __UpperCAmelCase ):
def __init__( self : Optional[int] ... | 49 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 79 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 49 | 0 |
'''simple docstring'''
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines... | 80 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _A ( __UpperCAmelCase ):
UpperCamelCase__ : Tuple = (DDPMParallelScheduler,)
def _lowerCamelCase ( self : int , **__SCREAMING_SNAKE_... | 49 | 0 |
"""simple docstring"""
import argparse
lowerCamelCase_ : int = """docs/source/_static/js/custom.js"""
def _A ( lowercase ):
"""simple docstring"""
with open(lowercase , encoding='''utf-8''' , newline='''\n''' ) as f:
... | 81 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch
from ..mode... | 49 | 0 |
A__ = """Input must be a string of 8 numbers plus letter"""
A__ = """TRWAGMYFPDXBNJZSQVHLCKE"""
def _UpperCAmelCase ( snake_case ):
"""simple docstring"""
if not isinstance(snake_case , snake_case ):
_lowerCAmelCase = F'Expected string a... | 82 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
__snake_case :str = logging.get_logger(__name__)
__snake_case ... | 49 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case_ : str = logging.get_logger(__name__)
snake_case_ : Any = {
'kssteven/ibert-rober... | 83 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers import (
Effic... | 49 | 0 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowercase__ : tuple[int, int] , lowercase__ : int ) -> list[tuple[int, int]]:
'''simple docstring'''
lowerCAmelCase_ , lowerCAmelCase_ :int = p... | 84 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__snake_case :Optional[Any] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__snake_case :Any = [file for fil... | 49 | 0 |
'''simple docstring'''
import os
import pytest
from attr import dataclass
_SCREAMING_SNAKE_CASE : str = "us-east-1" # defaults region
@dataclass
class _snake_case :
lowerCAmelCase_ : str
lowerCAmelCase_ : Optional[Any] = "arn:aws:iam::55810514172... | 85 |
from collections import defaultdict
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase ):
__a = first_str.lower().strip()
__a = second_str.lower().strip()
# Remove whitespace
__a = first_str.replace(''' ''' , '''''' )
__a ... | 49 | 0 |
"""simple docstring"""
def __lowerCAmelCase (_UpperCamelCase , _UpperCamelCase ):
__lowerCAmelCase : Optional[Any] = len(_UpperCamelCase )
__lowerCAmelCase : int = []
for i in range(len(_UpperCamelCase ) - pat_len + 1 ):
__lowerCAmelCase : Op... | 86 |
import logging
from transformers.configuration_utils import PretrainedConfig
__snake_case :Any = logging.getLogger(__name__)
class _A ( __UpperCAmelCase ):
UpperCamelCase__ : Optional[Any] = '''masked_bert'''
def __init__( self : str ... | 49 | 0 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class snake_case_ ( unittest.TestCase ,__A ):
def __UpperCamelCase ( self : Tuple ) -> Dict:
lowercase__ : Optional[Any] = l... | 87 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _A :
UpperCamelCase__ : Optional[Union[str, Path]] = None
UpperCamelCase__ : bool = False
UpperCamelCase__ : bool... | 49 | 0 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def a__ ( A_ ):
'''simple docstring'''
if not isinstance(A_, A_ ):
raise TypeError("""Undefined for non-integers""" )
elif precision < 1:
raise ValueError("""Undefined for non... | 88 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Union[str, Any] = logging.get_logger(__name__)
__snake_case :Any = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class ... | 49 | 0 |
'''simple docstring'''
def __lowerCamelCase ( ) -> Tuple:
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def __lowerCamelCase ( lowerCAmelCase_ ) -> List[Any]:
_a : Any = 1
_a : Tuple = 2
while i * i... | 89 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
__snake_case :List[Any] = logging.getLogger(__name__)
class _A :
def __init__( self : List[str]):... | 49 | 0 |
def lowerCamelCase_ ( UpperCamelCase__ : int = 6008_5147_5143 ) -> int:
"""simple docstring"""
try:
__lowerCamelCase = int(UpperCamelCase__ )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int... | 90 |
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ... | 49 | 0 |
"""simple docstring"""
from manim import *
class lowerCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self : Optional[int]):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ : List[str] = ... | 91 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __snak... | 49 | 0 |
from __future__ import annotations
def _a ( SCREAMING_SNAKE_CASE_ : list[int] ):
if not nums:
return 0
__lowerCAmelCase = nums[0]
__lowerCAmelCase = 0
for num in nums[1:]:
__lowerCAmelCase , __lowerCAmelCase ... | 92 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def __snake_case ( ):
__a , __a = 9, 14 # noqa: F841
__a = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, ... | 49 | 0 |
'''simple docstring'''
from __future__ import annotations
_lowercase : List[str] = [-1_0, -5, 0, 5, 5.1, 1_1, 1_3, 2_1, 3, 4, -2_1, -1_0, -5, -1, 0]
_lowercase : List[Any] = [-5, 0, 5, 5.1, 1_1, 1_3, 2_1, -1, 4, -1, -1_0, -5, -1, 0, -1]
def snake_case_ ( ... | 93 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _A ( unittest.TestCase ):
def _lowerCamelCase ( self : List[Any]):
'''simple docstring'''
__a = [
'''safety_checker/pytorch_mo... | 49 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : bytes ):
"""simple docstring"""
return "".join([hex(UpperCAmelCase_ )[2:].zfill(2 ).upper() for byte in list(UpperCAmelCase_ )] )
def __lowerCamelCase ( UpperCAmelCase_ : str ):
"""simp... | 94 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers i... | 49 | 0 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class __lowerCAmelCase ( UpperCamelCase__):
def... | 95 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_mo... | 49 | 0 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
fro... | 96 |
from __future__ import annotations
from typing import Any
def __snake_case ( _UpperCAmelCase ):
if not postfix_notation:
return 0
__a = {'''+''', '''-''', '''*''', '''/'''}
__a = []
for token in postfix_notation:
if token in operations:... | 49 | 0 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#... | 97 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
__snake_case :Optional[int] = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generati... | 49 | 0 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def a_ ( lowerCamelCase ):
Upp... | 98 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ):
# Initialise PyTorch model
... | 49 | 0 |
class A__ :
"""simple docstring"""
def __init__( self , lowercase) -> None:
'''simple docstring'''
a__ : Optional[Any] = len(lowercase)
a__ : Tuple = [0] * len_array
if len_array > 0:
a__ : List... | 99 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def __snake_case ( _UpperCAmelCase = "isbn/0140328726" ):
__a = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashes
if new_olid.count('''/''' )... | 49 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InformerConfig"... | 100 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class _A ( __UpperCAmelCase ):
def __init__( self : Optional[int] ... | 49 | 0 |
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
... | 101 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 49 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
SCREAMING_SNAKE_CASE : Optional[Any] = {
"""susnato/ernie-m-base_pytorch""": """https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json""",
... | 102 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _A ( __UpperCAmelCase ):
UpperCamelCase__ : Tuple = (DDPMParallelScheduler,)
def _lowerCamelCase ( self : int , **__SCREAMING_SNAKE_... | 49 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
A__ : Union[str, Any] = R'''
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control the model outputs.... | 103 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch
from ..mode... | 49 | 0 |
'''simple docstring'''
import random
def _A ( A__ , A__ , A__ ):
"""simple docstring"""
__lowercase = a[left_index]
__lowercase = left_index + 1
for j in range(left_index + 1 , A__ ):
if a[j] < pivot:
__lowercase , __lowercase ... | 104 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
__snake_case :str = logging.get_logger(__name__)
__snake_case ... | 49 | 0 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __UpperCamelCase ( a__ , a__ ):
@register_to_config
def __init__( sel... | 105 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers import (
Effic... | 49 | 0 |
"""simple docstring"""
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
__UpperCamelCase : int = logging.... | 106 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__snake_case :Optional[Any] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__snake_case :Any = [file for fil... | 49 | 0 |
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def __magic_name__ ( A : List[str], A : str, A : str, A : Path, A : str = None, A : str = None, A : str = None,... | 107 |
from collections import defaultdict
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase ):
__a = first_str.lower().strip()
__a = second_str.lower().strip()
# Remove whitespace
__a = first_str.replace(''' ''' , '''''' )
__a ... | 49 | 0 |
"""simple docstring"""
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... | 108 |
import logging
from transformers.configuration_utils import PretrainedConfig
__snake_case :Any = logging.getLogger(__name__)
class _A ( __UpperCAmelCase ):
UpperCamelCase__ : Optional[Any] = '''masked_bert'''
def __init__( self : str ... | 49 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, Tensor... | 109 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _A :
UpperCamelCase__ : Optional[Union[str, Path]] = None
UpperCamelCase__ : bool = False
UpperCamelCase__ : bool... | 49 | 0 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
Requ... | 110 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Union[str, Any] = logging.get_logger(__name__)
__snake_case :Any = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class ... | 49 | 0 |
def lowerCAmelCase_ ( _lowercase : Dict , _lowercase : List[str] , _lowercase : int) -> Union[str, Any]:
"""simple docstring"""
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(_UpperCAmelCase , n -... | 170 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
__snake_case :List[Any] = logging.getLogger(__name__)
class _A :
def __init__( self : List[str]):... | 49 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_A : Union[str, Any] = logging.get_logger(__name__)
_A : Optional[int] = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visu... | 229 |
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ... | 49 | 0 |
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE__ ( __a , __a , __a ):
# Initialise PyTorch model
snake_case_ ... | 327 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __snak... | 49 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__A : Tuple = logging.get_logger(__name__)
class _a ( __UpperCAmelCase):
"""simple docstring"""
def __init__( self :... | 260 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def __snake_case ( ):
__a , __a = 9, 14 # noqa: F841
__a = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, ... | 49 | 0 |
from __future__ import annotations
A : str = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def lowercase_ ( _A : List[Any] , _A : Optional[Any] , _A : int , _A : Dict , _A : Tuple , )... | 184 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _A ( unittest.TestCase ):
def _lowerCamelCase ( self : List[Any]):
'''simple docstring'''
__a = [
'''safety_checker/pytorch_mo... | 49 | 0 |
"""simple docstring"""
UpperCAmelCase__ : Tuple = [
9_9_9,
8_0_0,
7_9_9,
6_0_0,
5_9_9,
5_0_0,
4_0_0,
3_9_9,
3_7_7,
3_5_5,
3_3_3,
3_1_1,
2_8_8,
2_6_6,
2_4_4,
2_2_2,
2_0_0,
1_9_9,
1_7_7,
1_5_5,... | 25 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers i... | 49 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( __lowerCamelCase : Union[str, Any] ) ->List[Any]:
create_state_space_tree(_UpperCAmelCase , [] , 0 , [0 for i in range(len(_UpperCAmelCase ) )] )
def lowerCamelC... | 58 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_mo... | 49 | 0 |
'''simple docstring'''
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf... | 163 |
from __future__ import annotations
from typing import Any
def __snake_case ( _UpperCAmelCase ):
if not postfix_notation:
return 0
__a = {'''+''', '''-''', '''*''', '''/'''}
__a = []
for token in postfix_notation:
if token in operations:... | 49 | 0 |
from collections.abc import Generator
from math import sin
def __A ( __lowerCAmelCase )-> Union[str, Any]:
"""simple docstring"""
if len(_UpperCAmelCase ) != 32:
raise ValueError('Input must be of length 32' )
_UpperCAmelCase = b... | 39 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
__snake_case :Optional[int] = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generati... | 49 | 0 |
"""simple docstring"""
lowerCAmelCase__ = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''... | 153 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ):
# Initialise PyTorch model
... | 49 | 0 |
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