code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case : List[Any] = logging.get_logger(__name__)
__snake_case ... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : int = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransf... | 687 | 1 |
'''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 datasets.dataset_dict import I... | 687 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
... | 687 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_ava... | 687 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
__snake_case : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_ ):
'''simple docstring'''
def __init__( self : Tuple... | 687 | 1 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case : Optional[int] = logging.get_logger(__name__)
__snake_case : Tuple = {
'vo... | 687 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impo... | 687 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 687 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def __lowerCamelCase ( __snake_case : i... | 687 | 1 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__snake_case : int = '%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('Searc... | 687 |
'''simple docstring'''
from __future__ import annotations
import requests
__snake_case : Union[str, Any] = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category c... | 687 | 1 |
'''simple docstring'''
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
__snake_case : List[Any] = TypeVar('T')
class lowerCamelCase ( Generic[T]... | 687 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__snake_case : Union[str, Any] ... | 687 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identifie... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__snake_case : Union[str, Any] = {
'configuration_falcon': ['FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FalconConfig'],
}
try:
if not is_t... | 687 | 1 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
__snake_case : Dict = logging.get_logger(__nam... | 687 |
'''simple docstring'''
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[int] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__snake_case : Tuple ... | 687 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class lowerCamelCase :
'''simple docstring'''
__snake_case = field(
default='codeparrot/codeparrot' , metadata={'help': 'Model name or path of model to be trained.'} )
__sn... | 687 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.se... | 687 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import ... | 687 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
__snake_case : List[Any] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int ) -> int:
"""simple docstring"""
if a < 0:
raise ValueError("""Input value must be a positive integer""" )
elif isinstance(__snake_case, __snake_case ):
raise TypeError("""Input value ... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : List[str] = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeB... | 687 | 1 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
__snake_case : str = '\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (t... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Optional[int] = {
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_... | 687 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logg... | 687 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils im... | 687 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
__snake_case : Dict = get_tests_dir('fi... | 687 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__snake_case : List[Any] = ... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int = 10**12 ) -> int:
"""simple docstring"""
A__ : int =1
A__ : Any =0
A__ : str =1
A__ : Optional[int] =1
while numerator <= 2 * m... | 687 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__snake_case : Union[str, Any] = logging.get_logger(__name__)
__snake_case : Optional[int] ... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : float ) -> float:
"""simple docstring"""
return 10 - x * x
def __lowerCamelCase ( __snake_case : float, __snake_case : float ) -> float:
"""simple docstring"""
if equation(__snake_c... | 687 |
'''simple docstring'''
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...tes... | 687 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class lowerCamelCase :
'''simple docstring'''
def __init__( self : Optional[Any] , lowerCAmelCase_ : int , lowerCAmelCase_ : MutableSequence[float] ) -> None:
'... | 687 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
__snake_case : str = False
class lowerCamelCase ( ... | 687 | 1 |
'''simple docstring'''
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
__snake_case : str = (
'4S 3H 2C 7S 5H',
'9D 8H 2C 6S 7H',
'2D 6D 9D TH 7D',
'TC 8C 2S JH 6C',
'JH 8S TH AH QH',
'TS KS 5S 9S AC',
... | 687 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decode... | 687 | 1 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
... | 687 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case : Optional[int] = logging.get_logger(__name__)
__snake_case : Tuple = {
'vo... | 687 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
__snake_case : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class lowerCamelCas... | 687 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__snake_case : List[str] = logging.get_logger(__name__)
def __lowerCamelCase ( __snake_case : Any, __snake_case : Any ) -> int:
... | 687 | 1 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class lowerCamelCase ( datasets.BuilderConfig ):
'''simple docstring'''
__snak... | 687 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def __lowerCamelCase ( __snake_case... | 687 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCamelCase ( lowercase_ ):
... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : int = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransf... | 687 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : int = {
'configuration_instructblip': [
'INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InstructBlipConfig',
'Instruc... | 687 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
... | 687 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logg... | 687 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
__snake_case : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_ ):
'''simple docstring'''
def __init__( self : Tuple... | 687 | 1 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from ... | 687 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impo... | 687 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class lowerCamelCase :
'''simple docstring'''
def __init__( self : Optional[int] , lowerCAmelCase_ : Collection[float] | None = None ... | 687 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def __lowerCamelCase ( __snake_case : i... | 687 | 1 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__snake_case : 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_copies # noqa: E402
... | 687 |
'''simple docstring'''
from __future__ import annotations
import requests
__snake_case : Union[str, Any] = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category c... | 687 | 1 |
'''simple docstring'''
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
__snake_case : Optional[Any] = (
'This metric will be removed f... | 687 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__snake_case : Union[str, Any] ... | 687 | 1 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
__snake_case : str = False
class lowerCamelCase ( ... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__snake_case : Union[str, Any] = {
'configuration_falcon': ['FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FalconConfig'],
}
try:
if not is_t... | 687 | 1 |
'''simple docstring'''
from collections.abc import Generator
from math import sin
def __lowerCamelCase ( __snake_case : bytes ) -> bytes:
"""simple docstring"""
if len(__snake_case ) != 32:
raise ValueError("""Input must be of length 32""" )
A__ : Optiona... | 687 |
'''simple docstring'''
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[int] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__snake_case : Tuple ... | 687 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_ ):
'''simple docstring'''
__snake_case = 'encoder-deco... | 687 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.se... | 687 | 1 |
'''simple docstring'''
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
__snake_case : Any = 'scheduler_config.json'
class lowerCamelCase ( lowercase_ ):
'''... | 687 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
__snake_case : List[Any] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_... | 687 | 1 |
'''simple docstring'''
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def __lowerCamelCase ( __snake_case : Dataset, __snake_case : Dict[str, str] ) -> Any:
... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : List[str] = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeB... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int ) -> str:
"""simple docstring"""
if isinstance(__snake_case, __snake_case ):
raise TypeError("""'float' object cannot be interpreted as an integer""" )
if isinstance(__snake_case, __snake_case ):
... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Optional[int] = {
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_... | 687 | 1 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
__sna... | 687 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils im... | 687 | 1 |
'''simple docstring'''
import torch
from torch import nn
class lowerCamelCase ( nn.Module ):
'''simple docstring'''
def __init__( self : List[str] , lowerCAmelCase_ : Optional[Any] , lowerCAmelCase_ : Union[str, Any] , lowerCAmelCase_ : str , lowerCAmelCase_ : str , ... | 687 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__snake_case : List[Any] = ... | 687 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def __lowerCamelCase ( __snake_case : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 =... | 687 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__snake_case : Union[str, Any] = logging.get_logger(__name__)
__snake_case : Optional[int] ... | 687 | 1 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
... | 687 |
'''simple docstring'''
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...tes... | 687 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : str = logging.get_logger(__name__)
__snake_case : Tuple = {
'huggingface/time-series-transformer-tourism-monthly': (
... | 687 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
__snake_case : str = False
class lowerCamelCase ( ... | 687 | 1 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : List[Any] = logging.get_logger(__name__)
__snake_case : Union[str, Any] = {
'microsoft/wavlm-base': 'https://huggingface.co/microso... | 687 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decode... | 687 | 1 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes... | 687 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case : Optional[int] = logging.get_logger(__name__)
__snake_case : Tuple = {
'vo... | 687 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
fr... | 687 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__snake_case : List[str] = logging.get_logger(__name__)
def __lowerCamelCase ( __snake_case : Any, __snake_case : Any ) -> int:
... | 687 | 1 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class lowerCamelCase ( unittest.TestCase ):
'''simple docstring'''
def lowercase__ ( self : List[str] ) -> None:
... | 687 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def __lowerCamelCase ( __snake_case... | 687 | 1 |
'''simple docstring'''
import numpy as np
from PIL import Image
def __lowerCamelCase ( __snake_case : np.ndarray, __snake_case : int, __snake_case : int ) -> np.ndarray:
"""simple docstring"""
A__ : int =np.array(__snake_case )
if arr.shape[0] != arr.shape... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : int = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransf... | 687 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__snake_case : Union[str, Any] = {
'configuration_gpt_neo': ['GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoConfig', 'GPTNeoOnnxConfig'... | 687 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int, __snake_case : int ) -> int:
"""simple docstring"""
A__ : List[str] =1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
A__ : Tuple ... | 687 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
__snake_case : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_ ):
'''simple docstring'''
def __init__( self : Tuple... | 687 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : int = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransf... | 687 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impo... | 687 | 1 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__snake_case : List[Any] = ... | 687 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def __lowerCamelCase ( __snake_case : i... | 687 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelT... | 687 |
'''simple docstring'''
from __future__ import annotations
import requests
__snake_case : Union[str, Any] = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category c... | 687 | 1 |
'''simple docstring'''
import warnings
warnings.warn(
'memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '
'`from accelerate import find_executable_batch_size` to avoid this warning.',
FutureWarning,
)
| 687 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__snake_case : Union[str, Any] ... | 687 | 1 |
'''simple docstring'''
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__snake_case : Union[str, Any] = {
'configuration_falcon': ['FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FalconConfig'],
}
try:
if not is_t... | 687 | 1 |
'''simple docstring'''
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 ( lowercase_ , unittest... | 687 |
'''simple docstring'''
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[int] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__snake_case : Tuple ... | 687 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class lowerCamelCase ( unittest.TestCase ):
'''simple docstring'''
def lowercase__ ( self : Optional[Any] ) ... | 687 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.se... | 687 | 1 |
'''simple docstring'''
import os
import sys
import unittest
__snake_case : List[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 get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
g... | 687 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
__snake_case : List[Any] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : str, __snake_case : list[str] ) -> str:
"""simple docstring"""
A__ : Optional[Any] =""""""
for word_or_phrase in separated:
if not isinstance(__snake_case, __snake_case ):
... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : List[str] = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeB... | 687 | 1 |
'''simple docstring'''
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def __lowerCamelCase ( __snake_case : str = "laptop" ) -> DataFrame:
"""simple docstring"""
A__ : str =f"https://www.amazon.in/lapt... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Optional[int] = {
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_... | 687 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Optional[int] = {
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_... | 687 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils im... | 687 | 1 |
'''simple docstring'''
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_image... | 687 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__snake_case : List[Any] = ... | 687 | 1 |
'''simple docstring'''
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
__snake_case : List[Any] = object()
# For specifying empty leaf dict `{}`
__snake_case : Any = ... | 687 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__snake_case : Union[str, Any] = logging.get_logger(__name__)
__snake_case : Optional[int] ... | 687 | 1 |
'''simple docstring'''
from collections.abc import Sequence
from queue import Queue
class lowerCamelCase :
'''simple docstring'''
def __init__( self : str , lowerCAmelCase_ : Optional[Any] , lowerCAmelCase_ : List[str] , lowerCAmelCase_ : Optional[Any] , lowerCAmelCase_ : Li... | 687 |
'''simple docstring'''
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...tes... | 687 | 1 |
'''simple docstring'''
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
__snake_case : Optional[int] = datasets.utils.logging.get_logger(__name__)
class lowerCamelCase ( folder_based_builder.Fol... | 687 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
__snake_case : str = False
class lowerCamelCase ( ... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int ) -> int:
"""simple docstring"""
A__ : list[list[int]] =[[0 for _ in range(__snake_case )] for _ in range(m + 1 )]
for i in range(m + 1 ):
A__ : List[Any] =1
f... | 687 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decode... | 687 | 1 |
'''simple docstring'''
from collections import defaultdict
class lowerCamelCase :
'''simple docstring'''
def __init__( self : Optional[Any] , lowerCAmelCase_ : List[Any] , lowerCAmelCase_ : Optional[int] ) -> Union[str, Any]:
'''simple docstring'''
A__ ... | 687 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case : Optional[int] = logging.get_logger(__name__)
__snake_case : Tuple = {
'vo... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int = 100 ) -> int:
"""simple docstring"""
A__ : Tuple =n * (n + 1) * (2 * n + 1) / 6
A__ : Optional[Any] =(n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
... | 687 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__snake_case : List[str] = logging.get_logger(__name__)
def __lowerCamelCase ( __snake_case : Any, __snake_case : Any ) -> int:
... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int = 10, __snake_case : int = 22 ) -> int:
"""simple docstring"""
A__ : str =range(1, __snake_case )
A__ : Optional[int] =range(1, __snake_case )
return sum(
1 for ... | 687 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def __lowerCamelCase ( __snake_case... | 687 | 1 |
'''simple docstring'''
import doctest
from collections import deque
import numpy as np
class lowerCamelCase :
'''simple docstring'''
def __init__( self : List[Any] ) -> None:
'''simple docstring'''
A__ : Optional[int] =[2, 1, 2, -1]
A__ ... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : int = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransf... | 687 | 1 |
'''simple docstring'''
from __future__ import annotations
def __lowerCamelCase ( __snake_case : list[int], __snake_case : list[int], __snake_case : list[int], __snake_case : list[list[str]], __snake_case : int, ) -> None:
"""simple docstring"""
A__ : Union[str, Any] ... | 687 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : str, __snake_case : int ) -> list[str]:
"""simple docstring"""
return [sentence[i : i + ngram_size] for i in range(len(__snake_case ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest import testmod
t... | 687 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
__snake_case : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_ ):
'''simple docstring'''
def __init__( self : Tuple... | 687 | 1 |
'''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 : Optional[Any] = logging.get_logger(__name__)
__snake_case : Dict = {
'... | 687 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impo... | 687 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
A... | 687 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def __lowerCamelCase ( __snake_case : i... | 687 | 1 |
'''simple docstring'''
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.num... | 687 |
'''simple docstring'''
from __future__ import annotations
import requests
__snake_case : Union[str, Any] = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category c... | 687 | 1 |
'''simple docstring'''
from __future__ import annotations
import pandas as pd
def __lowerCamelCase ( __snake_case : list[int], __snake_case : list[int], __snake_case : int ) -> list[int]:
"""simple docstring"""
A__ : List[str] =[0] * no_of_processes
A__ ... | 687 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__snake_case : Union[str, Any] ... | 687 | 1 |
'''simple docstring'''
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('hub/hopper-medium-v2/unet/hor32', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/unet/hor128', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/value_function', exist_ok=True)
def __lowerCamelCase ( ... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__snake_case : Union[str, Any] = {
'configuration_falcon': ['FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FalconConfig'],
}
try:
if not is_t... | 687 | 1 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import ... | 687 |
'''simple docstring'''
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[int] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__snake_case : Tuple ... | 687 | 1 |
'''simple docstring'''
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_to... | 687 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.se... | 687 | 1 |
'''simple docstring'''
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'''
__snake_case ... | 687 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
__snake_case : List[Any] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_... | 687 | 1 |
'''simple docstring'''
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class lowerCamelCase :
'''simple docstring'''
__snake_case = None
__snake_case = False
__snake_case = False
__snake_ca... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : List[str] = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeB... | 687 | 1 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def __lowerCamelCase ( ) -> None:
"""simple docstring"""
print("""Making key files...""" )
make_key... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Optional[int] = {
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_... | 687 | 1 |
'''simple docstring'''
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
__snake_case : Tuple = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n titl... | 687 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils im... | 687 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__snake_case : Union[str, Any] ... | 687 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__snake_case : List[Any] = ... | 687 | 1 |
'''simple docstring'''
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
fro... | 687 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__snake_case : Union[str, Any] = logging.get_logger(__name__)
__snake_case : Optional[int] ... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : list ) -> list:
"""simple docstring"""
A__ : str =False
while is_sorted is False: # Until all the indices are traversed keep looping
A__ : Dict =True
for i i... | 687 |
'''simple docstring'''
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...tes... | 687 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.uti... | 687 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
__snake_case : str = False
class lowerCamelCase ( ... | 687 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def __lowerCamelCase ( __snake_case : str, __snake_case : str ) -> str | Literal[False]:
"""simple docstring"""
A__ : Any =list(__snake_case... | 687 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decode... | 687 | 1 |
'''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... | 687 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case : Optional[int] = logging.get_logger(__name__)
__snake_case : Tuple = {
'vo... | 687 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Dict = logging.get_logger(__name__)
__snake_case : Dict = {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCamelCase ( ... | 687 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__snake_case : List[str] = logging.get_logger(__name__)
def __lowerCamelCase ( __snake_case : Any, __snake_case : Any ) -> int:
... | 687 | 1 |
'''simple docstring'''
__snake_case : dict[str, float] = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.609344,
"knot": 1.852,
}
__snake_case : dict[str, float] = {
"km/h": 1.0,
"m/s": 0.277777778,
"mph": 0.621371192,
"knot": 0.539956803,
}
def __lowerCamelCase ( ... | 687 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def __lowerCamelCase ( __snake_case... | 687 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : int = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransf... | 687 | 1 |
'''simple docstring'''
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("""repo_id""", ["""canonical_dataset_name""", """org-name/dataset-name"""] )
@pytest.mark.parametrize("""path""", ["""filename.csv""", """filename with blanks.csv"""] )
@pytest.m... | 687 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
... | 687 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : str, __snake_case : int ) -> list:
"""simple docstring"""
A__ : int =word.split()
def justify(__snake_case : list, __snake_case : int, __snake_case : int ) -> str:
A__ : Tuple... | 687 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
__snake_case : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_ ):
'''simple docstring'''
def __init__( self : Tuple... | 687 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : str = {
'configuration_distilbert': [
'DIS... | 687 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impo... | 687 | 1 |
'''simple docstring'''
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
__snake_case... | 687 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def __lowerCamelCase ( __snake_case : i... | 687 | 1 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast... | 687 |
'''simple docstring'''
from __future__ import annotations
import requests
__snake_case : Union[str, Any] = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category c... | 687 | 1 |
'''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 TokenizerTesterMixin
@require_t... | 687 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__snake_case : Union[str, Any] ... | 687 | 1 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__snake_case : Union[str, Any] = {
'configuration_falcon': ['FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FalconConfig'],
}
try:
if not is_t... | 687 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Optional[Any] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_ ):
'''simple docstring'''
__snake_case = 'timm_backbone'
def __i... | 687 |
'''simple docstring'''
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[int] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__snake_case : Tuple ... | 687 | 1 |
'''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... | 687 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.se... | 687 | 1 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__snake_case : str = ''
__snake_case : List[Any] = ''
__snake_case : Optional[int] = ''
__snake_case : Union[str, Any] = 1 # (0 is vertical, 1 is horizo... | 687 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
__snake_case : List[Any] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_... | 687 | 1 |
'''simple docstring'''
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
__snake_case : Union[str, Any] = numpy.array([0, 0])
__snake_case : int = numpy.array([0.5, 0.8660254])
__snake_case : List[Any]... | 687 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : List[str] = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeB... | 687 | 1 |
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