code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def lowercase__ ( lowercase_ = 3 ) -> qiskit.result.counts.Counts:
"""simple docstring"""
if isinstance(lower... | 624 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 1 |
"""simple docstring"""
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils im... | 624 |
"""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
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 1 |
"""simple docstring"""
from math import factorial
lowerCamelCase__ = {str(digit): factorial(digit) for digit in range(10)}
def lowercase__ ( lowercase_ ) -> int:
"""simple docstring"""
if not isinstance(lowercase_ ,lowercase_ ):
raise Typ... | 624 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ = re.compile(R"^_i... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ = 3 ,lowercase_ = 7 ,lowercase_ = 1_000_000 ) -> int:
"""simple docstring"""
_UpperCamelCase : List[str] = 0
_UpperCamelCase : Optional[int] = 1
for current_denominato... | 624 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 1 |
"""simple docstring"""
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's e... | 624 |
"""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.util... | 624 | 1 |
"""simple docstring"""
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import ... | 624 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 1 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def lowercase__ ( lowercase_ ) -> List[str]:
"""simple docstring"""
if "model" in orig_key:
_UpperCamelCase : Any = orig_key.re... | 624 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> float:
"""simple docstring"""
if not nums: # Makes sure that the list is not empty
raise ValueError("List is empty" )
_UpperCamelCase : List[str] = sum(lowercase_ ... | 624 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ,lowercase_ ) -> float:
"""simple docstring"""
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f"""{price_plus_tax(100, 0.2_5) = }""")
print(f"""{price_plus_tax(1_2_5.5_0, 0.0_5) = }""")
| 624 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class __SCREAMING_SNAKE_CASE ( _... | 624 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 624 | 1 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
lowerCamelCase__ = pytest.mark.integration
@pytest.mark.parametrize("path" ... | 624 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> int:
"""simple docstring"""
if not isinstance(lowercase_ ,lowercase_ ):
raise ValueError("Input must be an integer" )
if input_num <= 0:
raise ValueError("Input must be... | 624 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 624 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
lowerCamelCase__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
def __init__( self : ... | 624 |
"""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,
)
| 624 | 1 |
"""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_configuration_commo... | 624 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 1 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import req... | 624 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 1 |
"""simple docstring"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.conf... | 624 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 1 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
def __init__( self : int , __a : Optional[... | 624 |
"""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_... | 624 | 1 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Any , __a : Any , __a : Dict , __a : Dict ) -> List[str]:
_UpperCamelCase : Tuple = None
_UpperCamelCase : ... | 624 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
if p < 2:
raise ValueError("p should not be less than 2!" )
elif p == 2:
return True
_UpperCamelCase : Optional[Any] = 4
... | 624 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 1 |
"""simple docstring"""
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
lowerCamelCase__ = "<<<<<<< This should probably be modified because it mentions: "
lowerCamelCase__... | 624 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 1 |
"""simple docstring"""
import string
import numpy
def lowercase__ ( lowercase_ ,lowercase_ ) -> int:
"""simple docstring"""
return b if a == 0 else greatest_common_divisor(b % a ,lowercase_ )
class __SCREAMING_SNAKE_CASE :
'''simple doc... | 624 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"configuration_nllb_moe": [
"NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP",
"NllbMoeConfig",
]
}
try:
if not is_torch_ava... | 624 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 1 |
"""simple docstring"""
from math import isqrt
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 ,isqrt(lowercase_ ) + 1 ) )
def lowercase__ ( lowercase_ = 1... | 624 |
"""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
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditi... | 624 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ = re.compile(R"^_i... | 624 | 1 |
"""simple docstring"""
import math
def lowercase__ ( lowercase_ ,lowercase_ ) -> float:
"""simple docstring"""
if (
not isinstance(lowercase_ ,(int, float) )
or power_factor < -1
or power_factor > 1
):
raise... | 624 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {"configuration_yolos": ["YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP", "YolosConfig", "YolosOnnxConfig"]}
try:
if not is_vision... | 624 |
"""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.util... | 624 | 1 |
"""simple docstring"""
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test... | 624 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 1 |
"""simple docstring"""
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
import tensorflow as tf
... | 624 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 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_identi... | 624 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 1 |
"""simple docstring"""
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execu... | 624 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 1 |
"""simple docstring"""
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
lowerCamelCase__ ... | 624 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 1 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrat... | 624 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 624 | 1 |
"""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_ARCHIV... | 624 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 1 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase__ = False
try:
lowerCamelC... | 624 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 624 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
lowerCamelCase__ = logging.get_logger(__name__)
lo... | 624 |
"""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,
)
| 624 | 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 versi... | 624 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> int:
"""simple docstring"""
_UpperCamelCase : Optional[int] = 1
for i in range(1 ,num + 1 ):
fact *= i
return fact
def lowercase__ ( lowercase... | 624 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ = 50 ) -> int:
"""simple docstring"""
_UpperCamelCase : List[Any] = [1] * (length + 1)
for row_length in range(3 ,length + 1 ):
for block_length in range(3 ,row_length + 1 ... | 624 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 1 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def lowercase__ ... | 624 |
"""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_... | 624 | 1 |
"""simple docstring"""
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTe... | 624 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 1 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
def __init__( self : int ... | 624 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 1 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"microsoft/git-base": "https://huggingface.co/microsoft/git-base/resolve/m... | 624 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 1 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ ... | 624 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 1 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ = re.compile(R"^_i... | 624 | 1 |
"""simple docstring"""
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
fr... | 624 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 1 |
"""simple docstring"""
import cmath
import math
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> complex:
"""simple docstring"""
_UpperCamelCase : str = math.radians(lowercase_ )
_UpperCamelCase : Dict ... | 624 |
"""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.util... | 624 | 1 |
"""simple docstring"""
lowerCamelCase__ = [
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
44,
22,
0,
]
lowerCamelCase__ =... | 624 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 1 |
"""simple docstring"""
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
lowerCamelCase__... | 624 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 1 |
"""simple docstring"""
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
lowerCamelCase__ = [
# (stable-diffusion, HF Diffusers)
("time_embed.0.weight", "time_embedding.li... | 624 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 1 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[int] = "SpeechT5FeatureExtractor"
SCREAMING_SNAKE_CASE__ :str = "SpeechT5Toke... | 624 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 624 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 1 |
"""simple docstring"""
import sys
import turtle
def lowercase__ ( lowercase_ ,lowercase_ ) -> tuple[float, float]:
"""simple docstring"""
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_... | 624 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 624 | 1 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 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-... | 624 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ = 10 ) -> str:
"""simple docstring"""
if not isinstance(lowercase_ ,lowercase_ ) or n < 0:
raise ValueError("Invalid input" )
_UpperCamelCase : Union[str, Any] = 10**n
... | 624 |
"""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,
)
| 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ) -> int:
"""simple docstring"""
def update_area_of_max_square(lowercase_ ,lowercase_ ) -> int:
# BASE CASE
if row >= rows or col >= cols:
r... | 624 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 1 |
"""simple docstring"""
from collections.abc import Sequence
def lowercase__ ( lowercase_ ,lowercase_ = False ) -> float:
"""simple docstring"""
if not arr:
return 0
_UpperCamelCase : List[str] = 0 if allow_empty_subarrays else... | 624 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import DistilBertConfig, 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 M... | 624 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> int:
"""simple docstring"""
if height >= 1:
move_tower(height - 1 ,lowercase_ ,lowercase_ ,lowercase_ )
move_disk(lowercase_ ,lowercase_ ... | 624 |
"""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_... | 624 | 1 |
"""simple docstring"""
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
... | 624 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowercase_ ) -> list[int]:
"""simple docstring"""
return [ord(lowercase_ ) - 96 for elem in plain]
def lowercase__ ( lowercase_ ) -> str:
... | 624 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 1 |
"""simple docstring"""
from math import loga
def lowercase__ ( lowercase_ ) -> int:
"""simple docstring"""
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(lowercase_ ,lowercase_ ):
ra... | 624 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 1 |
"""simple docstring"""
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import... | 624 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 1 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
lowerCamelCase__ = True
except (ImportError, ModuleNotFoundError):
lowerCamelCase__ = False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.download("punkt", quiet=True)
def lowercase__ ... | 624 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 1 |
"""simple docstring"""
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowercase__ ( lowercase_ ) -> str:
"""simple docstring"""
_UpperCamelCase : List[Any] = ... | 624 |
"""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
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json",
}
class __S... | 624 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ = re.compile(R"^_i... | 624 | 1 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 1 |
"""simple docstring"""
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_d... | 624 |
"""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.util... | 624 | 1 |
"""simple docstring"""
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
lowerCamelCase__ = logging.get_lo... | 624 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 1 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__na... | 624 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 1 |
"""simple docstring"""
from math import isqrt
def lowercase__ ( lowercase_ ) -> list[int]:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [True] * max_number
for i in range(2 ,isqrt(max_number - 1 ) + 1 ):
i... | 624 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 1 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
def lowercase__ ( lowercase_ ) -> tuple[np.ndarray, np.ndarray]:
"""simple docstring"""
_UpperCamelCase, _UpperCamelCase : List[Any] = np.shape(lowercase_ )
... | 624 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 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-... | 624 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 1 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaT... | 624 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 624 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available(... | 624 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 1 |
"""simple docstring"""
from pathlib import Path
import fire
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ) -> Any:
"""simple docstring"""
_UpperCamelCase : List[Any] = Path(lowercase_ )
_UpperCamelCase : int = ... | 624 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 624 | 1 |
"""simple docstring"""
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_at... | 624 |
"""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,
)
| 624 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {"vocab_file": "s... | 624 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __SCREAMING_SNAKE_CASE ( _Uppe... | 624 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : Any = 0
for ch in input_str:
_UpperCamelCase : Optional[Any] = ord(lowercase_ )
_UpperCamelCase... | 624 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#... | 624 |
"""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_... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> Optional[int]: # noqa: E741
"""simple docstring"""
_UpperCamelCase : List[Any] = len(lowercase_ )
_UpperCamelCase : str = 0
_UpperCamelCase : List[Any] ... | 624 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 1 |
"""simple docstring"""
from scipy.stats import spearmanr
import datasets
lowerCamelCase__ = "\nThe Spearman rank-order correlation coefficient is a measure of the\nrelationship between two datasets. Like other correlation coefficients,\nthis one varies between -1 and +1 with 0 implying no correlation.\n... | 624 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 1 |
"""simple docstring"""
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuratio... | 624 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 1 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 624 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 1 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 |
"""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
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 1 |
"""simple docstring"""
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ) -> str:
"""simple... | 624 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ = re.compile(R"^_i... | 624 | 1 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
lowerCamelCase__ = ""
lowerCamelCase__ = ""
lowerCamelCase__ = ""
lowerCamelCase__ = 1 # (0 is vertical, 1 is horizontal)
def lowercase__ ( ) -> None... | 624 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 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
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 |
"""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.util... | 624 | 1 |
"""simple docstring"""
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
lowerCamelCase__ = logging.getLogger(__name__)
class __SCREAMING_SNAKE_CASE :
'''simple docstri... | 624 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowercase__ ( lowercase_ ,lowercase_ ) -> str | Literal[False]:
"""simple docstring"""
_UpperCamelCase : Optional[int] = ... | 624 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"facebook/xmod-base": "http... | 624 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {"configuration_vit_mae": ["VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTMAEConfig"]... | 624 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 1 |
"""simple docstring"""
from collections import deque
def lowercase__ ( lowercase_ ) -> str:
"""simple docstring"""
_UpperCamelCase : List[str] = len(lowercase_ )
_UpperCamelCase : Tuple = deque()
_UpperCamelCase ... | 624 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 624 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
low... | 624 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 1 |
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