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 json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from... | 608 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 1 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class _snake_case ( unittest.TestCase ):
'''... | 608 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 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 = {
"roberta-base":... | 608 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 1 |
"""simple docstring"""
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
__lowerCamelCase = "sshleifer/ba... | 608 |
"""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 _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 1 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def a ( __snake_case : str, __snake_case : str = "cpu", __snake_case : Union[str, None] = None ):
'''simple docstring'''
UpperCAmelCase_ :str = torch.... | 608 |
"""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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
Image... | 608 | 1 |
"""simple docstring"""
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
__lowerCamelCase = parse(importlib.metadata.version("torch"))
def a ( __snake_case : Union[str, Version], __snak... | 608 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 1 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 1 |
"""simple docstring"""
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
... | 608 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 1 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 |
"""simple docstring"""
import os
import sys
import unittest
__lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 1 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
__lowerCamelCase = "us-east-1" # defaults region
@dataclass
class _snake_case :
'''simple docstring'''
UpperCamelCase__ =42
UpperCamelCase__ ="""arn:aws:iam::558105141721:role/sagemaker_execu... | 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 1 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfo... | 608 | 1 |
"""simple docstring"""
def a ( __snake_case : int ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeError('''\'float\' object cannot be interpreted as an integer''' )
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 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 $(realpath wavlm/modules.py) ./ # create simlink
# import classe... | 608 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"roberta-base":... | 608 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_av... | 608 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 1 |
"""simple docstring"""
import math
def a ( __snake_case : int ):
'''simple docstring'''
assert isinstance(__snake_case, __snake_case ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return... | 608 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 1 |
"""simple docstring"""
import re
def a ( __snake_case : str ):
'''simple docstring'''
UpperCAmelCase_ :Optional[Any] = re.compile(
r'''^(?:0|94|\+94|0{2}94)''' r'''7(0|1|2|4|5|6|7|8)''' r'''(-| |)''' r'''\d{7}$''' )
return bool(re.search(__snake_case,... | 608 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 1 |
"""simple docstring"""
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils... | 608 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 1 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 1 |
"""simple docstring"""
__lowerCamelCase = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def a ( __snake_case : Tuple, __snake_case : str, __snake_case : List[... | 608 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {
"configuration_mobilenet_v2": [
"MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP",
"MobileNetV2Config... | 608 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_c... | 608 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 1 |
"""simple docstring"""
from string import ascii_uppercase
__lowerCamelCase = {char: i for i, char in enumerate(ascii_uppercase)}
__lowerCamelCase = dict(enumerate(ascii_uppercase))
def a ( __snake_case : str, __snake_case : str ):
'''simple docstring'''
... | 608 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, Be... | 608 | 1 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
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.nump... | 608 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 1 |
"""simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def a ( __snake_case : int ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 ==... | 608 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 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,
)
__lowerCamelCase = {
"configuration_roformer": ["ROFORMER_PRETRA... | 608 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 1 |
"""simple docstring"""
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def a ( __snake_case : bytes, __snake_case : int ):
'''simple docstring'''
UpperCAmelCase_ :Dict = f'{sampling_rate}'
... | 608 |
"""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 _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin
... | 608 |
"""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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
Image... | 608 | 1 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def a ( __snake_case : Optional[Any], __snake_case : Union[str, Any], __sna... | 608 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 1 |
"""simple docstring"""
import os
from datetime import datetime as dt
from github import Github
__lowerCamelCase = [
"good first issue",
"good second issue",
"good difficult issue",
"enhancement",
"new pipeline/model",
"new scheduler",
"wip",
]
def a ( ):
... | 608 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 1 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : int ):
'''simple docstring'''
return x if y == 0 else greatest_common_divisor(__snake_case, x % y )
def a ( __snake_case : int, __snake_case : int ):
'''simple docstring'... | 608 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 1 |
"""simple docstring"""
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def a ( __snake_case : Any, __snake_case : ... | 608 |
"""simple docstring"""
import os
import sys
import unittest
__lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 1 |
"""simple docstring"""
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 1 |
"""simple docstring"""
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch... | 608 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfo... | 608 | 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,
EfficientFormerForImageClassificationWithTeac... | 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 1 |
"""simple docstring"""
from collections.abc import Sequence
def a ( __snake_case : Sequence[float], __snake_case : float ):
'''simple docstring'''
return sum(c * (x**i) for i, c in enumerate(__snake_case ) )
def a ( __snake_case : Sequence[float], _... | 608 |
"""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 = {
"roberta-base":... | 608 | 1 |
"""simple docstring"""
from sklearn.metrics import recall_score
import datasets
__lowerCamelCase = "\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true positives ... | 608 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 1 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
__lowerCamelCase = "\\n@inproceedings{snover-etal-2006-study,\n title = \"A Study of Translation Edit Rate with Targeted Human Annotation\",\n author = \"Snover, Matthew and... | 608 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 1 |
"""simple docstring"""
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope='''session''' )
def a ( ):
'''si... | 608 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 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_av... | 608 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 1 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common i... | 608 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 1 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
SCREAMING_SNAKE_CASE__ : Union[str, Any] = logging.g... | 0 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 0 |
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for tests
from os.path im... | 1 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 0 |
import datasets
UpperCAmelCase_ = """\
@InProceedings{conneau2018xnli,
author = \"Conneau, Alexis
and Rinott, Ruty
and Lample, Guillaume
and Williams, Adina
and Bowman, Samuel R.
and Schwenk, Holger
... | 2 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 0 |
'''simple docstring'''
from __future__ import annotations
lowerCAmelCase : Union[str, Any] = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
lowerCAmelCase : List[str] = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def A_( A : ... | 3 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, Be... | 608 | 0 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__UpperCamelCase : Union[str, Any] = '''examples/'''
__UpperCamelCase : str = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_v... | 4 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfig... | 5 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 0 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list ):
if any(not isinstance(UpperCamelCase__ , UpperCamelCase__ ) or x < 0 for x in sequence ):
raise TypeError("""Sequence must be list of non-negative integers""" )
for _ in range(len(UpperCamelCase__ ) ):
... | 6 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 0 |
"""simple docstring"""
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionMod... | 7 |
"""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 _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 0 |
'''simple docstring'''
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
lowercase__ : List[Any] = False
class SCREAMING... | 8 |
"""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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
Image... | 608 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json''',
# See all ViT MSN mod... | 9 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 0 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ... | 10 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 0 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,... | 11 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 0 |
from __future__ import annotations
lowerCamelCase__ : Optional[int] = list[list[int]]
# assigning initial values to the grid
lowerCamelCase__ : Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, ... | 12 |
"""simple docstring"""
import os
import sys
import unittest
__lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
A__ : str = logging.get_logger(__name__)
class UpperCAmelCase_ (_UpperCAmelCase ):
"""simple docstring"""
def __init__( self ... | 13 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 0 |
from __future__ import annotations
import queue
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self , _a ) -> Union[str, Any]:
_a : Optional[Any] = data
_a : Dict = None... | 14 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfo... | 608 | 0 |
import math
A : List[Any] = 1_0
A : Union[str, Any] = 7
A : List[str] = BALLS_PER_COLOUR * NUM_COLOURS
def UpperCamelCase ( __magic_name__ : int = 20 ) -> str:
"""simple docstring"""
lowercase__ = math.comb(_... | 15 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 0 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from .... | 16 |
"""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 = {
"roberta-base":... | 608 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase_ : Dict = {'''processing_layoutxlm''': ['''LayoutXLMProcessor''']... | 17 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 0 |
'''simple docstring'''
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX... | 18 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 0 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from .... | 19 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase: Tuple = logging.get_logger(__name__)
_lowerCAmelCase: Optional[Any] = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/con... | 20 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 0 |
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def lowerCAmelCase_ ( lowerCamelCase ):
__magic_name__ : int =[
"""encoder.version""",
"""decoder.version""",
... | 21 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 0 |
'''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 : Optional[int] = logging.get_logger(__na... | 22 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 0 |
import numpy as np
def _snake_case (__lowercase):
return 1 / (1 + np.exp(-vector))
def _snake_case (__lowercase):
return vector * sigmoid(__lowercase)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 23 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase_ : Any = logging.get_logger(__name__)
UpperCAmelCase_ : List[Any] =... | 24 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 0 |
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch_available():
import to... | 25 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, Be... | 608 | 0 |
'''simple docstring'''
from __future__ import annotations
__UpperCamelCase = list[list[int]]
# assigning initial values to the grid
__UpperCamelCase = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0,... | 26 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagem... | 27 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
UpperCamelCase_ = logging.get_logger(__name__)
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
... | 28 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 0 |
"""simple docstring"""
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils imp... | 29 |
"""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 _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 0 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils imp... | 30 |
"""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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
Image... | 608 | 0 |
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEmbeddings,
BertLay... | 31 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 0 |
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():
from transformers.m... | 32 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 0 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase ) -> Any:
snake_case__ = [
'''encoder.version''',
'''decoder.version''',
'''model.encode... | 33 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 0 |
"""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 impo... | 34 |
"""simple docstring"""
import os
import sys
import unittest
__lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 0 |
def a ( A__ , A__ ) -> int:
'''simple docstring'''
while b:
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ : Any = b, a % b
return a
def a ( A__ , A__ ) -> int:
'''simple docstring'''
... | 35 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 0 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_pytessera... | 36 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfo... | 608 | 0 |
def UpperCamelCase_ ( __a = 1_000_000 ) -> int:
a__ : int = limit + 1
a__ : str = [0] * limit
for first_term in range(1 , __a ):
for n in range(__a , __a , __a ):
a__ : Optional[int] = first_term + n / first_te... | 37 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase__ ( __magic_name__ : list[int] , __magic_name__ : list[int] , __magic_name__ : int ) -> tuple[float, list[float]]:
'''simple docstring'''
snake_case__ : List[str] ... | 38 |
"""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 = {
"roberta-base":... | 608 | 0 |
import random
from typing import Any
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ ):
for _ in range(len(SCREAMING_SNAKE_CASE__ ) ):
snake_case_ = random.randint(0 , len(SCREAMING_SNAKE_CASE__ ) - 1 )
snake_case_ = random.randint(0 ,... | 39 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 0 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTes... | 40 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_ten... | 41 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 0 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stabl... | 42 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 0 |
import math
from numpy import inf
from scipy.integrate import quad
def _a ( SCREAMING_SNAKE_CASE ):
"""simple docstring"""
if num <= 0:
raise ValueError('''math domain error''' )
return quad(SCREAMING_SNAKE_CASE , 0 , SCREAMING_SNAKE_CASE , args=(SCRE... | 43 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
UpperCAmelCase_ : Optional[int] = {
'configuration_trocr': ['TROCR_PRETRAINED_C... | 44 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
impo... | 45 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 0 |
"""simple docstring"""
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_configur... | 46 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 0 |
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
fr... | 47 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, Be... | 608 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ : List[Any] = {
"configuration_jukebox": [
"JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
"JukeboxConfig",
"JukeboxPriorCo... | 48 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 0 |
"""simple docstring"""
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale... | 49 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 0 |
'''simple docstring'''
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate imp... | 50 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 0 |
'''simple docstring'''
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class lowerCAmelCase__ ( UpperCAmelCase_ ):
'''simple docstring'''
_lowerCamelCase ="EncodecFeatureExtractor"
_l... | 51 |
"""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 _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 0 |
"""simple docstring"""
from __future__ import annotations
def __A ( a_ :list) -> float:
if not nums:
raise ValueError('''List is empty''')
return sum(a_) / len(a_)
if __name__ == "__main__":
import doctest
doctest.testmod() | 52 |
"""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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
Image... | 608 | 0 |
import torch
def a_ ( ):
if torch.cuda.is_available():
__lowerCAmelCase = torch.cuda.device_count()
else:
__lowerCAmelCase = 0
print(F"""Successfully ran on {num_gpus} GPUs""" )
if __name__ == "__main__":
main()
| 53 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : List[Any] =logging.get_logger(__name__)
__lowercase : Dict ={
"""BAAI/AltCLIP""": """https://huggingface.co/BAAI/AltCLIP/resolve/main/c... | 54 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 0 |
import requests
SCREAMING_SNAKE_CASE :List[str] = 'YOUR API KEY'
def UpperCAmelCase ( a_ , a_ = giphy_api_key ) -> list:
"""simple docstring"""
__A = "+".join(query.split() )
__A = F'''https://api.giphy.com/v1/gifs/search?q={for... | 55 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 0 |
'''simple docstring'''
def _a (lowercase__ : int ) -> bool:
"""simple docstring"""
if not isinstance(lowercase__ , lowercase__ ):
raise ValueError('check_bouncy() accepts only integer arguments' )
__snake_case = str(lowercase__ ... | 56 |
"""simple docstring"""
import os
import sys
import unittest
__lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 0 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_C... | 57 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 0 |
"""simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_STAR... | 58 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfo... | 608 | 0 |
from math import ceil, sqrt
def lowerCAmelCase_ ( __a = 1000000 ) -> int:
"""simple docstring"""
lowerCamelCase__: Any =0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
lowerCamelCase__: Optional[int] =... | 59 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 0 |
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