code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ : Any = {
"""configuration_pix2struct""": [
"""PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 318 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise Optio... | 318 | 1 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils impo... | 318 |
"""simple docstring"""
from __future__ import annotations
UpperCAmelCase_ : List[str] = list[list[int]]
# assigning initial values to the grid
UpperCAmelCase_ : 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, ... | 318 | 1 |
"""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 (
AutoProces... | 318 |
"""simple docstring"""
from itertools import permutations
def _A (__a ) -> bool:
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
SCREAMING_SNAK... | 318 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ... | 318 |
"""simple docstring"""
UpperCAmelCase_ : List[Any] = 9.8_0_6_6_5
def _A (__a , __a , __a = g ) -> float:
"""simple docstring"""
if fluid_density <= 0:
raise ValueError('''Impossible fluid density''' )
if volume < 0:
ra... | 318 | 1 |
"""simple docstring"""
from typing import Any
import numpy as np
def _A (__a ) -> bool:
"""simple docstring"""
return np.array_equal(__a , matrix.conjugate().T )
def _A (__a , __a ) -> Any:
"""simple docstring"""
SCREAMING_SNAKE... | 318 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev... | 318 | 1 |
"""simple docstring"""
from collections import defaultdict
def _A (__a , __a ) -> bool:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = first_str.lower().strip()
SCREAMING_SNAKE_CASE_ : List[Any] = second_str.lower().strip()
# Rem... | 318 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
UpperCAmelCase_ : Any = """examples/"""
UpperCAmelCase_ : Optional[int] = {
"""examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check... | 318 | 1 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _A (__a , __a , __a , __a , ) -> list[float]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CA... | 318 |
"""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
de... | 318 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ : Tuple = {
"""configuration_rag""": ["""RagConfig"""],
"""retrieval_rag""": ["""RagRetriever"""],
... | 318 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowerCAmelCase__ :
'''simple docstring'''
def __init__( self : Tuple , lowercase_ : Optional[int]):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ ... | 318 | 1 |
"""simple docstring"""
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _A () -> str:
"""simple docstring"""
import os as original_os
from os import path as original_path
from os import rename as original_rename
fr... | 318 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffus... | 318 | 1 |
"""simple docstring"""
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device... | 318 |
"""simple docstring"""
from scipy.stats import pearsonr
import datasets
UpperCAmelCase_ : List[Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculat... | 318 | 1 |
"""simple docstring"""
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, ... | 318 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase__ ( tf.keras.layers.Layer ):... | 318 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Any = logging.get_logger(__name__)
UpperCAmelCase_ : Dict = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=b... | 318 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vis... | 318 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Dict = logging.get_logger(__name__)
UpperCAmelCase_ : List[str] = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4... | 318 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Dict = logging.get_logger(__name__)
UpperCAmelCase_ : List[str] = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4... | 318 | 1 |
"""simple docstring"""
from __future__ import annotations
def _A (__a , __a ) -> list[int]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = 0
SCREAMING_SNAKE_CASE_ : Union[str, Any] = len(__a ) - 1
while i < j:
if n... | 318 |
"""simple docstring"""
UpperCAmelCase_ : Optional[int] = 8.3_1_4_4_5_9_8
def _A (__a , __a ) -> float:
"""simple docstring"""
if temperature < 0:
raise Exception('''Temperature cannot be less than 0 K''' )
if molar_mass <= 0:
... | 318 | 1 |
"""simple docstring"""
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatch... | 318 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.d... | 318 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_spe... | 318 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowerCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
__UpperCamelCase = ["image_processor", "feature_extractor"]
__UpperCamelCase = "TvltImageProcessor"
_... | 318 | 1 |
"""simple docstring"""
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _A (__a ) -> Dict:
"""simple docstring"""
if not is_accelerate_available():
return method
SCREAMING_SNAK... | 318 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowerCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
__UpperCamelCase = "SpeechT5FeatureExtractor"
__UpperCamelCase = "SpeechT5Tokenizer"
def __init__( ... | 318 | 1 |
"""simple docstring"""
import os
import unittest
from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTe... | 318 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_... | 318 | 1 |
"""simple docstring"""
from __future__ import annotations
import time
UpperCAmelCase_ : List[str] = list[tuple[int, int]]
UpperCAmelCase_ : Tuple = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, ... | 318 |
"""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,
MusicgenForConditionalGe... | 318 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ : Dict = {
"""configuration_bigbird_pegasus""": [
"""BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
""... | 318 |
"""simple docstring"""
from pathlib import Path
import numpy as np
from PIL import Image
def _A (__a ) -> np.ndarray:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Optional[int] = rgb[:, :, 0],... | 318 | 1 |
"""simple docstring"""
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import i... | 318 |
"""simple docstring"""
from collections import defaultdict
def _A (__a , __a ) -> bool:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = first_str.lower().strip()
SCREAMING_SNAKE_CASE_ : List[Any] = second_str.lower().strip()
# Rem... | 318 | 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
de... | 318 |
"""simple docstring"""
import argparse
from collections import defaultdict
import yaml
UpperCAmelCase_ : Optional[Any] = """docs/source/en/_toctree.yml"""
def _A (__a ) -> Union[str, Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str ... | 318 | 1 |
"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def _A (__a ) -> float:
"""simple docstring"""
return np.dot(__a , __a )
class lowerCAmelCase__ :
'''simple d... | 318 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise Optio... | 318 | 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/LIC... | 318 |
"""simple docstring"""
from __future__ import annotations
UpperCAmelCase_ : List[str] = list[list[int]]
# assigning initial values to the grid
UpperCAmelCase_ : 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, ... | 318 | 1 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
UpperCAmelCase_ :... | 318 |
"""simple docstring"""
from itertools import permutations
def _A (__a ) -> bool:
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
SCREAMING_SNAK... | 318 | 1 |
"""simple docstring"""
def _A (__a , __a , __a ) -> float:
"""simple docstring"""
if principal <= 0:
raise Exception('''Principal borrowed must be > 0''' )
if rate_per_annum < 0:
raise Exception('''Rate of interest must be >= 0''' )
... | 318 |
"""simple docstring"""
UpperCAmelCase_ : List[Any] = 9.8_0_6_6_5
def _A (__a , __a , __a = g ) -> float:
"""simple docstring"""
if fluid_density <= 0:
raise ValueError('''Impossible fluid density''' )
if volume < 0:
ra... | 318 | 1 |
"""simple docstring"""
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _A (__a , __a , __a = "x" , __a = 10**-10 , __a = 1 , ) -> complex:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = symb... | 318 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev... | 318 | 1 |
"""simple docstring"""
from queue import PriorityQueue
from typing import Any
import numpy as np
def _A (__a , __a , __a , __a , __a , __a , __a , __a , __a , ) -> float | int:
"""simple docstring"""
for nxt, d in graph[v]:
if n... | 318 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
UpperCAmelCase_ : Any = """examples/"""
UpperCAmelCase_ : Optional[int] = {
"""examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check... | 318 | 1 |
"""simple docstring"""
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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 ImageP... | 318 |
"""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
de... | 318 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase_ : Optional[int] = {"""configuration_vit_mae""": ["""VIT_MAE_PRET... | 318 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowerCAmelCase__ :
'''simple docstring'''
def __init__( self : Tuple , lowercase_ : Optional[int]):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ ... | 318 | 1 |
"""simple docstring"""
from scipy.stats import pearsonr
import datasets
UpperCAmelCase_ : List[Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculat... | 318 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffus... | 318 | 1 |
"""simple docstring"""
def _A (__a = 10_00 ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = 2**power
SCREAMING_SNAKE_CASE_ : List[str] = str(_UpperCAmelCase )
SCREAMING_SNAKE_CASE_ : Union[str, Any] = list(_Upp... | 350 |
"""simple docstring"""
from scipy.stats import pearsonr
import datasets
UpperCAmelCase_ : List[Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculat... | 318 | 0 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _A (__a = "isbn/0140328726" ) -> dict:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = olid.strip().strip('''/''' ) # ... | 351 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase__ ( tf.keras.layers.Layer ):... | 318 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, req... | 352 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vis... | 318 | 0 |
"""simple docstring"""
def _A (__a ) -> Optional[Any]:
"""simple docstring"""
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: ... | 353 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Dict = logging.get_logger(__name__)
UpperCAmelCase_ : List[str] = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4... | 318 | 0 |
"""simple docstring"""
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase_ = """src/transformer... | 354 |
"""simple docstring"""
UpperCAmelCase_ : Optional[int] = 8.3_1_4_4_5_9_8
def _A (__a , __a ) -> float:
"""simple docstring"""
if temperature < 0:
raise Exception('''Temperature cannot be less than 0 K''' )
if molar_mass <= 0:
... | 318 | 0 |
"""simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
Upper... | 355 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.d... | 318 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, requi... | 356 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowerCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
__UpperCamelCase = ["image_processor", "feature_extractor"]
__UpperCamelCase = "TvltImageProcessor"
_... | 318 | 0 |
"""simple docstring"""
def _A (__a ) -> Tuple:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = []
SCREAMING_SNAKE_CASE_ : Optional[int] = []
SCREAMING_SNAKE_CASE_ : List[str] = {
'''^''': 3,
'''*''': 2,
... | 357 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowerCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
__UpperCamelCase = "SpeechT5FeatureExtractor"
__UpperCamelCase = "SpeechT5Tokenizer"
def __init__( ... | 318 | 0 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
UpperCAmelCase_ : Union[str, Any] = tuple[int, int]
class lowerCAmelCase__ :
'''simple docstring'''
def __init__(... | 358 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_... | 318 | 0 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
UpperCAmelCase_ : Dict = tuple[int, int]
class lowerCAmelCase__ :
'''simple docstring'''
def __init__( self : Optional[int] , l... | 359 |
"""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,
MusicgenForConditionalGe... | 318 | 0 |
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def _A (__a ) -> Optional[int]:
"""simple docstring"""
return 1 / (1 + np.exp(-z ))
def _... | 360 |
"""simple docstring"""
from pathlib import Path
import numpy as np
from PIL import Image
def _A (__a ) -> np.ndarray:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Optional[int] = rgb[:, :, 0],... | 318 | 0 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logg... | 361 |
"""simple docstring"""
from collections import defaultdict
def _A (__a , __a ) -> bool:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = first_str.lower().strip()
SCREAMING_SNAKE_CASE_ : List[Any] = second_str.lower().strip()
# Rem... | 318 | 0 |
"""simple docstring"""
import math
def _A (__a , __a ) -> Optional[Any]:
"""simple docstring"""
return math.pow(lowercase__ , 2 ) - a
def _A (__a ) -> Tuple:
"""simple docstring"""
return 2 * x
def _A (__a ) -> i... | 362 |
"""simple docstring"""
import argparse
from collections import defaultdict
import yaml
UpperCAmelCase_ : Optional[Any] = """docs/source/en/_toctree.yml"""
def _A (__a ) -> Union[str, Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str ... | 318 | 0 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
UpperCAmelCase_ : Union[str, Any] = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.au... | 363 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise Optio... | 318 | 0 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ : int = logging.... | 364 |
"""simple docstring"""
from __future__ import annotations
UpperCAmelCase_ : List[str] = list[list[int]]
# assigning initial values to the grid
UpperCAmelCase_ : 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, ... | 318 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTest... | 365 |
"""simple docstring"""
from itertools import permutations
def _A (__a ) -> bool:
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
SCREAMING_SNAK... | 318 | 0 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature... | 366 |
"""simple docstring"""
UpperCAmelCase_ : List[Any] = 9.8_0_6_6_5
def _A (__a , __a , __a = g ) -> float:
"""simple docstring"""
if fluid_density <= 0:
raise ValueError('''Impossible fluid density''' )
if volume < 0:
ra... | 318 | 0 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
UpperCAmelCase_ : str = logging.getLogger()
@unittest.... | 367 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev... | 318 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def _A (__a , __a ) -> tuple:
"""simple docstring"""
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance <= 0:
rais... | 368 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
UpperCAmelCase_ : Any = """examples/"""
UpperCAmelCase_ : Optional[int] = {
"""examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check... | 318 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
... | 369 |
"""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
de... | 318 | 0 |
import functools
def _A (__a , __a ) -> List[Any]:
"""simple docstring"""
if not isinstance(__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) or not all(isinstance(__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) for day in days ):
raise Va... | 370 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowerCAmelCase__ :
'''simple docstring'''
def __init__( self : Tuple , lowercase_ : Optional[int]):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ ... | 318 | 0 |
"""simple docstring"""
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
'''split_dict''' , [
SplitDict(),
SplitDict({'''train''': SplitInfo(name='''train''' , num_bytes=13_37 , num_exam... | 371 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffus... | 318 | 0 |
"""simple docstring"""
def _A (__a ) -> int:
"""simple docstring"""
if edge <= 0 or not isinstance(__a , __a ):
raise ValueError('''Length must be a positive.''' )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def _A (__a ... | 350 |
"""simple docstring"""
from scipy.stats import pearsonr
import datasets
UpperCAmelCase_ : List[Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculat... | 318 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase_ : Optional[int] = {
"""funnel-transformer/small""": """https://huggingfac... | 351 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase__ ( tf.keras.layers.Layer ):... | 318 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionMode... | 352 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vis... | 318 | 0 |
"""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, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ : List[str] = logging.get_log... | 353 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Dict = logging.get_logger(__name__)
UpperCAmelCase_ : List[str] = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4... | 318 | 0 |
"""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 (
AutoProces... | 354 |
"""simple docstring"""
UpperCAmelCase_ : Optional[int] = 8.3_1_4_4_5_9_8
def _A (__a , __a ) -> float:
"""simple docstring"""
if temperature < 0:
raise Exception('''Temperature cannot be less than 0 K''' )
if molar_mass <= 0:
... | 318 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ : str = {
'''configuration_autoformer''': [
'''AUTOFORMER_PRETRAINED_CONFIG_... | 355 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.d... | 318 | 0 |
"""simple docstring"""
UpperCAmelCase_ : List[Any] = """\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingf... | 356 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowerCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
__UpperCamelCase = ["image_processor", "feature_extractor"]
__UpperCamelCase = "TvltImageProcessor"
_... | 318 | 0 |
"""simple docstring"""
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_con... | 357 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowerCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
__UpperCamelCase = "SpeechT5FeatureExtractor"
__UpperCamelCase = "SpeechT5Tokenizer"
def __init__( ... | 318 | 0 |
"""simple docstring"""
import math
def _A (__a ) -> Union[str, Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = [True] * n
SCREAMING_SNAKE_CASE_ : Optional[int] = False
SCREAMING_SNAKE_CASE_ : int ... | 358 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_... | 318 | 0 |
"""simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict ... | 359 |
"""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,
MusicgenForConditionalGe... | 318 | 0 |
from collections import defaultdict
def _A (__a ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : int = 1
SCREAMING_SNAKE_CASE_ : str = True
for v in tree[start]:
if v not in visited:
ret += dfs(lowerCAmelCase__ )
... | 360 |
"""simple docstring"""
from pathlib import Path
import numpy as np
from PIL import Image
def _A (__a ) -> np.ndarray:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Optional[int] = rgb[:, :, 0],... | 318 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen... | 361 |
"""simple docstring"""
from collections import defaultdict
def _A (__a , __a ) -> bool:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = first_str.lower().strip()
SCREAMING_SNAKE_CASE_ : List[Any] = second_str.lower().strip()
# Rem... | 318 | 0 |
"""simple docstring"""
from __future__ import annotations
def _A (__a , __a = None , __a = None ) -> None:
"""simple docstring"""
if start is None:
SCREAMING_SNAKE_CASE_ : List[str] = 0
if end is None:
SCREAMING_SNAKE_CASE_ : in... | 362 |
"""simple docstring"""
import argparse
from collections import defaultdict
import yaml
UpperCAmelCase_ : Optional[Any] = """docs/source/en/_toctree.yml"""
def _A (__a ) -> Union[str, Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str ... | 318 | 0 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | 363 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise Optio... | 318 | 0 |
"""simple docstring"""
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_... | 364 |
"""simple docstring"""
from __future__ import annotations
UpperCAmelCase_ : List[str] = list[list[int]]
# assigning initial values to the grid
UpperCAmelCase_ : 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, ... | 318 | 0 |
"""simple docstring"""
from __future__ import annotations
def _A (__a , __a , __a ) -> List[Any]:
"""simple docstring"""
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('''One and only one argument must be ... | 365 |
"""simple docstring"""
from itertools import permutations
def _A (__a ) -> bool:
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
SCREAMING_SNAK... | 318 | 0 |
"""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_t... | 366 |
"""simple docstring"""
UpperCAmelCase_ : List[Any] = 9.8_0_6_6_5
def _A (__a , __a , __a = g ) -> float:
"""simple docstring"""
if fluid_density <= 0:
raise ValueError('''Impossible fluid density''' )
if volume < 0:
ra... | 318 | 0 |
"""simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
UpperCAmelCase_ : Dict = {
'<': operator.lt,
'<=': operator.le,
'==': operator.eq,
'!=': operator.ne,
'>=': operator.ge,... | 367 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev... | 318 | 0 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def _A (__a , __a , __a = False ) -> list[float]:
"""simple docstring"""
if radian_mode:
return [magnitude *... | 368 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
UpperCAmelCase_ : Any = """examples/"""
UpperCAmelCase_ : Optional[int] = {
"""examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check... | 318 | 0 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf... | 369 |
"""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
de... | 318 | 0 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
UpperCAmelCase_ : Any = logging.getLogger(__name__)
class lowerCAmelCase__ :
'''simple docstri... | 370 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowerCAmelCase__ :
'''simple docstring'''
def __init__( self : Tuple , lowercase_ : Optional[int]):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ ... | 318 | 0 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowerCAmelCase__ ( _a ... | 371 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffus... | 318 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import loggi... | 350 |
"""simple docstring"""
from scipy.stats import pearsonr
import datasets
UpperCAmelCase_ : List[Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculat... | 318 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ : List[Any] = logging.get_logge... | 351 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase__ ( tf.keras.layers.Layer ):... | 318 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import YolosConfig
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 imp... | 352 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vis... | 318 | 0 |
"""simple docstring"""
def _A () -> Union[str, Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[Any] = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
SCREAMING_SNAKE_CASE_ : List[Any] = 6
SCREAMING_SNAKE_CASE_ : Union[str, Any] ... | 353 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Dict = logging.get_logger(__name__)
UpperCAmelCase_ : List[str] = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4... | 318 | 0 |
"""simple docstring"""
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowerCAmel... | 354 |
"""simple docstring"""
UpperCAmelCase_ : Optional[int] = 8.3_1_4_4_5_9_8
def _A (__a , __a ) -> float:
"""simple docstring"""
if temperature < 0:
raise Exception('''Temperature cannot be less than 0 K''' )
if molar_mass <= 0:
... | 318 | 0 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.uti... | 355 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.d... | 318 | 0 |
"""simple docstring"""
class lowerCAmelCase__ :
'''simple docstring'''
def __init__( self : Tuple):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ : Tuple = {}
def _SCREAMING_SNAKE_CASE ( self : Optional[Any]):
... | 356 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowerCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
__UpperCamelCase = ["image_processor", "feature_extractor"]
__UpperCamelCase = "TvltImageProcessor"
_... | 318 | 0 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def _A (__a , __a , __a = 10**-10 ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = a
while ... | 357 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class lowerCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
__UpperCamelCase = "SpeechT5FeatureExtractor"
__UpperCamelCase = "SpeechT5Tokenizer"
def __init__( ... | 318 | 0 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
UpperCAmelCase_ : Optional[Any] = logging.get_logger(__name__) ... | 358 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_... | 318 | 0 |
"""simple docstring"""
from __future__ import annotations
def _A (__a ) -> None:
"""simple docstring"""
create_state_space_tree(_UpperCAmelCase , [] , 0 , [0 for i in range(len(_UpperCAmelCase ) )] )
def _A (__a , __a , __a ... | 359 |
"""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,
MusicgenForConditionalGe... | 318 | 0 |
from collections.abc import Callable
import numpy as np
def _A (__a , __a , __a , __a , __a ) -> np.ndarray:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = int(np.ceil((x_end - xa) / step_size ) )
SCREAMING_SNAKE_CASE_ : ... | 360 |
"""simple docstring"""
from pathlib import Path
import numpy as np
from PIL import Image
def _A (__a ) -> np.ndarray:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Optional[int] = rgb[:, :, 0],... | 318 | 0 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, ran... | 361 |
"""simple docstring"""
from collections import defaultdict
def _A (__a , __a ) -> bool:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = first_str.lower().strip()
SCREAMING_SNAKE_CASE_ : List[Any] = second_str.lower().strip()
# Rem... | 318 | 0 |
"""simple docstring"""
from typing import Dict
from .base import GenericTensor, Pipeline
class lowerCAmelCase__ ( UpperCamelCase_ ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self : Union[str, Any] , lowercase_ : List[Any]=None ... | 362 |
"""simple docstring"""
import argparse
from collections import defaultdict
import yaml
UpperCAmelCase_ : Optional[Any] = """docs/source/en/_toctree.yml"""
def _A (__a ) -> Union[str, Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str ... | 318 | 0 |
"""simple docstring"""
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _A () -> List[Any]:
"""simple docstring"""
with offline(OfflineSi... | 363 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise Optio... | 318 | 0 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def _A (__a ) -> Any:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Union[str, Any] = os.path.join(args.tf_m... | 364 |
"""simple docstring"""
from __future__ import annotations
UpperCAmelCase_ : List[str] = list[list[int]]
# assigning initial values to the grid
UpperCAmelCase_ : 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, ... | 318 | 0 |
"""simple docstring"""
from typing import Any
import numpy as np
def _A (__a ) -> Optional[Any]:
"""simple docstring"""
return np.array_equal(_a , matrix.conjugate().T )
def _A (__a , __a ) -> Union[str, Any]:
... | 365 |
"""simple docstring"""
from itertools import permutations
def _A (__a ) -> bool:
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
SCREAMING_SNAK... | 318 | 0 |
"""simple docstring"""
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ ... | 366 |
"""simple docstring"""
UpperCAmelCase_ : List[Any] = 9.8_0_6_6_5
def _A (__a , __a , __a = g ) -> float:
"""simple docstring"""
if fluid_density <= 0:
raise ValueError('''Impossible fluid density''' )
if volume < 0:
ra... | 318 | 0 |
"""simple docstring"""
def _A () -> Dict:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : int = []
SCREAMING_SNAKE_CASE_ : Tuple = 1
while len(SCREAMING_SNAKE_CASE__ ) < 1e6:
constant.append(str(SCREAMING_SNAKE_CASE__ ) )
... | 367 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev... | 318 | 0 |
"""simple docstring"""
import tensorflow as tf
from ...tf_utils import shape_list
class lowerCAmelCase__ ( tf.keras.layers.Layer ):
'''simple docstring'''
def __init__( self : Tuple , lowercase_ : int , lowercase_ : List[Any] ... | 368 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
UpperCAmelCase_ : Any = """examples/"""
UpperCAmelCase_ : Optional[int] = {
"""examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check... | 318 | 0 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from ... | 369 |
"""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
de... | 318 | 0 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowerCAmelCase__ ( nn.Module ):
'''simple docstring'''
def __init__( self : Optional[int] , lowercase_ : int = 16 ... | 370 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowerCAmelCase__ :
'''simple docstring'''
def __init__( self : Tuple , lowercase_ : Optional[int]):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ ... | 318 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusi... | 371 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffus... | 318 | 0 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.process... | 350 |
"""simple docstring"""
from scipy.stats import pearsonr
import datasets
UpperCAmelCase_ : List[Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculat... | 318 | 0 |
"""simple docstring"""
import numpy as np
import datasets
UpperCAmelCase_ : List[Any] = """
Compute the Mahalanobis Distance
Mahalonobis distance is the distance between a point and a distribution.
And not between two distinct points. It is effectively a multivariate equivalent of... | 351 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase__ ( tf.keras.layers.Layer ):... | 318 | 0 |
"""simple docstring"""
def _A (__a = 1_00 ) -> Optional[int]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = (n * (n + 1) // 2) ** 2
SCREAMING_SNAKE_CASE_ : int = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ ... | 352 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vis... | 318 | 0 |
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