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 |
|---|---|---|---|---|
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
a_ : List[Any] = logging.get_logger(__name__)
class _snake_case ( A__ ):
def __init__( self , *a , **a) -> None:
warnings.warn(... | 73 |
def lowerCamelCase__ (_UpperCAmelCase = 10 , _UpperCAmelCase = 1000 , _UpperCAmelCase = True):
assert (
isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _U... | 73 | 1 |
a_ : dict[str, float] = {
"joule": 1.0,
"kilojoule": 10_00,
"megajoule": 1_00_00_00,
"gigajoule": 10_00_00_00_00,
"wattsecond": 1.0,
"watthour": 36_00,
"kilowatthour": 3_60_00_00,
"newtonmeter": 1.0,
"calorie_nutr": 41_86.8,
"kilocalorie_nutr": 4_18_68_00.... | 73 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 73 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a_ : Any = {'configuration_vit_mae': ['VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMAEConfig']}
try:
if not i... | 73 |
from __future__ import annotations
a_ : str = []
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase):
for i in range(len(_UpperCAmelCase)):
if board[row][i] == 1:
return False
for i in range(len(_UpperCAmelCase)):
... | 73 | 1 |
# 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-2.0
#
# Unless required by ap... | 73 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepInverseScheduler,
... | 73 | 1 |
import itertools
import math
def lowerCamelCase__ (_UpperCAmelCase):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# A... | 73 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : List[str] = logging.get_logger(__name__)
a_ : Any = {
'microsoft/unispeech-large-1500h-cv': (
'https://huggingface.co/microsoft/unispeech-large-... | 73 | 1 |
def lowerCamelCase__ (_UpperCAmelCase = 10 , _UpperCAmelCase = 1000 , _UpperCAmelCase = True):
assert (
isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _U... | 73 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a_ : Optional[Any] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a_ : List[str] = None
def lowerCamelCase__ ():
SCREAMING_SNAKE_CASE = argpa... | 73 | 1 |
from __future__ import annotations
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
SCREAMING_SNAKE_CASE = []
SCREAMING_SNAKE_CASE = []
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = sum(_UpperCAmelCase)
create_state_space_tree(_Upp... | 73 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a_ : Dict = logging.get_logger(__name__)
class _snake_case ( A__ ):
def __init__( self , *a , **a) -> None:
warnings.warn(
'The clas... | 73 | 1 |
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 logging
a_ : List[str] ... | 73 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _snake_case ( unittest.TestCase , A__ ):
def SCREAMING_SNAKE_CASE__ ( self) -> List[str]:
SCREAMING_SNAKE_CASE = load_tool('text-classification')
... | 73 | 1 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMi... | 73 |
import sys
import turtle
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , ):
my_p... | 73 | 1 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding,... | 73 |
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 import Accelerator
from accelerat... | 73 | 1 |
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
from ..test_model... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
a_ : List[str] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:... | 73 | 1 |
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
@flax.struct.dataclass
c... | 73 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
fr... | 73 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 73 |
from __future__ import annotations
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = 2
SCREAMING_SNAKE_CASE = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(_UpperCAmelCase)
if n > 1:
factors.... | 73 | 1 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_swi... | 73 |
import math
import os
import sys
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = ''
try:
with open(_UpperCAmelCase , 'rb') as binary_file:
SCREAMING_SNAKE_CASE = binary_file.read()
for dat in data:
SCREAMING_SNAKE_CASE ... | 73 | 1 |
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
if digit_amount > 0:
return round(number - int(_UpperCAmelCase) , _UpperCAmelCase)
return number - int(_UpperCAmelCase)
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(decimal_isolate(35.34... | 73 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIF... | 73 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.uti... | 73 |
import heapq as hq
import math
from collections.abc import Iterator
class _snake_case :
def __init__( self , a) -> Optional[Any]:
SCREAMING_SNAKE_CASE = str(id_)
SCREAMING_SNAKE_CASE = None
SCREAMING_SNAKE_CASE = None
SCREAMING_SNAK... | 73 | 1 |
import argparse
import json
import subprocess
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
SCREAMING_SNAKE_CASE = []
SCREAMING_SNAKE_CASE = (
F'''curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {token}"'''
' https:/... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ : Optional[Any] = {
'configuration_mask2former': [
'MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Mask2FormerConfig',
],
}
try:... | 73 | 1 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
a_ : Union[str, Any] = ... | 73 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Dict = logging.get_logger(__name__)
a_ : Union[str, Any] = {
'edbeeching/decision-transformer-gym-hopper-medium': (
'https://huggingface.co/edbeeching/decision-transformer-gym-ho... | 73 | 1 |
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def lowerCamelCase__ (_UpperCAmelCase)... | 73 |
import argparse
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 accelerate import Accelerator, Distribu... | 73 | 1 |
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = generate_pascal_triangle(_UpperCAmelCase)
for row_idx in range(_UpperCAmelCase):
# Print left spaces
for _ in range(num_rows - row_idx - 1):
print(end=' ')
# Print row values
for col_idx in rang... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ : int = {
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': ['RagTokenizer'],
}
try:
if not is_to... | 73 | 1 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : int = logging.get_logger(__name__)
a_ : Optional[Any] = {
'facebook/data2vec-base-960h': 'https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json',... | 73 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = False):
if radian_mode:
return [magnitude * cos(_UpperCAmelCase), m... | 73 | 1 |
from __future__ import annotations
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase):
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and array[indexa] < array[indexa]
):
SCREAMING_SN... | 73 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Optional[int] = logging.get_logger(__name__)
a_ : int = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# See all Cvt models at https://hugg... | 73 | 1 |
def lowerCamelCase__ (_UpperCAmelCase):
if not isinstance(_UpperCAmelCase , _UpperCAmelCase):
raise ValueError('multiplicative_persistence() only accepts integral values')
if num < 0:
raise ValueError('multiplicative_persistence() does not accept negative values')
SCREAMI... | 73 |
def lowerCamelCase__ (_UpperCAmelCase = 10 , _UpperCAmelCase = 1000 , _UpperCAmelCase = True):
assert (
isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _U... | 73 | 1 |
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 SPIECE_UNDERLINE, logging
a_ : List[Any] = logging.get_logger(__name... | 73 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 73 | 1 |
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
a_ : List[Any] = False
class _snake_case ( unittest.TestCase ):
pass
@slow... | 73 |
from __future__ import annotations
a_ : str = []
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase):
for i in range(len(_UpperCAmelCase)):
if board[row][i] == 1:
return False
for i in range(len(_UpperCAmelCase)):
... | 73 | 1 |
from __future__ import annotations
a_ : str = []
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase):
for i in range(len(_UpperCAmelCase)):
if board[row][i] == 1:
return False
for i in range(len(_UpperCAmelCase)):
... | 73 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepInverseScheduler,
... | 73 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Tuple = logging.get_logger(__name__)
a_ : Optional[int] = {
'facebook/wav2vec2-base-960h': 'https://huggingface.co/facebook/wav2vec2-base-960h/resolve/m... | 73 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : List[str] = logging.get_logger(__name__)
a_ : Any = {
'microsoft/unispeech-large-1500h-cv': (
'https://huggingface.co/microsoft/unispeech-large-... | 73 | 1 |
from random import randint, random
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = False , _UpperCAmelCase = False , _UpperCAmelCase = 5 , ):
SCREAMING_SNAKE_CASE = [[-1] * number_of_cell... | 73 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a_ : Optional[Any] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a_ : List[str] = None
def lowerCamelCase__ ():
SCREAMING_SNAKE_CASE = argpa... | 73 | 1 |
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
a_ : Tuple = logging.get_logger(__name__)
class _snake_case ( A__ ):
def __init__( self , *a , **a) -> None:
warnings.warn(
'The cla... | 73 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a_ : Dict = logging.get_logger(__name__)
class _snake_case ( A__ ):
def __init__( self , *a , **a) -> None:
warnings.warn(
'The clas... | 73 | 1 |
a_ : Optional[int] = 9.80_665
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = g):
if fluid_density <= 0:
raise ValueError('Impossible fluid density')
if volume < 0:
raise ValueError('Impossible Object volume')
if ... | 73 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _snake_case ( unittest.TestCase , A__ ):
def SCREAMING_SNAKE_CASE__ ( self) -> List[str]:
SCREAMING_SNAKE_CASE = load_tool('text-classification')
... | 73 | 1 |
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO
)
a_ : int = logging.getLogger(__name__)
if __name__ == "__main__":
a_ : ... | 73 |
import sys
import turtle
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , ):
my_p... | 73 | 1 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
a_ : str = False
class _snake_case ( unittest.TestCase ):
pass... | 73 |
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 import Accelerator
from accelerat... | 73 | 1 |
from __future__ import annotations
def lowerCamelCase__ (_UpperCAmelCase = 4):
SCREAMING_SNAKE_CASE = abs(_UpperCAmelCase) or 4
return [[1 + x + y * row_size for x in range(_UpperCAmelCase)] for y in range(_UpperCAmelCase)]
def lowerCamelCase__ (_UpperCAmelCase):
re... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
a_ : List[str] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:... | 73 | 1 |
import math
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = [True] * n
SCREAMING_SNAKE_CASE = False
SCREAMING_SNAKE_CASE = False
SCREAMING_SNAKE_CASE = True
for i in range(3 , int(n**0.5 + 1) , 2):
SCREAMING_SNA... | 73 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
fr... | 73 | 1 |
import argparse
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 accelerate import Accelerator, Distribu... | 73 |
from __future__ import annotations
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = 2
SCREAMING_SNAKE_CASE = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(_UpperCAmelCase)
if n > 1:
factors.... | 73 | 1 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTok... | 73 |
import math
import os
import sys
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = ''
try:
with open(_UpperCAmelCase , 'rb') as binary_file:
SCREAMING_SNAKE_CASE = binary_file.read()
for dat in data:
SCREAMING_SNAKE_CASE ... | 73 | 1 |
import numpy as np
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = 1e-12 , _UpperCAmelCase = 100 , ):
assert np.shape(_UpperCAmelCase)[0] == np.shape(_UpperCAmelCase)[1]
# Ensure proper dimensionality.
assert np.shape(_UpperC... | 73 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIF... | 73 | 1 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class _snake_case ( A__ ):
def __init__( self , a , a , a) -> Dict:
SCREAMING_SNAKE_CASE = dataset
SCREAMING_SNAK... | 73 |
import heapq as hq
import math
from collections.abc import Iterator
class _snake_case :
def __init__( self , a) -> Optional[Any]:
SCREAMING_SNAKE_CASE = str(id_)
SCREAMING_SNAKE_CASE = None
SCREAMING_SNAKE_CASE = None
SCREAMING_SNAK... | 73 | 1 |
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('hub/hopper-medium-v2/unet/hor32', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/unet/hor128', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/value_function', exist_ok=True)
def lowerCamelCase__ (_UpperCAmel... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ : Optional[Any] = {
'configuration_mask2former': [
'MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Mask2FormerConfig',
],
}
try:... | 73 | 1 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class _snake_case ( unittest.TestCase ):
def SCREAMING_SNAKE_CASE__ ( self) -> Optional[Any]:
SCREAMING_SNAKE_CASE ... | 73 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Dict = logging.get_logger(__name__)
a_ : Union[str, Any] = {
'edbeeching/decision-transformer-gym-hopper-medium': (
'https://huggingface.co/edbeeching/decision-transformer-gym-ho... | 73 | 1 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowerCamelCase__ (_UpperCAmelCase):
return getitem, k
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
return setitem, k, v
def ... | 73 |
import argparse
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 accelerate import Accelerator, Distribu... | 73 | 1 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a_ : Dict = logging.get_logger(__name__)
class _snake_case ( A__ ):
def __init__( self , *a , **a) -> None:
warnings.warn(
'The clas... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ : int = {
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': ['RagTokenizer'],
}
try:
if not is_to... | 73 | 1 |
from collections import namedtuple
import requests
from lxml import html # type: ignore
a_ : int = namedtuple('covid_data', 'cases deaths recovered')
def lowerCamelCase__ (_UpperCAmelCase = "https://www.worldometers.info/coronavirus/"):
SCREAMING_SNAKE_CASE = '//div[... | 73 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = False):
if radian_mode:
return [magnitude * cos(_UpperCAmelCase), m... | 73 | 1 |
import numpy as np
def lowerCamelCase__ (_UpperCAmelCase):
return 1 / (1 + np.exp(-vector))
def lowerCamelCase__ (_UpperCAmelCase):
return vector * sigmoid(_UpperCAmelCase)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 73 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Optional[int] = logging.get_logger(__name__)
a_ : int = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# See all Cvt models at https://hugg... | 73 | 1 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _snake_case ( A__ ):
_lowercase : Dict = ['''image_processor''', '''tokenizer''']
_lowercase : Optional[Any] = '''AutoImageProcessor'''
_lowercase : List[... | 73 |
def lowerCamelCase__ (_UpperCAmelCase = 10 , _UpperCAmelCase = 1000 , _UpperCAmelCase = True):
assert (
isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _U... | 73 | 1 |
from math import isqrt, loga
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = [True] * max_number
for i in range(2 , isqrt(max_number - 1) + 1):
if is_prime[i]:
for j in range(i**2 , _UpperCAmelCase , _UpperCAmelCase):
... | 73 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 73 | 1 |
def lowerCamelCase__ (_UpperCAmelCase):
if p < 2:
raise ValueError('p should not be less than 2!')
elif p == 2:
return True
SCREAMING_SNAKE_CASE = 4
SCREAMING_SNAKE_CASE = (1 << p) - 1
for _ in range(p - 2):
SCREAMING_SNAKE_CASE = ((s * s) - 2) ... | 73 |
from __future__ import annotations
a_ : str = []
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase):
for i in range(len(_UpperCAmelCase)):
if board[row][i] == 1:
return False
for i in range(len(_UpperCAmelCase)):
... | 73 | 1 |
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 import Accelerator
from accelerat... | 73 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepInverseScheduler,
... | 73 | 1 |
import numpy as np
import datasets
a_ : str = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was introduced by Prof... | 73 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : List[str] = logging.get_logger(__name__)
a_ : Any = {
'microsoft/unispeech-large-1500h-cv': (
'https://huggingface.co/microsoft/unispeech-large-... | 73 | 1 |
from __future__ import annotations
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
if len(_UpperCAmelCase) < k or k < 0:
raise ValueError('Invalid Input')
SCREAMING_SNAKE_CASE = SCREAMING_SNAKE_CASE = sum(array[:k])
for i in range(len(_UpperCAmelCa... | 73 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a_ : Optional[Any] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a_ : List[str] = None
def lowerCamelCase__ ():
SCREAMING_SNAKE_CASE = argpa... | 73 | 1 |
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 lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase):
SCREAMING_SNAKE_... | 73 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a_ : Dict = logging.get_logger(__name__)
class _snake_case ( A__ ):
def __init__( self , *a , **a) -> None:
warnings.warn(
'The clas... | 73 | 1 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
SCREAMING_SNAKE_CASE = list(_UpperCAmelCase)
SCREAMING_SNAKE_CASE = list(_UpperCAmelCase)
SCREAMING_SNAKE_... | 73 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _snake_case ( unittest.TestCase , A__ ):
def SCREAMING_SNAKE_CASE__ ( self) -> List[str]:
SCREAMING_SNAKE_CASE = load_tool('text-classification')
... | 73 | 1 |
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decord import VideoReader
... | 73 |
import sys
import turtle
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , ):
my_p... | 73 | 1 |
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 lowerCamelCase__ ():
SCREAMING_SNAKE_CASE... | 73 |
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 import Accelerator
from accelerat... | 73 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
a_ : Tuple = {'tokenization_herbert': ['HerbertTokenizer']}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDepe... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
a_ : List[str] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:... | 73 | 1 |
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowerCamelCase__ (_UpperCAmelCase = 8):
SCREAMING_SNAKE_CASE = ascii_letters + digits + punctuation
return "".join(secrets.choice(_UpperCAmelCase) for... | 73 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
fr... | 73 | 1 |
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_filename,
infer... | 73 |
from __future__ import annotations
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = 2
SCREAMING_SNAKE_CASE = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(_UpperCAmelCase)
if n > 1:
factors.... | 73 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : List[str] = logging.get_logger(__name__)
a_ : Any = {
'microsoft/unispeech-large-1500h-cv': (
'https://huggingface.co/microsoft/unispeech-large-... | 73 |
import math
import os
import sys
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = ''
try:
with open(_UpperCAmelCase , 'rb') as binary_file:
SCREAMING_SNAKE_CASE = binary_file.read()
for dat in data:
SCREAMING_SNAKE_CASE ... | 73 | 1 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _snake_case ( A__ ):
_lowercase : ... | 73 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIF... | 73 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : int = logging.get_logger(__name__)
a_ : Union[str, Any] = {
'SCUT-DLVCLab/lilt-roberta-en-base': (
'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.j... | 73 |
import heapq as hq
import math
from collections.abc import Iterator
class _snake_case :
def __init__( self , a) -> Optional[Any]:
SCREAMING_SNAKE_CASE = str(id_)
SCREAMING_SNAKE_CASE = None
SCREAMING_SNAKE_CASE = None
SCREAMING_SNAK... | 73 | 1 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a_ : Tuple = logging.get_logger(__name__)... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ : Optional[Any] = {
'configuration_mask2former': [
'MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Mask2FormerConfig',
],
}
try:... | 73 | 1 |
def lowerCamelCase__ (_UpperCAmelCase): # noqa: E741
SCREAMING_SNAKE_CASE = len(_UpperCAmelCase)
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = [0] * n
SCREAMING_SNAKE_CASE = [False] * n
SCREAMING_SNAKE_CASE = [False] * n
def dfs(_UpperCAmelCa... | 73 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Dict = logging.get_logger(__name__)
a_ : Union[str, Any] = {
'edbeeching/decision-transformer-gym-hopper-medium': (
'https://huggingface.co/edbeeching/decision-transformer-gym-ho... | 73 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ : Union[str, Any] = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'AutoformerConfig',... | 73 |
import argparse
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 accelerate import Accelerator, Distribu... | 73 | 1 |
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = len(_UpperCAmelCase) - 1
while left <= right:
# avoid divided by 0 during interpolation
if sorted_collection[left] == sorted_collection[right]:
... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ : int = {
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': ['RagTokenizer'],
}
try:
if not is_to... | 73 | 1 |
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tenso... | 73 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = False):
if radian_mode:
return [magnitude * cos(_UpperCAmelCase), m... | 73 | 1 |
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class _snake_case ( A__ , unitte... | 73 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Optional[int] = logging.get_logger(__name__)
a_ : int = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# See all Cvt models at https://hugg... | 73 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ : Optional[Any] = {
'configuration_mask2former': [
'MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Mask2FormerConfig',
],
}
try:... | 73 |
def lowerCamelCase__ (_UpperCAmelCase = 10 , _UpperCAmelCase = 1000 , _UpperCAmelCase = True):
assert (
isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _U... | 73 | 1 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelC... | 73 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 73 | 1 |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPipeline,
... | 73 |
from __future__ import annotations
a_ : str = []
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase):
for i in range(len(_UpperCAmelCase)):
if board[row][i] == 1:
return False
for i in range(len(_UpperCAmelCase)):
... | 73 | 1 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
imp... | 73 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepInverseScheduler,
... | 73 | 1 |
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class _snake_case ( A__ ):
def __init__( self , a , a , ... | 73 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : List[str] = logging.get_logger(__name__)
a_ : Any = {
'microsoft/unispeech-large-1500h-cv': (
'https://huggingface.co/microsoft/unispeech-large-... | 73 | 1 |
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = None):
if version.parse(hfh.__version__).release < version.parse('0.11.0').releas... | 73 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a_ : Optional[Any] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a_ : List[str] = None
def lowerCamelCase__ ():
SCREAMING_SNAKE_CASE = argpa... | 73 | 1 |
def lowerCamelCase__ (_UpperCAmelCase = 5000_0000):
SCREAMING_SNAKE_CASE = set()
SCREAMING_SNAKE_CASE = int((limit - 24) ** (1 / 2))
SCREAMING_SNAKE_CASE = set(range(3 , prime_square_limit + 1 , 2))
primes.add(2)
for p in range(3 , prime... | 73 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a_ : Dict = logging.get_logger(__name__)
class _snake_case ( A__ ):
def __init__( self , *a , **a) -> None:
warnings.warn(
'The clas... | 73 | 1 |
from math import factorial, pi
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase = 30):
if not isinstance(_UpperCAmelCase , (int, float)):
raise ValueError('maclaurin_sin() requires either an int or float for theta')
if not isinstance(_UpperCAmelCase , ... | 73 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _snake_case ( unittest.TestCase , A__ ):
def SCREAMING_SNAKE_CASE__ ( self) -> List[str]:
SCREAMING_SNAKE_CASE = load_tool('text-classification')
... | 73 | 1 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
a_ : Any = '2.13.1'
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse('3.7'):
raise Imp... | 73 |
import sys
import turtle
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , ):
my_p... | 73 | 1 |
class _snake_case :
def __init__( self) -> Optional[Any]:
SCREAMING_SNAKE_CASE = {}
def SCREAMING_SNAKE_CASE__ ( self) -> None:
print(self.vertex)
for i in self.vertex:
print(a , ' -> ' , ' -> '.join([str(a) for... | 73 |
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 import Accelerator
from accelerat... | 73 | 1 |
# Algorithm for the pigeonhole sorting
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = min(_UpperCAmelCase) # min() finds the minimum value
SCREAMING_SNAKE_CASE = max(_UpperCAmelCase) # max() finds the maximum value
SCREAMING_SNAKE_CASE = max_va... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
a_ : List[str] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:... | 73 | 1 |
from cva import destroyAllWindows, imread, imshow, waitKey
def lowerCamelCase__ (_UpperCAmelCase):
# getting number of pixels in the image
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = img.shape[0], img.shape[1]
# converting each pixel's color to its negative
for i in r... | 73 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
fr... | 73 | 1 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class _snake_case ( datasets.BeamBasedBuilder ):
def SCREAMING_SNAKE_CASE__ ( self) -> ... | 73 |
from __future__ import annotations
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = 2
SCREAMING_SNAKE_CASE = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(_UpperCAmelCase)
if n > 1:
factors.... | 73 | 1 |
from __future__ import annotations
class _snake_case :
def __init__( self , a) -> None:
SCREAMING_SNAKE_CASE = data
SCREAMING_SNAKE_CASE = None
SCREAMING_SNAKE_CASE = None
def lowerCamelCase__ (_UpperCAmelCase): # In Order... | 73 |
import math
import os
import sys
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_CASE = ''
try:
with open(_UpperCAmelCase , 'rb') as binary_file:
SCREAMING_SNAKE_CASE = binary_file.read()
for dat in data:
SCREAMING_SNAKE_CASE ... | 73 | 1 |
def lowerCamelCase__ (_UpperCAmelCase):
return "".join(chr(ord(_UpperCAmelCase) - 32) if 'a' <= char <= 'z' else char for char in word)
if __name__ == "__main__":
from doctest import testmod
testmod()
| 73 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIF... | 73 | 1 |
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
a_ : int = logging.get_logger(__name__)
a_ : List[str] = {
'hustv... | 73 |
import heapq as hq
import math
from collections.abc import Iterator
class _snake_case :
def __init__( self , a) -> Optional[Any]:
SCREAMING_SNAKE_CASE = str(id_)
SCREAMING_SNAKE_CASE = None
SCREAMING_SNAKE_CASE = None
SCREAMING_SNAK... | 73 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
a_ : Optional[Any] = logging.get_logger(__name__)
a_ : Tuple = {
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/resolve/main/config.json',... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ : Optional[Any] = {
'configuration_mask2former': [
'MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Mask2FormerConfig',
],
}
try:... | 73 | 1 |
import argparse
import os
# New Code #
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 accelerate impor... | 73 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Dict = logging.get_logger(__name__)
a_ : Union[str, Any] = {
'edbeeching/decision-transformer-gym-hopper-medium': (
'https://huggingface.co/edbeeching/decision-transformer-gym-ho... | 73 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a_ : Optional[int] = {'processing_layoutxlm': ['LayoutXLMProcessor']}
t... | 73 |
import argparse
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 accelerate import Accelerator, Distribu... | 73 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ : int = {
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': ['RagTokenizer'],
}
try:
if not is_to... | 73 | 1 |
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
return [sentence[i : i + ngram_size] for i in range(len(_UpperCAmelCase) - ngram_size + 1)]
if __name__ == "__main__":
from doctest import testmod
testmod()
| 73 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = False):
if radian_mode:
return [magnitude * cos(_UpperCAmelCase), m... | 73 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Any = logging.get_logger(__name__)
a_ : List[Any] = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class _snake_case ( A__ ):
_lowercase : Optional[Any] ... | 73 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Optional[int] = logging.get_logger(__name__)
a_ : int = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# See all Cvt models at https://hugg... | 73 | 1 |
def lowerCamelCase__ (_UpperCAmelCase = 100):
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = 0
for i in range(1 , n + 1):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
if __name__ == "__main__":
print(f"""{solution(... | 73 |
def lowerCamelCase__ (_UpperCAmelCase = 10 , _UpperCAmelCase = 1000 , _UpperCAmelCase = True):
assert (
isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _UpperCAmelCase)
and isinstance(_UpperCAmelCase , _U... | 73 | 1 |
from typing import Any
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , ):
_validation(
_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmel... | 73 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 73 | 1 |
from math import pi
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 73 |
from __future__ import annotations
a_ : str = []
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase):
for i in range(len(_UpperCAmelCase)):
if board[row][i] == 1:
return False
for i in range(len(_UpperCAmelCase)):
... | 73 | 1 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class _snake_case ( unittest.TestCase ):
def SCREAMING_SNAKE_CASE__ ( self) -> Optional[Any]:
SCREA... | 73 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepInverseScheduler,
... | 73 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : str = logging.get_logger(__name__)
a_ : List[Any] = {
'Salesforce/blip-vqa-base': 'https://huggingface.co/Salesforce/blip-vqa-base/resolve... | 73 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : List[str] = logging.get_logger(__name__)
a_ : Any = {
'microsoft/unispeech-large-1500h-cv': (
'https://huggingface.co/microsoft/unispeech-large-... | 73 | 1 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
a_ : Optional[Any] = 10
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _U... | 73 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a_ : Optional[Any] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a_ : List[str] = None
def lowerCamelCase__ ():
SCREAMING_SNAKE_CASE = argpa... | 73 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Dict = logging.get_logger(__name__)
a_ : Union[str, Any] = {
'edbeeching/decision-transformer-gym-hopper-medium': (
'https://huggingface.co/edbeeching/decision-transformer-gym-ho... | 73 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a_ : Dict = logging.get_logger(__name__)
class _snake_case ( A__ ):
def __init__( self , *a , **a) -> None:
warnings.warn(
'The clas... | 73 | 1 |
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
a_ : Union[str, Any] = logging.get_logger(__name__)
a_ : Union[str, Any] ... | 73 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _snake_case ( unittest.TestCase , A__ ):
def SCREAMING_SNAKE_CASE__ ( self) -> List[str]:
SCREAMING_SNAKE_CASE = load_tool('text-classification')
... | 73 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
a_ : Any = logging.get_logg... | 73 |
import sys
import turtle
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , ):
my_p... | 73 | 1 |
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
a_ : Any = logging.getLogger()
def lowerCamelCase__ (_UpperCAme... | 73 |
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 import Accelerator
from accelerat... | 73 | 1 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import require_elasticsearch, r... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
a_ : List[str] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:... | 73 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False)
... | 73 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
fr... | 73 | 1 |
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