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code string | code_codestyle int64 | style_context string | style_context_codestyle int64 | label int64 |
|---|---|---|---|---|
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spectrogram_diffusion imp... | 0 |
import sys
SCREAMING_SNAKE_CASE__ : Optional[Any] = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
... | 0 | 1 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask... | 0 |
SCREAMING_SNAKE_CASE__ : Tuple = {
"""a""": """AAAAA""",
"""b""": """AAAAB""",
"""c""": """AAABA""",
"""d""": """AAABB""",
"""e""": """AABAA""",
"""f""": """AABAB""",
"""g""": """AABBA""",
"""h""": """AABBB""",
"""i""": """ABAAA""",
"""j""": """BBBAA""",
"""... | 0 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase_ ( lowerCamelCase ):
a__ = ['''image_processor''', '''tokenizer''']
a__ = '''CLIPImageProcessor'''
a__ = ('''XLM... | 0 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def __lowercase ( snake_case ):
"""simple docstring"""
__magic_name__ :Optional[Any] = [
'''encoder.version''',
'''decoder.version''',
... | 0 | 1 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class lowerCamelCase_ :
a__ = None
a__ = False
a__ = False
a__ = False
a__ = None
a__ ... | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE__ : Dict = {
"""configuration_canine""": ["""CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CanineConfig"""],
"""tokenization_cani... | 0 | 1 |
import os
# Precomputes a list of the 100 first triangular numbers
SCREAMING_SNAKE_CASE__ : List[str] = [int(0.5 * n * (n + 1)) for n in range(1, 1_01)]
def __lowercase ( ):
"""simple docstring"""
__magic_name__ :List[Any] = os.path.dirname(os.path.realpath(snake_... | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase_ ( lowerCamelCase ):
a__ = ['''image_processor''', '''tokenizer''']
a__ = '''ChineseCLIPImageProcessor'''
a__ = ... | 0 | 1 |
import itertools
import math
def __lowercase ( snake_case ):
"""simple docstring"""
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 ... | 0 |
from sklearn.metrics import matthews_corrcoef
import datasets
SCREAMING_SNAKE_CASE__ : Optional[Any] = """
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It ta... | 0 | 1 |
import re
from filelock import FileLock
try:
import nltk
SCREAMING_SNAKE_CASE__ : Tuple = True
except (ImportError, ModuleNotFoundError):
SCREAMING_SNAKE_CASE__ : Union[str, Any] = False
if NLTK_AVAILABLE:
with FileLock(""".lock""") as lock:
nltk.download(... | 0 |
from __future__ import annotations
def __lowercase ( snake_case, snake_case ):
"""simple docstring"""
print(f'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(snake_case ):
print(f'''{i}\t\t{d}''' )
def __lowercase ( snake_cas... | 0 | 1 |
import numpy as np
def __lowercase ( snake_case ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def __lowercase ( snake_case ):
"""simple docstring"""
return vector * sigmoid(snake_case )
if __name__ == "__main__":
import ... | 0 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask... | 0 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : List[Any] = {
"""studio-ousia/luke-base""": """https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json... | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
SCREAMING_SNAKE_CASE__ : Optional[int] = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyN... | 0 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ : Any = {"""configuration_mmbt""": ["""MMBTConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Option... | 0 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisionConfig,
)
def __l... | 0 | 1 |
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTest... | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class lowerCamelCase_ ( lowerCamelCase ):
def __init__( self , __lowerCAmelCase , __lowerCAmelCase ):
"""simple docstring"""
__magic_name__ :Optional[... | 0 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ : str = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : Tup... | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ : str = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : Tup... | 0 | 1 |
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
SCREAMING_SNAKE_CASE__ : Any = logging.get_logger(__name__)
class lowerCamelCase_ ( lowerCamelCase ):
def __init__( self , *__lowerCAmelCase , **__lower... | 0 |
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils ... | 0 | 1 |
End of preview.
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