code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
snake_case__ : List[str] = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""tokenization_ctr... | 705 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
... | 618 | 0 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transfor... | 706 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTest... | 618 | 0 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
snake_case__ : Dict = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < versi... | 707 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
snake_case__ : List[str] = logging.get_logger(__name__)
class _a ( UpperCAmelCase__ ):
"""simple docstring"""
def __init__( ... | 618 | 0 |
'''simple docstring'''
from pathlib import Path
import fire
from tqdm import tqdm
def _snake_case (__lowercase="ro" , __lowercase="en" , __lowercase="wmt16" , __lowercase=None):
try:
import datasets
except (ModuleNotFoun... | 708 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:... | 618 | 0 |
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
IMAGEN... | 709 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTo... | 618 | 0 |
import numpy as np
import datasets
snake_case__ : int = '\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 ... | 710 |
from typing import Any
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ):
_validation(
__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ... | 618 | 0 |
'''simple docstring'''
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipelin... | 711 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _a ( unittest.TestCase ):
"""simple docstri... | 618 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import tor... | 712 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ..... | 618 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : Dict = logging.get_logger(__name__)
snake_case__ : List[Any] = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/ma... | 713 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _snake_case (__lowercase , __lowercase , __lowercase = "x" , __lowercase = 10**-10 , __lowercase = 1 , ):
UpperCamelCase_ = symbols(__lower... | 618 | 0 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
snake_case__ : Any = """\\n@misc{chen2021evaluating,\n ti... | 714 |
def _snake_case (__lowercase = 1000):
UpperCamelCase_ , UpperCamelCase_ = 1, 1
UpperCamelCase_ = 2
while True:
UpperCamelCase_ = 0
UpperCamelCase_ = fa + fa
UpperCamelCase_ , UpperCamelCase_ = f... | 618 | 0 |
'''simple docstring'''
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
... | 715 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer... | 618 | 0 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import requ... | 716 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
snake_case__ : List[str] = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCH... | 618 | 0 |
import numpy as np
import qiskit
def _snake_case (__lowercase = 8 , __lowercase = None):
UpperCamelCase_ = np.random.default_rng(seed=snake_case__)
# Roughly 25% of the qubits will contribute to the key.
# So we take more than we need.
UpperCamelC... | 717 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import requ... | 618 | 0 |
def _snake_case (__lowercase , __lowercase = False):
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n % 10 not in (1, 3, 7, 9): # can quickly check last digit
return False
if n > 3317044064679887385961981 and not all... | 718 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : Optional[int] = logging.get_logger(__name__)
snake_case__ : List[Any] = {
"""microsoft/git-base""": """https:/... | 618 | 0 |
from __future__ import annotations
from math import pi
def _snake_case (__lowercase , __lowercase , __lowercase):
if (inductance, frequency, reactance).count(0) != 1:
raise ValueError('One and only one argument must be 0')
if inductance < 0:
... | 719 |
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, require_vision
f... | 618 | 0 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_uti... | 720 |
def _snake_case (__lowercase , __lowercase , __lowercase):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(__lowercase))
def _snake_case (__lowercase , __lowercase , __lowercase ... | 618 | 0 |
import unittest
from transformers import XLMConfig, 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 ModelTesterMixin, ... | 721 |
import os
from math import logaa
def _snake_case (__lowercase = "base_exp.txt"):
UpperCamelCase_ = 0
UpperCamelCase_ = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(__lowercase) , __lowercase))):
UpperCamelCase_ , ... | 618 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ : Union[str, Any] = {
"""configuration_whisper""": ["""WHISP... | 700 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_conf... | 618 | 0 |
from __future__ import annotations
def _snake_case (__lowercase):
if len(_lowerCAmelCase) < 2:
raise ValueError('Monogons and Digons are not polygons in the Euclidean space')
if any(i <= 0 for i in nums):
raise ValueError('All values must be greater than 0')
U... | 701 |
def _snake_case (__lowercase , __lowercase):
_enforce_args(__lowercase , __lowercase)
if n == 0:
return 0
UpperCamelCase_ = float('-inf')
for i in range(1 , n + 1):
UpperCamelCase_ = max(
__lowercase , ... | 618 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : List[str] = logging.get_logger(__name__)
snake_case__ : Tuple = {
'Salesforce/blip-vqa-base': 'https://hugging... | 702 |
snake_case__ : List[Any] = """Tobias Carryer"""
from time import time
class _a :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase=int(time() ) ) -> Tuple: # noqa... | 618 | 0 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_availabl... | 703 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
snake_case__ : Optional[int] = pytest.mark.integration
@p... | 618 | 0 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , __lowercase):
if (ksize % 2) == 0:
... | 704 |
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class _a ... | 618 | 0 |
import os
import re
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
snake_case__ : Union[str, Any] = logging.get_logger... | 705 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
... | 618 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
snake_case__ : Union[str, Any] = {'processing_layoutx... | 706 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTest... | 618 | 0 |
def _snake_case (__lowercase):
if not all(char in '01' for char in bin_string):
raise ValueError('Non-binary value was passed to the function')
if not bin_string:
raise ValueError('Empty string was passed to the function')
UpperCamelCase_ = ''
while len(_... | 707 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
snake_case__ : List[str] = logging.get_logger(__name__)
class _a ( UpperCAmelCase__ ):
"""simple docstring"""
def __init__( ... | 618 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokeni... | 708 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:... | 618 | 0 |
import argparse
import os
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_task_guides.py
snake_case__ : List[Any] = """src/transformers"""
s... | 709 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTo... | 618 | 0 |
import math
from numpy import inf
from scipy.integrate import quad
def _snake_case (__lowercase ):
if num <= 0:
raise ValueError('math domain error' )
return quad(__lowercase , 0 , __lowercase , args=(__lowercase) )[0]
... | 710 |
from typing import Any
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ):
_validation(
__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ... | 618 | 0 |
'''simple docstring'''
import math
from collections.abc import Iterator
from itertools import takewhile
def _snake_case (__lowercase):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 711 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _a ( unittest.TestCase ):
"""simple docstri... | 618 | 0 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : Optional[int] = logging.get_logger(__name__)
snake_case__ : Dict = {
"facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960h/resol... | 712 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ..... | 618 | 0 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
snake_case__ : Any = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
snake_case__ : Tuple = ... | 713 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _snake_case (__lowercase , __lowercase , __lowercase = "x" , __lowercase = 10**-10 , __lowercase = 1 , ):
UpperCamelCase_ = symbols(__lower... | 618 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
snake_case__ : str = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MA... | 714 |
def _snake_case (__lowercase = 1000):
UpperCamelCase_ , UpperCamelCase_ = 1, 1
UpperCamelCase_ = 2
while True:
UpperCamelCase_ = 0
UpperCamelCase_ = fa + fa
UpperCamelCase_ , UpperCamelCase_ = f... | 618 | 0 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.te... | 715 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer... | 618 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case__ : Any = {
"""configuration_poolformer""": [
"""POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""PoolFormerC... | 716 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
snake_case__ : List[str] = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCH... | 618 | 0 |
from __future__ import annotations
def _snake_case (__lowercase , __lowercase):
print(f"""Vertex\tShortest Distance from vertex {src}""")
for i, d in enumerate(__lowercase):
print(f"""{i}\t\t{d}""")
def _snake_case (__lowercase , __low... | 717 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import requ... | 618 | 0 |
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
snake_case__ : int = logging.get_logger(__... | 718 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : Optional[int] = logging.get_logger(__name__)
snake_case__ : List[Any] = {
"""microsoft/git-base""": """https:/... | 618 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : int = logging.get_logger(__name__)
snake_case__ : str = {
'alibaba-damo/mgp-str-base': 'https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json'... | 719 |
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, require_vision
f... | 618 | 0 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class _a ( unittest.TestCase ):
"""simple docstring"""
def _UpperCAmelCase ( self ) -> List[str]:
... | 720 |
def _snake_case (__lowercase , __lowercase , __lowercase):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(__lowercase))
def _snake_case (__lowercase , __lowercase , __lowercase ... | 618 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
snake_case__ : List[str] = {"""tokenization_wav2vec2_phoneme""": ["""Wav2Vec2PhonemeCTCTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
snake_case__ ... | 721 |
import os
from math import logaa
def _snake_case (__lowercase = "base_exp.txt"):
UpperCamelCase_ = 0
UpperCamelCase_ = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(__lowercase) , __lowercase))):
UpperCamelCase_ , ... | 618 | 0 |
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
snake_case__ : Union[str, Any] = version.... | 700 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_conf... | 618 | 0 |
from __future__ import annotations
def _snake_case (__lowercase , __lowercase):
UpperCamelCase_ = []
UpperCamelCase_ = []
UpperCamelCase_ = 0
UpperCamelCase_ = sum(__lowercase)
create_state_space_tree(__lowerca... | 701 |
def _snake_case (__lowercase , __lowercase):
_enforce_args(__lowercase , __lowercase)
if n == 0:
return 0
UpperCamelCase_ = float('-inf')
for i in range(1 , n + 1):
UpperCamelCase_ = max(
__lowercase , ... | 618 | 0 |
def _snake_case (__lowercase):
# bit count represents no. of bits in the gray code
if bit_count < 0:
raise ValueError('The given input must be positive')
# get the generated string sequence
UpperCamelCase_ = gray_code_sequence_string(__lowercase)
#
# co... | 702 |
snake_case__ : List[Any] = """Tobias Carryer"""
from time import time
class _a :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase=int(time() ) ) -> Tuple: # noqa... | 618 | 0 |
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 _snake_case ():
UpperCame... | 703 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
snake_case__ : Optional[int] = pytest.mark.integration
@p... | 618 | 0 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --host <... | 704 |
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class _a ... | 618 | 0 |
def _snake_case (__lowercase , __lowercase):
UpperCamelCase_ = len(__lowercase)
UpperCamelCase_ = []
for i in range(len(__lowercase) - pat_len + 1):
UpperCamelCase_ = True
for j in range(__lowercase):
if s[i + j] != pat... | 705 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
... | 618 | 0 |
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
snake_case__ : List[Any] = logging.get_logger(__name__)
snake_case__ : Optional... | 706 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTest... | 618 | 0 |
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
snake_case__ : Any = datasets.utils.logging.get_logger(__name__)
@dataclass
class ... | 707 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
snake_case__ : List[str] = logging.get_logger(__name__)
class _a ( UpperCAmelCase__ ):
"""simple docstring"""
def __init__( ... | 618 | 0 |
'''simple docstring'''
def _snake_case (__lowercase , __lowercase):
return base * power(__lowercase , (exponent - 1)) if exponent else 1
if __name__ == "__main__":
print("""Raise base to the power of exponent using recursion...""")
snake_case__ : int ... | 708 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:... | 618 | 0 |
snake_case__ : Dict = 8.31_4462 # Unit - J mol-1 K-1
def _snake_case (__lowercase , __lowercase , __lowercase):
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('Invalid inputs. Enter positive value.')
return moles * kelvin * U... | 709 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTo... | 618 | 0 |
from ..utils import DummyObject, requires_backends
class _a ( metaclass=UpperCAmelCase__ ):
"""simple docstring"""
A_ = ["""speech"""]
def __init__( self , *_UpperCAmelCase , **_UpperCAmelCase ) -> int:
requires_backends(se... | 710 |
from typing import Any
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ):
_validation(
__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ... | 618 | 0 |
'''simple docstring'''
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS... | 711 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _a ( unittest.TestCase ):
"""simple docstri... | 618 | 0 |
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
require_... | 712 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ..... | 618 | 0 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _a ( unittest.TestCase ):
"""simple docstri... | 713 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _snake_case (__lowercase , __lowercase , __lowercase = "x" , __lowercase = 10**-10 , __lowercase = 1 , ):
UpperCamelCase_ = symbols(__lower... | 618 | 0 |
from __future__ import annotations
import typing
from collections import Counter
def _snake_case (__lowercase):
UpperCamelCase_ = Counter()
for base in range(1 , max_perimeter + 1):
for perpendicular in range(__lowercase , max_perimeter + ... | 714 |
def _snake_case (__lowercase = 1000):
UpperCamelCase_ , UpperCamelCase_ = 1, 1
UpperCamelCase_ = 2
while True:
UpperCamelCase_ = 0
UpperCamelCase_ = fa + fa
UpperCamelCase_ , UpperCamelCase_ = f... | 618 | 0 |
'''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
snake_case__ : Optional[int] = pytes... | 715 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer... | 618 | 0 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ..... | 716 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
snake_case__ : List[str] = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCH... | 618 | 0 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
sna... | 717 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import requ... | 618 | 0 |
import os
from datetime import datetime as dt
from github import Github
snake_case__ : Optional[Any] = [
"""good first issue""",
"""feature request""",
"""wip""",
]
def _snake_case ():
UpperCamelCase_ = Github(os.environ['GITHUB... | 718 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : Optional[int] = logging.get_logger(__name__)
snake_case__ : List[Any] = {
"""microsoft/git-base""": """https:/... | 618 | 0 |
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)
snake_case__ : List[Any] = logging.getLogger()
... | 719 |
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, require_vision
f... | 618 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : int = logging.get_logger(__name__)
snake_case__ : Union[str, Any] = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/co... | 720 |
def _snake_case (__lowercase , __lowercase , __lowercase):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(__lowercase))
def _snake_case (__lowercase , __lowercase , __lowercase ... | 618 | 0 |
def _snake_case (__lowercase , __lowercase):
UpperCamelCase_ = word.split()
def justify(__lowercase , __lowercase , __lowercase) -> str:
UpperCamelCase_ = max_width - width
UpperCamelCase_ = len(__lowercase)
if len(__lowe... | 721 |
import os
from math import logaa
def _snake_case (__lowercase = "base_exp.txt"):
UpperCamelCase_ = 0
UpperCamelCase_ = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(__lowercase) , __lowercase))):
UpperCamelCase_ , ... | 618 | 0 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _snake_case (__lowercase , __lowercase , __lowercase = "x" , __lowercase = 10**-10 , __lowercase = 1 , ):
UpperCamelCase_ = symbols(__lowercase)
Up... | 700 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_conf... | 618 | 0 |
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, rand... | 701 |
def _snake_case (__lowercase , __lowercase):
_enforce_args(__lowercase , __lowercase)
if n == 0:
return 0
UpperCamelCase_ = float('-inf')
for i in range(1 , n + 1):
UpperCamelCase_ = max(
__lowercase , ... | 618 | 0 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
snake_case__ : Optional[int] = get_logger(__name__)
class _a ( enum.Enum ):
"""simple docstring"""
... | 702 |
snake_case__ : List[Any] = """Tobias Carryer"""
from time import time
class _a :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase=int(time() ) ) -> Tuple: # noqa... | 618 | 0 |
snake_case__ : dict[tuple[int, int, int], int] = {}
def _snake_case (__lowercase , __lowercase , __lowercase):
# if we are absent twice, or late 3 consecutive days,
# no further prize strings are possible
if late == 3 or absent == 2:
return 0
... | 703 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
snake_case__ : Optional[int] = pytest.mark.integration
@p... | 618 | 0 |
import os
import unittest
from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tok... | 704 |
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class _a ... | 618 | 0 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
c... | 705 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
... | 618 | 0 |
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType,... | 706 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTest... | 618 | 0 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
snake_case__ : List[str] = logging.get_logger(__name__)
class _a ( UpperCAmelCase__ ):
"""simple docstring"""
def __init__( ... | 707 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
snake_case__ : List[str] = logging.get_logger(__name__)
class _a ( UpperCAmelCase__ ):
"""simple docstring"""
def __init__( ... | 618 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case__ : List[Any] = logging.g... | 708 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:... | 618 | 0 |
from __future__ import annotations
import unittest
from transformers import 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
... | 709 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTo... | 618 | 0 |
def _snake_case (__lowercase , __lowercase ):
UpperCamelCase_ = ''
for i in table:
res += inp[i - 1]
return res
def _snake_case (__lowercase ):
return data[1:] + data[0]
def _snake_case (__lowercase , _... | 710 |
from typing import Any
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ):
_validation(
__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ... | 618 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def _snake_case (__lowercase):
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 numbe... | 711 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _a ( unittest.TestCase ):
"""simple docstri... | 618 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer, TFAutoModelForSeqaSeqLM
@re... | 712 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ..... | 618 | 0 |
snake_case__ : List[Any] = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],
"""G""": ["""C"""],
}
... | 713 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _snake_case (__lowercase , __lowercase , __lowercase = "x" , __lowercase = 10**-10 , __lowercase = 1 , ):
UpperCamelCase_ = symbols(__lower... | 618 | 0 |
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class _a ... | 714 |
def _snake_case (__lowercase = 1000):
UpperCamelCase_ , UpperCamelCase_ = 1, 1
UpperCamelCase_ = 2
while True:
UpperCamelCase_ = 0
UpperCamelCase_ = fa + fa
UpperCamelCase_ , UpperCamelCase_ = f... | 618 | 0 |
'''simple docstring'''
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def _snake_case (__lowercase = True , *__lowercase , **__lowercase):
if not is_tqdm_availa... | 715 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer... | 618 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer... | 716 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
snake_case__ : List[str] = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCH... | 618 | 0 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def _snake_case (__lowercase , __lowercase):
UpperCamelCase_ = k_size // 2
UpperCamelCase_ ... | 717 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import requ... | 618 | 0 |
import numpy
# List of input, output pairs
snake_case__ : List[str] = (
((5, 2, 3), 1_5),
((6, 5, 9), 2_5),
((1_1, 1_2, 1_3), 4_1),
((1, 1, 1), 8),
((1_1, 1_2, 1_3), 4_1),
)
snake_case__ : Optional[Any] = (((5_1_5, 2_2, 1_3), 5_5_5), ((6_1, ... | 718 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : Optional[int] = logging.get_logger(__name__)
snake_case__ : List[Any] = {
"""microsoft/git-base""": """https:/... | 618 | 0 |
def _snake_case (__lowercase):
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(__lowercase))
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__("""doctest""").testmod()
| 719 |
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, require_vision
f... | 618 | 0 |
def _snake_case ( __lowercase):
if p < 2:
raise ValueError('p should not be less than 2!')
elif p == 2:
return True
UpperCamelCase_ = 4
UpperCamelCase_ = (1 << p) - 1
for _ in range(p - 2):
UpperCamelCase_ = ((s * s) -... | 720 |
def _snake_case (__lowercase , __lowercase , __lowercase):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(__lowercase))
def _snake_case (__lowercase , __lowercase , __lowercase ... | 618 | 0 |
import qiskit
def _snake_case (__lowercase , __lowercase):
UpperCamelCase_ = qiskit.Aer.get_backend('aer_simulator')
# Create a Quantum Circuit acting on the q register
UpperCamelCase_ = qiskit.QuantumCircuit(__lowercase , __lowercase)
# Map the ... | 721 |
import os
from math import logaa
def _snake_case (__lowercase = "base_exp.txt"):
UpperCamelCase_ = 0
UpperCamelCase_ = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(__lowercase) , __lowercase))):
UpperCamelCase_ , ... | 618 | 0 |
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCallback,
Trai... | 700 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_conf... | 618 | 0 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTes... | 701 |
def _snake_case (__lowercase , __lowercase):
_enforce_args(__lowercase , __lowercase)
if n == 0:
return 0
UpperCamelCase_ = float('-inf')
for i in range(1 , n + 1):
UpperCamelCase_ = max(
__lowercase , ... | 618 | 0 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
... | 702 |
snake_case__ : List[Any] = """Tobias Carryer"""
from time import time
class _a :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase=int(time() ) ) -> Tuple: # noqa... | 618 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case__ : List[Any] = logging.get_logger(__name__)
snake_case_... | 703 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
snake_case__ : Optional[int] = pytest.mark.integration
@p... | 618 | 0 |
def _snake_case (__lowercase = 50):
UpperCamelCase_ = [1] * (length + 1)
for row_length in range(length + 1):
for tile_length in range(2 , 5):
for tile_start in range(row_length - tile_length + 1):
ways_number[row_length] += ways_number[
... | 704 |
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class _a ... | 618 | 0 |
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
)
snake_case__ :... | 705 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
... | 618 | 0 |
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 _snake_case ... | 706 |
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTest... | 618 | 0 |
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
snake_case__ : Tuple = [
# (stable-diffusion, HF Diffusers)
("""time_embed.0.weight""", """ti... | 707 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
snake_case__ : List[str] = logging.get_logger(__name__)
class _a ( UpperCAmelCase__ ):
"""simple docstring"""
def __init__( ... | 618 | 0 |
'''simple docstring'''
def _snake_case (__lowercase):
if any(not isinstance(__lowercase , __lowercase) or x < 0 for x in sequence):
raise TypeError('Sequence must be list of non-negative integers')
for _ in range(len(__lowercase)):
for i, (rod_upper, rod_low... | 708 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:... | 618 | 0 |
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_tf_... | 709 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTo... | 618 | 0 |
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_proper... | 710 |
from typing import Any
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ):
_validation(
__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ... | 618 | 0 |
'''simple docstring'''
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import ... | 711 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _a ( unittest.TestCase ):
"""simple docstri... | 618 | 0 |
import argparse
import json
from tqdm import tqdm
def _snake_case ():
UpperCamelCase_ = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'--src_path' , type=__lowercase , default='biencoder-nq-dev.json' , help='Path to raw DPR... | 712 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ..... | 618 | 0 |
def _snake_case (__lowercase , __lowercase , __lowercase):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(__lowercase))
def _snake_case (__lowercase , __lowercase , __lowercase ... | 713 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _snake_case (__lowercase , __lowercase , __lowercase = "x" , __lowercase = 10**-10 , __lowercase = 1 , ):
UpperCamelCase_ = symbols(__lower... | 618 | 0 |
def _snake_case (__lowercase , __lowercase):
UpperCamelCase_ = len(__lowercase)
UpperCamelCase_ = len(__lowercase)
UpperCamelCase_ = [[False for _ in range(m + 1)] for _ in range(n + 1)]
UpperCamelCase_ = True
for i in rang... | 714 |
def _snake_case (__lowercase = 1000):
UpperCamelCase_ , UpperCamelCase_ = 1, 1
UpperCamelCase_ = 2
while True:
UpperCamelCase_ = 0
UpperCamelCase_ = fa + fa
UpperCamelCase_ , UpperCamelCase_ = f... | 618 | 0 |
'''simple docstring'''
def _snake_case (__lowercase , __lowercase , __lowercase):
def count_of_possible_combinations(__lowercase) -> int:
if target < 0:
return 0
if target == 0:
return 1
return sum(count_of_possible_combinati... | 715 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer... | 618 | 0 |
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 716 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
snake_case__ : List[str] = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCH... | 618 | 0 |
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