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 |
|---|---|---|---|---|
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_file... | 618 |
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 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
snake_case__ : Optional[int] = {
"""configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5Onnx... | 618 |
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 | 1 |
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... | 618 |
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 | 1 |
from __future__ import annotations
class _a :
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase ) -> Any:
UpperCamelCase_ , UpperCamelCase_ = text, pattern
UpperCamelCase_ , UpperCamelCas... | 618 |
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 | 1 |
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.ber... | 618 |
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 | 1 |
from __future__ import annotations
import time
snake_case__ : Union[str, Any] = list[tuple[int, int]]
snake_case__ : Any = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, ... | 618 |
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 | 1 |
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 |
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 | 1 |
import argparse
import json
import subprocess
def _snake_case (__lowercase , __lowercase):
UpperCamelCase_ = []
UpperCamelCase_ = (
f"""curl -H \"Accept: application/vnd.github+json\" -H \"Authorization: Bearer {token}\""""
' ... | 618 |
from typing import Any
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ):
_validation(
__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ... | 618 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
... | 618 |
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 | 1 |
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:
... | 618 |
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 | 1 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class _a ( UpperCAmelCase__ ):
"""simple docstring"""
def _UpperCAmelCase ( self , _UpperCAmelCase ) ... | 618 |
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 | 1 |
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes
from... | 618 |
def _snake_case (__lowercase = 1000):
UpperCamelCase_ , UpperCamelCase_ = 1, 1
UpperCamelCase_ = 2
while True:
UpperCamelCase_ = 0
UpperCamelCase_ = fa + fa
UpperCamelCase_ , UpperCamelCase_ = f... | 618 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case__ : List[Any] = {
"""configuration_mobilenet_v2""": [
"""MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""M... | 618 |
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 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case__ : Union[str, Any] = {"""configuration_deit""": ["""DEIT_PRETRAINED_CONFIG_ARCHIVE... | 618 |
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 | 1 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_av... | 618 |
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 | 1 |
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
... | 618 |
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 | 1 |
from __future__ import annotations
def _snake_case (__lowercase):
if len(__lowercase) < 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')
Upper... | 618 |
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 | 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)
snake_case__ : List[Any] = logging.getLogger()
... | 618 |
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 | 1 |
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
snake_case__ : Tuple = logging.get_logger(__name__)
def _snake_case (__lowercase):
UpperCamelCase_ ... | 618 |
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 | 1 |
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class _a ( UpperCAmelCase__ ... | 618 |
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 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
snake_case__ : List[Any] = {
"""configuration_xlm""": ["""XLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMConfig""", """XLMOnnxConfig"""],
"... | 618 |
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 | 1 |
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
fr... | 618 |
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 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from d... | 618 |
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 | 1 |
import numpy as np
def _snake_case (__lowercase):
return 1 / (1 + np.exp(-vector))
def _snake_case (__lowercase):
return vector * sigmoid(1.702 * vector)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 618 |
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 | 1 |
def _snake_case (__lowercase , __lowercase):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__lowercase , int(b / 2)) * actual_power(__lowercase , int(b / 2))
else:
return a * actual_power(__lowercase , int(b / 2)) * actual_... | 618 |
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 | 1 |
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
... | 618 |
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 | 1 |
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 |
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 | 1 |
from __future__ import annotations
def _snake_case (__lowercase , __lowercase):
if len(__lowercase) == 0:
return False
UpperCamelCase_ = len(__lowercase) // 2
if a_list[midpoint] == item:
return True
if item < a_list[midpoint]:
r... | 618 |
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 | 1 |
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... | 618 |
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 | 1 |
def _snake_case (__lowercase , __lowercase):
return x if y == 0 else greatest_common_divisor(__lowercase , x % y)
def _snake_case (__lowercase , __lowercase):
return (x * y) // greatest_common_divisor(__lowercase , __lowercase)
... | 618 |
from typing import Any
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ):
_validation(
__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ... | 618 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPas... | 618 |
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 | 1 |
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 |
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 | 1 |
def _snake_case (__lowercase):
UpperCamelCase_ = len(__lowercase)
for i in range(1 , __lowercase):
UpperCamelCase_ = collection[i]
UpperCamelCase_ = 0
UpperCamelCase_ = i - 1
while low <= high:
U... | 618 |
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 | 1 |
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_INDEX_NAME, shard_checkpoint
... | 618 |
def _snake_case (__lowercase = 1000):
UpperCamelCase_ , UpperCamelCase_ = 1, 1
UpperCamelCase_ = 2
while True:
UpperCamelCase_ = 0
UpperCamelCase_ = fa + fa
UpperCamelCase_ , UpperCamelCase_ = f... | 618 | 1 |
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 |
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 | 1 |
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 = int(input("""Enter the ... | 618 |
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 | 1 |
def _snake_case (__lowercase , __lowercase):
return int((input_a, input_a).count(0) != 0)
def _snake_case ():
assert nand_gate(0 , 0) == 1
assert nand_gate(0 , 1) == 1
assert nand_gate(1 , 0) == 1
assert nand_gate(1 , 1... | 618 |
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 | 1 |
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__ : Optional[Any] = logging.get_logger(_... | 618 |
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 | 1 |
from __future__ import annotations
def _snake_case (__lowercase , __lowercase):
UpperCamelCase_ = []
UpperCamelCase_ = []
UpperCamelCase_ = 0
UpperCamelCase_ = sum(__lowercase)
create_state_space_tree(__lowerca... | 618 |
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 | 1 |
import inspect
import unittest
from transformers import MobileNetVaConfig
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 Confi... | 618 |
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 | 1 |
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch... | 618 |
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 | 1 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class _a ( UpperCAmelCase__ ):
"""simple docstring"""
A_ = """EncodecFeatureExtractor"""
A_ = ("""T5Tok... | 618 |
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 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case__ : Optional[Any] = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""Luk... | 618 |
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 | 1 |
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
... | 618 |
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 | 1 |
from string import ascii_lowercase, ascii_uppercase
def _snake_case (__lowercase):
if not sentence:
return ""
UpperCamelCase_ = dict(zip(__lowercase , __lowercase))
return lower_to_upper.get(sentence[0] , sentence[0]) + sentence[1:]
i... | 618 |
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 | 1 |
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.spectro... | 618 |
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 | 1 |
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 |
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 | 1 |
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_ ... | 618 |
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 | 1 |
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 |
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 | 1 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class _a ( unittest.TestCase ):
"""simple docstring"""
A_ = JukeboxTokenizer
A_ = {
"""artist""": """Zac Brown Band"""... | 618 |
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 | 1 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conver... | 618 |
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 | 1 |
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"""],
}
... | 618 |
from typing import Any
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ):
_validation(
__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ... | 618 | 1 |
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, ... | 618 |
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 | 1 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
snake_case__ : Tuple = logging.get_logger(__name__)
... | 618 |
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 | 1 |
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import r... | 618 |
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 | 1 |
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 numbers, all multiples of 3 are not pri... | 618 |
def _snake_case (__lowercase = 1000):
UpperCamelCase_ , UpperCamelCase_ = 1, 1
UpperCamelCase_ = 2
while True:
UpperCamelCase_ = 0
UpperCamelCase_ = fa + fa
UpperCamelCase_ , UpperCamelCase_ = f... | 618 | 1 |
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,
TrainerCallbac... | 618 |
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 | 1 |
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_x... | 618 |
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 | 1 |
import comet # From: unbabel-comet
import torch
import datasets
snake_case__ : str = datasets.logging.get_logger(__name__)
snake_case__ : Any = """\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and ... | 618 |
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 | 1 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
@re... | 618 |
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 | 1 |
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
@require_sentencep... | 618 |
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 | 1 |
def _snake_case (__lowercase , __lowercase):
if mass < 0:
raise ValueError('The mass of a body cannot be negative')
return 0.5 * mass * abs(__lowercase) * abs(__lowercase)
if __name__ == "__main__":
import doctest
doctest.testmod(verbose=True)
| 618 |
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 | 1 |
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] = ... | 618 |
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 | 1 |
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_available(... | 618 |
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 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
snake_case__ : Tuple = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvaila... | 618 |
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 | 1 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
snake_case__ : Optional[Any] = logging.get_logger(__name__)
def _snake_case (__lowercase... | 618 |
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 | 1 |
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
snake_case__ : Optional[int] = """."""... | 618 |
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 | 1 |
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 |
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 | 1 |
from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import AttentionProcessor, AttnProce... | 618 |
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 | 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
snake_case__ : Optional[int] = logging.get_logger(__name__)
snake_c... | 618 |
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 | 1 |
from __future__ import annotations
def _snake_case (__lowercase , __lowercase):
if b == 0:
return (1, 0)
((UpperCamelCase_) , (UpperCamelCase_)) = extended_euclid(__lowercase , a % b)
UpperCamelCase_ = a // b
return (... | 618 |
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 | 1 |
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_lower) in enumerate(zip(__lowercase ... | 618 |
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 | 1 |
from ..utils import DummyObject, requires_backends
class _a ( metaclass=UpperCAmelCase__ ):
"""simple docstring"""
A_ = ["""flax""", """transformers"""]
def __init__( self , *_UpperCAmelCase , **_UpperCAmelCase ) -> List[Any]:
... | 618 |
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 | 1 |
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... | 618 |
from typing import Any
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ):
_validation(
__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ... | 618 | 1 |
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... | 618 |
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 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
snake_case__ : List[str] = logging.get_logger(__name__)
snake_case__ : Any = {
... | 618 |
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 | 1 |
def _snake_case (__lowercase):
UpperCamelCase_ = len(__lowercase)
for i in range(length - 1):
UpperCamelCase_ = i
for k in range(i + 1 , __lowercase):
if collection[k] < collection[least]:
UpperCamelCase_ = k
... | 618 |
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 | 1 |
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 |
def _snake_case (__lowercase = 1000):
UpperCamelCase_ , UpperCamelCase_ = 1, 1
UpperCamelCase_ = 2
while True:
UpperCamelCase_ = 0
UpperCamelCase_ = fa + fa
UpperCamelCase_ , UpperCamelCase_ = f... | 618 | 1 |
from __future__ import annotations
def _snake_case (__lowercase , __lowercase = None , __lowercase = None , __lowercase = False , ):
UpperCamelCase_ = cipher_alphabet or [chr(__lowercase) for i in range(97 , 123)]
# If the a... | 618 |
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 | 1 |
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 |
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 | 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
snake_ca... | 618 |
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 | 1 |
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 |
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 | 1 |
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
cla... | 618 |
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 | 1 |
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 |
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 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ : Tuple = {
"""configuration_deberta""": ["""DEBERTA_PRETRAINED_CONFIG_A... | 618 |
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 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ : str = {"""configuration_opt""": ["""OPT_PRETRAINED_... | 618 |
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 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case__ : str = logging.get_logger(__name__)
snake_case__ : List[Any] = {
... | 618 |
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 | 1 |
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
class ... | 618 |
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 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ : Tuple = {
"""configuration_mobilebert""": [
"""MOBILEBERT_PRE... | 618 |
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 | 1 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_available(... | 618 |
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 | 1 |
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 |
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 | 1 |
snake_case__ : str = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
snake_case__... | 618 |
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 | 1 |
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 |
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 | 1 |
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase):
UpperCamelCase_ = {
'en': 'Machine learning is great, isn\'t it?',
'ru': 'Маши... | 618 |
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 | 1 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
snake_case__ : Tuple = logging.get_logger(__name__)
def _snake_case (__lowercase ... | 618 |
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 | 1 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL... | 618 |
from typing import Any
def _snake_case (__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ):
_validation(
__lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ... | 618 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
snake_case__ : int = {"""tokenization_wav2vec2_phoneme""": ["""Wav2Vec2PhonemeCTCTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
... | 618 |
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 | 1 |
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 , __lowerca... | 618 |
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 | 1 |
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)
#
# c... | 618 |
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 | 1 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bl... | 618 |
def _snake_case (__lowercase = 1000):
UpperCamelCase_ , UpperCamelCase_ = 1, 1
UpperCamelCase_ = 2
while True:
UpperCamelCase_ = 0
UpperCamelCase_ = fa + fa
UpperCamelCase_ , UpperCamelCase_ = f... | 618 | 1 |
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