code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTransformerConfig",
],
}
try:
if not ... | 632 |
import re
def lowerCAmelCase__ ( UpperCamelCase_ : str )-> str:
if len(re.findall('''[ATCG]''' , UpperCamelCase_ ) ) != len(UpperCamelCase_ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : Optional[int] , UpperCamelCase_ : Optional[Any]=False )-> Optional[Any]:
if isinstance(UpperCamelCase_ , UpperCamelCase_ ) and isinstance(UpperCamelCase_ , UpperC... | 632 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
"configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
"p... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
if n == 1 or not isinstance(UpperCamelCase_ , UpperCamelCase_ ):
return 0
elif n == 2:
return 1
else:
A__ = [0, 1]
for i in range(2 , n + 1 ):
... | 632 |
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase_ : dict , UpperCamelCase_ : str )-> set[str]:
A__ , A__ = set(UpperCamelCase_ ), [start]
while stack:
A__ = stack.pop()
explored.add(Upper... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int )-> int:
while second != 0:
A__ = first & second
first ^= second
A__ = c << 1
return first
if __name__ == "__main__":
import doctest
doctest.... | 632 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from... | 632 | 1 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class _UpperCAmelCase ( A__ ):
def __init__( self , a__ , a__ ... | 632 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
ge... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int = 6_0_0_8_5_1_4_7_5_1_4_3 )-> int:
try:
A__ = int(UpperCamelCase_ )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <= 0:
raise Va... | 632 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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
f... | 632 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase_ : float , UpperCamelCase_ : float , UpperCamelCase_ : float )-> dict[str, float]:
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('''One and... | 632 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, ... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : Optional[int] )-> Optional[Any]:
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
A__ = len(UpperCamelCase_ )
A__ = max(Uppe... | 632 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 632 | 1 |
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_model... | 632 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokeni... | 632 | 1 |
from datetime import datetime as dt
import os
from github import Github
_lowercase = [
"good first issue",
"good second issue",
"good difficult issue",
"feature request",
"new model",
"wip",
]
def lowerCAmelCase__ ( )-> Tuple:
A__ = Github(os.environ['''G... | 632 |
_lowercase = [0, 2, 4, 6, 8]
_lowercase = [1, 3, 5, 7, 9]
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : list[int] , UpperCamelCase_ : int )-> int:
if remaining_length == 0:
... | 632 | 1 |
from scipy.stats import spearmanr
import datasets
_lowercase = "\nThe Spearman rank-order correlation coefficient is a measure of the\nrelationship between two datasets. Like other correlation coefficients,\nthis one varies between -1 and +1 with 0 implying no correlation.\nPositive correlations imply that ... | 632 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 632 | 1 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
_lowercase = HfArgumentParser(InitializationArguments)
_lowercase = parser.parse_args()
# Load codeparrot tokenizer trained for Python code tokenizat... | 632 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCon... | 632 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"],
}
try:
if ... | 632 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 0
while number > 0:
... | 632 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {"vocab_file": "sentencepiece.model"}
_lowercase = ... | 632 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, r... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 0
while number > 0:
... | 632 |
from manim import *
class _UpperCAmelCase ( A__ ):
def snake_case_ ( self):
A__ = Rectangle(height=0.5 , width=0.5)
A__ = Rectangle(height=0.2_5 , width=0.2_5)
A__ = Rectangle(height=0.4_6 , width=0.4_6).set_... | 632 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"processing_mctct": ["MCTCTP... | 632 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
"iou_prediction_head.layers.... | 632 | 1 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase ( A__ ):
def __init__( self , *a__ , **a__):
warnings.warn(
'''The c... | 632 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = '''timm_backbone'''
def __init__( self , a__=None , a__=3 , a__=True , ... | 632 | 1 |
from math import ceil
def lowerCAmelCase__ ( UpperCamelCase_ : str , UpperCamelCase_ : List[str] )-> Optional[int]:
A__ = list(range(0 , UpperCamelCase_ ) )
A__ = [item for sublist in list(device_map.values() ) for i... | 632 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"processing_mctct": ["MCTCTP... | 632 | 1 |
from copy import deepcopy
class _UpperCAmelCase :
def __init__( self , a__ = None , a__ = None):
if arr is None and size is not None:
A__ = size
A__ = [0] * size
elif arr is not None:
self.init(a__)
... | 632 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here to h... | 632 | 1 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class _U... | 632 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resol... | 632 | 1 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFeat... | 632 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _UpperCAm... | 632 | 1 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
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... | 632 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,... | 632 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 632 |
import re
def lowerCAmelCase__ ( UpperCamelCase_ : str )-> str:
if len(re.findall('''[ATCG]''' , UpperCamelCase_ ) ) != len(UpperCamelCase_ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '... | 632 | 1 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokeni... | 632 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
"configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
"p... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int = 5_0 )-> int:
A__ = [[0] * 3 for _ in range(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 + ... | 632 |
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase_ : dict , UpperCamelCase_ : str )-> set[str]:
A__ , A__ = set(UpperCamelCase_ ), [start]
while stack:
A__ = stack.pop()
explored.add(Upper... | 632 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowercase = {
"configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
"tokenization_tapas": ["TapasTokenizer"],
}
try:
if not is_torch_av... | 632 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from... | 632 | 1 |
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
_lowercase = logging.get_logger(__name__) # pylint: disable=invalid-name
class _UpperCAmelCase ( A__ ):
d... | 632 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
ge... | 632 | 1 |
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase :
def __init__( self , a__ ,... | 632 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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
f... | 632 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resol... | 632 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, ... | 632 | 1 |
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")
def lowerCAmelCase__ ( UpperCamelCase_ : Dict )-> str:
A__ = test_file.split(os.path.sep )
... | 632 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : list[int] , UpperCamelCase_ : list[int] )-> None:
A__ = len(UpperCamelCase_ )
print('''The following activities are selected:''' )
# The first activity is always selected
A__ = 0
... | 632 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokeni... | 632 | 1 |
import re
def lowerCAmelCase__ ( UpperCamelCase_ : str )-> list:
return [char.split() for char in re.split(r'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def lowerCAmelCase__ ( UpperCamelCase_ : str )-> str:
A__ = split_input(str_ ... | 632 |
_lowercase = [0, 2, 4, 6, 8]
_lowercase = [1, 3, 5, 7, 9]
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : list[int] , UpperCamelCase_ : int )-> int:
if remaining_length == 0:
... | 632 | 1 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowercase = 10
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int , ... | 632 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 632 | 1 |
_lowercase = frozenset(
[
"prompt",
"height",
"width",
"guidance_scale",
"negative_prompt",
"prompt_embeds",
"negative_prompt_embeds",
"cross_attention_kwargs",
]
)
_lowercase = frozenset(["prompt", "negative_prompt"])
_lowercase ... | 632 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCon... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
if not isinstance(UpperCamelCase_ , UpperCamelCase_ ) or number < 0:
raise ValueError('''Input must be a non-negative integer''' )
A__ = 0
while number:
# This way we arrive at n... | 632 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 0
while number > 0:
... | 632 | 1 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_lowercase = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1), 6: (3, 2), 7: (7, 1), 8: (4, ... | 632 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, r... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> list:
# 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
A__ = gray_code_sequence_stri... | 632 |
from manim import *
class _UpperCAmelCase ( A__ ):
def snake_case_ ( self):
A__ = Rectangle(height=0.5 , width=0.5)
A__ = Rectangle(height=0.2_5 , width=0.2_5)
A__ = Rectangle(height=0.4_6 , width=0.4_6).set_... | 632 | 1 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def lowerCAmelCase__ ( )-> Optional[int]:
A__ = ArgumentParser('''Diffusers CLI tool''' , usage='''diffusers-cli <command> [<args>]''' )
A__ = parser.add_subparsers(help='''diffusers-cli ... | 632 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
"iou_prediction_head.layers.... | 632 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
_lowercase = logging.get_logger(__name__)
_lowercase = {
"Intel/dpt-large": "https://huggingface.co/Intel/dpt-large/resolve/main/config.json",
# See all DPT models at https:... | 632 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = '''timm_backbone'''
def __init__( self , a__=None , a__=3 , a__=True , ... | 632 | 1 |
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
_lowercase = _symbol_database.Def... | 632 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"processing_mctct": ["MCTCTP... | 632 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = "▁"
_lowercase ... | 632 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here to h... | 632 | 1 |
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datasets import load_dataset, ... | 632 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resol... | 632 | 1 |
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...t... | 632 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _UpperCAm... | 632 | 1 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowercase = get_tests_dir("fixtures/spiece.model")
@requ... | 632 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,... | 632 | 1 |
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, logging
_lowerc... | 632 |
import re
def lowerCAmelCase__ ( UpperCamelCase_ : str )-> str:
if len(re.findall('''[ATCG]''' , UpperCamelCase_ ) ) != len(UpperCamelCase_ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '... | 632 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
... | 632 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
"configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
"p... | 632 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"microsoft/wavlm-base": "https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json",
# See all WavLM models at h... | 632 |
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase_ : dict , UpperCamelCase_ : str )-> set[str]:
A__ , A__ = set(UpperCamelCase_ ), [start]
while stack:
A__ = stack.pop()
explored.add(Upper... | 632 | 1 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import __ve... | 632 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from... | 632 | 1 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def lowerCAmelCase__ ( UpperCamelCase_ : List[str] , UpperCamelCase_ : Union[str, Any] , UpperCamelCase_ : Dict )-> Optional[Any]:
A__ = 0
if start < ... | 632 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
ge... | 632 | 1 |
import itertools
import math
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> bool:
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 no... | 632 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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
f... | 632 | 1 |
import requests
from bsa import BeautifulSoup
def lowerCAmelCase__ ( UpperCamelCase_ : str = "AAPL" )-> str:
A__ = f"https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"
A__ = BeautifulSoup(requests.get(UpperCamelCase_ ).text , '''html.parser... | 632 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, ... | 632 | 1 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, r... | 632 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
if not isinstance(UpperCamelCase_ , UpperCamelCase_ ):
raise TypeError('''only integers accepted as input''' )
else:
A__ = str(abs(UpperCamelCase_ ) )
A__ = ... | 632 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokeni... | 632 | 1 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _UpperCAm... | 632 |
_lowercase = [0, 2, 4, 6, 8]
_lowercase = [1, 3, 5, 7, 9]
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : list[int] , UpperCamelCase_ : int )-> int:
if remaining_length == 0:
... | 632 | 1 |
from __future__ import annotations
from math import ceil, floor, sqrt
def lowerCAmelCase__ ( UpperCamelCase_ : int = 2_0_0_0_0_0_0 )-> int:
A__ = [0]
A__ = 42
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ):
triangl... | 632 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 632 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_visio... | 632 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCon... | 632 | 1 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class _UpperCAmelCas... | 632 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 0
while number > 0:
... | 632 | 1 |
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
_lowercase = logging.getLogger(__name__)
@d... | 632 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, r... | 632 | 1 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import is_xformers_availa... | 632 |
from manim import *
class _UpperCAmelCase ( A__ ):
def snake_case_ ( self):
A__ = Rectangle(height=0.5 , width=0.5)
A__ = Rectangle(height=0.2_5 , width=0.2_5)
A__ = Rectangle(height=0.4_6 , width=0.4_6).set_... | 632 | 1 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import HeunDiscreteScheduler
from ... | 632 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
"iou_prediction_head.layers.... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int )-> int:
return x if y == 0 else greatest_common_divisor(UpperCamelCase_ , x % y )
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : ... | 632 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = '''timm_backbone'''
def __init__( self , a__=None , a__=3 , a__=True , ... | 632 | 1 |
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
import ja... | 632 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"processing_mctct": ["MCTCTP... | 632 | 1 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface i... | 632 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here to h... | 632 | 1 |
import socket
def lowerCAmelCase__ ( )-> Dict:
A__ = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
A__ = socket.gethostname()
A__ = 1_2_3_1_2
sock.connect((host, port) )
sock.send(b'''Hello server!''' )
with open('''... | 632 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resol... | 632 | 1 |
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
to_channel_dimens... | 632 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _UpperCAm... | 632 | 1 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 632 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,... | 632 | 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_xpu,
require_torch_... | 632 |
import re
def lowerCAmelCase__ ( UpperCamelCase_ : str )-> str:
if len(re.findall('''[ATCG]''' , UpperCamelCase_ ) ) != len(UpperCamelCase_ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '... | 632 | 1 |
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
_lowercase = logging.get_logger(__name__)
class _Upper... | 632 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
"configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
"p... | 632 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = '''ctrl'''
U... | 632 |
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase_ : dict , UpperCamelCase_ : str )-> set[str]:
A__ , A__ = set(UpperCamelCase_ ), [start]
while stack:
A__ = stack.pop()
explored.add(Upper... | 632 | 1 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
_lowercase = logging.get_logger(__name__)
_lowercase = {"vocab_file": "vocab.json", "merges_file": "merges.txt", "toke... | 632 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int = 1_0 )-> str:
if not isinstance(UpperCamelCase_ , UpperCamelCase_ ) or n < 0:
raise ValueError('''Invalid input''' )
A__ = 1_0**n
A__ = 2_8_4_3_3 * (pow(2 , 7_8_3_0_4_5_7 , ... | 632 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
ge... | 632 | 1 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def lowerCAmelCase__ (... | 632 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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
f... | 632 | 1 |
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def lowerCAmelCase__ ( )-> Optional[int]... | 632 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, ... | 632 | 1 |
from math import pi
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int )-> float:
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 632 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int )-> int:
return int((input_a, input_a).count(0 ) != 0 )
def lowerCAmelCase__ ( )-> None:
assert nand_gate(0 , 0 ) == 1
assert nand_gate(0 , 1 ... | 632 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokeni... | 632 | 1 |
import math
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
if not isinstance(UpperCamelCase_ , UpperCamelCase_ ):
A__ = f"Input value of [number={number}] must be an integer"
raise TypeError(UpperCamelCase_ )
if number < 1:
... | 632 |
_lowercase = [0, 2, 4, 6, 8]
_lowercase = [1, 3, 5, 7, 9]
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : list[int] , UpperCamelCase_ : int )-> int:
if remaining_length == 0:
... | 632 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCon... | 632 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 632 | 1 |
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
_lowercase = "\\n@inproceedings{snover-etal-2006-study,\n title = \"A Study of Translation Edit Rate with Targeted Human Annotation\",\n author = \"Snover, Matthew and\n Dorr, Bonnie and\n Schwa... | 632 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCon... | 632 | 1 |
# Function to print upper half of diamond (pyramid)
def lowerCAmelCase__ ( UpperCamelCase_ : Optional[Any] )-> Any:
for i in range(0 , UpperCamelCase_ ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(''' ''' , end='''... | 632 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 0
while number > 0:
... | 632 | 1 |
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,
)
_lowercase = pytest.mark.integration
@pytest.mark.parametrize('''path''' , ['''paws''', '''csv'... | 632 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, r... | 632 | 1 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepInverseScheduler,
DP... | 632 |
from manim import *
class _UpperCAmelCase ( A__ ):
def snake_case_ ( self):
A__ = Rectangle(height=0.5 , width=0.5)
A__ = Rectangle(height=0.2_5 , width=0.2_5)
A__ = Rectangle(height=0.4_6 , width=0.4_6).set_... | 632 | 1 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
_lowercase = "%20".join(argv[1:]) if len(argv) > 1 else quote(str(input("Search: ")))
print("Googling.....")
... | 632 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
"iou_prediction_head.layers.... | 632 | 1 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checko... | 632 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = '''timm_backbone'''
def __init__( self , a__=None , a__=3 , a__=True , ... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : str , UpperCamelCase_ : str )-> str:
if not (isinstance(UpperCamelCase_ , UpperCamelCase_ ) and isinstance(UpperCamelCase_ , UpperCamelCase_ )):
raise ValueError('''longest_common_substring()... | 632 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"processing_mctct": ["MCTCTP... | 632 | 1 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
_lowercase = logging.getLogger(__name__)
@dataclass
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = ... | 632 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here to h... | 632 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = '''encoder-decoder'''
UpperCamelCase__ = True
def __init__( ... | 632 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resol... | 632 | 1 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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
f... | 632 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _UpperCAm... | 632 | 1 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.rob... | 632 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,... | 632 | 1 |
from manim import *
class _UpperCAmelCase ( A__ ):
def snake_case_ ( self):
A__ = Rectangle(height=0.5 , width=0.5)
A__ = Rectangle(height=0.2_5 , width=0.2_5)
A__ = Rectangle(height=0.4_6 , width=0.4_6).set_... | 632 |
import re
def lowerCAmelCase__ ( UpperCamelCase_ : str )-> str:
if len(re.findall('''[ATCG]''' , UpperCamelCase_ ) ) != len(UpperCamelCase_ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '... | 632 | 1 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def lowerCAmelCase__ ( UpperCamelCase_ : Li... | 632 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
"configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
"p... | 632 | 1 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
ge... | 632 |
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase_ : dict , UpperCamelCase_ : str )-> set[str]:
A__ , A__ = set(UpperCamelCase_ ), [start]
while stack:
A__ = stack.pop()
explored.add(Upper... | 632 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int )-> int:
return int(input_a == input_a == 0 )
def lowerCAmelCase__ ( )-> None:
print('''Truth Table of NOR Gate:''' )
print('''| Input 1 | Input 2 | Output |''... | 632 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from... | 632 | 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 _UpperCAmelCase ( A__ ):
UpperCame... | 632 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
ge... | 632 | 1 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"google/efficientnet-b7": "ht... | 632 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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
f... | 632 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfig", "ResNetOnnxConfig"]
}
try:
... | 632 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, ... | 632 | 1 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCAmelCase__ ( )-> Dict:
A__ = ArgumentParser(
description=(
'''PyTorch TPU distributed training launc... | 632 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 632 | 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 require_torch, require... | 632 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokeni... | 632 | 1 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
_lowercase = TypeVar("T")
class _UpperCAmelCase ( Generic[T] ):
UpperCamelCase__ = 42 # Cache store of keys
UpperCamelCase__ = 42 # References of... | 632 |
_lowercase = [0, 2, 4, 6, 8]
_lowercase = [1, 3, 5, 7, 9]
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : list[int] , UpperCamelCase_ : int )-> int:
if remaining_length == 0:
... | 632 | 1 |
import copy
import random
from transformers import CLIPTokenizer
class _UpperCAmelCase ( A__ ):
def __init__( self , *a__ , **a__):
super().__init__(*a__ , **a__)
A__ = {}
def snake_case_ ( self , a__ , *a__ , ... | 632 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 632 | 1 |
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
require_torch,
r... | 632 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCon... | 632 | 1 |
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