


"""simple docstring"""



import os
import tempfile
import unittest
import uuid
from pathlib import Path

from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_torch_available, is_vision_available


if is_torch_available():
  import torch

if is_soundfile_availble():
  import soundfile as sf

if is_vision_available():
  from PIL import Image







def     __lowerCAmelCase		(		lowercase    :    Any=""					)      ->		str:


    """simple docstring"""





    snake_case       : Dict    =       tempfile.mkdtemp()
    return os.path.join(lowercase		,				str(uuid.uuida()					) + suffix					)







@require_soundfile
@require_torch
class _lowerCAmelCase							( unittest.TestCase      ):







   def 					lowerCamelCase						(      self		)      ->						Dict:

       '''simple docstring'''




       snake_case       : Optional[int]    =       torch.rand(12		,      dtype=torch.floataa		) - 0.5
       snake_case       : Tuple    =       AgentAudio(UpperCamelCase__		)
       snake_case       : List[Any]    =       str(agent_type.to_string()		)

       # Ensure that the tensor and the agent_type's tensor are the same
       self.assertTrue(torch.allclose(UpperCamelCase__		,      agent_type.to_raw()		,      atol=1e-4		)		)

       del agent_type

       # Ensure the path remains even after the object deletion
       self.assertTrue(os.path.exists(UpperCamelCase__		)		)

       # Ensure that the file contains the same value as the original tensor
       snake_case   ,snake_case       : List[Any]    =       sf.read(UpperCamelCase__		)
       self.assertTrue(torch.allclose(UpperCamelCase__		,      torch.tensor(UpperCamelCase__		)		,      atol=1e-4		)		)







   def 					lowerCamelCase						(      self		)      ->						str:

       '''simple docstring'''




       snake_case       : Any    =       torch.rand(12		,      dtype=torch.floataa		) - 0.5
       snake_case       : Union[str, Any]    =       get_new_path(suffix=".wav"		)
       sf.write(UpperCamelCase__		,      UpperCamelCase__		,      1_6000		)

       snake_case       : Optional[int]    =       AgentAudio(UpperCamelCase__		)

       self.assertTrue(torch.allclose(UpperCamelCase__		,      agent_type.to_raw()		,      atol=1e-4		)		)
       self.assertEqual(agent_type.to_string()		,      UpperCamelCase__		)







@require_vision
@require_torch
class _lowerCAmelCase							( unittest.TestCase      ):







   def 					lowerCamelCase						(      self		)      ->						int:

       '''simple docstring'''




       snake_case       : Union[str, Any]    =       torch.randint(0		,      256		,      (64, 64, 3)		)
       snake_case       : int    =       AgentImage(UpperCamelCase__		)
       snake_case       : Tuple    =       str(agent_type.to_string()		)

       # Ensure that the tensor and the agent_type's tensor are the same
       self.assertTrue(torch.allclose(UpperCamelCase__		,      agent_type._tensor		,      atol=1e-4		)		)

       self.assertIsInstance(agent_type.to_raw()		,      Image.Image		)

       # Ensure the path remains even after the object deletion
       del agent_type
       self.assertTrue(os.path.exists(UpperCamelCase__		)		)







   def 					lowerCamelCase						(      self		)      ->						Optional[int]:

       '''simple docstring'''




       snake_case       : Dict    =       Path(get_tests_dir("fixtures/tests_samples/COCO"		)		) / "000000039769.png"
       snake_case       : str    =       Image.open(UpperCamelCase__		)
       snake_case       : int    =       AgentImage(UpperCamelCase__		)

       self.assertTrue(path.samefile(agent_type.to_string()		)		)
       self.assertTrue(image == agent_type.to_raw()		)

       # Ensure the path remains even after the object deletion
       del agent_type
       self.assertTrue(os.path.exists(UpperCamelCase__		)		)







   def 					lowerCamelCase						(      self		)      ->						Any:

       '''simple docstring'''




       snake_case       : Any    =       Path(get_tests_dir("fixtures/tests_samples/COCO"		)		) / "000000039769.png"
       snake_case       : Dict    =       Image.open(UpperCamelCase__		)
       snake_case       : Optional[Any]    =       AgentImage(UpperCamelCase__		)

       self.assertFalse(path.samefile(agent_type.to_string()		)		)
       self.assertTrue(image == agent_type.to_raw()		)

       # Ensure the path remains even after the object deletion
       del agent_type
       self.assertTrue(os.path.exists(UpperCamelCase__		)		)







class _lowerCAmelCase							( unittest.TestCase      ):







   def 					lowerCamelCase						(      self		)      ->						Optional[int]:

       '''simple docstring'''




       snake_case       : Tuple    =       "Hey!"
       snake_case       : Optional[int]    =       AgentText(UpperCamelCase__		)

       self.assertEqual(UpperCamelCase__		,      agent_type.to_string()		)
       self.assertEqual(UpperCamelCase__		,      agent_type.to_raw()		)
       self.assertEqual(UpperCamelCase__		,      UpperCamelCase__		)









"""simple docstring"""



from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging


if TYPE_CHECKING:
  from ...onnx.config import PatchingSpec
  from ...tokenization_utils_base import PreTrainedTokenizerBase


__snake_case       =       logging.get_logger(__name__)

__snake_case       =       {
    """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/config.json""",
    """allenai/longformer-large-4096""": """https://huggingface.co/allenai/longformer-large-4096/resolve/main/config.json""",
    """allenai/longformer-large-4096-finetuned-triviaqa""": (
        """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/config.json"""
    ),
    """allenai/longformer-base-4096-extra.pos.embd.only""": (
        """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/config.json"""
    ),
    """allenai/longformer-large-4096-extra.pos.embd.only""": (
        """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/config.json"""
    ),
}







class _lowerCAmelCase							( snake_case_      ):
   __UpperCAmelCase					:			Tuple				    =    '''longformer'''







   def __init__(      self		,      UpperCamelCase__ = 512		,      UpperCamelCase__ = 2		,      UpperCamelCase__ = 1		,      UpperCamelCase__ = 0		,      UpperCamelCase__ = 2		,      UpperCamelCase__ = 3_0522		,      UpperCamelCase__ = 768		,      UpperCamelCase__ = 12		,      UpperCamelCase__ = 12		,      UpperCamelCase__ = 3072		,      UpperCamelCase__ = "gelu"		,      UpperCamelCase__ = 0.1		,      UpperCamelCase__ = 0.1		,      UpperCamelCase__ = 512		,      UpperCamelCase__ = 2		,      UpperCamelCase__ = 0.02		,      UpperCamelCase__ = 1e-12		,      UpperCamelCase__ = False		,      **UpperCamelCase__		,      )      ->						str:

       '''simple docstring'''




       super().__init__(pad_token_id=UpperCamelCase__		,      **UpperCamelCase__		)

       snake_case       : int    =       attention_window
       snake_case       : Any    =       sep_token_id
       snake_case       : Dict    =       bos_token_id
       snake_case       : int    =       eos_token_id
       snake_case       : List[str]    =       vocab_size
       snake_case       : Dict    =       hidden_size
       snake_case       : Optional[int]    =       num_hidden_layers
       snake_case       : List[str]    =       num_attention_heads
       snake_case       : Dict    =       hidden_act
       snake_case       : Union[str, Any]    =       intermediate_size
       snake_case       : Optional[int]    =       hidden_dropout_prob
       snake_case       : List[Any]    =       attention_probs_dropout_prob
       snake_case       : Any    =       max_position_embeddings
       snake_case       : Union[str, Any]    =       type_vocab_size
       snake_case       : Union[str, Any]    =       initializer_range
       snake_case       : int    =       layer_norm_eps
       snake_case       : str    =       onnx_export







class _lowerCAmelCase							( snake_case_      ):







   def __init__(      self		,      UpperCamelCase__		,      UpperCamelCase__ = "default"		,      UpperCamelCase__ = None		)      ->						List[str]:

       '''simple docstring'''




       super().__init__(UpperCamelCase__		,      UpperCamelCase__		,      UpperCamelCase__		)
       snake_case       : int    =       True







   @property
   def 					lowerCamelCase						(      self		)      ->						Mapping[str, Mapping[int, str]]:

       '''simple docstring'''




       if self.task == "multiple-choice":
           snake_case       : str    =       {0: "batch", 1: "choice", 2: "sequence"}
       else:
           snake_case       : List[str]    =       {0: "batch", 1: "sequence"}
       return OrderedDict(
           [
               ("input_ids", dynamic_axis),
               ("attention_mask", dynamic_axis),
               ("global_attention_mask", dynamic_axis),
           ]		)







   @property
   def 					lowerCamelCase						(      self		)      ->						Mapping[str, Mapping[int, str]]:

       '''simple docstring'''




       snake_case       : str    =       super().outputs
       if self.task == "default":
           snake_case       : str    =       {0: "batch"}
       return outputs







   @property
   def 					lowerCamelCase						(      self		)      ->						float:

       '''simple docstring'''




       return 1e-4







   @property
   def 					lowerCamelCase						(      self		)      ->						int:

       '''simple docstring'''




       return max(super().default_onnx_opset		,      14		)







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		,      UpperCamelCase__ = -1		,      UpperCamelCase__ = -1		,      UpperCamelCase__ = False		,      UpperCamelCase__ = None		,      )      ->						Mapping[str, Any]:

       '''simple docstring'''




       snake_case       : Optional[int]    =       super().generate_dummy_inputs(
           preprocessor=UpperCamelCase__		,      batch_size=UpperCamelCase__		,      seq_length=UpperCamelCase__		,      is_pair=UpperCamelCase__		,      framework=UpperCamelCase__		)
       import torch

       # for some reason, replacing this code by inputs["global_attention_mask"] = torch.randint(2, inputs["input_ids"].shape, dtype=torch.int64)
       # makes the export fail randomly
       snake_case       : Any    =       torch.zeros_like(inputs["input_ids"]		)
       # make every second token global
       snake_case       : Any    =       1

       return inputs





