from __future__ import annotations

import unittest

import numpy as np

from transformers import LayoutLMConfig, 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
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
    import tensorflow as tf

    from transformers.models.layoutlm.modeling_tf_layoutlm import (
        TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFLayoutLMForMaskedLM,
        TFLayoutLMForQuestionAnswering,
        TFLayoutLMForSequenceClassification,
        TFLayoutLMForTokenClassification,
        TFLayoutLMModel,
    )
class     a_			:






 '''simple docstring'''






 def __init__(      self :  Optional[Any]      ,   lowercase__ :  Dict      ,   lowercase__ :  Union[str, Any]=13      ,   lowercase__ :  List[str]=7      ,   lowercase__ :  int=True      ,   lowercase__ :  int=True      ,   lowercase__ :  Optional[int]=True      ,   lowercase__ :  str=True      ,   lowercase__ :  List[str]=99      ,   lowercase__ :  Tuple=32      ,   lowercase__ :  Optional[int]=2      ,   lowercase__ :  List[str]=4      ,   lowercase__ :  Optional[Any]=37      ,   lowercase__ :  Union[str, Any]="gelu"      ,   lowercase__ :  Optional[Any]=0.1      ,   lowercase__ :  str=0.1      ,   lowercase__ :  Union[str, Any]=512      ,   lowercase__ :  Optional[int]=16      ,   lowercase__ :  Dict=2      ,   lowercase__ :  Optional[Any]=0.02      ,   lowercase__ :  List[Any]=3      ,   lowercase__ :  Tuple=4      ,   lowercase__ :  Dict=None      ,   lowercase__ :  Optional[Any]=1_000      ,   ):







        '''simple docstring'''



        lowerCAmelCase__					     = parent
        lowerCAmelCase__					     = batch_size
        lowerCAmelCase__					     = seq_length
        lowerCAmelCase__					     = is_training
        lowerCAmelCase__					     = use_input_mask
        lowerCAmelCase__					     = use_token_type_ids
        lowerCAmelCase__					     = use_labels
        lowerCAmelCase__					     = vocab_size
        lowerCAmelCase__					     = hidden_size
        lowerCAmelCase__					     = num_hidden_layers
        lowerCAmelCase__					     = num_attention_heads
        lowerCAmelCase__					     = intermediate_size
        lowerCAmelCase__					     = hidden_act
        lowerCAmelCase__					     = hidden_dropout_prob
        lowerCAmelCase__					     = attention_probs_dropout_prob
        lowerCAmelCase__					     = max_position_embeddings
        lowerCAmelCase__					     = type_vocab_size
        lowerCAmelCase__					     = type_sequence_label_size
        lowerCAmelCase__					     = initializer_range
        lowerCAmelCase__					     = num_labels
        lowerCAmelCase__					     = num_choices
        lowerCAmelCase__					     = scope
        lowerCAmelCase__					     = range_bbox




 def 		__snake_case						(      self :  List[str]):







        '''simple docstring'''



        lowerCAmelCase__					     = ids_tensor([self.batch_size, self.seq_length]      ,   self.vocab_size)

        # convert bbox to numpy since TF does not support item assignment
        lowerCAmelCase__					     = ids_tensor([self.batch_size, self.seq_length, 4]      ,   self.range_bbox).numpy()
        # Ensure that bbox is legal
        for i in range(bbox.shape[0]):
               for j in range(bbox.shape[1]):
                      if bbox[i, j, 3] < bbox[i, j, 1]:
                             lowerCAmelCase__					     = bbox[i, j, 3]
                             lowerCAmelCase__					     = bbox[i, j, 1]
                             lowerCAmelCase__					     = t
                      if bbox[i, j, 2] < bbox[i, j, 0]:
                             lowerCAmelCase__					     = bbox[i, j, 2]
                             lowerCAmelCase__					     = bbox[i, j, 0]
                             lowerCAmelCase__					     = t
        lowerCAmelCase__					     = tf.convert_to_tensor(lowercase__)

        lowerCAmelCase__					     = None
        if self.use_input_mask:
               lowerCAmelCase__					     = random_attention_mask([self.batch_size, self.seq_length])

        lowerCAmelCase__					     = None
        if self.use_token_type_ids:
               lowerCAmelCase__					     = ids_tensor([self.batch_size, self.seq_length]      ,   self.type_vocab_size)

        lowerCAmelCase__					     = None
        lowerCAmelCase__					     = None
        lowerCAmelCase__					     = None
        if self.use_labels:
               lowerCAmelCase__					     = ids_tensor([self.batch_size]      ,   self.type_sequence_label_size)
               lowerCAmelCase__					     = ids_tensor([self.batch_size, self.seq_length]      ,   self.num_labels)
               lowerCAmelCase__					     = ids_tensor([self.batch_size]      ,   self.num_choices)

        lowerCAmelCase__					     = LayoutLMConfig(
            vocab_size=self.vocab_size      ,   hidden_size=self.hidden_size      ,   num_hidden_layers=self.num_hidden_layers      ,   num_attention_heads=self.num_attention_heads      ,   intermediate_size=self.intermediate_size      ,   hidden_act=self.hidden_act      ,   hidden_dropout_prob=self.hidden_dropout_prob      ,   attention_probs_dropout_prob=self.attention_probs_dropout_prob      ,   max_position_embeddings=self.max_position_embeddings      ,   type_vocab_size=self.type_vocab_size      ,   initializer_range=self.initializer_range      ,   )

        return config, input_ids, bbox, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels




 def 		__snake_case						(      self :  str      ,   lowercase__ :  Dict      ,   lowercase__ :  int      ,   lowercase__ :  str      ,   lowercase__ :  List[str]      ,   lowercase__ :  str      ,   lowercase__ :  int      ,   lowercase__ :  Union[str, Any]      ,   lowercase__ :  List[Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = TFLayoutLMModel(config=lowercase__)

        lowerCAmelCase__					     = model(lowercase__      ,   lowercase__      ,   attention_mask=lowercase__      ,   token_type_ids=lowercase__)
        lowerCAmelCase__					     = model(lowercase__      ,   lowercase__      ,   token_type_ids=lowercase__)
        lowerCAmelCase__					     = model(lowercase__      ,   lowercase__)
        self.parent.assertEqual(result.last_hidden_state.shape      ,   (self.batch_size, self.seq_length, self.hidden_size))
        self.parent.assertEqual(result.pooler_output.shape      ,   (self.batch_size, self.hidden_size))




 def 		__snake_case						(      self :  Optional[Any]      ,   lowercase__ :  Tuple      ,   lowercase__ :  str      ,   lowercase__ :  List[str]      ,   lowercase__ :  List[Any]      ,   lowercase__ :  Union[str, Any]      ,   lowercase__ :  List[str]      ,   lowercase__ :  Optional[Any]      ,   lowercase__ :  Union[str, Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = TFLayoutLMForMaskedLM(config=lowercase__)

        lowerCAmelCase__					     = model(lowercase__      ,   lowercase__      ,   attention_mask=lowercase__      ,   token_type_ids=lowercase__      ,   labels=lowercase__)
        self.parent.assertEqual(result.logits.shape      ,   (self.batch_size, self.seq_length, self.vocab_size))




 def 		__snake_case						(      self :  Optional[Any]      ,   lowercase__ :  str      ,   lowercase__ :  Union[str, Any]      ,   lowercase__ :  Optional[Any]      ,   lowercase__ :  str      ,   lowercase__ :  Dict      ,   lowercase__ :  Optional[int]      ,   lowercase__ :  List[Any]      ,   lowercase__ :  List[Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = self.num_labels
        lowerCAmelCase__					     = TFLayoutLMForSequenceClassification(config=lowercase__)

        lowerCAmelCase__					     = model(lowercase__      ,   lowercase__      ,   attention_mask=lowercase__      ,   token_type_ids=lowercase__)
        self.parent.assertEqual(result.logits.shape      ,   (self.batch_size, self.num_labels))




 def 		__snake_case						(      self :  Dict      ,   lowercase__ :  List[str]      ,   lowercase__ :  str      ,   lowercase__ :  Tuple      ,   lowercase__ :  Tuple      ,   lowercase__ :  int      ,   lowercase__ :  List[Any]      ,   lowercase__ :  Union[str, Any]      ,   lowercase__ :  str):







        '''simple docstring'''



        lowerCAmelCase__					     = self.num_labels
        lowerCAmelCase__					     = TFLayoutLMForTokenClassification(config=lowercase__)

        lowerCAmelCase__					     = model(lowercase__      ,   lowercase__      ,   attention_mask=lowercase__      ,   token_type_ids=lowercase__      ,   labels=lowercase__)
        self.parent.assertEqual(result.logits.shape      ,   (self.batch_size, self.seq_length, self.num_labels))




 def 		__snake_case						(      self :  Optional[Any]      ,   lowercase__ :  Optional[Any]      ,   lowercase__ :  Any      ,   lowercase__ :  Dict      ,   lowercase__ :  int      ,   lowercase__ :  str      ,   lowercase__ :  Any      ,   lowercase__ :  int      ,   lowercase__ :  Union[str, Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = TFLayoutLMForQuestionAnswering(config=lowercase__)

        lowerCAmelCase__					     = model(lowercase__      ,   lowercase__      ,   attention_mask=lowercase__      ,   token_type_ids=lowercase__)
        self.parent.assertEqual(result.start_logits.shape      ,   (self.batch_size, self.seq_length))
        self.parent.assertEqual(result.end_logits.shape      ,   (self.batch_size, self.seq_length))




 def 		__snake_case						(      self :  Optional[int]):







        '''simple docstring'''



        lowerCAmelCase__					     = self.prepare_config_and_inputs()
        (
            (
            lowerCAmelCase__
        )     , (
            lowerCAmelCase__
        )     , (
            lowerCAmelCase__
        )     , (
            lowerCAmelCase__
        )     , (
            lowerCAmelCase__
        )     , (
            lowerCAmelCase__
        )     , (
            lowerCAmelCase__
        )     , (
            lowerCAmelCase__
        )     , 
        )					     = config_and_inputs
        lowerCAmelCase__					     = {
            'input_ids': input_ids,
            'bbox': bbox,
            'token_type_ids': token_type_ids,
            'attention_mask': input_mask,
        }
        return config, inputs_dict






@require_tf
class     a_			(						SCREAMING_SNAKE_CASE	,					SCREAMING_SNAKE_CASE	,					unittest.TestCase						):






 '''simple docstring'''






 UpperCAmelCase_     			= (
     (
         TFLayoutLMModel,
         TFLayoutLMForMaskedLM,
         TFLayoutLMForTokenClassification,
         TFLayoutLMForSequenceClassification,
         TFLayoutLMForQuestionAnswering,
     )
     if is_tf_available()
     else ()
 )
 UpperCAmelCase_     			= (
     {
         'feature-extraction': TFLayoutLMModel,
         'fill-mask': TFLayoutLMForMaskedLM,
         'text-classification': TFLayoutLMForSequenceClassification,
         'token-classification': TFLayoutLMForTokenClassification,
         'zero-shot': TFLayoutLMForSequenceClassification,
     }
     if is_tf_available()
     else {}
 )
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= True
 UpperCAmelCase_     			= 10




 def 		__snake_case						(      self :  str):







        '''simple docstring'''



        lowerCAmelCase__					     = TFLayoutLMModelTester(self)
        lowerCAmelCase__					     = ConfigTester(self      ,   config_class=lowercase__      ,   hidden_size=37)




 def 		__snake_case						(      self :  Union[str, Any]):







        '''simple docstring'''



        self.config_tester.run_common_tests()




 def 		__snake_case						(      self :  List[Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = self.model_tester.prepare_config_and_inputs()
        self.model_tester.create_and_check_model(*lowercase__)




 def 		__snake_case						(      self :  int):







        '''simple docstring'''



        lowerCAmelCase__					     = self.model_tester.prepare_config_and_inputs()
        self.model_tester.create_and_check_for_masked_lm(*lowercase__)




 def 		__snake_case						(      self :  int):







        '''simple docstring'''



        lowerCAmelCase__					     = self.model_tester.prepare_config_and_inputs()
        self.model_tester.create_and_check_for_sequence_classification(*lowercase__)




 def 		__snake_case						(      self :  Tuple):







        '''simple docstring'''



        lowerCAmelCase__					     = self.model_tester.prepare_config_and_inputs()
        self.model_tester.create_and_check_for_token_classification(*lowercase__)




 def 		__snake_case						(      self :  List[str]):







        '''simple docstring'''



        lowerCAmelCase__					     = self.model_tester.prepare_config_and_inputs()
        self.model_tester.create_and_check_for_question_answering(*lowercase__)




 @slow
 def 		__snake_case						(      self :  List[str]):







        '''simple docstring'''



        for model_name in TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
               lowerCAmelCase__					     = TFLayoutLMModel.from_pretrained(lowercase__)
               self.assertIsNotNone(lowercase__)




 @unittest.skip('Onnx compliancy broke with TF 2.10')
 def 		__snake_case						(      self :  Optional[Any]):







        '''simple docstring'''



        pass






def 				__lowerCamelCase		(						):
       # Here we prepare a batch of 2 sequences to test a LayoutLM forward pass on:
       # fmt: off
       lowerCAmelCase__					     = tf.convert_to_tensor([[1_0_1,1_0_1_9,1_0_1_4,1_0_1_6,1_0_3_7,1_2_8_4_9,4_7_4_7,1_0_0_4,1_4_2_4_6,2_2_7_8,5_4_3_9,4_5_2_4,5_0_0_2,2_9_3_0,2_1_9_3,2_9_3_0,4_3_4_1,3_2_0_8,1_0_0_5,1_0_5_5,2_1_7_1,2_8_4_8,1_1_3_0_0,3_5_3_1,1_0_2],[1_0_1,4_0_7_0,4_0_3_4,7_0_2_0,1_0_2_4,3_0_5_8,1_0_1_5,1_0_1_3,2_8_6_1,1_0_1_3,6_0_7_0,1_9_2_7_4,2_7_7_2,6_2_0_5,2_7_8_1_4,1_6_1_4_7,1_6_1_4_7,4_3_4_3,2_0_4_7,1_0_2_8_3,1_0_9_6_9,1_4_3_8_9,1_0_1_2,2_3_3_8,1_0_2]]     )  # noqa: E231
       lowerCAmelCase__					     = tf.convert_to_tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],]     )  # noqa: E231
       lowerCAmelCase__					     = tf.convert_to_tensor([[[0,0,0,0],[4_2_3,2_3_7,4_4_0,2_5_1],[4_2_7,2_7_2,4_4_1,2_8_7],[4_1_9,1_1_5,4_3_7,1_2_9],[9_6_1,8_8_5,9_9_2,9_1_2],[2_5_6,3_8,3_3_0,5_8],[2_5_6,3_8,3_3_0,5_8],[3_3_6,4_2,3_5_3,5_7],[3_6_0,3_9,4_0_1,5_6],[3_6_0,3_9,4_0_1,5_6],[4_1_1,3_9,4_7_1,5_9],[4_7_9,4_1,5_2_8,5_9],[5_3_3,3_9,6_3_0,6_0],[6_7,1_1_3,1_3_4,1_3_1],[1_4_1,1_1_5,2_0_9,1_3_2],[6_8,1_4_9,1_3_3,1_6_6],[1_4_1,1_4_9,1_8_7,1_6_4],[1_9_5,1_4_8,2_8_7,1_6_5],[1_9_5,1_4_8,2_8_7,1_6_5],[1_9_5,1_4_8,2_8_7,1_6_5],[2_9_5,1_4_8,3_4_9,1_6_5],[4_4_1,1_4_9,4_9_2,1_6_6],[4_9_7,1_4_9,5_4_6,1_6_4],[6_4,2_0_1,1_2_5,2_1_8],[1_0_0_0,1_0_0_0,1_0_0_0,1_0_0_0]],[[0,0,0,0],[6_6_2,1_5_0,7_5_4,1_6_6],[6_6_5,1_9_9,7_4_2,2_1_1],[5_1_9,2_1_3,5_5_4,2_2_8],[5_1_9,2_1_3,5_5_4,2_2_8],[1_3_4,4_3_3,1_8_7,4_5_4],[1_3_0,4_6_7,2_0_4,4_8_0],[1_3_0,4_6_7,2_0_4,4_8_0],[1_3_0,4_6_7,2_0_4,4_8_0],[1_3_0,4_6_7,2_0_4,4_8_0],[1_3_0,4_6_7,2_0_4,4_8_0],[3_1_4,4_6_9,3_7_6,4_8_2],[5_0_4,6_8_4,5_8_2,7_0_6],[9_4_1,8_2_5,9_7_3,9_0_0],[9_4_1,8_2_5,9_7_3,9_0_0],[9_4_1,8_2_5,9_7_3,9_0_0],[9_4_1,8_2_5,9_7_3,9_0_0],[6_1_0,7_4_9,6_5_2,7_6_5],[1_3_0,6_5_9,1_6_8,6_7_2],[1_7_6,6_5_7,2_3_7,6_7_2],[2_3_8,6_5_7,3_1_2,6_7_2],[4_4_3,6_5_3,6_2_8,6_7_2],[4_4_3,6_5_3,6_2_8,6_7_2],[7_1_6,3_0_1,8_2_5,3_1_7],[1_0_0_0,1_0_0_0,1_0_0_0,1_0_0_0]]]     )  # noqa: E231
       lowerCAmelCase__					     = tf.convert_to_tensor([[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]]     )  # noqa: E231
       # these are sequence labels (i.e. at the token level)
       lowerCAmelCase__					     = tf.convert_to_tensor([[-1_0_0,1_0,1_0,1_0,9,1,-1_0_0,7,7,-1_0_0,7,7,4,2,5,2,8,8,-1_0_0,-1_0_0,5,0,3,2,-1_0_0],[-1_0_0,1_2,1_2,1_2,-1_0_0,1_2,1_0,-1_0_0,-1_0_0,-1_0_0,-1_0_0,1_0,1_2,9,-1_0_0,-1_0_0,-1_0_0,1_0,1_0,1_0,9,1_2,-1_0_0,1_0,-1_0_0]]     )  # noqa: E231
       # fmt: on

       return input_ids, attention_mask, bbox, token_type_ids, labels



@require_tf
class     a_			(						unittest.TestCase						):






 '''simple docstring'''






 @slow
 def 		__snake_case						(      self :  Tuple):







        '''simple docstring'''



        lowerCAmelCase__					     = TFLayoutLMModel.from_pretrained('microsoft/layoutlm-base-uncased')

        lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__					     = prepare_layoutlm_batch_inputs()

        # forward pass
        lowerCAmelCase__					     = model(input_ids=lowercase__      ,   bbox=lowercase__      ,   attention_mask=lowercase__      ,   token_type_ids=lowercase__)

        # test the sequence output on [0, :3, :3]
        lowerCAmelCase__					     = tf.convert_to_tensor(
            [[0.1_785, -0.1_947, -0.0_425], [-0.3_254, -0.2_807, 0.2_553], [-0.5_391, -0.3_322, 0.3_364]]      ,   )

        self.assertTrue(np.allclose(outputs.last_hidden_state[0, :3, :3]      ,   lowercase__      ,   atol=1e-3))

        # test the pooled output on [1, :3]
        lowerCAmelCase__					     = tf.convert_to_tensor([-0.6_580, -0.0_214, 0.8_552])

        self.assertTrue(np.allclose(outputs.pooler_output[1, :3]      ,   lowercase__      ,   atol=1e-3))




 @slow
 def 		__snake_case						(      self :  Union[str, Any]):







        '''simple docstring'''



        lowerCAmelCase__					     = TFLayoutLMForSequenceClassification.from_pretrained('microsoft/layoutlm-base-uncased'      ,   num_labels=2)

        lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__					     = prepare_layoutlm_batch_inputs()

        # forward pass
        lowerCAmelCase__					     = model(
            input_ids=lowercase__      ,   bbox=lowercase__      ,   attention_mask=lowercase__      ,   token_type_ids=lowercase__      ,   labels=tf.convert_to_tensor([1, 1])      ,   )

        # test whether we get a loss as a scalar
        lowerCAmelCase__					     = outputs.loss
        lowerCAmelCase__					     = (2,)
        self.assertEqual(loss.shape      ,   lowercase__)

        # test the shape of the logits
        lowerCAmelCase__					     = outputs.logits
        lowerCAmelCase__					     = (2, 2)
        self.assertEqual(logits.shape      ,   lowercase__)




 @slow
 def 		__snake_case						(      self :  int):







        '''simple docstring'''



        lowerCAmelCase__					     = TFLayoutLMForTokenClassification.from_pretrained('microsoft/layoutlm-base-uncased'      ,   num_labels=13)

        lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__					     = prepare_layoutlm_batch_inputs()

        # forward pass
        lowerCAmelCase__					     = model(
            input_ids=lowercase__      ,   bbox=lowercase__      ,   attention_mask=lowercase__      ,   token_type_ids=lowercase__      ,   labels=lowercase__)

        # test the shape of the logits
        lowerCAmelCase__					     = outputs.logits
        lowerCAmelCase__					     = tf.convert_to_tensor((2, 25, 13))
        self.assertEqual(logits.shape      ,   lowercase__)




 @slow
 def 		__snake_case						(      self :  str):







        '''simple docstring'''



        lowerCAmelCase__					     = TFLayoutLMForQuestionAnswering.from_pretrained('microsoft/layoutlm-base-uncased')

        lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__     , lowerCAmelCase__					     = prepare_layoutlm_batch_inputs()

        # forward pass
        lowerCAmelCase__					     = model(input_ids=lowercase__      ,   bbox=lowercase__      ,   attention_mask=lowercase__      ,   token_type_ids=lowercase__)

        # test the shape of the logits
        lowerCAmelCase__					     = tf.convert_to_tensor((2, 25))
        self.assertEqual(outputs.start_logits.shape      ,   lowercase__)
        self.assertEqual(outputs.end_logits.shape      ,   lowercase__)

import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class     a_			:






 '''simple docstring'''






 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= True
 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= 1
 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= False
 UpperCAmelCase_     			= None
 UpperCAmelCase_     			= None




 def 		__snake_case						(      self :  Dict):







        '''simple docstring'''



        return self.__class__(**{k: copy.deepcopy(lowercase__) for k, v in self.__dict__.items()})
