





from __future__ import annotations

import unittest

from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
    import numpy
    import tensorflow as tf

    from transformers.models.esm.modeling_tf_esm import (
        TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST,
        TFEsmForMaskedLM,
        TFEsmForSequenceClassification,
        TFEsmForTokenClassification,
        TFEsmModel,
    )


class     lowercase__  :






  def __init__(					self      :					Union[str, Any]		,						_lowercase      :					Optional[Any]		,						):




         """simple docstring"""







         UpperCAmelCase__										=     parent
         UpperCAmelCase__										=     13
         UpperCAmelCase__										=     7
         UpperCAmelCase__										=     True
         UpperCAmelCase__										=     True
         UpperCAmelCase__										=     True
         UpperCAmelCase__										=     99
         UpperCAmelCase__										=     32
         UpperCAmelCase__										=     2
         UpperCAmelCase__										=     4
         UpperCAmelCase__										=     37
         UpperCAmelCase__										=     'gelu'
         UpperCAmelCase__										=     0.1
         UpperCAmelCase__										=     0.1
         UpperCAmelCase__										=     5_12
         UpperCAmelCase__										=     16
         UpperCAmelCase__										=     2
         UpperCAmelCase__										=     0.0_2
         UpperCAmelCase__										=     3
         UpperCAmelCase__										=     4
         UpperCAmelCase__										=     None






  def 			_UpperCAmelCase  (					self      :					Any ):




         """simple docstring"""







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

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

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

         UpperCAmelCase__										=     EsmConfig(
             vocab_size=self.vocab_size		,						hidden_size=self.hidden_size		,						num_hidden_layers=self.num_hidden_layers		,						pad_token_id=1		,						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, input_mask, sequence_labels, token_labels, choice_labels






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         (
             UpperCAmelCase__      
         )										=     self.prepare_config_and_inputs()

         UpperCAmelCase__										=     True
         UpperCAmelCase__										=     floats_tensor([self.batch_size, self.seq_length, self.hidden_size] )
         UpperCAmelCase__										=     ids_tensor([self.batch_size, self.seq_length]		,						vocab_size=2 )

         return (
             config,
             input_ids,
             input_mask,
             sequence_labels,
             token_labels,
             choice_labels,
             encoder_hidden_states,
             encoder_attention_mask,
         )






  def 			_UpperCAmelCase  (					self      :					str		,						_lowercase      :					int		,						_lowercase      :					Union[str, Any]		,						_lowercase      :					List[Any]		,						_lowercase      :					Optional[Any]		,						_lowercase      :					List[str]		,						_lowercase      :					Any ):




         """simple docstring"""







         UpperCAmelCase__										=     TFEsmModel(config=_lowercase )
         UpperCAmelCase__										=     {'input_ids': input_ids, 'attention_mask': input_mask}
         UpperCAmelCase__										=     model(_lowercase )

         UpperCAmelCase__										=     [input_ids, input_mask]
         UpperCAmelCase__										=     model(_lowercase )

         UpperCAmelCase__										=     model(_lowercase )

         self.parent.assertEqual(result.last_hidden_state.shape		,						(self.batch_size, self.seq_length, self.hidden_size) )






  def 			_UpperCAmelCase  (					self      :					Tuple		,						_lowercase      :					Dict		,						_lowercase      :					int		,						_lowercase      :					Optional[Any]		,						_lowercase      :					List[Any]		,						_lowercase      :					Dict		,						_lowercase      :					Optional[Any]		,						_lowercase      :					List[Any]		,						_lowercase      :					int		,						):




         """simple docstring"""







         UpperCAmelCase__										=     True

         UpperCAmelCase__										=     TFEsmModel(config=_lowercase )
         UpperCAmelCase__										=     {
             'input_ids': input_ids,
             'attention_mask': input_mask,
             'encoder_hidden_states': encoder_hidden_states,
             'encoder_attention_mask': encoder_attention_mask,
         }
         UpperCAmelCase__										=     model(_lowercase )

         UpperCAmelCase__										=     [input_ids, input_mask]
         UpperCAmelCase__										=     model(_lowercase		,						encoder_hidden_states=_lowercase )

         # Also check the case where encoder outputs are not passed
         UpperCAmelCase__										=     model(_lowercase		,						attention_mask=_lowercase )

         self.parent.assertEqual(result.last_hidden_state.shape		,						(self.batch_size, self.seq_length, self.hidden_size) )






  def 			_UpperCAmelCase  (					self      :					str		,						_lowercase      :					Dict		,						_lowercase      :					Tuple		,						_lowercase      :					Any		,						_lowercase      :					Tuple		,						_lowercase      :					Optional[Any]		,						_lowercase      :					Optional[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     TFEsmForMaskedLM(config=_lowercase )
         UpperCAmelCase__										=     model([input_ids, input_mask] )
         self.parent.assertEqual(result.logits.shape		,						(self.batch_size, self.seq_length, self.vocab_size) )






  def 			_UpperCAmelCase  (					self      :					List[Any]		,						_lowercase      :					str		,						_lowercase      :					Optional[Any]		,						_lowercase      :					Tuple		,						_lowercase      :					Dict		,						_lowercase      :					List[str]		,						_lowercase      :					Union[str, Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     self.num_labels
         UpperCAmelCase__										=     TFEsmForTokenClassification(config=_lowercase )
         UpperCAmelCase__										=     {'input_ids': input_ids, 'attention_mask': input_mask}
         UpperCAmelCase__										=     model(_lowercase )
         self.parent.assertEqual(result.logits.shape		,						(self.batch_size, self.seq_length, self.num_labels) )






  def 			_UpperCAmelCase  (					self      :					List[str] ):




         """simple docstring"""







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




@require_tf
class     lowercase__  (					UpperCAmelCase_					,							UpperCAmelCase_					,							unittest.TestCase		):
  A__=  (
      (
          TFEsmModel,
          TFEsmForMaskedLM,
          TFEsmForSequenceClassification,
          TFEsmForTokenClassification,
      )
      if is_tf_available()
      else ()
  )
  A__=  (
      {
          'feature-extraction': TFEsmModel,
          'fill-mask': TFEsmForMaskedLM,
          'text-classification': TFEsmForSequenceClassification,
          'token-classification': TFEsmForTokenClassification,
          'zero-shot': TFEsmForSequenceClassification,
      }
      if is_tf_available()
      else {}
  )
  A__=  False
  A__=  False






  def 			_UpperCAmelCase  (					self      :					int ):




         """simple docstring"""







         UpperCAmelCase__										=     TFEsmModelTester(self )
         UpperCAmelCase__										=     ConfigTester(self		,						config_class=_lowercase		,						hidden_size=37 )






  def 			_UpperCAmelCase  (					self      :					Tuple ):




         """simple docstring"""







         self.config_tester.run_common_tests()






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




         """simple docstring"""







         UpperCAmelCase__										=     self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_model(*_lowercase )






  def 			_UpperCAmelCase  (					self      :					List[Any] ):




         """simple docstring"""







         UpperCAmelCase__										=     self.model_tester.prepare_config_and_inputs_for_decoder()
         self.model_tester.create_and_check_model_as_decoder(*_lowercase )






  def 			_UpperCAmelCase  (					self      :					Tuple ):




         """simple docstring"""







         UpperCAmelCase__										=     self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_masked_lm(*_lowercase )






  def 			_UpperCAmelCase  (					self      :					Any ):




         """simple docstring"""







         UpperCAmelCase__										=     self.model_tester.prepare_config_and_inputs()
         self.model_tester.create_and_check_for_token_classification(*_lowercase )






  @slow
  def 			_UpperCAmelCase  (					self      :					Optional[Any] ):




         """simple docstring"""







         for model_name in TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
                UpperCAmelCase__										=     TFEsmModel.from_pretrained(_lowercase )
                self.assertIsNotNone(_lowercase )






  @unittest.skip("Protein models do not support embedding resizing." )
  def 			_UpperCAmelCase  (					self      :					Optional[int] ):




         """simple docstring"""







         pass






  @unittest.skip("Protein models do not support embedding resizing." )
  def 			_UpperCAmelCase  (					self      :					Any ):




         """simple docstring"""







         pass






  def 			_UpperCAmelCase  (					self      :					Dict ):




         """simple docstring"""







         UpperCAmelCase__										=     self.model_tester.prepare_config_and_inputs_for_common()

         for model_class in self.all_model_classes:
                UpperCAmelCase__										=     model_class(_lowercase )
                assert isinstance(model.get_input_embeddings()		,						tf.keras.layers.Layer )
                if model_class is TFEsmForMaskedLM:
                       # Output embedding test differs from the main test because they're a matrix, not a layer
                       UpperCAmelCase__										=     model.get_bias()
                       assert isinstance(_lowercase		,						_lowercase )
                       for k, v in name.items():
                              assert isinstance(_lowercase		,						tf.Variable )
                else:
                       UpperCAmelCase__										=     model.get_output_embeddings()
                       assert x is None
                       UpperCAmelCase__										=     model.get_bias()
                       assert name is None




@require_tf
class     lowercase__  (					unittest.TestCase		):






  @slow
  def 			_UpperCAmelCase  (					self      :					int ):




         """simple docstring"""







         UpperCAmelCase__										=     TFEsmForMaskedLM.from_pretrained("facebook/esm2_t6_8M_UR50D" )

         UpperCAmelCase__										=     tf.constant([[0, 1, 2, 3, 4, 5]] )
         UpperCAmelCase__										=     model(_lowercase )[0]
         UpperCAmelCase__										=     [1, 6, 33]
         self.assertEqual(list(output.numpy().shape )		,						_lowercase )
         # compare the actual values for a slice.
         UpperCAmelCase__										=     tf.constant(
             [
                 [
                     [8.9_2_1_5_1_8, -1_0.5_8_9_8_1_4, -6.4_6_7_1_3_0_7],
                     [-6.3_9_6_7_1_5_6, -1_3.9_1_1_3_7_7, -1.1_2_1_1_9_1_5],
                     [-7.7_8_1_2_4_7, -1_3.9_5_1_5_5_7, -3.7_4_0_5_9_2],
                 ]
             ] )
         self.assertTrue(numpy.allclose(output[:, :3, :3].numpy()		,						expected_slice.numpy()		,						atol=1E-2 ) )






  @slow
  def 			_UpperCAmelCase  (					self      :					Any ):




         """simple docstring"""







         UpperCAmelCase__										=     TFEsmModel.from_pretrained("facebook/esm2_t6_8M_UR50D" )

         UpperCAmelCase__										=     tf.constant([[0, 6, 4, 13, 5, 4, 16, 12, 11, 7, 2]] )
         UpperCAmelCase__										=     model(_lowercase )[0]
         # compare the actual values for a slice.
         UpperCAmelCase__										=     tf.constant(
             [
                 [
                     [0.1_4_4_4_3_0_9_2, 0.5_4_1_2_5_3_2_7, 0.3_2_4_7_7_3_9],
                     [0.3_0_3_4_0_4_8_4, 0.0_0_5_2_6_6_7_6, 0.3_1_0_7_7_7_2_2],
                     [0.3_2_2_7_8_0_4_3, -0.2_4_9_8_7_0_9_6, 0.3_4_1_4_6_2_8],
                 ]
             ] )
         self.assertTrue(numpy.allclose(output[:, :3, :3].numpy()		,						expected_slice.numpy()		,						atol=1E-4 ) )









class     lowercase__  :






  def __init__(					self      :					List[str]		,						_lowercase      :					list ):




         """simple docstring"""







         UpperCAmelCase__										=     set_counts
         UpperCAmelCase__										=     max(_lowercase )
         UpperCAmelCase__										=     len(_lowercase )
         UpperCAmelCase__										=     [1] * num_sets
         UpperCAmelCase__										=     list(range(_lowercase ) )






  def 			_UpperCAmelCase  (					self      :					Dict		,						_lowercase      :					int		,						_lowercase      :					int ):




         """simple docstring"""







         UpperCAmelCase__										=     self.get_parent(_lowercase )
         UpperCAmelCase__										=     self.get_parent(_lowercase )

         if src_parent == dst_parent:
                return False

         if self.ranks[dst_parent] >= self.ranks[src_parent]:
                self.set_counts[dst_parent] += self.set_counts[src_parent]
                UpperCAmelCase__										=     0
                UpperCAmelCase__										=     dst_parent
                if self.ranks[dst_parent] == self.ranks[src_parent]:
                       self.ranks[dst_parent] += 1
                UpperCAmelCase__										=     self.set_counts[dst_parent]
         else:
                self.set_counts[src_parent] += self.set_counts[dst_parent]
                UpperCAmelCase__										=     0
                UpperCAmelCase__										=     src_parent
                UpperCAmelCase__										=     self.set_counts[src_parent]

         UpperCAmelCase__										=     max(self.max_set		,						_lowercase )
         return True






  def 			_UpperCAmelCase  (					self      :					Optional[Any]		,						_lowercase      :					int ):




         """simple docstring"""







         if self.parents[disj_set] == disj_set:
                return disj_set
         UpperCAmelCase__										=     self.get_parent(self.parents[disj_set] )
         return self.parents[disj_set]





