runtime error

Exit code: 1. Reason: e': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 0.0010000000474974513, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}, 'registered_name': None}, 'loss': 'binary_crossentropy', 'metrics': ['accuracy'], 'loss_weights': None, 'weighted_metrics': None, 'run_eagerly': None, 'steps_per_execution': None, 'jit_compile': None}}. Exception encountered: <class 'keras.src.layers.core.embedding.Embedding'> could not be deserialized properly. Please ensure that components that are Python object instances (layers, models, etc.) returned by `get_config()` are explicitly deserialized in the model's `from_config()` method. config={'module': 'keras.layers', 'class_name': 'Embedding', 'config': {'name': 'embedding', 'trainable': True, 'dtype': 'float32', 'batch_input_shape': [None, 100], 'input_dim': 350939, 'output_dim': 64, 'embeddings_initializer': {'module': 'keras.initializers', 'class_name': 'RandomUniform', 'config': {'minval': -0.05, 'maxval': 0.05, 'seed': None}, 'registered_name': None}, 'embeddings_regularizer': None, 'activity_regularizer': None, 'embeddings_constraint': None, 'mask_zero': False, 'input_length': 100}, 'registered_name': None, 'build_config': {'input_shape': [None, 100]}}. Exception encountered: Error when deserializing class 'Embedding' using config={'name': 'embedding', 'trainable': True, 'dtype': 'float32', 'batch_input_shape': [None, 100], 'input_dim': 350939, 'output_dim': 64, 'embeddings_initializer': {'module': 'keras.initializers', 'class_name': 'RandomUniform', 'config': {'minval': -0.05, 'maxval': 0.05, 'seed': None}, 'registered_name': None}, 'embeddings_regularizer': None, 'activity_regularizer': None, 'embeddings_constraint': None, 'mask_zero': False, 'input_length': 100}. Exception encountered: Unrecognized keyword arguments passed to Embedding: {'batch_input_shape': [None, 100]}

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