class_docstr: Implements the PCT model for multi-label classification.
code: def build_flax_model(self) -> nn.Module:
      return PointCloudTransformerClassifier(
          in_dim=self.config.in_dim,
          feature_dim=self.config.feature_dim,
          kernel_size=self.config.kernel_size,
          num_classes=self.config.dataset_configs.num_classes,
          dropout_rate=self.config.dropout_rate,
          attention_type=self.config.attention_type,
          attention_fn_configs=self.config.attention_fn_configs,
          use_attention_masking=self.config.use_attention_masking,
          use_knn_mask=self.config.attention_masking_configs.use_knn_mask,
          nearest_neighbour_count=self.config.attention_masking_configs.nearest_neighbour_count,
          mask_function=self.config.attention_masking_configs.mask_function,
      )
  
imports: from typing import Any
  import flax.linen
  from flax.linen.initializers import zeros
  import jax
  import jax.numpy
  import ml_collections
  from scenic.model_lib.base_models.multilabel_classification_model import MultiLabelClassificationModel
  from scenic.projects.performer import performer
label_desc: Use image node_id 1 for calling the PointCloudTransformerClassificationModel obj's underlying member method code with example usage: obj.build_flax_model() and returns: PointCloudTransformerClassifier