code: def build_positional_encoding(
      block_size: int, configuration: Dict[str, Any]
  ) -> RelPositionalEncoding:
      """Build positional encoding block.
  
      Args:
          block_size: Input/output size.
          configuration: Positional encoding configuration.
  
      Returns:
          : Positional encoding module.
  
      """
      return RelPositionalEncoding(
          block_size,
          configuration.get("pos_enc_dropout_rate", 0.0),
          max_len=configuration.get("pos_enc_max_len", 5000),
      )
  
imports: from typing import Any, Dict, List, Optional, Union
  from espnet2.asr_transducer.activation import get_activation
  from espnet2.asr_transducer.encoder.blocks.branchformer import Branchformer
  from espnet2.asr_transducer.encoder.blocks.conformer import Conformer
  from espnet2.asr_transducer.encoder.blocks.conv1d import Conv1d
  from espnet2.asr_transducer.encoder.blocks.conv_input import ConvInput
  from espnet2.asr_transducer.encoder.blocks.ebranchformer import EBranchformer
  from espnet2.asr_transducer.encoder.modules.attention import RelPositionMultiHeadedAttention
  from espnet2.asr_transducer.encoder.modules.convolution import ConformerConvolution, ConvolutionalSpatialGatingUnit, DepthwiseConvolution
  from espnet2.asr_transducer.encoder.modules.multi_blocks import MultiBlocks
  from espnet2.asr_transducer.encoder.modules.positional_encoding import RelPositionalEncoding
  from espnet2.asr_transducer.normalization import get_normalization
  from espnet.nets.pytorch_backend.transformer.positionwise_feed_forward import PositionwiseFeedForward
label_desc: Use image node_id 2 for calling a global function with example usage: build_positional_encoding(block_size, configuration) and returns: RelPositionalEncoding