code: def jasper_encoder_config(num_layers=1) -> Dict:
      return {
          "_target_": "nemo.collections.asr.modules.ConvASREncoder",
          "feat_in": 64,
          "activation": "relu",
          "conv_mask": True,
          "jasper": [
              {
                  "filters": 4,
                  "repeat": 1,
                  "kernel": [1],
                  "stride": [1],
                  "dilation": [1],
                  "dropout": 0.0,
                  "residual": False,
                  "separable": True,
                  "se": True,
                  "se_context_size": -1,
              }
          ]
          * num_layers,
      }
  
file_path: NeMo/tests/collections/asr/test_asr_interctc_models.py
imports: from typing import Dict
  import pytest
  import pytorch_lightning
  import torch
  from omegaconf import DictConfig, ListConfig
  from nemo.collections.asr.models import EncDecCTCModel, EncDecHybridRNNTCTCModel
  from nemo.collections.asr.parts.submodules.ctc_decoding import CTCDecodingConfig
  from nemo.core.classes.mixins import AccessMixin
label_desc: Use image node_id 1 for calling a global function with example usage: jasper_encoder_config(num_layers) and returns: dict