class_docstr: Base predictor type for Gluon-based models.
  
  Parameters
  ----------
  input_names
      Input tensor names for the graph
  prediction_net
      Network that will be called for prediction
  batch_size
      Number of time series to predict in a single batch
  prediction_length
      Number of time steps to predict
  input_transform
      Input transformation pipeline
  output_transform
      Output transformation
  ctx
      MXNet context to use for computation
  forecast_generator
      Class to generate forecasts from network outputs
code: def serialize(self, path: Path) -> None:
      # call Predictor.serialize() in order to serialize the class name
      super().serialize(path)
  
      # serialize every GluonPredictor-specific parameters
      # serialize the prediction network
      self.serialize_prediction_net(path)
  
      # serialize transformation chain
      with (path / "input_transform.json").open("w") as fp:
          print(dump_json(self.input_transform), file=fp)
  
      # FIXME: also needs to serialize the output_transform
  
      # serialize all remaining constructor parameters
      with (path / "parameters.json").open("w") as fp:
          parameters = dict(
              batch_size=self.batch_size,
              prediction_length=self.prediction_length,
              lead_time=self.lead_time,
              ctx=self.ctx,
              dtype=self.dtype,
              forecast_generator=self.forecast_generator,
              input_names=self.input_names,
          )
          print(dump_json(parameters), file=fp)
  
imports: import logging
  from functools import partial
  from pathlib import Path
  from typing import Callable, Iterator, List, Optional, Type
  import mxnet
  import numpy
  from gluonts.core.serde import dump_json, load_json
  from gluonts.dataset.common import DataEntry, Dataset
  from gluonts.dataset.loader import DataBatch, InferenceDataLoader
  from gluonts.model.forecast import Forecast
  from gluonts.model.forecast_generator import ForecastGenerator, SampleForecastGenerator, to_numpy
  from gluonts.model.predictor import OutputTransform, Predictor
  from gluonts.mx.batchify import batchify
  from gluonts.mx.component import equals
  from gluonts.mx.context import get_mxnet_context
  from gluonts.mx.util import export_repr_block, export_symb_block, get_hybrid_forward_input_names, hybrid_block_to_symbol_block, import_repr_block, import_symb_block
  from gluonts.transform import Transformation
label_desc: Use image node_id 7 for calling the GluonPredictor obj's underlying member method code with example usage: obj.serialize(path) without return types