class_docstr: Repacks stream for Reshape layer
class_docstr_tok: ["Repacks","stream","for","Reshape","layer"]
code: def transform(self, model, node):
      if model.config.get_config_value("IOType") != "io_stream":
          return False
  
      attrs = {"target_shape": node.get_attr("target_shape")}
  
      # Insert new Repack node instead of Reshape
      repack_layer = model.make_node(
          Repack, "repack_" + node.name, attrs, node.inputs.copy()
      )
      # As result_t attribute is not honored by type conversion, set it manually here
      repack_layer.attributes[repack_layer.name].type = node.attributes[
          node.name
      ].type
      model.replace_node(node, repack_layer)
  
      return True
  
file_path: hls4ml/hls4ml/backends/fpga/passes/repack_stream.py
imports: import numpy
  from hls4ml.backends.template import FunctionCallTemplate
  from hls4ml.model.layers import Layer, Reshape, register_layer
  from hls4ml.model.optimizer import OptimizerPass
label_desc: Use image node_id 2 for calling the ReshapeStream obj's underlying member method code with example usage: obj.transform(model, node) and returns: True, False