Need Transpose Before Flatten Layer 1D model Training

I applied this transform :

model = ModelWrapper(build_dir + "/end2end_cnv_w1a1_pre_post.onnx")
model = model.transform(MoveScalarLinearPastInvariants())
model = model.transform(Streamline())
model = model.transform(LowerConvsToMatMul())
model = model.transform(MakeMaxPoolNHWC())
model = model.transform(absorb.AbsorbTransposeIntoMultiThreshold())
model = model.transform(absorb.AbsorbConsecutiveTransposes())
model = model.transform(ConvertBipolarMatMulToXnorPopcount())
model = model.transform(Streamline())
model = model.transform(absorb.AbsorbScalarMulAddIntoTopK())
model = model.transform(InferDataLayouts())
model = model.transform(RemoveUnusedTensors())
model.save(build_dir + "/end2end_cnv_w1a1_streamlined.onnx")
And my onnx output this :

Then i applied hls conversion :

mem_mode = "decoupled"
model = ModelWrapper(build_dir + "/end2end_cnv_w1a1_streamlined.onnx")
model = model.transform(to_hls.InferBinaryMatrixVectorActivation(mem_mode))
model = model.transform(to_hls.InferQuantizedMatrixVectorActivation(mem_mode))
model = model.transform(to_hls.InferLabelSelectLayer())
model = model.transform(to_hls.InferThresholdingLayer())
model = model.transform(to_hls.InferConvInpGen())
model = model.transform(MakeMaxPoolNHWC())
model = model.transform(absorb.AbsorbConsecutiveTransposes())
model = model.transform(to_hls.InferStreamingMaxPool())
model = model.transform(RemoveCNVtoFCFlatten())
model = model.transform(absorb.AbsorbConsecutiveTransposes())
model = model.transform(InferDataLayouts())
parent_model = model.transform(CreateDataflowPartition())
parent_model.save(build_dir + "/end2end_cnv_w1a1_dataflow_parent.onnx")
sdp_node = parent_model.get_nodes_by_op_type("StreamingDataflowPartition")[0]
sdp_node = getCustomOp(sdp_node)
dataflow_model_filename = sdp_node.get_nodeattr("model")
dataflow_model = ModelWrapper(dataflow_model_filename)
dataflow_model.save(build_dir + "/end2end_cnv_w1a1_dataflow_model.onnx")

And my onnx output this :

I need transpose after maxpool_streaming layer for flatten , how can i do that ?

Reproduce the transformation pipeline beginning with ModelWrapper and the listed Streamline, InferDataLayouts, RemoveCNVtoFCFlatten, and CreateDataflowPartition transforms. Inspect the model graphs around InferStreamingMaxPool and flatten handling; done means the dataflow model contains the required transpose before flatten without breaking partition creation.