[TensorRT] Fix DDS output bug during engine update

[toothache]

Description

Fix a bug in the TRT Execution Provider where the DDS output tensor was not bound after an engine update.

Motivation and Context

The dds_output_allocator_map is not cleared on engine update, so that it will mis-recognized as a known DDS and will not bind the output allocation.

Script to reproduce the issue:

# create an onnx model with:
# inputs: data -> NonZeros(data) -> GatherND -> output
# then run the model with onnxruntime

def create_model():
    import onnx
    from onnx import helper, TensorProto

    input = helper.make_tensor_value_info("data", TensorProto.FLOAT, ["d1", "d2"])
    output = helper.make_tensor_value_info("output", TensorProto.FLOAT, ["nzr"])

    nonzeros_node = helper.make_node("NonZero", ["data"], ["nonzeros"], "nonzeros_node")
    transpose_node = helper.make_node(
        "Transpose", ["nonzeros"], ["nonzeros_t"], "transpose_node"
    )
    gathernd_node = helper.make_node(
        "GatherND", ["data", "nonzeros_t"], ["output"], "gathernd_node"
    )

    value_info = [
        helper.make_tensor_value_info("nonzeros", TensorProto.INT64, [2, "nzr"]),
        helper.make_tensor_value_info("nonzeros_t", TensorProto.INT64, ["nzr", 2]),
    ]

    graph = helper.make_graph(
        [nonzeros_node, transpose_node, gathernd_node],
        "test_graph",
        [input],
        [output],
        value_info=value_info,
    )

    model = helper.make_model(graph)
    onnx.save(model, "model_dds.onnx")


def run_model():
    import onnxruntime as ort
    import numpy as np

    sess = ort.InferenceSession("model_dds.onnx", providers=["TensorrtExecutionProvider", "CUDAExecutionProvider", "CPUExecutionProvider"])

    print("Running with data shape (3,4)")
    data = np.random.randn(3, 4).astype(np.float32)
    sess.run(None, {"data": data})

    print("Running with data shape (5,6)")
    data = np.random.randn(5, 6).astype(np.float32)
    sess.run(None, {"data": data})


create_model()
run_model()

Before the change:

IExecutionContext::enqueueV3: Error Code 3: API Usage Error (Parameter check failed, condition: mContext.profileObliviousBindings.at(profileObliviousIndex) || getPtrOrNull(mOutputAllocators, profileObliviousIndex). Neither address or allocator is set for output tensor scores. Call setOutputTensorAddress, setTensorAddress or setOutputAllocator before enqueue/execute.) ... Status Message: TensorRT EP execution context enqueue failed.

[tianleiwu]

/azp run Linux QNN CI Pipeline,Win_TRT_Minimal_CUDA_Test_CI,Windows ARM64 QNN CI Pipeline,Windows GPU Doc Gen CI Pipeline

[azure-pipelines]

Azure Pipelines successfully started running 4 pipeline(s).

[Copilot]

Pull Request Overview

This PR fixes a bug in the TensorRT Execution Provider where DDS (Direct Data Structure) output tensors were not properly bound after an engine update, causing execution failures during dynamic shape inference scenarios.

• Clears the dds_output_allocator_map when the TensorRT engine is recreated to prevent stale mappings
• Ensures proper output tensor binding during engine updates with different input shapes

---

_{Tip: Customize your code reviews with copilot-instructions.md. Create the file or learn how to get started.}

[chilo-ms]

Thanks for fixing this issue.
Could you help also add a unit test that uses your repro script?

[toothache]

Thanks for fixing this issue. Could you help also add a unit test that uses your repro script?

Where should I put the repo script? I didn't find a dedicate python test script for tensorrt EP.

[toothache]

Thanks for fixing this issue. Could you help also add a unit test that uses your repro script?

Where should I put the repo script? I didn't find a dedicate python test script for tensorrt EP.

Added C++ test case for TensorrtExecutionProviderTest.DDSOutputTest

[tianleiwu]

/azp run Linux QNN CI Pipeline,Win_TRT_Minimal_CUDA_Test_CI,Windows ARM64 QNN CI Pipeline,Windows GPU Doc Gen CI Pipeline

[azure-pipelines]

Azure Pipelines successfully started running 4 pipeline(s).

[apsonawane]

Cherry-picked for 1.23.2. Removing the release tag and adding cherry-pick tag