chore: import upstream snapshot with attribution

plugin/multilevelCropAndResizePlugin/CMakeLists.txt

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+#
+# SPDX-FileCopyrightText: Copyright (c) 1993-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+add_plugin_source(
+    multilevelCropAndResizePlugin.cpp
+    multilevelCropAndResizePlugin.h
+)
+

plugin/multilevelCropAndResizePlugin/MultilevelCropAndResize_PluginConfig.yaml

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+#
+# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+---
+name: MultilevelCropAndResize_TRT
+interface: "IPluginV2Ext"
+versions:
+  "1":
+    attributes:
+      - pooled_size
+      - image_size
+    attribute_types:
+      pooled_size: int32
+      image_size: int32
+    attribute_length:
+      pooled_size: 1
+      image_size: 3
+    attribute_options:
+      pooled_size:
+        min: "0"
+        max: "=pinf"
+      image_size:
+        min: "0, 0, 0"
+        max: "=pinf, =pinf, =pinf"
+    attributes_required:
+      - pooled_size
+...

plugin/multilevelCropAndResizePlugin/README.md

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+# MultilevelCropAndResize [DEPRECATED]
+
+**This plugin is deprecated since TensorRT 10.12 and will be removed in a future release. Note alternatives are planned to be provided.**
+
+**Table Of Contents**
+- [Description](#description)
+    * [Structure](#structure)
+- [Parameters](#parameters)
+- [Additional resources](#additional-resources)
+- [License](#license)
+- [Changelog](#changelog)
+- [Known issues](#known-issues)
+
+## Description
+
+The `MultilevelCropAndResize` plugin performs the ROIAlign operation on the output feature maps from FPN (Feature Pyramid Network). It is used for MaskRCNN inference in Transfer Learning Toolkit. 
+
+
+### Structure
+
+This plugin supports the NCHW format. It takes 6 inputs in the following order: `roi`, and 5 `feature_maps` from FPN (Note: 5 `feature_maps` are required for this plugin and will not function properly with a lesser number of `feature_maps`).
+
+`roi` is the ROI candidates from the `MultilevelProposeROI` plugin. Its shape is `[N, rois, 4]` where `N` is the batch_size, `rois` is the number of ROI candidates and `4` is the number of coordinates.
+
+`feature_maps` are the output of FPN. In TLT MaskRCNN, the model we provide contains 5 feature maps from FPN's different stages.
+
+This plugin generates one output tensor of shape `[N, rois, C, pooled_size, pooled_size]` where `C` is the channel of mutiple feature maps from FPN and `pooled_size` is the height(and width) of the feature area after ROIAlign.
+
+## Parameters
+
+This plugin has the plugin creator class `MultilevelCropAndResizePluginCreator` and the plugin class `MultilevelCropAndResize`.
+  
+The following parameters were used to create `MultilevelCropAndResize` instance:
+
+| Type             | Parameter                       | Description
+|------------------|---------------------------------|--------------------------------------------------------
+|`int`             |`pooled_size`                    | The spatial size of a feature area after ROIAlgin will be `[pooled_size, pooled_size]`  
+|`int[3]`          |`image_size`                     | The size of the input image in CHW. Defaults to [3, 832, 1344]
+
+## Additional resources
+
+
+## License
+
+For terms and conditions for use, reproduction, and distribution, see the [TensorRT Software License Agreement](https://docs.nvidia.com/deeplearning/sdk/tensorrt-sla/index.html) 
+documentation.
+
+
+## Changelog
+
+May 2025: Add deprecation note.
+
+March 2022: This is the second release of this `README.md` file.
+
+June 2020: First release of this `README.md` file.
+
+
+## Known issues
+
+There are no known issues in this plugin.

plugin/multilevelCropAndResizePlugin/multilevelCropAndResizePlugin.cpp

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+/*
+ * SPDX-FileCopyrightText: Copyright (c) 1993-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "multilevelCropAndResizePlugin.h"
+#include "common/plugin.h"
+#include <algorithm>
+#include <cuda_runtime_api.h>
+#include <string_view>
+
+#include <fstream>
+
+using namespace nvinfer1;
+using namespace plugin;
+using nvinfer1::plugin::MultilevelCropAndResize;
+using nvinfer1::plugin::MultilevelCropAndResizePluginCreator;
+
+namespace
+{
+char const* const kMULTILEVELCROPANDRESIZE_PLUGIN_VERSION{"1"};
+char const* const kMULTILEVELCROPANDRESIZE_PLUGIN_NAME{"MultilevelCropAndResize_TRT"};
+} // namespace
+
+MultilevelCropAndResizePluginCreator::MultilevelCropAndResizePluginCreator() noexcept
+{
+    mPluginAttributes.clear();
+    mPluginAttributes.emplace_back(PluginField("pooled_size", nullptr, PluginFieldType::kINT32, 1));
+    mPluginAttributes.emplace_back(PluginField("image_size", nullptr, PluginFieldType::kINT32, 3));
+
+    mFC.nbFields = mPluginAttributes.size();
+    mFC.fields = mPluginAttributes.data();
+}
+
+char const* MultilevelCropAndResizePluginCreator::getPluginName() const noexcept
+{
+    return kMULTILEVELCROPANDRESIZE_PLUGIN_NAME;
+}
+
+char const* MultilevelCropAndResizePluginCreator::getPluginVersion() const noexcept
+{
+    return kMULTILEVELCROPANDRESIZE_PLUGIN_VERSION;
+}
+
+PluginFieldCollection const* MultilevelCropAndResizePluginCreator::getFieldNames() noexcept
+{
+    return &mFC;
+}
+
+IPluginV2Ext* MultilevelCropAndResizePluginCreator::createPlugin(
+    char const* name, PluginFieldCollection const* fc) noexcept
+{
+    try
+    {
+        using namespace std::string_view_literals;
+        plugin::validateRequiredAttributesExist({"pooled_size"}, fc);
+
+        auto imageSize = TLTMaskRCNNConfig::IMAGE_SHAPE;
+        PluginField const* fields = fc->fields;
+        for (int32_t i = 0; i < fc->nbFields; ++i)
+        {
+            std::string_view const attrName = fields[i].name;
+            if (attrName == "pooled_size"sv)
+            {
+                PLUGIN_VALIDATE(fields[i].type == PluginFieldType::kINT32);
+                mPooledSize = *(static_cast<int32_t const*>(fields[i].data));
+            }
+            if (attrName == "image_size"sv)
+            {
+                PLUGIN_VALIDATE(fields[i].type == PluginFieldType::kINT32);
+                auto const dims = static_cast<int32_t const*>(fields[i].data);
+                std::copy_n(dims, 3, imageSize.d);
+            }
+        }
+        return new MultilevelCropAndResize(mPooledSize, imageSize);
+    }
+    catch (std::exception const& e)
+    {
+        caughtError(e);
+    }
+    return nullptr;
+}
+
+IPluginV2Ext* MultilevelCropAndResizePluginCreator::deserializePlugin(
+    char const* name, void const* data, size_t length) noexcept
+{
+    try
+    {
+        return new MultilevelCropAndResize(data, length);
+    }
+    catch (std::exception const& e)
+    {
+        caughtError(e);
+    }
+    return nullptr;
+}
+
+MultilevelCropAndResize::MultilevelCropAndResize(int32_t pooled_size, nvinfer1::Dims const& imageSize)
+    : mPooledSize({pooled_size, pooled_size})
+{
+
+    PLUGIN_VALIDATE(pooled_size > 0);
+    PLUGIN_VALIDATE(imageSize.nbDims == 3);
+    PLUGIN_VALIDATE(imageSize.d[0] > 0 && imageSize.d[1] > 0 && imageSize.d[2] > 0);
+    // shape
+    mInputHeight = imageSize.d[1];
+    mInputWidth = imageSize.d[2];
+    // Threshold to P3: Smaller -> P2
+    mThresh = (224 * 224) / (4.0F);
+}
+
+int32_t MultilevelCropAndResize::getNbOutputs() const noexcept
+{
+    return 1;
+}
+
+int32_t MultilevelCropAndResize::initialize() noexcept
+{
+    return 0;
+}
+
+void MultilevelCropAndResize::terminate() noexcept {}
+
+void MultilevelCropAndResize::destroy() noexcept
+{
+    delete this;
+}
+
+size_t MultilevelCropAndResize::getWorkspaceSize(int32_t) const noexcept
+{
+    return 0;
+}
+
+bool MultilevelCropAndResize::supportsFormat(DataType type, PluginFormat format) const noexcept
+{
+    return ((type == DataType::kFLOAT || type == DataType::kHALF) && format == PluginFormat::kLINEAR);
+}
+
+char const* MultilevelCropAndResize::getPluginType() const noexcept
+{
+    return "MultilevelCropAndResize_TRT";
+}
+
+char const* MultilevelCropAndResize::getPluginVersion() const noexcept
+{
+    return "1";
+}
+
+IPluginV2Ext* MultilevelCropAndResize::clone() const noexcept
+{
+    try
+    {
+        return new MultilevelCropAndResize(*this);
+    }
+    catch (std::exception const& e)
+    {
+        caughtError(e);
+    }
+    return nullptr;
+}
+
+void MultilevelCropAndResize::setPluginNamespace(char const* libNamespace) noexcept
+{
+    mNameSpace = libNamespace;
+}
+
+char const* MultilevelCropAndResize::getPluginNamespace() const noexcept
+{
+    return mNameSpace.c_str();
+}
+
+void MultilevelCropAndResize::check_valid_inputs(nvinfer1::Dims const* inputs, int32_t nbInputDims) noexcept
+{
+    // to be compatible with tensorflow node's input:
+    // roi: [N, anchors, 4],
+    // feature_map list(5 maps): p2, p3, p4, p5, p6
+    PLUGIN_ASSERT(nbInputDims == 1 + mFeatureMapCount);
+
+    nvinfer1::Dims rois = inputs[0];
+    PLUGIN_ASSERT(rois.nbDims == 2);
+    PLUGIN_ASSERT(rois.d[1] == 4);
+
+    for (int32_t i = 1; i < nbInputDims; ++i)
+    {
+        nvinfer1::Dims dims = inputs[i];
+
+        // CHW with the same #C
+        PLUGIN_ASSERT(dims.nbDims == 3 && dims.d[0] == inputs[1].d[0]);
+    }
+}
+
+Dims MultilevelCropAndResize::getOutputDimensions(int32_t index, Dims const* inputs, int32_t nbInputDims) noexcept
+{
+
+    check_valid_inputs(inputs, nbInputDims);
+    PLUGIN_ASSERT(index == 0);
+
+    nvinfer1::Dims result{};
+    result.nbDims = 4;
+
+    // mROICount
+    result.d[0] = inputs[0].d[0];
+    // mFeatureLength
+    result.d[1] = inputs[1].d[0];
+    // height
+    result.d[2] = mPooledSize.y;
+    // width
+    result.d[3] = mPooledSize.x;
+
+    return result;
+}
+
+int32_t MultilevelCropAndResize::enqueue(
+    int32_t batch_size, void const* const* inputs, void* const* outputs, void* workspace, cudaStream_t stream) noexcept
+{
+
+    void* pooled = outputs[0];
+
+    cudaError_t status = roiAlignHalfCenter(stream, batch_size, mFeatureLength, mROICount, mThresh,
+
+        mInputHeight, mInputWidth, inputs[0], &inputs[1], mFeatureSpatialSize,
+
+        pooled, mPooledSize, mPrecision);
+
+    PLUGIN_ASSERT(status == cudaSuccess);
+    return 0;
+}
+
+size_t MultilevelCropAndResize::getSerializationSize() const noexcept
+{
+    return sizeof(int32_t) * 2 + sizeof(int32_t) * 4 + sizeof(float) + sizeof(int32_t) * 2 * mFeatureMapCount
+        + sizeof(DataType);
+}
+
+void MultilevelCropAndResize::serialize(void* buffer) const noexcept
+{
+    char *d = reinterpret_cast<char*>(buffer), *a = d;
+    write(d, mPooledSize.y);
+    write(d, mPooledSize.x);
+    write(d, mFeatureLength);
+    write(d, mROICount);
+    write(d, mInputHeight);
+    write(d, mInputWidth);
+    write(d, mThresh);
+    for (int32_t i = 0; i < mFeatureMapCount; i++)
+    {
+        write(d, mFeatureSpatialSize[i].y);
+        write(d, mFeatureSpatialSize[i].x);
+    }
+    write(d, mPrecision);
+    PLUGIN_ASSERT(d == a + getSerializationSize());
+}
+MultilevelCropAndResize::MultilevelCropAndResize(void const* data, size_t length)
+{
+    deserialize(static_cast<int8_t const*>(data), length);
+}
+
+void MultilevelCropAndResize::deserialize(int8_t const* data, size_t length)
+{
+    auto const* d{data};
+    mPooledSize = {read<int32_t>(d), read<int32_t>(d)};
+    mFeatureLength = read<int32_t>(d);
+    mROICount = read<int32_t>(d);
+    mInputHeight = read<int32_t>(d);
+    mInputWidth = read<int32_t>(d);
+    mThresh = read<float>(d);
+    for (int32_t i = 0; i < mFeatureMapCount; i++)
+    {
+        mFeatureSpatialSize[i].y = read<int32_t>(d);
+        mFeatureSpatialSize[i].x = read<int32_t>(d);
+    }
+    mPrecision = read<DataType>(d);
+    PLUGIN_VALIDATE(d == static_cast<int8_t const*>(data) + length);
+}
+
+// Return the DataType of the plugin output at the requested index
+DataType MultilevelCropAndResize::getOutputDataType(
+    int32_t index, nvinfer1::DataType const* inputTypes, int32_t nbInputs) const noexcept
+{
+    // Only DataType::kFLOAT is acceptable by the plugin layer
+    // return DataType::kFLOAT;
+    // Align output types with the input feature map data types
+    if ((inputTypes[1] == DataType::kFLOAT) || (inputTypes[1] == DataType::kHALF))
+        return inputTypes[1];
+
+    return DataType::kFLOAT;
+}
+
+// Configure the layer with input and output data types.
+void MultilevelCropAndResize::configurePlugin(Dims const* inputDims, int32_t nbInputs, Dims const* outputDims,
+    int32_t nbOutputs, DataType const* inputTypes, DataType const* outputTypes, bool const* inputIsBroadcast,
+    bool const* outputIsBroadcast, PluginFormat floatFormat, int32_t maxBatchSize) noexcept
+{
+    PLUGIN_ASSERT(supportsFormat(inputTypes[0], floatFormat));
+    check_valid_inputs(inputDims, nbInputs);
+
+    PLUGIN_ASSERT(nbOutputs == 1);
+    PLUGIN_ASSERT(nbInputs == 1 + mFeatureMapCount);
+
+    try
+    {
+        mROICount = dimToInt32(inputDims[0].d[0]);
+        mFeatureLength = dimToInt32(inputDims[1].d[0]);
+
+        for (size_t layer = 0; layer < mFeatureMapCount; ++layer)
+        {
+            mFeatureSpatialSize[layer] = {dimToInt32(inputDims[layer + 1].d[1]), dimToInt32(inputDims[layer + 1].d[2])};
+        }
+    }
+    catch (std::exception const& e)
+    {
+        caughtError(e);
+    }
+
+    mPrecision = inputTypes[1];
+}
+
+// Attach the plugin object to an execution context and grant the plugin the access to some context resource.
+void MultilevelCropAndResize::attachToContext(
+    cudnnContext* cudnnContext, cublasContext* cublasContext, IGpuAllocator* gpuAllocator) noexcept
+{
+}
+
+// Detach the plugin object from its execution context.
+void MultilevelCropAndResize::detachFromContext() noexcept {}

plugin/multilevelCropAndResizePlugin/multilevelCropAndResizePlugin.h

@@ -0,0 +1,128 @@
+/*
+ * SPDX-FileCopyrightText: Copyright (c) 1993-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef TRT_MULTILEVEL_CROP_AND_RESIZE_PLUGIN_H
+#define TRT_MULTILEVEL_CROP_AND_RESIZE_PLUGIN_H
+
+#include <cuda_runtime_api.h>
+#include <string.h>
+#include <string>
+#include <vector>
+
+#include "NvInfer.h"
+#include "NvInferPlugin.h"
+#include "common/kernels/maskRCNNKernels.h"
+#include "multilevelProposeROI/tlt_mrcnn_config.h"
+
+namespace nvinfer1
+{
+namespace plugin
+{
+
+class MultilevelCropAndResize : public IPluginV2Ext
+{
+public:
+    MultilevelCropAndResize(int32_t pooled_size, nvinfer1::Dims const& image_size);
+
+    MultilevelCropAndResize(void const* data, size_t length);
+
+    ~MultilevelCropAndResize() noexcept override = default;
+
+    int32_t getNbOutputs() const noexcept override;
+
+    Dims getOutputDimensions(int32_t index, Dims const* inputs, int32_t nbInputDims) noexcept override;
+
+    int32_t initialize() noexcept override;
+
+    void terminate() noexcept override;
+
+    void destroy() noexcept override;
+
+    size_t getWorkspaceSize(int32_t) const noexcept override;
+
+    int32_t enqueue(int32_t batch_size, void const* const* inputs, void* const* outputs, void* workspace,
+        cudaStream_t stream) noexcept override;
+
+    size_t getSerializationSize() const noexcept override;
+
+    void serialize(void* buffer) const noexcept override;
+
+    bool supportsFormat(DataType type, PluginFormat format) const noexcept override;
+
+    char const* getPluginType() const noexcept override;
+
+    char const* getPluginVersion() const noexcept override;
+
+    IPluginV2Ext* clone() const noexcept override;
+
+    void setPluginNamespace(char const* libNamespace) noexcept override;
+
+    char const* getPluginNamespace() const noexcept override;
+
+    DataType getOutputDataType(
+        int32_t index, nvinfer1::DataType const* inputTypes, int32_t nbInputs) const noexcept override;
+
+    void attachToContext(
+        cudnnContext* cudnnContext, cublasContext* cublasContext, IGpuAllocator* gpuAllocator) noexcept override;
+
+    void configurePlugin(Dims const* inputDims, int32_t nbInputs, Dims const* outputDims, int32_t nbOutputs,
+        DataType const* inputTypes, DataType const* outputTypes, bool const* inputIsBroadcast,
+        bool const* outputIsBroadcast, PluginFormat floatFormat, int32_t maxBatchSize) noexcept override;
+
+    void detachFromContext() noexcept override;
+
+private:
+    void deserialize(int8_t const* data, size_t length);
+    void check_valid_inputs(nvinfer1::Dims const* inputs, int32_t nbInputDims) noexcept;
+
+    xy_t mPooledSize{};
+    static const int32_t mFeatureMapCount = 5; // p2, p3, p4, p5, p6(Maxpooling)
+    int32_t mFeatureLength{};
+    int32_t mROICount{};
+    float mThresh{};
+    int32_t mInputHeight;
+    int32_t mInputWidth{};
+    xy_t mFeatureSpatialSize[mFeatureMapCount]{};
+    std::string mNameSpace;
+    DataType mPrecision{};
+};
+
+class MultilevelCropAndResizePluginCreator : public nvinfer1::pluginInternal::BaseCreator
+{
+public:
+    MultilevelCropAndResizePluginCreator() noexcept;
+
+    ~MultilevelCropAndResizePluginCreator() noexcept override {}
+
+    char const* getPluginName() const noexcept override;
+
+    char const* getPluginVersion() const noexcept override;
+
+    PluginFieldCollection const* getFieldNames() noexcept override;
+
+    IPluginV2Ext* createPlugin(char const* name, PluginFieldCollection const* fc) noexcept override;
+
+    IPluginV2Ext* deserializePlugin(char const* name, void const* data, size_t length) noexcept override;
+
+private:
+    PluginFieldCollection mFC;
+    int32_t mPooledSize;
+    std::vector<PluginField> mPluginAttributes;
+};
+} // namespace plugin
+} // namespace nvinfer1
+#endif // TRT_MULTILEVEL_CROP_AND_RESIZE_PLUGIN_H