chore: import upstream snapshot with attribution

2026-07-13 13:36:55 +08:00
commit c8a779b1bb
1887 changed files with 3245738 additions and 0 deletions
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+/*
+ * SPDX-FileCopyrightText: Copyright (c) 1993-2024 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.
+ */
+#include "common/kernels/kernel.h"
+#include "reducedMathPlugin.h"
+#include <iostream>
+
+using namespace nvinfer1;
+using namespace nvinfer1::plugin;
+using nvinfer1::plugin::ReducedDivisor;
+template <unsigned nthdsPerCTA>
+__launch_bounds__(nthdsPerCTA) __global__ void gridAnchorKernel(const GridAnchorParameters param,
+    const int numAspectRatios, ReducedDivisor divObj, const float* widths, const float* heights, float* outputData)
+{
+    // output dims: (H, W, param.numMinSize, (1+haveMaxSize+numAR-1), 4)
+    const int dim = param.H * param.W * numAspectRatios;
+    /*
+     * Parameters used to calculate the bounding box coordinates back to input image scale
+     * Normally we calculate the anchorStride = image_input_size (in pixel) / feature_map_size
+     * Here we do not use image_input_size for the moment
+     * Instead we use 1.0
+     * The coordinates calculated are scaled by the input image size.
+     * Most of the coordinates will be in a range of [0, 1], except for the bounding box coordinates going outside of
+     * the image Every coordinate will go back to the pixel coordinates in the input image if being multiplied by
+     * image_input_size.
+     */
+    float anchorStrideH = (1.0F / param.H);
+    float anchorStrideW = (1.0F / param.W);
+    float anchorOffsetH = 0.5F * anchorStrideH;
+    float anchorOffsetW = 0.5F * anchorStrideW;
+
+    int tid = blockIdx.x * blockDim.x + threadIdx.x;
+    if (tid >= dim)
+        return;
+    int arId, currIndex;
+    divObj.divmod(tid, currIndex, arId);
+
+    const int w = currIndex % param.W;
+    const int h = currIndex / param.W;
+
+    // Center coordinates
+    float yC = h * anchorStrideH + anchorOffsetH;
+    float xC = w * anchorStrideW + anchorOffsetW;
+
+    // x_min, y_min
+    float xMin = xC - 0.5 * widths[arId];
+    float yMin = yC - 0.5 * heights[arId];
+
+    // x_max, y_max
+    float xMax = xC + 0.5 * widths[arId];
+    float yMax = yC + 0.5 * heights[arId];
+
+    outputData[tid * 4] = xMin;
+    outputData[tid * 4 + 1] = yMin;
+    outputData[tid * 4 + 2] = xMax;
+    outputData[tid * 4 + 3] = yMax;
+
+    // Remember to move the output cursor
+    float* output = outputData + dim * 4;
+
+    // Simply copying the variance
+    output[tid * 4] = param.variance[0];
+    output[tid * 4 + 1] = param.variance[1];
+    output[tid * 4 + 2] = param.variance[2];
+    output[tid * 4 + 3] = param.variance[3];
+}
+
+pluginStatus_t anchorGridInference(cudaStream_t stream, const GridAnchorParameters param, const int numAspectRatios,
+    const void* widths, const void* heights, void* outputData)
+{
+    const int dim = param.H * param.W * numAspectRatios;
+    ReducedDivisor divObj(numAspectRatios);
+    if (dim > 5120)
+    {
+        const int BS = 128;
+        const int GS = (dim + BS - 1) / BS;
+        gridAnchorKernel<BS><<<GS, BS, 0, stream>>>(
+            param, numAspectRatios, divObj, (const float*) widths, (const float*) heights, (float*) outputData);
+    }
+    else
+    {
+        const int BS = 32;
+        const int GS = (dim + BS - 1) / BS;
+        gridAnchorKernel<BS><<<GS, BS, 0, stream>>>(
+            param, numAspectRatios, divObj, (const float*) widths, (const float*) heights, (float*) outputData);
+    }
+    CSC(cudaGetLastError(), STATUS_FAILURE);
+    return STATUS_SUCCESS;
+}
+
+namespace nvinfer1
+{
+namespace plugin
+{
+pluginStatus_t anchorGridInference(cudaStream_t stream, const GridAnchorParameters param, const int numAspectRatios,
+    const void* widths, const void* heights, void* outputData)
+{
+    const int dim = param.H * param.W * numAspectRatios;
+    ReducedDivisor divObj(numAspectRatios);
+    if (dim > 5120)
+    {
+        const int BS = 128;
+        const int GS = (dim + BS - 1) / BS;
+        gridAnchorKernel<BS><<<GS, BS, 0, stream>>>(
+            param, numAspectRatios, divObj, (const float*) widths, (const float*) heights, (float*) outputData);
+    }
+    else
+    {
+        const int BS = 32;
+        const int GS = (dim + BS - 1) / BS;
+        gridAnchorKernel<BS><<<GS, BS, 0, stream>>>(
+            param, numAspectRatios, divObj, (const float*) widths, (const float*) heights, (float*) outputData);
+    }
+    CSC(cudaGetLastError(), STATUS_FAILURE);
+    return STATUS_SUCCESS;
+}
+
+} // namespace plugin
+} // namespace nvinfer1