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 <array>
+
+namespace nvinfer1
+{
+namespace plugin
+{
+
+template <typename Dtype, unsigned nthds_per_cta>
+__launch_bounds__(nthds_per_cta) __global__ void permuteData_kernel(const int nthreads, const int num_classes,
+    const int num_data, const int num_dim, bool confSigmoid, const Dtype* data, Dtype* new_data)
+{
+    // data format: [batch_size, num_data, num_classes, num_dim]
+    for (int index = blockIdx.x * nthds_per_cta + threadIdx.x; index < nthreads; index += nthds_per_cta * gridDim.x)
+    {
+        const int i = index % num_dim;
+        const int c = (index / num_dim) % num_classes;
+        const int d = (index / num_dim / num_classes) % num_data;
+        const int n = index / num_dim / num_classes / num_data;
+        const int new_index = ((n * num_classes + c) * num_data + d) * num_dim + i;
+        float result = data[index];
+        if (confSigmoid)
+            result = exp(result) / (1 + exp(result));
+
+        new_data[new_index] = result;
+    }
+    // new data format: [batch_size, num_classes, num_data, num_dim]
+}
+
+template <typename Dtype>
+pluginStatus_t permuteData_gpu(
+    cudaStream_t stream,
+    const int nthreads,
+    const int num_classes,
+    const int num_data,
+    const int num_dim,
+    bool confSigmoid,
+    const void* data,
+    void* new_data)
+{
+    const int BS = 512;
+    const int GS = (nthreads + BS - 1) / BS;
+    permuteData_kernel<Dtype, BS><<<GS, BS, 0, stream>>>(nthreads, num_classes, num_data, num_dim, confSigmoid,
+                                                         (const Dtype*) data, (Dtype*) new_data);
+    CSC(cudaGetLastError(), STATUS_FAILURE);
+    return STATUS_SUCCESS;
+}
+
+// permuteData LAUNCH CONFIG
+typedef pluginStatus_t (*pdFunc)(cudaStream_t, const int, const int, const int, const int, bool, const void*, void*);
+
+struct pdLaunchConfig
+{
+    DataType t_data;
+    pdFunc function;
+
+    pdLaunchConfig(DataType t_data)
+        : t_data(t_data)
+        , function(nullptr)
+    {
+    }
+    pdLaunchConfig(DataType t_data, pdFunc function)
+        : t_data(t_data)
+        , function(function)
+    {
+    }
+    bool operator==(pdLaunchConfig const& other) const
+    {
+        return t_data == other.t_data;
+    }
+};
+
+static std::array<pdLaunchConfig, 2> pdLCOptions = {
+    pdLaunchConfig(DataType::kFLOAT, permuteData_gpu<float>), pdLaunchConfig(DataType::kHALF, permuteData_gpu<__half>)};
+
+pluginStatus_t permuteData(cudaStream_t stream, const int nthreads, const int num_classes, const int num_data,
+    const int num_dim, const DataType DT_DATA, bool confSigmoid, const void* data, void* new_data)
+{
+    pdLaunchConfig lc = pdLaunchConfig(DT_DATA);
+    for (unsigned i = 0; i < pdLCOptions.size(); ++i)
+    {
+        if (lc == pdLCOptions[i])
+        {
+            DEBUG_PRINTF("permuteData kernel %d\n", i);
+            return pdLCOptions[i].function(stream,
+                                         nthreads,
+                                         num_classes,
+                                         num_data,
+                                         num_dim,
+                                         confSigmoid,
+                                         data,
+                                         new_data);
+        }
+    }
+    return STATUS_BAD_PARAM;
+}
+} // namespace plugin
+} // namespace nvinfer1