chore: import upstream snapshot with attribution

2026-07-13 12:40:42 +08:00
commit e25996e7db
15472 changed files with 3536181 additions and 0 deletions
@@ -0,0 +1,85 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// 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 "paddle/phi/kernels/nonzero_kernel.h"
+
+#include "glog/logging.h"
+
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/common/memory_utils.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void NonZeroKernel(const Context& dev_ctx,
+                   const DenseTensor& condition,
+                   DenseTensor* out) {
+  auto numel = condition.numel();
+  auto dims = condition.dims();
+  const int64_t rank = dims.size();
+
+  using XPUType = typename XPUTypeTrait<T>::Type;
+
+  if (numel == 0) {
+    dev_ctx.template Alloc<int64_t>(out);
+    return;
+  }
+
+  xpu::ctx_guard RAII_GUARD(dev_ctx.x_context());
+  int64_t* true_num = RAII_GUARD.alloc_l3_or_gm<int64_t>(1);
+  int64_t* workspace =
+      RAII_GUARD.alloc_l3_or_gm<int64_t>(dev_ctx.x_context()->ncluster() * 64);
+  auto cond_data = reinterpret_cast<const XPUType*>(condition.data<T>());
+  int ret = xpu::nonzero_count<XPUType, int64_t>(
+      dev_ctx.x_context(), cond_data, true_num, numel, workspace);
+  PADDLE_ENFORCE_XDNN_SUCCESS(ret, "nonzero_count");
+
+  int64_t true_num_cpu;
+  memory_utils::Copy(CPUPlace(),
+                     static_cast<void*>(&true_num_cpu),
+                     dev_ctx.GetPlace(),
+                     static_cast<void*>(true_num),
+                     sizeof(int64_t));
+  if (std::getenv("XPUSIM_SKIP_RUN") &&
+      std::strcmp(std::getenv("XPUSIM_SKIP_RUN"), "1") == 0) {
+    VLOG(3) << "WARNING: In the simulator mode, the variable true_num_cpu "
+               "stores an uninitialized value. To avoid allocating a memory of "
+               "random size, we assign numel to true_num_cpu";
+    true_num_cpu = numel;
+  }
+
+  out->Resize({true_num_cpu, rank});
+  auto* out_data = dev_ctx.template Alloc<int64_t>(out);
+
+  if (true_num_cpu == 0) {
+    return;
+  }
+
+  auto condition_shape = vectorize<int64_t>(dims);
+  ret = xpu::nonzero_compute<XPUType, int64_t, int64_t>(dev_ctx.x_context(),
+                                                        cond_data,
+                                                        out_data,
+                                                        condition_shape,
+                                                        true_num_cpu,
+                                                        workspace);
+  PADDLE_ENFORCE_XDNN_SUCCESS(ret, "nonzero_compute");
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    nonzero, XPU, ALL_LAYOUT, phi::NonZeroKernel, int, bool, float, int64_t) {
+  kernel->OutputAt(0).SetDataType(phi::DataType::INT64);
+}