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) 2023 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/check_numerics_kernel.h"
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/check_numerics_utils.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void CheckNumericsKernel(const Context& dev_ctx,
+                         const DenseTensor& tensor,
+                         const std::string& op_type,
+                         const std::string& var_name,
+                         const int check_nan_inf_level,
+                         const int stack_height_limit,
+                         const std::string& output_dir,
+                         DenseTensor* stats,
+                         DenseTensor* values) {
+  // stats stores the checking result of num_nan, num_inf and num_zero.
+  stats->Resize({static_cast<int64_t>(3)});
+  int64_t* stats_ptr = dev_ctx.template Alloc<int64_t>(stats);
+
+  // values stores the max_value, min_value and mean_value.
+  values->Resize({static_cast<int64_t>(3)});
+  float* values_ptr = dev_ctx.template Alloc<float>(values);
+
+  if (tensor.numel() == 0) {
+    stats_ptr[0] = 0;
+    stats_ptr[1] = 0;
+    stats_ptr[2] = 0;
+    values_ptr[0] = static_cast<float>(0);
+    values_ptr[1] = static_cast<float>(0);
+    values_ptr[2] = static_cast<float>(0);
+    return;
+  }
+
+  std::string cpu_hint_str =
+      funcs::GetCpuHintString<T>(op_type, var_name, tensor.place());
+  funcs::CheckNumericsCpuImpl(tensor.data<T>(),
+                              tensor.numel(),
+                              cpu_hint_str,
+                              check_nan_inf_level,
+                              "cpu",
+                              output_dir,
+                              stats_ptr,
+                              values_ptr);
+}
+#ifdef _WIN32
+INSTANTIATE_CHECKNUMBERICS_KERNEL(float, CPUContext)
+INSTANTIATE_CHECKNUMBERICS_KERNEL(double, CPUContext)
+INSTANTIATE_CHECKNUMBERICS_KERNEL(float16, CPUContext)
+INSTANTIATE_CHECKNUMBERICS_KERNEL(bfloat16, CPUContext)
+INSTANTIATE_CHECKNUMBERICS_KERNEL(complex64, CPUContext)
+INSTANTIATE_CHECKNUMBERICS_KERNEL(complex128, CPUContext)
+INSTANTIATE_CHECKNUMBERICS_KERNEL(float8_e4m3fn, CPUContext)
+INSTANTIATE_CHECKNUMBERICS_KERNEL(float8_e5m2, CPUContext)
+#endif
+}  // namespace phi
+
+PD_REGISTER_KERNEL(check_numerics,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::CheckNumericsKernel,
+                   float,
+                   double,
+                   phi::float16,
+                   phi::bfloat16,
+                   phi::complex64,
+                   phi::complex128,
+                   phi::float8_e4m3fn,
+                   phi::float8_e5m2) {}