chore: import upstream snapshot with attribution

paddle/phi/kernels/gpu/bce_loss_kernel.cu

@@ -0,0 +1,71 @@
+// 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/bce_loss_kernel.h"
+
+#include <algorithm>
+#include <vector>
+
+#include "paddle/common/hostdevice.h"
+#include "paddle/phi/backends/gpu/gpu_context.h"
+#include "paddle/phi/common/amp_type_traits.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/elementwise_base.h"
+#include "paddle/phi/kernels/primitive/functor_primitives.h"
+
+namespace phi {
+
+template <typename T>
+struct BCELossFunctor {
+  using MT = typename MPTypeTrait<T>::Type;
+  MT zero = static_cast<MT>(0);
+  MT one = static_cast<MT>(1.0f);
+  MT neg_100 = static_cast<MT>(-100.);
+
+  HOSTDEVICE inline T operator()(const T x, const T label) const {
+    MT x_mt = static_cast<MT>(x);
+    MT label_mt = static_cast<MT>(label);
+
+    PADDLE_ENFORCE(
+        (x_mt >= zero) && (x_mt <= one),
+        "Input is expected to be within the interval [0, 1], but received %f.",
+        x_mt);
+
+    MT term1 = max(kps::details::Log(x_mt), neg_100);
+    MT term2 = max(kps::details::Log(one - x_mt), neg_100);
+    return static_cast<T>((label_mt - one) * term2 - label_mt * term1);
+  }
+};
+
+template <typename T, typename Context>
+void BCELossKernel(const Context& dev_ctx,
+                   const DenseTensor& input,
+                   const DenseTensor& label,
+                   DenseTensor* out) {
+  dev_ctx.template Alloc<T>(out);
+  std::vector<const DenseTensor*> ins = {&input, &label};
+  std::vector<DenseTensor*> outs = {out};
+  auto functor = BCELossFunctor<T>();
+  funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(bce_loss,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::BCELossKernel,
+                   float,
+                   double,
+                   phi::float16) {}