chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/clip_kernel_impl.h

@@ -0,0 +1,74 @@
+// 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.
+
+#pragma once
+
+#include "paddle/phi/backends/all_context.h"
+#include "paddle/phi/common/transform.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/clip_kernel.h"
+#if defined(__NVCC__) || defined(__HIPCC__)
+#include "paddle/phi/kernels/funcs/broadcast_function.h"
+#endif
+
+namespace phi {
+
+template <typename T>
+class ClipFunctor {
+ public:
+  explicit ClipFunctor(const T min, const T max) : min_(min), max_(max) {}
+  HOSTDEVICE T operator()(const T x) const {
+    return x < min_ ? min_ : x > max_ ? max_ : x;
+  }
+
+ private:
+  T min_;
+  T max_;
+};
+
+template <typename T, typename Context>
+void ClipKernel(const Context& dev_ctx,
+                const DenseTensor& x,
+                const Scalar& min,
+                const Scalar& max,
+                DenseTensor* out) {
+  auto max_ = max.to<T>();
+  auto min_ = min.to<T>();
+
+  PADDLE_ENFORCE_LE(
+      min_,
+      max_,
+      errors::InvalidArgument("max should be greater than or equal to min. "
+                              "But received min = %f, max = %f",
+                              static_cast<float>(min_),
+                              static_cast<float>(max_)));
+
+  T* out_data = dev_ctx.template Alloc<T>(out);
+  const T* x_data = x.data<T>();
+  int64_t numel = x.numel();
+  if (dev_ctx.GetPlace().GetType() == AllocationType::GPU) {
+#if defined(__NVCC__) || defined(__HIPCC__)
+    std::vector<const DenseTensor*> ins = {&x};
+    std::vector<DenseTensor*> outs = {out};
+    auto functor = ClipFunctor<T>(min_, max_);
+    funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
+#endif
+  } else {
+    Transform<Context> trans;
+    trans(
+        dev_ctx, x_data, x_data + numel, out_data, ClipFunctor<T>(min_, max_));
+  }
+}
+
+}  // namespace phi