chore: import upstream snapshot with attribution

paddle/phi/kernels/gpu/dequantize_abs_max_kernel.cu

@@ -0,0 +1,67 @@
+/* Copyright (c) 2019 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/dequantize_abs_max_kernel.h"
+
+#include "paddle/common/hostdevice.h"
+#include "paddle/phi/backends/gpu/gpu_context.h"
+#include "paddle/phi/backends/gpu/gpu_primitives.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/math.h"
+
+namespace phi {
+
+template <typename T>
+__global__ void KeDequantize(
+    const T* in, const float* scale, float max_range, int num, float* out) {
+  const int idx = threadIdx.x + blockIdx.x * blockDim.x;
+  if (idx < num) {
+    out[idx] = in[idx] * scale[0] / max_range;
+  }
+}
+
+template <typename T, typename Context>
+void DequantizeAbsMaxKernel(const Context& dev_ctx,
+                            const DenseTensor& x,
+                            const DenseTensor& scale,
+                            float max_range,
+                            DenseTensor* out) {
+  const T* in_data = x.data<T>();
+  const float* scale_factor = scale.data<float>();
+  float* out_data = dev_ctx.template Alloc<float>(out);
+
+  int64_t num = x.numel();
+
+  // big tensor currently not supported
+  PADDLE_ENFORCE_LE(num,
+                    (1LL << 31) - 1,
+                    ::common::errors::PreconditionNotMet(
+                        "x's numel too large, allowed size is 2 ^ 31 - 1 "
+                        "elements, but got %lld",
+                        num));
+  int block = 512;
+  int grid = (num + block - 1) / block;
+
+  KeDequantize<T><<<grid, block, 0, dev_ctx.stream()>>>(
+      in_data, scale_factor, max_range, num, out_data);
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(dequantize_abs_max,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::DequantizeAbsMaxKernel,
+                   int8_t,
+                   int16_t) {}