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 +1,69 @@
+// 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/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+namespace phi {
+template <typename TX, typename TY, typename Context>
+void QuantizeKernelImpl(const Context& dev_ctx,
+                        const DenseTensor& x,
+                        float scale,
+                        DenseTensor* y) {
+  using XPUInX = typename XPUTypeTrait<TX>::Type;
+  using XPUOutY = typename XPUTypeTrait<TY>::Type;
+
+  auto* y_data = dev_ctx.template Alloc<TY>(y);
+  const auto* x_data = x.data<TX>();
+  int64_t len = x.numel();
+  int max_ptr_size = dev_ctx.x_context()->max_ptr_size();
+  xpu::ctx_guard RAII_GUARD(dev_ctx.x_context());
+  auto max_data = RAII_GUARD.alloc_l3_or_gm<float>(max_ptr_size);
+  int r =
+      xpu::constant<float>(dev_ctx.x_context(), max_data, max_ptr_size, scale);
+  PADDLE_ENFORCE_XDNN_SUCCESS(r, "constant");
+  r = xpu::quantization<XPUInX, XPUOutY>(
+      dev_ctx.x_context(),
+      reinterpret_cast<const XPUInX*>(x_data),
+      reinterpret_cast<XPUOutY*>(y_data),
+      len,
+      max_data);
+  PADDLE_ENFORCE_XDNN_SUCCESS(r, "quantization");
+}
+
+template <typename T, typename Context>
+void QuantizeKernel(const Context& dev_ctx,
+                    const DenseTensor& x,
+                    DataType out_dtype,
+                    float scale,
+                    DenseTensor* y) {
+  switch (out_dtype) {
+    case DataType::INT16:
+      QuantizeKernelImpl<T, int16_t, Context>(dev_ctx, x, scale, y);
+      break;
+    case DataType::INT8:
+      QuantizeKernelImpl<T, int8_t, Context>(dev_ctx, x, scale, y);
+      break;
+    default:
+      PADDLE_THROW(common::errors::Unavailable(
+          "Not supported quantize data type from %d -> %d ",
+          x.dtype(),
+          out_dtype));
+  }
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    quantize_xpu, XPU, ALL_LAYOUT, phi::QuantizeKernel, float, phi::float16) {}