chore: import upstream snapshot with attribution

paddle/phi/kernels/onednn/quantize_kernel.cc

@@ -0,0 +1,115 @@
+/* Copyright (c) 2024 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/quantize_kernel.h"
+#include "paddle/phi/backends/onednn/onednn_reuse.h"
+#include "paddle/phi/core/compat/convert_utils.h"
+#include "paddle/phi/core/enforce.h"
+#include "paddle/phi/core/expect.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/utils/data_type.h"
+
+namespace phi {
+
+using dnnl::memory;
+
+template <typename T, typename Context>
+void QuantOpKernel(const Context& dev_ctx,
+                   const DenseTensor& input,
+                   bool is_negative_input,
+                   const float scale,
+                   const float shift,
+                   const std::string& output_format,
+                   bool bfloat16,
+                   DenseTensor* output) {
+  const auto quantization_shift = static_cast<int32_t>(shift);
+  const bool with_scale = scale != 1.0f;
+  const bool with_shift = quantization_shift != 0.0f;
+
+  PADDLE_ENFORCE_NE(scale,
+                    0.0f,
+                    common::errors::InvalidArgument(
+                        "Quantization scale must be different than 0.0f"));
+  PADDLE_ENFORCE(
+      quantization_shift <= 255 && quantization_shift >= 0,
+      common::errors::InvalidArgument(
+          "Quantization shift must be lower or equal to 255 and greater or "
+          "equal to 0, but got %d",
+          quantization_shift));
+
+  auto x_tz = vectorize<int64_t>(input.dims());
+  dnnl::primitive_attr attrs;
+  static constexpr int32_t mask = 0;
+
+  if (with_scale) {
+    attrs.set_scales_mask(DNNL_ARG_SRC, mask);
+  }
+
+  if (with_shift) {
+    attrs.set_zero_points_mask(DNNL_ARG_DST, mask);
+  }
+
+  auto x_type = funcs::ToOneDNNDataType(input.dtype());
+  DataType out_dtype;
+
+  if (bfloat16) {
+    out_dtype = DataType::BFLOAT16;
+  } else if (is_negative_input && !with_shift) {
+    out_dtype = DataType::INT8;
+  } else {
+    out_dtype = DataType::UINT8;
+  }
+
+  auto out_type = funcs::ToOneDNNDataType(out_dtype);
+
+  funcs::ReorderOneDNNHandler reorder_handler(
+      x_tz, input.dtype(), x_type, out_dtype, out_type, dev_ctx.GetEngine());
+
+  auto reorder_src_memory_p = reorder_handler.AcquireSrcMemory(
+      input.mem_desc(), funcs::to_void_cast(input.data<T>()));
+  auto reorder_dst_memory_p = reorder_handler.AcquireDstMemory(
+      output, input.mem_desc(), dev_ctx.GetPlace());
+
+  auto reorder_p = reorder_handler.AcquireReorder(
+      reorder_dst_memory_p, reorder_src_memory_p, attrs);
+
+  auto& astream = OneDNNContext::tls().get_stream();
+
+  auto scales_md = dnnl::memory::desc(
+      {1}, dnnl::memory::data_type::f32, dnnl::memory::format_tag::x);
+  auto scales_mem = dnnl::memory(
+      scales_md, dev_ctx.GetEngine(), funcs::to_void_cast<float>(&scale));
+  auto zero_points_md = dnnl::memory::desc(
+      {1}, dnnl::memory::data_type::s32, dnnl::memory::format_tag::x);
+  auto zero_points_mem =
+      dnnl::memory(zero_points_md,
+                   dev_ctx.GetEngine(),
+                   funcs::to_void_cast<int32_t>(&quantization_shift));
+
+  std::unordered_map<int, dnnl::memory> reorder_args;
+  reorder_args.insert({DNNL_ARG_SRC, *reorder_src_memory_p});
+  reorder_args.insert({DNNL_ARG_DST, *reorder_dst_memory_p});
+  if (with_scale) {
+    reorder_args.insert({DNNL_ARG_ATTR_SCALES | DNNL_ARG_SRC, scales_mem});
+  }
+  if (with_shift) {
+    reorder_args.insert(
+        {DNNL_ARG_ATTR_ZERO_POINTS | DNNL_ARG_DST, zero_points_mem});
+  }
+
+  reorder_p->execute(astream, reorder_args);
+  astream.wait();
+
+  output->set_mem_desc(reorder_dst_memory_p->get_desc());
+}
+}  // namespace phi
+
+PD_REGISTER_KERNEL(quantize, OneDNN, ONEDNN, phi::QuantOpKernel, float) {}