【Hackathon 6th No.52】move quantize、dequantize op to phi -part

paddle/fluid/operators/dequantize_op.cc

@@ -1,11 +1,8 @@
 /* Copyright (c) 2016 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.

paddle/fluid/operators/dequantize_op.h

@@ -1,11 +1,8 @@
 /* Copyright (c) 2016 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.

paddle/fluid/operators/ops_signature/dequantize_sig.cc

@@ -1,11 +1,8 @@
 /* Copyright (c) 2023 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.

paddle/fluid/operators/ops_signature/quantize_sig.cc

@@ -0,0 +1,26 @@
+/* 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/core/compat/op_utils.h"
+
+namespace phi {
+
+KernelSignature QuantOpArgumentMapping(const ArgumentMappingContext& ctx) {
+  return KernelSignature(
+      "quantize",
+      {"Input"},
+      {"is_negative_input", "Scale", "Shift", "output_format", "bfloat16"},
+      {"Output"});
+}
+
+}  // namespace phi
+
+PD_REGISTER_ARG_MAPPING_FN(quantize, phi::QuantOpArgumentMapping);

paddle/fluid/operators/quantize_op.cc

@@ -21,11 +21,11 @@ namespace operators {
 
 phi::KernelKey QuantOp::GetExpectedKernelType(
     const framework::ExecutionContext& ctx) const {
-  return phi::KernelKey(
-      phi::Backend::ONEDNN,
-      phi::DataLayout::ONEDNN,
-      phi::TransToPhiDataType(
-          OperatorWithKernel::IndicateVarDataType(ctx, "Input")));
+  auto input_data_type =
+      framework::OperatorWithKernel::IndicateVarDataType(ctx, "Input");
+  return phi::KernelKey(phi::Backend::ONEDNN,
+                        phi::DataLayout::ONEDNN,
+                        phi::TransToPhiDataType(input_data_type));
 }
 
 void QuantOpMaker::Make() {

paddle/fluid/operators/quantize_op.h

@@ -1,11 +1,8 @@
 /* Copyright (c) 2016 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.

paddle/phi/infermeta/unary.cc

@@ -3453,6 +3453,17 @@ void QrInferMeta(const MetaTensor& x,
   r->set_dtype(x.dtype());
 }
 
+void QuantizeInferMeta(const MetaTensor& input,
+                       bool is_negative_input,
+                       float scale,
+                       float shift,
+                       const std::string& output_format,
+                       bool bfloat16,
+                       MetaTensor* output) {
+  output->set_dims(input.dims());
+  output->share_lod(input);
+}
+
 DDim ReduceInferDim(const MetaTensor& x,
                     const std::vector<int64_t>& axis,
                     bool keep_dim,

paddle/phi/infermeta/unary.h

@@ -527,6 +527,14 @@ void QrInferMeta(const MetaTensor& x,
                  MetaTensor* q,
                  MetaTensor* r);
 
+void QuantizeInferMeta(const MetaTensor& input,
+                       bool is_negative_input,
+                       float scale,
+                       float shift,
+                       const std::string& output_format,
+                       bool bfloat16,
+                       MetaTensor* output);
+
 void QuantizeXPUInferMeta(const MetaTensor& x,
                           DataType out_dtype,
                           float scale,

paddle/phi/kernels/onednn/quantize_kernel.cc

@@ -0,0 +1,117 @@
+/* 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,
+                   float scale,
+                   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,
+                    phi::errors::InvalidArgument(
+                        "Quantization scale must be different than 0.0f"));
+  PADDLE_ENFORCE(quantization_shift <= 255 && quantization_shift >= 0,
+                 phi::errors::InvalidArgument(
+                     "Quantization shift must be lower or equal to ",
+                     "255 and greater or equal to 0, but got %f",
+                     quantization_shift));
+
+  auto x_tz = common::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 = phi::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 = phi::funcs::ToOneDNNDataType(out_dtype);
+
+  phi::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(), phi::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 = phi::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(), phi::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(),
+                   phi::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) {}