Merge pull request #1505 from risemeup1/fix_abs_bug

fix abs bug

paddle2onnx/mapper/activation/activation.cc

@@ -15,9 +15,6 @@
 #include "paddle2onnx/mapper/exporter.h"
 
 namespace paddle2onnx {
-
-REGISTER_MAPPER(abs, ActivationMapper)
-REGISTER_PIR_MAPPER(abs, ActivationMapper)
 REGISTER_MAPPER(acos, ActivationMapper)
 REGISTER_MAPPER(asin, ActivationMapper)
 REGISTER_MAPPER(atan, ActivationMapper)
@@ -114,28 +111,12 @@ void ActivationMapper::Opset7() {
     auto output = helper_->MakeNode(iter->second, {input})->output(0);
     helper_->AutoCast(output, output_info[0].name, P2ODataType::FP32,
                       output_info[0].dtype);
-  } else {
-    if (convert_pir_op_name(OpType()) == "abs" && input_info[0].dtype == P2ODataType::COMPLEX64){
-      input_info[0].dtype = P2ODataType::FP32;
-      int shape_size = input_info[0].shape.size();
-      std::string one_str = helper_->Constant(GetOnnxDtype(P2ODataType::INT64), std::vector<int64_t>({1}));
-      auto split_node = helper_->MakeNode("Split", {input_info[0].name},2);
-      AddAttribute(split_node,"axis",int64_t(-1));
-
-      auto real_squre = helper_->MakeNode("Mul", {split_node->output(0),split_node->output(0)});
-      auto imag_squre = helper_->MakeNode("Mul", {split_node->output(1),split_node->output(1)});
-
-      auto node_add = helper_->MakeNode("Add", {real_squre->output(0),imag_squre->output(0)});
-
-      helper_->MakeNode("Sqrt", {node_add->output(0)},
-                      {output_info[0].name});
-    }else{
+  } else{
       helper_->MakeNode(iter->second, {input_info[0].name},
                       {output_info[0].name});
-    }
-
   }
 
+
 }
 
 int32_t PReluMapper::GetMinOpsetVersion(bool verbose) {

paddle2onnx/mapper/activation/activation.h

@@ -38,7 +38,6 @@ class ActivationMapper : public Mapper {
     op_mapper_["cos"] = "Cos";
     op_mapper_["sin"] = "Sin";
     op_mapper_["round"] = "Round";
-    op_mapper_["abs"] = "Abs";
     op_mapper_["acos"] = "Acos";
     op_mapper_["asin"] = "Asin";
     op_mapper_["atan"] = "Atan";
@@ -64,7 +63,6 @@ class ActivationMapper : public Mapper {
     op_mapper_["cos"] = "Cos";
     op_mapper_["sin"] = "Sin";
     op_mapper_["round"] = "Round";
-    op_mapper_["abs"] = "Abs";
     op_mapper_["acos"] = "Acos";
     op_mapper_["asin"] = "Asin";
     op_mapper_["atan"] = "Atan";

paddle2onnx/mapper/tensor/abs.cc

@@ -0,0 +1,67 @@
+// 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 "paddle2onnx/mapper/tensor/abs.h"
+
+namespace paddle2onnx {
+REGISTER_PIR_MAPPER(abs, AbsMapper)
+REGISTER_MAPPER(abs, AbsMapper)
+
+int32_t AbsMapper::GetMinOpsetVersion(bool verbose) {
+    return 13;
+
+}
+
+void AbsMapper::Opset13() {
+    auto input_info = GetInput("X");
+    auto output_info = GetOutput("Out");
+    if (input_info[0].dtype == P2ODataType::COMPLEX64){
+        std::string one_str = helper_->Constant(GetOnnxDtype(P2ODataType::INT64), std::vector<int64_t>({1}));
+        auto split_node = helper_->MakeNode("Split", {input_info[0].name},2);
+        AddAttribute(split_node,"axis",int64_t(-1));
+        std::string split_node1 = helper_->Squeeze(split_node->output(0), {-1});
+        std::string split_node2 = helper_->Squeeze(split_node->output(1), {-1});
+        auto real_squre = helper_->MakeNode("Mul", {split_node1,split_node1});
+        auto imag_squre = helper_->MakeNode("Mul", {split_node2 ,split_node2});
+        auto node_add = helper_->MakeNode("Add", {real_squre->output(0),imag_squre->output(0)});
+        helper_->MakeNode("Sqrt", {node_add->output(0)},
+                    {output_info[0].name});
+    }else{
+        helper_->MakeNode("Abs", {input_info[0].name},
+                    {output_info[0].name});
+    }
+}
+void AbsMapper::Opset18() {
+    auto input_info = GetInput("X");
+    auto output_info = GetOutput("Out");
+    if (input_info[0].dtype == P2ODataType::COMPLEX64){
+        std::string one_str = helper_->Constant(GetOnnxDtype(P2ODataType::INT64), std::vector<int64_t>({1}));
+        auto split_node = helper_->MakeNode("Split", {input_info[0].name},2);
+        AddAttribute(split_node,"axis",int64_t(-1));
+        AddAttribute(split_node,"num_outputs",int64_t(2));
+        std::string split_node1 = helper_->Squeeze(split_node->output(0), {-1});
+        std::string split_node2 = helper_->Squeeze(split_node->output(1), {-1});
+        auto real_squre = helper_->MakeNode("Mul", {split_node1,split_node1});
+        auto imag_squre = helper_->MakeNode("Mul", {split_node2 ,split_node2});
+        auto node_add = helper_->MakeNode("Add", {real_squre->output(0),imag_squre->output(0)});
+        helper_->MakeNode("Sqrt", {node_add->output(0)},
+                    {output_info[0].name});
+    }else{
+        helper_->MakeNode("Abs", {input_info[0].name},
+                    {output_info[0].name});
+    }
+
+}
+
+}  // namespace paddle2onnx

paddle2onnx/mapper/tensor/abs.h

@@ -0,0 +1,40 @@
+// 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 <string>
+#include <vector>
+
+#include "paddle2onnx/mapper/mapper.h"
+
+namespace paddle2onnx {
+
+class AbsMapper : public Mapper {
+ public:
+  AbsMapper(const PaddleParser& p, OnnxHelper* helper, int64_t block_id,
+              int64_t op_id)
+      : Mapper(p, helper, block_id, op_id) {}
+  AbsMapper(const PaddlePirParser& p, OnnxHelper* helper, int64_t i,
+              bool c)
+      : Mapper(p, helper, i, c) {
+      in_pir_mode = true;
+  }
+
+  int32_t GetMinOpsetVersion(bool verbose) override;
+  void Opset13() override;
+  void Opset18() override;
+
+};
+
+}  // namespace paddle2onnx

tests/test_abs.py

@@ -35,66 +35,31 @@ def forward(self, inputs):
 
 
 @_test_with_pir
-def test_abs_9():
+def test_abs_13():
     """
     api: paddle.abs
-    op version: 9
-    """
-    op = Net()
-    op.eval()
-    # net, name, ver_list, delta=1e-6, rtol=1e-5
-    obj = APIOnnx(op, "abs", [9])
-    obj.set_input_data(
-        "input_data",
-        paddle.to_tensor(randtool("float", -1, 1, [3, 3, 3]).astype("float32")),
-    )
-    obj.run()
-
-
-@_test_with_pir
-def test_abs_10():
-    """
-    api: paddle.abs
-    op version: 10
-    """
-    op = Net()
-    op.eval()
-    # net, name, ver_list, delta=1e-6, rtol=1e-5
-    obj = APIOnnx(op, "abs", [10])
-    obj.set_input_data(
-        "input_data",
-        paddle.to_tensor(randtool("float", -1, 1, [3, 3, 3]).astype("float32")),
-    )
-    obj.run()
-
-
-@_test_with_pir
-def test_abs_11():
-    """
-    api: paddle.abs
-    op version: 11
+    op version: 12
     """
     op = Net()
     op.eval()
     # net, name, ver_list, delta=1e-6, rtol=1e-5
-    obj = APIOnnx(op, "abs", [11])
+    obj = APIOnnx(op, "abs", [13])
     obj.set_input_data(
         "input_data",
         paddle.to_tensor(randtool("float", -1, 1, [3, 3, 3]).astype("float32")),
     )
     obj.run()
 
 
-@_test_with_pir
-def test_abs_12():
+def test_abs_18():
     """
     api: paddle.abs
-    op version: 12
+    op version: 18
     """
     op = Net()
     op.eval()
     # net, name, ver_list, delta=1e-6, rtol=1e-5
-    obj = APIOnnx(op, "abs", [12])
+    obj = APIOnnx(op, "abs", [18])
     obj.set_input_data(
         "input_data",
         paddle.to_tensor(randtool("float", -1, 1, [3, 3, 3]).astype("float32")),

tests/test_auto_scan_unary_ops.py

@@ -12,9 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 from auto_scan_test import OPConvertAutoScanTest, BaseNet
-from hypothesis import reproduce_failure
 import hypothesis.strategies as st
-import numpy as np
 import unittest
 import paddle
 
@@ -56,7 +54,7 @@
 }
 
 opset_version_map = {
-    "abs": [7, 13, 15],
+    "abs": [13, 18],
     "acos": [7, 15],
     "asin": [7, 15],
     "atan": [7, 15],
@@ -103,9 +101,8 @@ class TestUnaryOPConvert(OPConvertAutoScanTest):
 
     def sample_convert_config(self, draw):
         input_shape = draw(
-            st.lists(
-                st.integers(
-                    min_value=2, max_value=20), min_size=0, max_size=4))
+            st.lists(st.integers(min_value=2, max_value=20), min_size=0, max_size=4)
+        )
         data_shapes = input_shape
         dtype = draw(st.sampled_from(["float32"]))
         config = {