update roll (#1228)

Author: Zheng-Bicheng

.gitignore

@@ -4,7 +4,6 @@
 
 *.pyc
 .pydevproject
-build/*
 .eggs/*
 dist/*
 .setuptools*
@@ -13,4 +12,15 @@ paddle2onnx.egg-info/*
 *_*.onnx
 *.log
 version.py
-paddle2onnx/mappers_registry.h
+paddle2onnx/mappers_registry.h
+
+# CMD
+build/*
+paddle2onnx-*
+
+# Clion
+cmake-build-*
+.idea
+
+# VSCode
+.vscode

VERSION_NUMBER

@@ -1 +1 @@
-1.2.0
+1.2.1

paddle2onnx/mapper/tensor/roll.cc

@@ -0,0 +1,63 @@
+// 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 <limits>
+#include "paddle2onnx/mapper/tensor/roll.h"
+
+namespace paddle2onnx {
+REGISTER_MAPPER(roll, RollMapper)
+
+void RollMapper::Opset7() {
+  auto input_info = GetInput("X");
+  auto output_info = GetOutput("Out");
+
+  std::vector<int64_t> shifts;
+  GetAttr("shifts", &shifts);
+
+  std::vector<int64_t> axis;
+  GetAttr("axis", &axis);
+
+  std::shared_ptr<ONNX_NAMESPACE::NodeProto> temp_node= nullptr;
+  auto result_name = input_info[0].name;
+  if (axis.empty())
+  {
+    int64_t axes = 0;
+    result_name = helper_->Flatten(result_name);
+    for(int i = 0;i < shifts.size();i++) {
+      auto shift = shifts[i];
+      auto result_0 = helper_->Slice(result_name, {axes}, {-shift}, {(std::numeric_limits<int64_t>::max)()});
+      auto result_1 = helper_->Slice(result_name, {axes}, {0}, {-shift});
+      temp_node = helper_->MakeNode("Concat", {result_0, result_1});
+      AddAttribute(temp_node, "axis", axes);
+      result_name = temp_node->output(0);
+    }
+    helper_->Reshape(result_name, output_info[0].name, input_info[0].shape);
+    // helper_->MakeNode("Reshape", {result_name, input_info[0].shape}, {output_info[0].name});
+  } else {
+    for(int i = 0;i < shifts.size();i++) {
+      auto shift = shifts[i];
+      int64_t axes = axis[i];
+      auto result_0 = helper_->Slice(result_name, {axes}, {-shift}, {(std::numeric_limits<int64_t>::max)()});
+      auto result_1 = helper_->Slice(result_name, {axes}, {0}, {-shift});
+      if(i+1 == shifts.size()) {
+        temp_node = helper_->MakeNode("Concat", {result_0, result_1}, {output_info[0].name});
+      } else {
+        temp_node = helper_->MakeNode("Concat", {result_0, result_1});
+      }
+      AddAttribute(temp_node, "axis", axes);
+      result_name = temp_node->output(0);
+    }
+  }
+}
+}  // namespace paddle2onnx

paddle2onnx/mapper/tensor/roll.h

@@ -0,0 +1,31 @@
+// 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 RollMapper : public Mapper {
+ public:
+  RollMapper(const PaddleParser& p, OnnxHelper* helper, int64_t block_id,
+             int64_t op_id)
+      : Mapper(p, helper, block_id, op_id) {}
+  void Opset7();
+};
+
+}  // namespace paddle2onnx

tests/test_roll.py

@@ -0,0 +1,54 @@
+# Copyright (c) 2021  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.
+
+import paddle
+from onnxbase import APIOnnx
+from onnxbase import randtool
+
+
+class Net(paddle.nn.Layer):
+    """
+    simple Net
+    """
+
+    def __init__(self):
+        super(Net, self).__init__()
+
+    def forward(self, inputs):
+        """
+        forward
+        """
+        x = paddle.roll(inputs, 1)
+        return x
+
+
+def test_roll():
+    """
+    api: paddle.roll
+    op version: 9
+    """
+    op = Net()
+    op.eval()
+    # net, name, ver_list, delta=1e-6, rtol=1e-5
+    obj = APIOnnx(op, 'roll', [9])
+    input_data = paddle.to_tensor(randtool("float", -1, 1, [2,2]).astype('float32'))
+    print(input_data)
+    obj.set_input_data(
+        "input_data",
+        input_data
+        )
+    obj.run()
+
+if __name__ == "__main__":
+    test_roll()