【PaddlePaddle Hackathon 3】No.102：为 OpenVINO 实现 Paddle 算子 elementwise_floordiv 转换

src/core/tests/frontend/paddle/op_fuzzy.cpp

@@ -100,20 +100,26 @@ static const std::vector<std::string> models{
     std::string("dropout_upscale_in_train"),
     std::string("elementwise_add1"),
     std::string("elementwise_div1"),
+    std::string("elementwise_floordiv1_int32"),
+    std::string("elementwise_floordiv1_int64"),
     std::string("elementwise_max1"),
     std::string("elementwise_min1"),
     std::string("elementwise_mul1"),
     std::string("elementwise_pow1"),
     std::string("elementwise_sub1"),
     std::string("elementwise_add2"),
     std::string("elementwise_div2"),
+    std::string("elementwise_floordiv2_int32"),
+    std::string("elementwise_floordiv2_int64"),
     std::string("elementwise_max2"),
     std::string("elementwise_min2"),
     std::string("elementwise_mul2"),
     std::string("elementwise_pow2"),
     std::string("elementwise_sub2"),
     std::string("elementwise_add3"),
     std::string("elementwise_div3"),
+    std::string("elementwise_floordiv3_int32"),
+    std::string("elementwise_floordiv3_int64"),
     std::string("elementwise_max3"),
     std::string("elementwise_min3"),
     std::string("elementwise_mul3"),

src/core/tests/frontend/paddle/test_models/gen_scripts/generate_elementwise_floordiv.py

@@ -0,0 +1,48 @@
+# Copyright (C) 2018-2022 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+#
+# elementwise_floordiv paddle model generator
+#
+import numpy as np
+import sys
+from save_model import saveModel
+
+def elementwise_floordiv(name : str, x, y, in_dtype):
+    import paddle
+    paddle.enable_static()
+
+    with paddle.static.program_guard(paddle.static.Program(), paddle.static.Program()):
+        node_x = paddle.static.data(name = 'x', shape = x.shape, dtype = in_dtype)
+        node_y = paddle.static.data(name = 'y', shape = y.shape, dtype = in_dtype)
+        out = paddle.floor_divide(node_x, node_y)
+
+        cpu = paddle.static.cpu_places(1)
+        exe = paddle.static.Executor(cpu[0])
+
+        # startup program will call initializer to initialize the parameters.
+        exe.run(paddle.static.default_startup_program())
+        outs = exe.run(
+        feed={'x': x, 'y': y},
+        fetch_list=[out])
+        saveModel(name, exe, feedkeys=['x', 'y'], fetchlist=[out], inputs=[x, y], outputs=[outs[0]], target_dir=sys.argv[1])
+
+    return outs[0]
+
+def main():
+    for in_dtype in ['int64', 'int32']:
+        data_x = np.array([2, 3, 4]).astype(in_dtype)
+        data_y = np.array([1, 5, 2]).astype(in_dtype)
+        elementwise_floordiv(f"elementwise_floordiv1_{in_dtype}", data_x, data_y, in_dtype)
+
+        # data_y's shape is the continuous subsequence of data_x's shape
+        data_x = np.random.randint(1, 5, size=[2, 3, 4, 5]).astype(in_dtype)
+        data_y = np.random.randint(-10, -1, size=[2, 3, 4, 5]).astype(in_dtype)
+        elementwise_floordiv(f"elementwise_floordiv2_{in_dtype}", data_x, data_y, in_dtype)
+
+        data_y = np.random.randint(1, 5, size=[5]).astype(in_dtype)
+        elementwise_floordiv(f"elementwise_floordiv3_{in_dtype}", data_x, data_y, in_dtype)
+
+if __name__ == "__main__":
+    main()
+

src/frontends/paddle/src/op/elementwise_ops.cpp

@@ -46,6 +46,16 @@ NamedOutputs elementwise_greater_equal(const NodeContext& node_context) {
     return elementwise_ops<default_opset::GreaterEqual>(node_context);
 }
 
+NamedOutputs elementwise_floordiv(const NodeContext& node_context) {
+    auto x = node_context.get_input("X");
+    auto y = node_context.get_input("Y");
+
+    const auto axis = node_context.get_attribute<int>("axis", -1);
+    auto autob = ov::op::AutoBroadcastSpec(ov::op::AutoBroadcastType::PDPD, axis);
+
+    return node_context.default_single_output_mapping({std::make_shared<default_opset::Floor>(std::make_shared<default_opset::Divide>(x, y, false, autob))}, {"Out"});
+}
+
 }  // namespace op
 }  // namespace paddle
 }  // namespace frontend

src/frontends/paddle/src/op_table.cpp

@@ -25,6 +25,7 @@ OP_CONVERTER(dropout);
 OP_CONVERTER(elementwise_add);
 OP_CONVERTER(elementwise_div);
 OP_CONVERTER(elementwise_equal);
+OP_CONVERTER(elementwise_floordiv);
 OP_CONVERTER(elementwise_greater_equal);
 OP_CONVERTER(elementwise_max);
 OP_CONVERTER(elementwise_min);
@@ -122,6 +123,7 @@ std::map<std::string, CreatorFunction> get_supported_ops() {
             {"dropout", op::dropout},
             {"elementwise_add", op::elementwise_add},
             {"elementwise_div", op::elementwise_div},
+            {"elementwise_floordiv", op::elementwise_floordiv},
             {"elementwise_max", op::elementwise_max},
             {"elementwise_min", op::elementwise_min},
             {"elementwise_mul", op::elementwise_mul},