【Hackathon 6th No.44】add paddle rsqrt (openvinotoolkit#23985)

Add `paddle.rsqrt` op for openvino

paddle.rsqrt(x, name=None)

The rsqrt activation function.

The calculation formula is as follows:

$$
out=\frac{1}{\sqrt{x}}
$$


![image](https://github.com/openvinotoolkit/openvino/assets/55493212/b197c068-96f8-47f4-8d48-913ee93d01a9)

Waiting for:
- openvinotoolkit#23010

---------

Co-authored-by: mei, yang <[email protected]>

src/frontends/paddle/src/op/rsqrt.cpp

@@ -0,0 +1,26 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "default_opset.hpp"
+#include "openvino/frontend/paddle/node_context.hpp"
+
+namespace ov {
+namespace frontend {
+namespace paddle {
+namespace op {
+
+NamedOutputs rsqrt(const NodeContext& node) {
+    auto data = node.get_input("X");
+
+    auto rsqrt = std::make_shared<default_opset::Power>(
+        data,
+        default_opset::Constant::create(data.get_element_type(), Shape{}, {-0.5}));
+
+    return node.default_single_output_mapping({rsqrt}, {"Out"});
+}
+
+}  // namespace op
+}  // namespace paddle
+}  // namespace frontend
+}  // namespace ov

src/frontends/paddle/src/op_table.cpp

@@ -99,6 +99,7 @@ OP_CONVERTER(reverse);
 OP_CONVERTER(rnn);
 OP_CONVERTER(roi_align);
 OP_CONVERTER(round);
+OP_CONVERTER(rsqrt);
 OP_CONVERTER(scale);
 OP_CONVERTER(select_input);
 OP_CONVERTER(set_value);
@@ -237,6 +238,7 @@ std::map<std::string, CreatorFunction> get_supported_ops() {
             {"rnn", op::rnn},
             {"roi_align", op::roi_align},
             {"round", op::round},
+            {"rsqrt", op::rsqrt},
             {"scale", op::scale},
             {"select_input", op::select_input},
             {"set_value", op::set_value},

src/frontends/paddle/tests/test_models/gen_scripts/generate_rsqrt.py

@@ -0,0 +1,45 @@
+import sys
+import paddle
+import numpy as np
+from save_model import saveModel
+
+
+def rsqrt(name: str, x):
+    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=x.dtype)
+        out = paddle.rsqrt(node_x)
+
+        cpu = paddle.static.cpu_places(1)
+        exe = paddle.static.Executor(cpu[0])
+        # Initialize the variables with the provided inputs
+        exe.run(paddle.static.default_startup_program())
+        outs = exe.run(feed={"x": x}, fetch_list=[out])
+
+        saveModel(
+            name,
+            exe,
+            feed_vars=[node_x],
+            fetchlist=[out],
+            inputs=[x],
+            outputs=[outs[0]],
+            target_dir=sys.argv[1],
+        )
+
+
+def main():
+    # Test case 1: float32, 1D array
+    x1 = np.array([0.25, 1, 4, 16], dtype=np.float32)
+    rsqrt("rsqrt_float32_1D", x1)
+
+    # Test case 2: float32, 2D array
+    x2 = np.array([[0.25, 1], [4, 16]], dtype=np.float32)
+    rsqrt("rsqrt_float32_2D", x2)
+
+    x3 = np.random.rand(2, 3, 4, 5).astype(np.float32)
+    rsqrt("rsqrt_float32_4D", x3)
+
+
+if __name__ == "__main__":
+    main()