Expose relu and relup

doc/changelog.rst

@@ -9,6 +9,10 @@ Changelog
 New
 ~~~
 
+- Add a model for feed-forward neural networks
+  (`#142 <https://github.com/bluescarni/heyoka.py/pull/142>`__).
+- Implement (leaky) ``ReLU`` and its derivative in the expression
+  system (`#141 <https://github.com/bluescarni/heyoka.py/pull/141>`__).
 - Implement the eccentric longitude :math:`F` in the expression
   system (`#140 <https://github.com/bluescarni/heyoka.py/pull/140>`__).
 - Implement the delta eccentric anomaly :math:`\Delta E` in the expression
@@ -19,6 +23,8 @@ New
   (`#140 <https://github.com/bluescarni/heyoka.py/pull/140>`__).
 - New example notebook implementing Lagrange propagation
   (`#140 <https://github.com/bluescarni/heyoka.py/pull/140>`__).
+- New example notebook on the continuation of periodic orbits
+  in the CR3BP (`#97 <https://github.com/bluescarni/heyoka.py/pull/97>`__).
 
 Changes
 ~~~~~~~

heyoka/_test_expression.py

@@ -334,3 +334,18 @@ def test_fix_unfix(self):
         self.assertEqual(fix_nn(expression(1.1)), expression(1.1))
         self.assertEqual(unfix(fix(x + y)), x + y)
         self.assertEqual(unfix(arg=[fix(x + fix(y)), fix(x - fix(y))]), [x + y, x - y])
+
+    def test_relu_wrappers(self):
+        from . import make_vars, leaky_relu, leaky_relup, relu, relup
+
+        x, y = make_vars("x", "y")
+
+        self.assertEqual(leaky_relu(0.)(x), relu(x))
+        self.assertEqual(leaky_relup(0.)(x), relup(x))
+        self.assertEqual(leaky_relu(0.1)(x+y), relu(x+y,0.1))
+        self.assertEqual(leaky_relup(0.1)(x+y), relup(x+y,0.1))
+
+        self.assertEqual(leaky_relu(0.)(x*y), relu(x*y))
+        self.assertEqual(leaky_relup(0.)(x*y), relup(x*y))
+        self.assertEqual(leaky_relu(0.1)(x*y+y), relu(x*y+y,0.1))
+        self.assertEqual(leaky_relup(0.1)(x*y+y), relup(x*y+y,0.1))

heyoka/_test_sympy.py

@@ -294,6 +294,12 @@ def test_func_conversion(self):
             to_sympy(core.kepDE(hx, hy, hz)), spy.Function("heyoka_kepDE")(x, y, z)
         )
 
+        # relu/relup.
+        self.assertEqual(to_sympy(core.relu(hx)), spy.Piecewise((x, x > 0), (0., True)))
+        self.assertEqual(to_sympy(core.relup(hx)), spy.Piecewise((1., x > 0), (0., True)))
+        self.assertEqual(to_sympy(core.relu(hx, 0.1)), spy.Piecewise((x, x > 0), (x*0.1, True)))
+        self.assertEqual(to_sympy(core.relup(hx, 0.1)), spy.Piecewise((1., x > 0), (0.1, True)))
+
         self.assertEqual(-1.0 * hx, from_sympy(-x))
         self.assertEqual(to_sympy(-hx), -x)
 

heyoka/expose_expression.cpp

@@ -278,23 +278,34 @@ void expose_expression(py::module_ &m)
     m.def("prod", &hey::prod, "terms"_a);
 
     // NOTE: need explicit casts for sqrt and exp due to the presence of overloads for number.
-    m.def("sqrt", static_cast<hey::expression (*)(hey::expression)>(&hey::sqrt));
-    m.def("exp", static_cast<hey::expression (*)(hey::expression)>(&hey::exp));
-    m.def("log", &hey::log);
-    m.def("sin", &hey::sin);
-    m.def("cos", &hey::cos);
-    m.def("tan", &hey::tan);
-    m.def("asin", &hey::asin);
-    m.def("acos", &hey::acos);
-    m.def("atan", &hey::atan);
-    m.def("sinh", &hey::sinh);
-    m.def("cosh", &hey::cosh);
-    m.def("tanh", &hey::tanh);
-    m.def("asinh", &hey::asinh);
-    m.def("acosh", &hey::acosh);
-    m.def("atanh", &hey::atanh);
-    m.def("sigmoid", &hey::sigmoid);
-    m.def("erf", &hey::erf);
+    m.def("sqrt", static_cast<hey::expression (*)(hey::expression)>(&hey::sqrt), "arg"_a);
+    m.def("exp", static_cast<hey::expression (*)(hey::expression)>(&hey::exp), "arg"_a);
+    m.def("log", &hey::log, "arg"_a);
+    m.def("sin", &hey::sin, "arg"_a);
+    m.def("cos", &hey::cos, "arg"_a);
+    m.def("tan", &hey::tan, "arg"_a);
+    m.def("asin", &hey::asin, "arg"_a);
+    m.def("acos", &hey::acos, "arg"_a);
+    m.def("atan", &hey::atan, "arg"_a);
+    m.def("sinh", &hey::sinh, "arg"_a);
+    m.def("cosh", &hey::cosh, "arg"_a);
+    m.def("tanh", &hey::tanh, "arg"_a);
+    m.def("asinh", &hey::asinh, "arg"_a);
+    m.def("acosh", &hey::acosh, "arg"_a);
+    m.def("atanh", &hey::atanh, "arg"_a);
+    m.def("sigmoid", &hey::sigmoid, "arg"_a);
+    m.def("erf", &hey::erf, "arg"_a);
+    m.def("relu", &hey::relu, "arg"_a, "slope"_a = 0.);
+    m.def("relup", &hey::relup, "arg"_a, "slope"_a = 0.);
+
+    // Leaky relu wrappers.
+    py::class_<hey::leaky_relu> lr_class(m, "leaky_relu", py::dynamic_attr{});
+    lr_class.def(py::init([](double slope) { return hey::leaky_relu(slope); }), "slope"_a);
+    lr_class.def("__call__", &hey::leaky_relu::operator(), "arg"_a);
+
+    py::class_<hey::leaky_relup> lrp_class(m, "leaky_relup", py::dynamic_attr{});
+    lrp_class.def(py::init([](double slope) { return hey::leaky_relup(slope); }), "slope"_a);
+    lrp_class.def("__call__", &hey::leaky_relup::operator(), "arg"_a);
 
     // NOTE: when exposing multivariate functions, we want to be able to pass
     // in numerical arguments for convenience. Thus, we expose such functions taking

heyoka/setup_sympy.cpp

@@ -308,6 +308,55 @@ void setup_sympy(py::module &m)
         auto sympy_kepDE = py::object(detail::spy->attr("Function")("heyoka_kepDE"));
         detail::fmap[typeid(hy::detail::kepDE_impl)] = sympy_kepDE;
 
+        // relu, relup and leaky variants.
+        // NOTE: these are implemented as piecewise functions:
+        // https://medium.com/@mathcube7/piecewise-functions-in-pythons-sympy-83f857948d3
+        detail::fmap[typeid(hy::detail::relu_impl)]
+            = [](std::unordered_map<const void *, py::object> &func_map, const hy::func &f) -> py::object {
+            assert(f.args().size() == 1u);
+
+            // Convert the argument to SymPy.
+            auto s_arg = detail::to_sympy_impl(func_map, f.args()[0]);
+
+            // Fetch the slope value.
+            const auto slope = f.extract<hy::detail::relu_impl>()->get_slope();
+
+            // Create the condition arg > 0.
+            auto cond = s_arg.attr("__gt__")(0);
+
+            // Fetch the piecewise function.
+            auto pw = detail::spy->attr("Piecewise");
+
+            if (slope == 0) {
+                return pw(py::make_tuple(s_arg, cond), py::make_tuple(0., true));
+            } else {
+                return pw(py::make_tuple(s_arg, cond), py::make_tuple(py::cast(slope) * s_arg, true));
+            }
+        };
+
+        detail::fmap[typeid(hy::detail::relup_impl)]
+            = [](std::unordered_map<const void *, py::object> &func_map, const hy::func &f) -> py::object {
+            assert(f.args().size() == 1u);
+
+            // Convert the argument to SymPy.
+            auto s_arg = detail::to_sympy_impl(func_map, f.args()[0]);
+
+            // Fetch the slope value.
+            const auto slope = f.extract<hy::detail::relup_impl>()->get_slope();
+
+            // Create the condition arg > 0.
+            auto cond = s_arg.attr("__gt__")(0);
+
+            // Fetch the piecewise function.
+            auto pw = detail::spy->attr("Piecewise");
+
+            if (slope == 0) {
+                return pw(py::make_tuple(1., cond), py::make_tuple(0., true));
+            } else {
+                return pw(py::make_tuple(1., cond), py::make_tuple(slope, true));
+            }
+        };
+
         // sigmoid.
         detail::fmap[typeid(hy::detail::sigmoid_impl)]
             = [](std::unordered_map<const void *, py::object> &func_map, const hy::func &f) {