Revert "Add GraphExecutor bindings removed from torch to torch_xla"

torch_xla/csrc/init_python_bindings.cpp

@@ -12,9 +12,6 @@
 #include "tensorflow/compiler/xla/xla_client/util.h"
 #include "torch/csrc/autograd/utils/wrap_outputs.h"
 #include "torch/csrc/autograd/variable.h"
-#include "torch/csrc/jit/passes/dead_code_elimination.h"
-#include "torch/csrc/jit/passes/lower_tuples.h"
-#include "torch/csrc/jit/python_tracer.h"
 #include "torch_xla/csrc/aten_xla_bridge.h"
 #include "torch_xla/csrc/aten_xla_type.h"
 #include "torch_xla/csrc/device.h"
@@ -546,91 +543,12 @@ void InitXlaTensorBindings(py::module m) {
       py::arg("count_include_pad") = true);
 }
 
-// FIXME: copied from torch/csrc/jit/python_tracer.cpp since it's only available
-// in libtorch_python.so.
-std::shared_ptr<torch::jit::Graph> CreateGraphByTracing(
-    const py::function& func, torch::jit::Stack trace_inputs,
-    const py::function& var_name_lookup_fn, bool force_outplace,
-    const c10::optional<size_t>& num_real_inputs = c10::nullopt) {
-  size_t num_func_inputs = num_real_inputs.value_or(trace_inputs.size());
-  auto enter_info = torch::jit::tracer::enter(std::move(trace_inputs));
-  torch::jit::tracer::getTracingState()->lookup_var_name_fn =
-      [var_name_lookup_fn](
-          const torch::autograd::Variable& var) -> std::string {
-    AutoGIL ag;
-    return py::cast<std::string>(var_name_lookup_fn(var));
-  };
-  torch::jit::tracer::getTracingState()->force_outplace = force_outplace;
-  try {
-    py::tuple py_inputs(num_func_inputs);
-    for (size_t i = 0; i < num_func_inputs; ++i) {
-      py_inputs[i] = py::cast(enter_info.second[i]);
-    }
-    auto out = func(*py_inputs);
-    if (out.ptr() == Py_None) {
-      AT_ERROR(
-          "The traced function didn't return any values! Side-effects are not "
-          "captured in traces, so it would be a no-op.");
-    }
-    torch::jit::tracer::exit({torch::jit::toIValue(out)});
-    auto graph = enter_info.first->graph;
-    EliminateDeadCode(graph);
-    LowerSimpleTuples(graph);
-
-    return graph;
-  } catch (...) {
-    torch::jit::tracer::abandon();
-    throw;
-  }
-}
-
-void InitGraphExecutorBindings(py::module m) {
-  py::class_<torch::jit::GraphExecutor>(m, "GraphExecutor", py::dynamic_attr())
-      .def(py::init([](py::function func, py::tuple inputs,
-                       py::function var_name_lookup_fn, bool optimize,
-                       bool _force_outplace) {
-             auto graph =
-                 CreateGraphByTracing(func, torch::jit::toStack(inputs),
-                                      var_name_lookup_fn, _force_outplace);
-             return torch::jit::GraphExecutor(graph, optimize);
-           }),
-           py::arg("func"), py::arg("inputs"), py::arg("var_name_lookup_fn"),
-           py::arg("optimize") = true, py::arg("_force_outplace") = false)
-      .def(
-          py::init([](std::shared_ptr<torch::jit::Graph> graph, bool optimize) {
-            return torch::jit::GraphExecutor(std::move(graph), optimize);
-          }),
-          py::arg("graph"), py::arg("optimize") = true)
-      .def(
-          "graph_for",
-          [](torch::jit::GraphExecutor& ge, py::args args) {
-            return ge.graphFor(torch::jit::evilDeprecatedBadCreateStackDoNotUse(
-                args, ge.graph()->inputs()));
-          })
-      .def_property_readonly(
-          "graph", [](torch::jit::GraphExecutor& ge) { return ge.graph(); })
-      .def("get_debug_state",
-           [](torch::jit::GraphExecutor& ge) { return ge.getDebugState(); })
-      .def("__call__",
-           [](torch::jit::GraphExecutor& ge, py::args args) -> py::object {
-             const auto& graph = ge.graph();
-             auto stack = torch::jit::evilDeprecatedBadCreateStackDoNotUse(
-                 args, graph->inputs());
-             {
-               AutoNoGIL no_gil_guard;
-               ge.run(stack);
-             }
-             return torch::jit::createPyObjectForStack(std::move(stack));
-           });
-}
-
 }  // namespace
 
 void InitXlaBindings(py::module m) {
   InitXlaModuleBindings(m);
   InitXlaPassesBindings(m);
   InitXlaTensorBindings(m);
-  InitGraphExecutorBindings(m);
 }
 
 }  // namespace torch_xla