pytorch · eqy · Sep 22, 2022 · Sep 23, 2022 · Sep 23, 2022 · Sep 29, 2022
diff --git a/aten/src/ATen/cuda/CUDAGraph.cpp b/aten/src/ATen/cuda/CUDAGraph.cpp
@@ -8,6 +8,8 @@
 namespace at {
 namespace cuda {
 
+static bool _cuda_graphs_debug = false;
+
 MempoolId_t graph_pool_handle() {
 #if defined(CUDA_VERSION) && CUDA_VERSION >= 11000
   // uuid count starts at 1. 0 is reserved to mean "wasn't set by graph_pool_handle".
@@ -16,7 +18,7 @@ MempoolId_t graph_pool_handle() {
   // cudaStreamGetCaptureInfo id_s in capture_begin.
   return {0, uuid++};
 #else
-  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and not yet supported on ROCM");
+  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and is not yet supported on ROCM");
   return {0, 0};
 #endif
 }
@@ -46,7 +48,7 @@ CUDAGraph::CUDAGraph()
   // CUDAStreams may not be default-constructed.
   : capture_stream_(at::cuda::getCurrentCUDAStream()) {
 #if (defined(CUDA_VERSION) && CUDA_VERSION < 11000) || defined(USE_ROCM)
-  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and not yet supported on ROCM");
+  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and is not yet supported on ROCM");
 #endif
 }
 
@@ -122,7 +124,7 @@ void CUDAGraph::capture_begin(MempoolId_t pool/*=0*/) {
   // kernel will end up as part of the capture or not.
   c10::cuda::CUDACachingAllocator::notifyCaptureBegin(capture_dev_, id_, mempool_id_);
 #else
-  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and not yet supported on ROCM");
+  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and is not yet supported on ROCM");
 #endif
 }
 
@@ -186,12 +188,17 @@ void CUDAGraph::capture_end() {
                  "attempted to be captured on wrong device or stream.");
   }
 
-  // Now that we've instantiated graph_ into graph_exec_,
-  // we don't need graph_ anymore.
-  AT_CUDA_CHECK(cudaGraphDestroy(graph_));
-  has_graph_ = false;
+  // check if debug path is set
+  if (!_cuda_graphs_debug) {
+    // Now that we've instantiated graph_ into graph_exec_,
+    // we don't need graph_ anymore.
+    AT_CUDA_CHECK(cudaGraphDestroy(graph_));
+    has_graph_ = false;
+  } else {
+    TORCH_WARN("DEBUG: TORCH_CUDAGRAPHS_DEBUG_PATH detected. graph_ will not be freed until debug_dump is called.");
+  }
 #else
-  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and not yet supported on ROCM");
+  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and is not yet supported on ROCM");
 #endif
 }
 
@@ -226,7 +233,33 @@ void CUDAGraph::replay() {
     AT_CUDA_CHECK(cudaDeviceSynchronize());
   }
 #else
-  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and not yet supported on ROCM");
+  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and is not yet supported on ROCM");
+#endif
+}
+
+void CUDAGraph::enable_debug_mode() {
+#if defined(CUDA_VERSION) && CUDA_VERSION >= 11000
+  _cuda_graphs_debug = true;
+#else
+  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and is not yet supported on ROCM");
+#endif
+
+}
+
+void CUDAGraph::debug_dump(const std::string& debug_path) {
+#if defined(CUDA_VERSION) && CUDA_VERSION >= 11000
+  if (_cuda_graphs_debug) {
+    TORCH_WARN("DEBUG: calling debug_dump()");
+    if (has_graph_) {
+      TORCH_WARN("DEBUG: calling cudaGraphDebugDotPrint() with ", debug_path);
+      C10_CUDA_CHECK_WARN(cudaGraphDebugDotPrint(graph_, debug_path.c_str(), 1<<10)); // most verbose output
+      AT_CUDA_CHECK(cudaGraphDestroy(graph_));
+    }
+  } else {
+    TORCH_WARN("CUDA Graphs debug not enabled, set with torch._C._cuda_enable_graphs_debug_mode");
+  }
+#else
+  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and is not yet supported on ROCM");
 #endif
 }
 
@@ -262,7 +295,7 @@ void CUDAGraph::reset() {
     C10_CUDA_CHECK_WARN(cudaGraphExecDestroy(graph_exec_));
   }
 #else
-  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and not yet supported on ROCM");
+  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and is not yet supported on ROCM");
 #endif
 }
 
@@ -272,7 +305,7 @@ MempoolId_t CUDAGraph::pool() {
   TORCH_CHECK(has_graph_exec_,
               "Called CUDAGraph::pool() without a preceding successful capture.");
 #else
-  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and not yet supported on ROCM");
+  TORCH_CHECK(false, "CUDA graphs may only be used in Pytorch built with CUDA >= 11.0 and is not yet supported on ROCM");
 #endif
   return mempool_id_;
 }

diff --git a/aten/src/ATen/cuda/CUDAGraph.h b/aten/src/ATen/cuda/CUDAGraph.h
@@ -24,6 +24,8 @@ struct TORCH_CUDA_CPP_API CUDAGraph {
   void replay();
   void reset();
   MempoolId_t pool();
+  void enable_debug_mode();
+  void debug_dump(const std::string& debug_path);
 
   protected:
 #if defined(CUDA_VERSION) && CUDA_VERSION >= 11000

diff --git a/torch/_C/__init__.pyi.in b/torch/_C/__init__.pyi.in
@@ -1306,6 +1306,9 @@ class _CUDAGraph:
     def replay(self) -> None: ...
     def reset(self) -> None: ...
     def pool(self) -> Tuple[_int, _int]: ...
+    def enable_debug_mode(self) -> None: ...
+    def debug_dump(self,
+                   debug_path: str) -> None: ...
 
 def _cuda_isCurrentStreamCapturing() -> _bool: ...
 

diff --git a/torch/csrc/cuda/Graph.cpp b/torch/csrc/cuda/Graph.cpp
@@ -48,5 +48,19 @@ void THCPGraph_init(PyObject* module) {
       .def(
           "pool",
           torch::wrap_pybind_function(&at::cuda::CUDAGraph::pool),
-          py::call_guard<py::gil_scoped_release>());
+          py::call_guard<py::gil_scoped_release>())
+      .def(
+          "debug_dump",
+          torch::wrap_pybind_function(&::at::cuda::CUDAGraph::debug_dump),
+          py::call_guard<py::gil_scoped_release>())
+      .def(
+          "enable_debug_mode",
+          torch::wrap_pybind_function(
+              &::at::cuda::CUDAGraph::enable_debug_mode),
+          py::call_guard<py::gil_scoped_release>())
+      .def(
+          "debug_dump",
+          torch::wrap_pybind_function(&::at::cuda::CUDAGraph::debug_dump),
+          py::call_guard<py::gil_scoped_release>(),
+          py::arg("debug_path"));
 }
diff --git a/torch/cuda/graphs.py b/torch/cuda/graphs.py
@@ -100,6 +100,22 @@ def pool(self):
         """
         return super(CUDAGraph, self).pool()
 
+    def enable_debug_mode(self):
+        r"""
+        Enables debugging mode for CUDAGraph.debug_dump.
+        """
+        return super(CUDAGraph, self).enable_debug_mode()
+
+    def debug_dump(self, debug_path):
+        r"""
+        Arguments:
+            debug_path (required): Path to dump the graph to.
+
+        Calls a debugging function to dump the graph if the debugging is
+        enabled via CUDAGraph.enable_debug_mode()
+        """
+        return super(CUDAGraph, self).debug_dump(debug_path)
+
 
 class graph(object):
     r"""