Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into graph_quantization

test=develop

paddle/fluid/operators/distributed/CMakeLists.txt

@@ -37,7 +37,7 @@ else()
       variable_response.cc
       collective_client.cc collective_server.cc
       ${BRPC_SRCS}
-    PROTO ${CMAKE_CURRENT_BINARY_DIR}/send_recv.proto
+    PROTO send_recv.proto
     DEPS lod_tensor selected_rows memory)
 
   set(RPC_DEPS sendrecvop_rpc brpc ssl crypto protobuf leveldb snappystream snappy zlib)

paddle/fluid/operators/group_norm_op.cu

@@ -21,20 +21,20 @@ namespace operators {
 
 enum GroupNormKernelFlags { kHasScale = 1, kHasBias = 2 };
 
-#define CHECK_CASE(i, flags, kernel_name, args...)                   \
-  if (i == flags) {                                                  \
-    kernel_name<T, i><<<grid, threads, 0, dev_ctx.stream()>>>(args); \
+#define CHECK_CASE(i, flags, kernel_name, ...)                              \
+  if (i == flags) {                                                         \
+    kernel_name<T, i><<<grid, threads, 0, dev_ctx.stream()>>>(__VA_ARGS__); \
   }
 
 // 0 for no scale, no bias
 // 1 for has scale, no bias
 // 2 for no scale, has bias
 // 3 for has scale, has bias
-#define UNROLL_ALL_CASES(flags, kernel_name, args...) \
-  CHECK_CASE(0, flags, kernel_name, args)             \
-  CHECK_CASE(1, flags, kernel_name, args)             \
-  CHECK_CASE(2, flags, kernel_name, args)             \
-  CHECK_CASE(3, flags, kernel_name, args)
+#define UNROLL_ALL_CASES(flags, kernel_name, ...) \
+  CHECK_CASE(0, flags, kernel_name, __VA_ARGS__)  \
+  CHECK_CASE(1, flags, kernel_name, __VA_ARGS__)  \
+  CHECK_CASE(2, flags, kernel_name, __VA_ARGS__)  \
+  CHECK_CASE(3, flags, kernel_name, __VA_ARGS__)
 
 template <typename T>
 __device__ __inline__ void CudaAtomicAddWithWarp(T* sum, T value) {

python/paddle/fluid/executor.py

@@ -305,7 +305,9 @@ class Executor(object):
     def __init__(self, place):
         self.place = place
         self.program_caches = dict()
-        self.executor = None
+        p = core.Place()
+        p.set_place(self.place)
+        self._default_executor = core.Executor(p)
         self._closed = False
 
     def _get_program_cache(self, program_cache_key):
@@ -397,12 +399,13 @@ class Executor(object):
             >>> ...
             >>> exe.close()
         """
-        if not self._closed and self.executor:
-            self.executor.close()
+        if not self._closed:
+            self._default_executor.close()
             self._closed = True
 
     def _run_parallel(self, program, scope, feed, fetch_list, fetch_var_name,
                       return_numpy):
+        exe = program._executor
         if isinstance(feed, dict):
             feed_tensor_dict = dict()
             for feed_name in feed:
@@ -414,8 +417,7 @@ class Executor(object):
                     feed_tensor.set(feed[feed_name], core.CPUPlace())
                 feed_tensor_dict[feed_name] = feed_tensor
 
-            self.executor.feed_and_split_tensor_into_local_scopes(
-                feed_tensor_dict)
+            exe.feed_and_split_tensor_into_local_scopes(feed_tensor_dict)
         elif isinstance(feed, list) or isinstance(feed, tuple):
             if len(feed) != len(program._places):
                 raise ValueError(
@@ -436,10 +438,10 @@ class Executor(object):
                         tensor = tmp
                     res_dict[feed_name] = tensor
                 res.append(res_dict)
-            self.executor.feed_tensors_into_local_scopes(res)
+            exe.feed_tensors_into_local_scopes(res)
 
         fetch_var_names = list(map(_to_name_str, fetch_list))
-        self.executor.run(fetch_var_names, fetch_var_name)
+        exe.run(fetch_var_names, fetch_var_name)
         arr = scope.find_var(fetch_var_name).get_lod_tensor_array()
 
         if return_numpy:
@@ -511,12 +513,9 @@ class Executor(object):
         compiled = isinstance(program, compiler.CompiledProgram)
         # For backward compatibility, run directly.
         if not compiled:
-            if not self.executor:
-                p = core.Place()
-                p.set_place(self.place)
-                self.executor = core.Executor(p)
             return self._run(
                 program,
+                self._default_executor,
                 feed=feed,
                 fetch_list=fetch_list,
                 feed_var_name=feed_var_name,
@@ -526,7 +525,6 @@ class Executor(object):
                 use_program_cache=use_program_cache)
 
         program._compile(scope, self.place)
-        self.executor = program._executor
         if program._is_data_parallel:
             return self._run_parallel(
                 program,
@@ -536,12 +534,13 @@ class Executor(object):
                 fetch_var_name=fetch_var_name,
                 return_numpy=return_numpy)
         elif program._is_inference:
-            return self._run_inference(program, feed)
+            return self._run_inference(program._executor, feed)
         else:
             # TODO(panyx0718): Can compile program to optimize executor
             # performance.
             return self._run(
                 program._program,
+                self._default_executor,
                 feed=feed,
                 fetch_list=fetch_list,
                 feed_var_name=feed_var_name,
@@ -550,8 +549,8 @@ class Executor(object):
                 return_numpy=return_numpy,
                 use_program_cache=use_program_cache)
 
-    def _run(self, program, feed, fetch_list, feed_var_name, fetch_var_name,
-             scope, return_numpy, use_program_cache):
+    def _run(self, program, exe, feed, fetch_list, feed_var_name,
+             fetch_var_name, scope, return_numpy, use_program_cache):
 
         if feed is None:
             feed = {}
@@ -589,11 +588,11 @@ class Executor(object):
                 fetch_var_name=fetch_var_name)
 
         self._feed_data(program, feed, feed_var_name, scope)
-        self.executor.run(program.desc, scope, 0, True, True)
+        exe.run(program.desc, scope, 0, True, True)
         outs = self._fetch_data(fetch_list, fetch_var_name, scope)
         if return_numpy:
             outs = as_numpy(outs)
         return outs
 
-    def _run_inference(self, program, feed):
-        return self.executor.run(feed)
+    def _run_inference(self, exe, feed):
+        return exe.run(feed)