Add checking for the fetch_list of Executor.run (#18957)

* update exe.run

paddle/fluid/API.spec

@@ -38,7 +38,7 @@ paddle.fluid.DistributeTranspilerConfig.__init__
 paddle.fluid.ParallelExecutor ('paddle.fluid.parallel_executor.ParallelExecutor', ('document', '2b4d2e859f2e0c6161f4fed995f7956d'))
 paddle.fluid.ParallelExecutor.__init__ (ArgSpec(args=['self', 'use_cuda', 'loss_name', 'main_program', 'share_vars_from', 'exec_strategy', 'build_strategy', 'num_trainers', 'trainer_id', 'scope'], varargs=None, keywords=None, defaults=(None, None, None, None, None, 1, 0, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.ParallelExecutor.drop_local_exe_scopes (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '77c739744ea5708b80fb1b37cc89db40'))
-paddle.fluid.ParallelExecutor.run (ArgSpec(args=['self', 'fetch_list', 'feed', 'feed_dict', 'return_numpy'], varargs=None, keywords=None, defaults=(None, None, True)), ('document', '33ce6ec50f8eeb05d340e6b114b026fd'))
+paddle.fluid.ParallelExecutor.run (ArgSpec(args=['self', 'fetch_list', 'feed', 'feed_dict', 'return_numpy'], varargs=None, keywords=None, defaults=(None, None, True)), ('document', '0af092676e5b1320bb4232396154ce4b'))
 paddle.fluid.create_lod_tensor (ArgSpec(args=['data', 'recursive_seq_lens', 'place'], varargs=None, keywords=None, defaults=None), ('document', 'b82ea20e2dc5ff2372e0643169ca47ff'))
 paddle.fluid.create_random_int_lodtensor (ArgSpec(args=['recursive_seq_lens', 'base_shape', 'place', 'low', 'high'], varargs=None, keywords=None, defaults=None), ('document', '74dc6d23185d90a7a50fbac19f5b65fb'))
 paddle.fluid.DataFeedDesc ('paddle.fluid.data_feed_desc.DataFeedDesc', ('document', '43877a0d9357db94d3dbc7359cbe8c73'))

python/paddle/fluid/contrib/slim/graph/executor.py

@@ -44,12 +44,12 @@ class SlimGraphExecutor(object):
         feed = None
         if data is not None:
             feeder = DataFeeder(
-                feed_list=graph.in_nodes.values(),
+                feed_list=list(graph.in_nodes.values()),
                 place=self.place,
                 program=graph.program)
             feed = feeder.feed(data)
 
-        fetch_list = graph.out_nodes.values()
+        fetch_list = list(graph.out_nodes.values())
         program = graph.compiled_graph if graph.compiled_graph else graph.program
         results = self.exe.run(program,
                                scope=scope,

python/paddle/fluid/executor.py

@@ -18,6 +18,7 @@ import logging
 import os
 import multiprocessing
 import sys
+import warnings
 import numpy as np
 from .wrapped_decorator import signature_safe_contextmanager
 import six
@@ -611,17 +612,30 @@ class Executor(object):
         except Exception as e:
             if not isinstance(e, core.EOFException):
                 print("An exception was thrown!\n {}".format(str(e)))
-            raise e
+            six.reraise(*sys.exc_info())
 
     def _run_impl(self, program, feed, fetch_list, feed_var_name,
                   fetch_var_name, scope, return_numpy, use_program_cache):
-
         if self._closed:
             raise RuntimeError("Attempted to use a closed Executor")
 
+        if program is None:
+            program = default_main_program()
+        if isinstance(program,Program) and \
+                        len(program.global_block().ops) == 0:
+            warnings.warn("The current program is empty.")
+
         if scope is None:
             scope = global_scope()
-        if fetch_list is None:
+
+        if fetch_list is not None:
+            if isinstance(fetch_list, Variable) or isinstance(fetch_list, str):
+                fetch_list = [fetch_list]
+            assert isinstance(fetch_list, tuple) or isinstance(fetch_list, list), \
+                "Currently , The fetch_list type only should be list or tuple, \n"\
+                "but the input type is {}. For more information please refer to \n"\
+                "the executor.run(...).".format(type(fetch_list))
+        else:
             fetch_list = []
 
         compiled = isinstance(program, compiler.CompiledProgram)
@@ -679,9 +693,8 @@ class Executor(object):
             raise TypeError(
                 "feed requires dict as its Parameter. But you passed in %s" %
                 (type(feed)))
-        if program is None:
-            program = default_main_program()
 
+        assert program is not None, "The program should not be Empty"
         if not isinstance(program, Program):
             raise TypeError(
                 "Executor requires Program as its Parameter. But you passed in %s"

python/paddle/fluid/parallel_executor.py

@@ -180,7 +180,7 @@ class ParallelExecutor(object):
 
         The feed parameter can be a dict or a list. If feed is a dict, the
         feed data will be split into multiple devices. If feed is a list, we
-        assume the data has been splitted into multiple devices, the each
+        assume the data has been split into multiple devices, the each
         element in the list will be copied to each device directly.
 
         Examples:
@@ -212,7 +212,6 @@ class ParallelExecutor(object):
                   loss = fluid.layers.mean(hidden)
                   fluid.optimizer.SGD(learning_rate=0.01).minimize(loss)
 
-              startup_program.random_seed=1
               exe.run(startup_program)
 
               train_exe = fluid.ParallelExecutor(use_cuda=use_cuda,
@@ -239,7 +238,7 @@ class ParallelExecutor(object):
         Args:
             fetch_list(list): The fetched variable names
             feed(list|dict|None): The feed variables. If the feed is a dict,
-                tensors in that dict will be splitted into each devices. If
+                tensors in that dict will be split into each devices. If
                 the feed is a list, each element of the list will be copied
                 to each device. Default None.
             feed_dict: Alias for feed parameter, for backward compatibility.