!4916 fix generator_dataset hangs and test_graphdata_distributed.py failing randomly

Merge pull request !4916 from heleiwang/gnn_fix_bug

mindspore/dataset/engine/datasets.py

@@ -3222,12 +3222,14 @@ def _generator_worker_loop(dataset, idx_queue, result_queue, eoe, eof):
     while True:
         # Fetch index, block
         try:
-            idx = idx_queue.get(timeout=10)
+            # Index is generated very fast, so the timeout is very short
+            idx = idx_queue.get(timeout=0.01)
         except KeyboardInterrupt:
             raise Exception("Generator worker receives KeyboardInterrupt")
         except queue.Empty:
             if eof.is_set() or eoe.is_set():
-                raise Exception("Generator worker receives queue.Empty")
+                return
+            # If eoe or eof is not set, continue to get data from idx_queue
             continue
         if idx is None:
             # When the queue is out of scope from master process, a None item can be fetched from the queue.
@@ -3239,10 +3241,17 @@ def _generator_worker_loop(dataset, idx_queue, result_queue, eoe, eof):
         # Fetch data, any exception from __getitem__ will terminate worker and timeout master process
         result = dataset[idx]
         # Send data, block
-        try:
-            result_queue.put(result)
-        except KeyboardInterrupt:
-            raise Exception("Generator worker receives KeyboardInterrupt")
+        while True:
+            try:
+                result_queue.put(result, timeout=5)
+            except KeyboardInterrupt:
+                raise Exception("Generator worker receives KeyboardInterrupt")
+            except queue.Full:
+                if eof.is_set():
+                    return
+                # If eof is not set, continue to put data to result_queue
+                continue
+            break
         del result, idx
         if eoe.is_set() and idx_queue.empty():
             return

mindspore/dataset/engine/validators.py

@@ -929,10 +929,10 @@ def check_split(method):
 
 
 def check_hostname(hostname):
-    if len(hostname) > 255:
+    if not hostname or len(hostname) > 255:
         return False
     if hostname[-1] == ".":
-        hostname = hostname[:-1] # strip exactly one dot from the right, if present
+        hostname = hostname[:-1]  # strip exactly one dot from the right, if present
     allowed = re.compile("(?!-)[A-Z\\d-]{1,63}(?<!-)$", re.IGNORECASE)
     return all(allowed.match(x) for x in hostname.split("."))
 
@@ -952,7 +952,7 @@ def check_gnn_graphdata(method):
             raise ValueError("The hostname is illegal")
         type_check(working_mode, (str,), "working_mode")
         if working_mode not in {'local', 'client', 'server'}:
-            raise ValueError("Invalid working mode")
+            raise ValueError("Invalid working mode, please enter 'local', 'client' or 'server'")
         type_check(port, (int,), "port")
         check_value(port, (1024, 65535), "port")
         type_check(num_client, (int,), "num_client")

tests/ut/python/dataset/test_graphdata_distributed.py

@@ -23,12 +23,12 @@ from mindspore import log as logger
 DATASET_FILE = "../data/mindrecord/testGraphData/testdata"
 
 
-def graphdata_startserver():
+def graphdata_startserver(server_port):
     """
     start graphdata server
     """
     logger.info('test start server.\n')
-    ds.GraphData(DATASET_FILE, 1, 'server')
+    ds.GraphData(DATASET_FILE, 1, 'server', port=server_port)
 
 
 class RandomBatchedSampler(ds.Sampler):
@@ -83,11 +83,13 @@ def test_graphdata_distributed():
     """
     logger.info('test distributed.\n')
 
-    p1 = Process(target=graphdata_startserver)
+    server_port = random.randint(10000, 60000)
+
+    p1 = Process(target=graphdata_startserver, args=(server_port,))
     p1.start()
     time.sleep(2)
 
-    g = ds.GraphData(DATASET_FILE, 1, 'client')
+    g = ds.GraphData(DATASET_FILE, 1, 'client', port=server_port)
     nodes = g.get_all_nodes(1)
     assert nodes.tolist() == [101, 102, 103, 104, 105, 106, 107, 108, 109, 110]
     row_tensor = g.get_node_feature(nodes.tolist(), [1, 2, 3])