fix parallel timeout

tests/ut/python/parallel/test_auto_parallel_double_subgraphs.py

@@ -105,7 +105,7 @@ class TrainStepWarp(nn.Cell):
 
 def test_double_subgraphs():
     _set_multi_subgraphs()
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     context.set_auto_parallel_context(device_num=8, global_rank=0)
     context.set_auto_parallel_context(parallel_mode="auto_parallel")
     net = TrainStepWarp(NetWithLoss(Net()))
@@ -156,7 +156,7 @@ class DatasetLenet():
         return self
 
 def test_double_subgraphs_train():
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     context.set_auto_parallel_context(device_num=1, global_rank=0)
     context.set_auto_parallel_context(parallel_mode="auto_parallel")
     net = TrainStepWarp(NetWithLoss(Net()))

tests/ut/python/parallel/test_auto_parallel_for_loop.py

@@ -118,7 +118,7 @@ _w1 = Tensor(np.ones([512, 128]), dtype=ms.float32)
 
 
 def test_auto_parallel():
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=16, global_rank=0)
     net = Full(_w1, 3)
     net.set_auto_parallel()

tests/ut/python/parallel/test_auto_parallel_for_loop_multi_subgraph.py

@@ -121,7 +121,7 @@ class TrainStepWarp(nn.Cell):
 
 
 def test_double_subgraphs():
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=8, global_rank=0)
     net = TrainStepWarp(NetWithLoss(Net()))
     _set_multi_subgraphs()

tests/ut/python/parallel/test_auto_parallel_for_loop_reshape.py

@@ -125,7 +125,7 @@ _w1 = Tensor(np.ones([512, 128, 1]), dtype=ms.float32)
 
 
 def test_auto_parallel():
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=16, global_rank=0)
     net = Full(_w1, 3)
     net.set_auto_parallel()

tests/ut/python/parallel/test_auto_parallel_for_loop_simplify.py

@@ -83,7 +83,7 @@ _w1 = Tensor(np.ones([512, 128]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     learning_rate = 0.1
     momentum = 0.9
     epoch_size = 2

tests/ut/python/parallel/test_auto_parallel_two_bn.py

@@ -68,7 +68,7 @@ def test_two_bn():
             out = self.block2(out)
             return out
 
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     context.set_auto_parallel_context(device_num=8, global_rank=0)
     context.set_auto_parallel_context(parallel_mode="auto_parallel")
     net = NetWithLoss(Net())

tests/ut/python/parallel/test_broadcast_to.py

@@ -64,7 +64,7 @@ _x2 = Tensor(np.ones([64, 64]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()
@@ -74,7 +74,7 @@ def compile_net(net):
 
 
 def compile_net2(net):
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()

tests/ut/python/parallel/test_concat.py

@@ -80,7 +80,7 @@ w3 = Tensor(np.ones([64, 64, 32]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()

tests/ut/python/parallel/test_embeddinglookup.py

@@ -95,7 +95,7 @@ def test_embeddinglookup_reducescatter_false_grad():
 
 
 def test_embeddinglookup_reducescatter_true_grad():
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     shape = [8, 8]
     offset = 8
     net = GradWrap(NetWithLoss(Net(shape, offset)))

tests/ut/python/parallel/test_eval.py

@@ -52,7 +52,7 @@ _b = Tensor(np.ones([64, 64]), dtype=ms.float32)
 
 
 def test_train_and_eval():
-    context.set_context(save_graphs=True, mode=0)
+    context.set_context(save_graphs=False, mode=0)
     context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=16)
     strategy1 = ((4, 4), (4, 4))
     strategy2 = ((4, 4),)
@@ -69,7 +69,7 @@ def test_train_and_eval():
     context.reset_auto_parallel_context()
 
 def test_train_and_eval_auto():
-    context.set_context(save_graphs=True, mode=0)
+    context.set_context(save_graphs=False, mode=0)
     context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=16)
     strategy1 = ((4, 4), (4, 4))
     strategy2 = ((4, 4),)

tests/ut/python/parallel/test_loss_and_o2_level.py

@@ -63,7 +63,7 @@ _w1 = Tensor(np.ones([512, 128]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     learning_rate = 0.1
     momentum = 0.9
     epoch_size = 2

tests/ut/python/parallel/test_loss_scale.py

@@ -194,7 +194,7 @@ def test_loss_scale():
 
 
 def test_loss_scale2():
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     context.set_auto_parallel_context(parallel_mode=ParallelMode.SEMI_AUTO_PARALLEL, device_num=8)
     predict = Tensor(np.ones([64, 64]), dtype=ms.float32)
     label = Tensor(np.ones([64,]), dtype=ms.int32)

tests/ut/python/parallel/test_manual_embedding_lookup.py

@@ -66,7 +66,7 @@ _b = Tensor(np.ones([8, 8, 8]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     optimizer = LazyAdam(net.trainable_params(), learning_rate=0.1)
     optimizer.sparse_opt.add_prim_attr("primitive_target", "CPU")
     train_net = TrainOneStepCell(net, optimizer)
@@ -113,7 +113,7 @@ def test_normal_split_with_offset():
 
 
 def test_auto_parallel_error():
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=2, global_rank=0)
     net = Net()
     with pytest.raises(RuntimeError):
@@ -121,7 +121,7 @@ def test_auto_parallel_error():
 
 
 def test_auto_parallel():
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=2, global_rank=0)
     net = Net(split_string="fake")
     compile_net(net)

tests/ut/python/parallel/test_manual_gatherv2.py

@@ -60,7 +60,7 @@ _b = Tensor(np.ones([64, 8]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()
@@ -106,7 +106,7 @@ def test_normal_split_with_offset():
 
 
 def test_auto_parallel_error():
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=2, global_rank=0)
     net = Net()
     with pytest.raises(RuntimeError):

tests/ut/python/parallel/test_model_with_loss.py

@@ -63,7 +63,7 @@ _w1 = Tensor(np.ones([512, 128]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     learning_rate = 0.1
     momentum = 0.9
     epoch_size = 2

tests/ut/python/parallel/test_model_without_loss.py

@@ -103,7 +103,7 @@ w3 = Tensor(np.ones([64, 64, 32]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     learning_rate = 0.1
     momentum = 0.9
     epoch_size = 2

tests/ut/python/parallel/test_o2_level.py

@@ -90,7 +90,7 @@ _w2 = Tensor(np.ones([128, 64, 1]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     learning_rate = 0.1
     momentum = 0.9
     epoch_size = 2

tests/ut/python/parallel/test_pack.py

@@ -136,7 +136,7 @@ _x_c = Tensor(np.ones([8, 8, 8]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()
@@ -146,7 +146,7 @@ def compile_net(net):
 
 
 def compile_net1(net):
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()
@@ -156,7 +156,7 @@ def compile_net1(net):
 
 
 def compile_net2(net):
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()
@@ -166,7 +166,7 @@ def compile_net2(net):
 
 
 def compile_net_con(net):
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()

tests/ut/python/parallel/test_parameter_merge.py

@@ -79,7 +79,7 @@ def clean_all_ckpt_files(folder_path):
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     learning_rate = 0.1
     momentum = 0.9
     epoch_size = 2

tests/ut/python/parallel/test_range.py

@@ -74,7 +74,7 @@ _w1 = Tensor(np.ones([64, 8]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     learning_rate = 0.1
     momentum = 0.9
     epoch_size = 2

tests/ut/python/parallel/test_reluv2.py

@@ -40,7 +40,7 @@ _x = Tensor(np.ones([32, 16, 48, 64]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()

tests/ut/python/parallel/test_repeated_calc.py

@@ -73,7 +73,7 @@ def test_tensoradd_reshape_matmul():
     strategy2 = ((8, 1), (1, 8))
     net = GradWrap(NetWithLoss(Net(strategy1, strategy2)))
     context.set_auto_parallel_context(parallel_mode="semi_auto_parallel")
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
 
     x = Tensor(np.ones([32, 8, 16]), dtype=ms.float32)
     y = Tensor(np.ones([32, 8, 16]), dtype=ms.float32)
@@ -99,7 +99,7 @@ def test_two_matmul():
     strategy2 = ((8, 1), (1, 1))
     net = GradWrap(NetWithLoss(Net(strategy1, strategy2)))
     context.set_auto_parallel_context(parallel_mode="semi_auto_parallel")
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
 
     x = Tensor(np.ones([128, 32]), dtype=ms.float32)
     y = Tensor(np.ones([32, 64]), dtype=ms.float32)

tests/ut/python/parallel/test_reshape_optimized.py

@@ -40,7 +40,7 @@ _b = Tensor(np.ones([128, 64, 32]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()

tests/ut/python/parallel/test_reshape_skip_redistribution.py

@@ -43,7 +43,7 @@ _x = Tensor(np.ones([64, 64]), dtype=ms.float32)
 _b = Tensor(np.ones([128, 64, 32]), dtype=ms.float32)
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()

tests/ut/python/parallel/test_split.py

@@ -75,7 +75,7 @@ _x1 = Tensor(np.ones([48, 64, 32]), dtype=ms.float32)
 _w2 = Tensor(np.ones([48, 64, 32]), dtype=ms.float32)
 
 def compile_net(net):
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()
@@ -85,7 +85,7 @@ def compile_net(net):
 
 
 def compile_net1(net):
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()

tests/ut/python/parallel/test_stridedslice.py

@@ -67,7 +67,7 @@ _b = Tensor(np.ones([128, 64, 32]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()

tests/ut/python/parallel/test_tile.py

@@ -60,7 +60,7 @@ _b = Tensor(np.ones([128, 64, 32]), dtype=ms.float32)
 
 
 def compile_net(net):
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()

tests/ut/python/parallel/test_train_and_eval.py

@@ -52,7 +52,7 @@ _b = Tensor(np.ones([64, 64]), dtype=ms.float32)
 
 
 def test_train_and_eval():
-    context.set_context(save_graphs=True, mode=0)
+    context.set_context(save_graphs=False, mode=0)
     context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=16)
     strategy1 = ((4, 4), (4, 4))
     strategy2 = ((4, 4),)

tests/ut/python/parallel/test_two_matmul.py

@@ -141,7 +141,7 @@ def test_matmul_forward_reduce_scatter():
             return out
 
     context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     strategy1 = ((2, 2), (2, 2))
     strategy2 = ((4, 2), (4, 2))
     net = GradWrap(NetWithLoss(Net(strategy1, strategy2)))
@@ -166,7 +166,7 @@ def test_matmul_forward_reduce_scatter_transpose():
             return out
 
     context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=16, global_rank=0)
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     strategy1 = ((2, 4), (2, 4))
     strategy2 = ((8, 2), (8, 2))
     net = GradWrap(NetWithLoss(Net(strategy1, strategy2)))

tests/ut/python/parallel/test_uniform_candidate_sampler.py

@@ -73,7 +73,7 @@ _x = Tensor(np.ones([48, 16]), dtype=ms.int32)
 
 
 def compile_net(net):
-    context.set_context(mode=context.GRAPH_MODE, save_graphs=True)
+    context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
     optimizer = Momentum(net.trainable_params(), learning_rate=0.1, momentum=0.9)
     train_net = TrainOneStepCell(net, optimizer)
     train_net.set_auto_parallel()

tests/ut/python/parallel/test_virtual_dataset_3_input.py

@@ -93,7 +93,7 @@ def test_virtualdataset_cell_3_inputs():
             out = self.matmul2(out, b)
             return out
 
-    context.set_context(save_graphs=True)
+    context.set_context(save_graphs=False)
     context.set_auto_parallel_context(parallel_mode="auto_parallel")
     context.set_auto_parallel_context(device_num=8, global_rank=0)
     net = GradWrap(VirtualDatasetCellTriple(NetWithLoss(Net(None, None, None))))

tests/ut/python/runtest.sh

@@ -41,7 +41,7 @@ if [ $# -eq 1 ]  &&  ([ "$1" == "stage1" ] || [ "$1" == "stage2" ] || [ "$1" ==
 
     elif [ $1 == "stage2" ]; then
         echo "run python parallel"
-        pytest -v $CURRPATH/parallel
+        pytest -s $CURRPATH/parallel/*.py
 
         RET=$?
         if [ ${RET} -ne 0 ]; then
@@ -87,7 +87,7 @@ else
         exit ${RET}
     fi
 
-    pytest -v $CURRPATH/parallel
+    pytest -v $CURRPATH/parallel/*.py
     RET=$?
     if [ ${RET} -ne 0 ]; then
         exit ${RET}