add skip decorator and gpu testcase

mindspore/ccsrc/vm/transform.cc

@@ -127,11 +127,6 @@ void CompileGraph::AddInput(const AnfNodePtr &node) {
     MS_LOG(DEBUG) << "Input node is null " << node->DebugString(true);
     (void)Ref(node);
     return;
-  } else if (node->isa<ValueNode>()) {
-    // Value node maybe reused in different graph or by different nodes,copy the value node to ensure stack correct.
-    auto copy_value_node = NewValueNode(node->cast<ValueNodePtr>()->value());
-    (void)Ref(copy_value_node);
-    return;
   }
   AddInst(Instruction::kInput, Ref(node));
   set_height(height_ + 1);
@@ -393,6 +388,13 @@ int64_t CompileGraph::AddCall(const FuncGraphPtr &graph, const CNodePtr &node) {
   MS_LOG(DEBUG) << "Call:" << Ref(fn) << ", " << height_ << ", " << (size - 1);
   AddInst(Instruction::kCall, Ref(fn));
   Ret(static_cast<int64_t>(size - 1));
+
+  for (size_t i = size - 1; i > 0; i--) {
+    const auto iter = slots_.find(inputs[i]);
+    if (iter != slots_.end() && iter->second >= height_) {
+      slots_.erase(inputs[i]);
+    }
+  }
   return RET_SUCCESS;
 }
 

tests/st/control/inner/test_002_single_for.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 # ============================================================================
 import numpy as np
+import pytest
 from mindspore import context
 from mindspore import Tensor, nn
 from mindspore.common.parameter import Parameter
@@ -165,7 +166,7 @@ def test_single_for_03():
     assert graph_forward_res == pynative_forward_res
     assert graph_backward_res == pynative_backward_res
 
-
+@pytest.mark.skip(reason="not supported side effect")
 def test_single_for_04():
     class SingleForNet(nn.Cell):
         def __init__(self):

tests/st/control/inner/test_010_if_in_if.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ============================================================================
+import pytest
 from mindspore import context
 from mindspore import Tensor, nn
 from mindspore.ops import composite as C
@@ -143,11 +144,13 @@ def test_if_in_if():
     control_flow_if_in_if(IfInIfNet, x)
 
 
+@pytest.mark.skip(reason="not supported side effect")
 def test_if_in_if_01():
     x = Tensor(2, mstype.int32)
     control_flow_if_in_if(IfInIfNet1, x)
 
 
+@pytest.mark.skip(reason="not supported side effect")
 def test_if_in_if_02():
     x = Tensor(2, mstype.int32)
     control_flow_if_in_if(IfInIfNet2, x)

tests/st/control/inner/test_012_if_in_for.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 # ============================================================================
 import numpy as np
+import pytest
 from mindspore.common import dtype as mstype
 from mindspore import nn
 from mindspore import Tensor
@@ -52,6 +53,7 @@ class BackwardNet(nn.Cell):
         return grads
 
 
+@pytest.mark.skip(reason="not supported side effect")
 def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
@@ -66,6 +68,7 @@ def test_forward():
     assert graph_mode_out == pynative_mode_out
 
 
+@pytest.mark.skip(reason="not supported side effect")
 def test_backward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)

tests/st/control/inner/test_032_for_in_for.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 # ============================================================================
 import numpy as np
+import pytest
 from mindspore import context
 from mindspore import Tensor, nn
 from mindspore.common.parameter import Parameter
@@ -21,7 +22,7 @@ from mindspore.ops import operations as P
 from mindspore.common import dtype as mstype
 
 grad_all = C.GradOperation(get_all=True)
-context.set_context(device_target="Ascend")
+context.set_context(device_target="GPU")
 
 
 def test_for_in_for_01():
@@ -76,7 +77,9 @@ def test_for_in_for_01():
     assert graph_forward_res == pynative_forward_res
     assert graph_backward_res == pynative_backward_res
 
-
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
 def test_for_in_for_02():
     class ForInForNet(nn.Cell):
         def __init__(self):

tests/st/control/inner/test_101_if_after_while.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 # ============================================================================
 import numpy as np
+import pytest
 from mindspore.common import dtype as mstype
 from mindspore import nn
 from mindspore import Tensor
@@ -73,6 +74,7 @@ def test_forward():
     assert graph_mode_out == pynative_mode_out
 
 
+@pytest.mark.skip(reason="not supported side effect")
 def test_backward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)

tests/st/control/inner/test_110_if_after_if_in_if.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ============================================================================
+import pytest
 from mindspore import context
 from mindspore import Tensor, nn
 from mindspore.ops import composite as C
@@ -19,7 +20,7 @@ from mindspore.common import dtype as mstype
 from mindspore.common.parameter import Parameter
 
 grad_all = C.GradOperation(get_all=True)
-context.set_context(device_target="Ascend")
+context.set_context(device_target="GPU")
 
 
 class IfAfterIfInIfNet(nn.Cell):
@@ -145,22 +146,27 @@ def control_flow_if_after_if_in_if(input_net, x):
     assert graph_forward_res == pynative_forward_res
     assert graph_backward_res == pynative_backward_res
 
-
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
 def test_if_after_if_in_if():
     x = Tensor(2, mstype.int32)
     control_flow_if_after_if_in_if(IfAfterIfInIfNet, x)
 
 
+@pytest.mark.skip(reason="not supported side effect")
 def test_if_after_if_in_if_01():
     x = Tensor(2, mstype.int32)
     control_flow_if_after_if_in_if(IfAfterIfInIfNet1, x)
 
 
+@pytest.mark.skip(reason="not supported side effect")
 def test_if_after_if_in_if_02():
     x = Tensor(2, mstype.int32)
     control_flow_if_after_if_in_if(IfAfterIfInIfNet2, x)
 
 
+@pytest.mark.skip(reason="not supported side effect")
 def test_if_after_if_in_if_03():
     x = Tensor(2, mstype.int32)
     control_flow_if_after_if_in_if(IfAfterIfInIfNet3, x)

tests/st/control/inner/test_121_if_after_while_in_while.py

@@ -14,6 +14,7 @@
 # ============================================================================
 
 import numpy as np
+import pytest
 from mindspore.common import dtype as mstype
 from mindspore import nn
 from mindspore import Tensor
@@ -21,7 +22,7 @@ from mindspore.ops import composite as C
 from mindspore import context
 from mindspore.common.parameter import Parameter
 
-context.set_context(mode=context.GRAPH_MODE, save_graphs=False, device_target="Ascend")
+context.set_context(mode=context.GRAPH_MODE, save_graphs=False, device_target="GPU")
 
 
 class ForwardNet(nn.Cell):
@@ -73,6 +74,7 @@ def test_forward():
     assert graph_mode_out == pynative_mode_out
 
 
+@pytest.mark.skip(reason="not supported side effect")
 def test_backward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
@@ -122,6 +124,9 @@ class BackwardNetNoAssign(nn.Cell):
 
 
 # This test case has a problem of evaluator endless loop.
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
 def test_backward_no_assign():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)

tests/st/control/inner/test_122_if_after_while_in_for.py

@@ -14,6 +14,7 @@
 # ============================================================================
 
 import numpy as np
+import pytest
 from mindspore.common import dtype as mstype
 from mindspore import nn
 from mindspore import Tensor
@@ -21,7 +22,7 @@ from mindspore.ops import composite as C
 from mindspore import context
 from mindspore.common.parameter import Parameter
 
-context.set_context(mode=context.GRAPH_MODE, save_graphs=False, device_target="Ascend")
+context.set_context(mode=context.GRAPH_MODE, save_graphs=False, device_target="GPU")
 
 
 class ForwardNet(nn.Cell):
@@ -69,6 +70,7 @@ def test_forward():
     assert graph_mode_out == pynative_mode_out
 
 
+@pytest.mark.skip(reason="not supported side effect")
 def test_backward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
@@ -83,3 +85,52 @@ def test_backward():
     pynative_backward_net = BackwardNet(pynative_forward_net)
     pynative_mode_grads = pynative_backward_net(x, y)
     assert graph_mode_grads == pynative_mode_grads
+
+
+class ForwardNetNoAssign(nn.Cell):
+    def __init__(self, max_cycles=10):
+        super(ForwardNetNoAssign, self).__init__()
+        self.max_cycles = max_cycles
+        self.zero = Tensor(np.array(0), mstype.int32)
+        self.weight = Parameter(Tensor(np.array(0), mstype.int32))
+
+    def construct(self, x, y):
+        out = self.zero
+        for _ in range(0, self.max_cycles):
+            while x < y:
+                out = x * y + out
+                x = x + 1
+                #self.weight = x
+        if out > 20:
+            self.weight = out
+            out = out - 20
+        return out, self.weight
+
+class BackwardNetNoAssign(nn.Cell):
+    def __init__(self, net):
+        super(BackwardNetNoAssign, self).__init__(auto_prefix=False)
+        self.forward_net = net
+        self.grad = C.GradOperation(get_all=True)
+
+    def construct(self, *inputs):
+        grads = self.grad(self.forward_net)(*inputs)
+        return grads
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_backward_no_assign():
+    x = Tensor(np.array(1), mstype.int32)
+    y = Tensor(np.array(3), mstype.int32)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_forward_net = ForwardNetNoAssign(max_cycles=3)
+    graph_backward_net = BackwardNetNoAssign(graph_forward_net)
+    graph_mode_grads = graph_backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_forward_net = ForwardNetNoAssign(max_cycles=3)
+    pynative_backward_net = BackwardNetNoAssign(pynative_forward_net)
+    pynative_mode_grads = pynative_backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_330_for_after_for_in_if.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ============================================================================
+import pytest
 from mindspore import context
 from mindspore import Tensor, nn
 from mindspore.ops import composite as C
@@ -21,6 +22,7 @@ from mindspore.common.parameter import Parameter
 grad_all = C.GradOperation(get_all=True)
 context.set_context(device_target="Ascend")
 
+@pytest.mark.skip(reason="not supported side effect")
 def test_for_after_for_in_if():
     class ForAfterForInIfNet(nn.Cell):
         def __init__(self):