!15462 [ME][Control]Add assert of inner testcases

From: @chenfei52
Reviewed-by: @zh_qh,@ginfung
Signed-off-by: @zh_qh

tests/st/control/inner/test_011_if_in_while.py

@@ -43,7 +43,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -54,8 +54,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -63,5 +68,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_012_if_in_for.py

@@ -40,7 +40,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -51,8 +51,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -60,5 +65,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_020_while_in_if.py

@@ -44,7 +44,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -55,8 +55,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -64,5 +69,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_101_if_after_while.py

@@ -44,7 +44,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -55,8 +55,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -64,5 +69,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_111_if_after_if_in_while.py

@@ -45,7 +45,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -56,8 +56,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -65,5 +70,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_120_if_after_while_in_if.py

@@ -46,7 +46,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -57,8 +57,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -66,5 +71,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_121_if_after_while_in_while.py

@@ -47,7 +47,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -58,8 +58,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -67,5 +72,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_122_if_after_while_in_for.py

@@ -31,10 +31,10 @@ class ForwardNet(nn.Cell):
 
     def construct(self, x, y):
         out = self.zero
-        while x < y:
-            for _ in range(0, self.max_cycles):
+        for _ in range(0, self.max_cycles):
+            while x < y:
                 out = x * y + out
-            x = x + 1
+                x = x + 1
         if out > 20:
             out = out - 20
         return out
@@ -44,7 +44,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -55,8 +55,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -64,5 +69,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_200_while_after_if.py

@@ -44,7 +44,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -55,8 +55,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -64,5 +69,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_210_while_after_if_in_if.py

@@ -45,7 +45,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -56,8 +56,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -65,5 +70,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_211_while_after_if_in_while.py

@@ -45,7 +45,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -56,8 +56,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -65,5 +70,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=10)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_212_while_after_if_in_for.py

@@ -37,6 +37,7 @@ class ForwardNet(nn.Cell):
                 out = x * y + out
         while i < self.max_cycles:
             out = out + 10
+            i = i + 1
         return out
 
 
@@ -44,7 +45,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -52,17 +53,28 @@ class BackwardNet(nn.Cell):
 
 
 def test_forward():
-    x = Tensor(np.array(1), mstype.int32)
-    y = Tensor(np.array(3), mstype.int32)
-    forward_net = ForwardNet(max_cycles=10)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    x = Tensor(np.array(3), mstype.int32)
+    y = Tensor(np.array(5), mstype.int32)
+    forward_net = ForwardNet(max_cycles=3)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
+
 
 
 def test_backward():
-    x = Tensor(np.array(1), mstype.int32)
-    y = Tensor(np.array(3), mstype.int32)
-    forward_net = ForwardNet(max_cycles=10)
+    x = Tensor(np.array(3), mstype.int32)
+    y = Tensor(np.array(5), mstype.int32)
+    forward_net = ForwardNet(max_cycles=3)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_220_while_after_while_in_if.py

@@ -46,7 +46,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -57,8 +57,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -66,5 +71,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads

tests/st/control/inner/test_230_while_after_for_in_if.py

@@ -43,7 +43,7 @@ class BackwardNet(nn.Cell):
     def __init__(self, net):
         super(BackwardNet, self).__init__(auto_prefix=False)
         self.forward_net = net
-        self.grad = C.GradOperation()
+        self.grad = C.GradOperation(get_all=True)
 
     def construct(self, *inputs):
         grads = self.grad(self.forward_net)(*inputs)
@@ -54,8 +54,13 @@ def test_forward():
     x = Tensor(np.array(1), mstype.int32)
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
-    out = forward_net(x, y)
-    print("forward out:", out)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_out = forward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_out = forward_net(x, y)
+    assert graph_mode_out == pynative_mode_out
 
 
 def test_backward():
@@ -63,5 +68,10 @@ def test_backward():
     y = Tensor(np.array(3), mstype.int32)
     forward_net = ForwardNet(max_cycles=3)
     backward_net = BackwardNet(forward_net)
-    grads = backward_net(x, y)
-    print("grads:", grads)
+    # Graph Mode
+    context.set_context(mode=context.GRAPH_MODE)
+    graph_mode_grads = backward_net(x, y)
+    # Pynative Mode
+    context.set_context(mode=context.PYNATIVE_MODE)
+    pynative_mode_grads = backward_net(x, y)
+    assert graph_mode_grads == pynative_mode_grads