[control flow]update st testcases for while bp

tests/st/control/test_cont_grad.py

@@ -104,6 +104,10 @@ def test_while_with_const_param_grad():
     assert np.allclose(graph_output[0].asnumpy(), expect_one, 0.0001, 0.0001)
     assert np.allclose(graph_output[1].asnumpy(), expect_two, 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_while_with_variable_grad():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -166,7 +170,10 @@ def test_while_with_param_forward():
     expect = np.array([[[6, 8], [10, 12]], [[19, 22], [25, 28]]], dtype=np.int32)
     assert np.allclose(graph_output.asnumpy(), expect, 0.0001, 0.0001)
 
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_while_endless_case():
     """endless case when optimization"""
     class MyWhileNet(nn.Cell):
@@ -235,6 +242,10 @@ def test_while_with_param_grad():
     expect = np.array([[[2, 2], [2, 2]], [[2, 2], [2, 2]]], dtype=np.int32)
     assert np.allclose(graph_output[0].asnumpy(), expect, 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_while_with_param_forward_with_const_branch():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -266,7 +277,10 @@ def test_while_with_param_forward_with_const_branch():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_while_opt_endless():
     """endless during optimization case"""
     class MyWhileNet(nn.Cell):
@@ -307,6 +321,12 @@ def test_while_opt_endless():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+
+@pytest.mark.skip(reason="not supported yet")
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_no_while_call():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -336,7 +356,10 @@ def test_no_while_call():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_while_with_param_grad_with_const_branch():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -377,6 +400,11 @@ def test_while_with_param_grad_with_const_branch():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.skip(reason="not supported yet")
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_for_while_with_param_grad_with_const_branch():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -420,6 +448,10 @@ def test_for_while_with_param_grad_with_const_branch():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_for_while_with_param_grad_basic():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -460,6 +492,10 @@ def test_for_while_with_param_grad_basic():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_for_while_with_param_grad_normal():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -500,6 +536,10 @@ def test_for_while_with_param_grad_normal():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_while_with_param_basic_grad():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -537,6 +577,10 @@ def test_while_with_param_basic_grad():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_while_with_param_basic_grad_mul():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -574,6 +618,10 @@ def test_while_with_param_basic_grad_mul():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_while_with_param_basic_grad_two():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -613,6 +661,10 @@ def test_while_with_param_basic_grad_two():
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
     assert np.allclose(graph_output[1].asnumpy(), pynative_output[1].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_while_with_param_basic_grad_three():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -654,6 +706,10 @@ def test_while_with_param_basic_grad_three():
     assert np.allclose(graph_output[1].asnumpy(), pynative_output[1].asnumpy(), 0.0001, 0.0001)
     assert np.allclose(graph_output[2].asnumpy(), pynative_output[2].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_while_if_with_param_grad():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -694,6 +750,11 @@ def test_while_if_with_param_grad():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.skip(reason="not supported yet")
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_while_with_param_grad_not_enter_while():
     class MyWhileNet(nn.Cell):
         def __init__(self):
@@ -730,6 +791,10 @@ def test_while_with_param_grad_not_enter_while():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_with_param_if_by_if_forward():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):
@@ -762,7 +827,10 @@ def test_with_param_if_by_if_forward():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_with_param_if_by_if_grad_inputs():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):
@@ -801,6 +869,10 @@ def test_with_param_if_by_if_grad_inputs():
     assert np.allclose(graph_output[1].asnumpy(), pynative_output[1].asnumpy(), 0.0001, 0.0001)
     assert np.allclose(graph_output[2].asnumpy(), pynative_output[2].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_with_param_if_by_if_grad_parameter():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):
@@ -838,6 +910,10 @@ def test_with_param_if_by_if_grad_parameter():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_with_param_if_by_if_grad_param_excute_null():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):
@@ -873,6 +949,10 @@ def test_with_param_if_by_if_grad_param_excute_null():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_if_by_if_return_inside_grad():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):
@@ -910,6 +990,10 @@ def test_if_by_if_return_inside_grad():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output[0].asnumpy(), pynative_output[0].asnumpy(), 0.0001, 0.0001)
 
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_if_by_if_forward():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):
@@ -948,7 +1032,10 @@ def test_if_by_if_forward():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_if_by_if_forward_control_tuple_switch():
     """tuple_get from  switch op will generate new switch inside to eliminate tuple_get"""
     class Branch3Net(nn.Cell):
@@ -1012,9 +1099,10 @@ def test_if_by_if_forward_control_tuple_switch():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-
-
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_if_by_if_forward_control_inside_net():
     class Branch3Net(nn.Cell):
         def __init__(self):
@@ -1077,8 +1165,10 @@ def test_if_by_if_forward_control_inside_net():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_if_by_if_forward_use_namespace():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):
@@ -1117,7 +1207,10 @@ def test_if_by_if_forward_use_namespace():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_if_by_if_forward_use_global_op():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):
@@ -1160,7 +1253,10 @@ def test_if_by_if_forward_use_global_op():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_for_with_if_by_if_forward():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):
@@ -1190,8 +1286,10 @@ def test_for_with_if_by_if_forward():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_for_with_if_by_if_forward_namespace():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):
@@ -1224,7 +1322,10 @@ def test_for_with_if_by_if_forward_namespace():
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
 
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_if_by_if_forward_const_branch_inner():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):
@@ -1267,9 +1368,10 @@ def test_if_by_if_forward_const_branch_inner():
     pynative_output = net(idx, end, x)
     assert np.allclose(graph_output.asnumpy(), pynative_output.asnumpy(), 0.0001, 0.0001)
 
-
-
-
+@pytest.mark.level0
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
 def test_if_by_if_forward_all_const_branch():
     class MyIfByIfNet(nn.Cell):
         def __init__(self):