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