forked from mindspore-Ecosystem/mindspore
add control test cases for ci
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@ -13,6 +13,7 @@
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# limitations under the License.
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# ============================================================================
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import numpy as np
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import pytest
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from mindspore.common import dtype as mstype
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from mindspore import nn
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from mindspore import Tensor
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@ -70,6 +71,10 @@ def test_forward():
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assert graph_mode_out == pynative_mode_out
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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_backward():
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# Graph Mode
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context.set_context(mode=context.GRAPH_MODE)
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@ -13,6 +13,7 @@
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# limitations under the License.
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# ============================================================================
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import numpy as np
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import pytest
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from mindspore.common import dtype as mstype
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from mindspore import nn
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from mindspore import Tensor
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@ -87,6 +88,10 @@ def test_forward():
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# Problem: Exceed function call depth limit 1000.
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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_backward():
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x = Tensor(np.array(1), mstype.int32)
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y = Tensor(np.array(3), mstype.int32)
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@ -12,6 +12,7 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import pytest
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import mindspore.context as context
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from mindspore import Tensor, ms_function
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from mindspore.common import dtype as mstype
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@ -33,7 +34,10 @@ def hof(x):
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ret = g(x)(x)
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return ret
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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_fun_fun():
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context.set_context(mode=context.GRAPH_MODE)
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x = Tensor([10], mstype.int32)
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