forked from huawei/mindspore2022
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@ -88,7 +88,7 @@ class GRUWeightBias():
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return w_ih_list, w_hh_list, b_ih_list, b_hh_list
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@pytest.mark.level1
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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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@ -129,7 +129,8 @@ def test_sit_gru_forward_input_3_32_32_is_32_hs_16():
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assert np.allclose(out.asnumpy(), out_pynative.asnumpy(), 0.001, 0.001)
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assert np.allclose(hy.asnumpy(), hy_pynative.asnumpy(), 0.001, 0.001)
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@pytest.mark.level1
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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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@ -87,7 +87,8 @@ class LSTMWeightBias():
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b_hh_list = ParameterTuple(b_hh_list)
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return w_ih_list, w_hh_list, b_ih_list, b_hh_list
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@pytest.mark.level1
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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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@ -131,7 +132,8 @@ def test_sit_lstm_forward_input_3_32_32_is_32_hs_16():
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assert np.allclose(hy.asnumpy(), hy_pynative.asnumpy(), 0.002, 0.002)
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assert np.allclose(cy.asnumpy(), cy_pynative.asnumpy(), 0.002, 0.002)
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@pytest.mark.level1
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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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