forked from OSSInnovation/mindspore
!14535 Modify the results in the dicelos example and the example of occlusion sensitivity
From: @lijiaqi0612 Reviewed-by: @kingxian,@zh_qh Signed-off-by: @kingxian
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479ffdfcbd
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@ -436,7 +436,7 @@ class DiceLoss(_Loss):
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>>> y = Tensor(np.array([[0, 1], [1, 0], [0, 1]]), mstype.float32)
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>>> output = loss(y_pred, y)
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>>> print(output)
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[0.38596618]
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0.38596618
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"""
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def __init__(self, smooth=1e-5):
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super(DiceLoss, self).__init__()
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@ -52,7 +52,7 @@ class OcclusionSensitivity(Metric):
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Example:
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>>> class DenseNet(nn.Cell):
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... def __init__(self):
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... super(DenseNet, self).init()
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... super(DenseNet, self).__init__()
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... w = np.array([[0.1, 0.8, 0.1, 0.1],[1, 1, 1, 1]]).astype(np.float32)
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... b = np.array([0.3, 0.6]).astype(np.float32)
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... self.dense = nn.Dense(4, 2, weight_init=Tensor(w), bias_init=Tensor(b))
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