change lenet&alexnet dir
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@ -148,7 +148,7 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework a
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| Loss | 0.108 |
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| Loss | 0.108 |
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| Params (M) | 61.10 |
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| Params (M) | 61.10 |
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| Checkpoint for Fine tuning | 445MB(.ckpt file) |
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| Checkpoint for Fine tuning | 445MB(.ckpt file) |
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| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/alexnet|
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| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/alexnet|
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#### [LeNet](#table-of-contents)
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#### [LeNet](#table-of-contents)
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@ -168,7 +168,7 @@ In order to facilitate developers to enjoy the benefits of MindSpore framework a
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| Loss | 0.004 |
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| Loss | 0.004 |
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| Params (M) | 0.06 |
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| Params (M) | 0.06 |
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| Checkpoint for Fine tuning | 483KB(.ckpt file) |
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| Checkpoint for Fine tuning | 483KB(.ckpt file) |
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| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/lenet|
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| Scripts | https://gitee.com/mindspore/mindspore/tree/master/model_zoo/official/cv/lenet|
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### Object Detection and Segmentation
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### Object Detection and Segmentation
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@ -29,7 +29,7 @@ def fc_with_initialize(input_channels, out_channels):
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return nn.Dense(input_channels, out_channels, weight, bias)
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return nn.Dense(input_channels, out_channels, weight, bias)
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def weight_variable():
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def weight_variable():
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return TruncatedNormal(0.02) # 0.02
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return TruncatedNormal(0.02)
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class AlexNet(nn.Cell):
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class AlexNet(nn.Cell):
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