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[TUTORIAL] Revise Naming tutorial #15365
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thomelane
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Jun 26, 2019
docs/tutorials/gluon/naming.md
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| The same principle applies to container blocks like [`Sequential`](https://mxnet.incubator.apache.org/versions/master/api/python/gluon/gluon.html#mxnet.gluon.nn.Sequential). `name_scope` can be used inside as well as outside of `__init__`: |
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The same principle applies -> The same principle applies
docs/tutorials/gluon/naming.md
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| The same principle applies to container blocks like [`Sequential`](https://mxnet.incubator.apache.org/versions/master/api/python/gluon/gluon.html#mxnet.gluon.nn.Sequential). `name_scope` can be used inside as well as outside of `__init__`: |
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Can tell whether you're saying this is recommended or not? Using name scope with Sequential?
docs/tutorials/gluon/naming.md
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| Parameter model1_mydense_bias (shape=(20,), dtype=<type 'numpy.float32'>) | ||
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| As a result, if you try to save parameters from model0 and load it with model1, you'll get an error due to unmatching names: |
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"load it with model1"? Might want to rephrase this.
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| - In Gluon model zoo, all image classification models follow the format where the feature extraction layers are named `features` while the output layer is named `output`. | ||
| - Note that the output layer is a dense block with 1000 dimension outputs. | ||
| Sometimes you may want to load a pretrained model, and replace certain Blocks in it for fine-tuning. For example, the [`AlexNet`](https://mxnet.incubator.apache.org/versions/master/api/python/gluon/model_zoo.html#vision) model in the model zoo has 1000 output dimensions, but maybe you have only 100 classes in your application. Let's see how to change the number of output dimensions from 1000 to 100. |
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Would mention that you can just set classes argument for this case. Guess you're doing like this for demonstration purposes.
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Great, thanks for updates. LGTM. |
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@mxnet-label-bot add [pr-awaiting-review] |
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Description
Update the text of Naming tutorials to make it more readable. Plus adding conclusion and next step sections.