Support SperableConv2D and one hot crossentropy #1944
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yiheng
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PR validation pass |
| """ | ||
| |input_tensor = Input(shape=[3]) | ||
| |target_tensor = Input(shape=[3]) | ||
| |loss = categorical_crossentropy(target_tensor, input_tensor) |
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Looks good as some other guys put "input_tensor" at the first position.
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it's the sequence in keras API
| p1.almostEqual(p2, 1e-3) should be(true) | ||
| } | ||
| } | ||
| } |
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Do we need a serialization test?
| Seq(Tensor[Float](4, 24, 24, 3).rand(), filter), | ||
| 0 | ||
| ) | ||
| } |
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Do we need a serialization test?
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we don't need for tf loaders, but have added for the new added operation
| Seq(input, filterSize, gradOutput), | ||
| 0, 1e-3 | ||
| ) | ||
| } |
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Do we need a serialization test?
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we don't need for tf loaders, but have added for the new added operation
| Seq(size, filter, Tensor[Float](4, 23, 23, 6).rand()), | ||
| 0 | ||
| ) | ||
| } |
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Do we need a serialization test?
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we don't need for tf loaders, but have added for the new added operation
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if we save model, will tf loaders not be saved ?
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no. It is only used when load tf model, which will generate an operation. I have added for the operations test
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@yiheng it doesn't look so when I ran the SessionSpec unit test, seems loaders are part of the graph meaning it will be serialized as well
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Any progress for this? |
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@zhichao-li as required by the reviewer, need to add serialization test |
* Revert "Create deploy_googlenet_places365.prototxt" This reverts commit ceaa3f9346faa66e3c4355590d91c4eff5d78e2c. * fix piip python test issue
What changes were proposed in this pull request?
How was this patch tested?
unit test