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Write and discuss ideas for new classifier implementations here.
E.g. Factorization Machines, DNNs, CNNs, RNNs, etc.
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The latest releases of TensorFlow 2 have been accompanied by excellent tutorials which made it straightforward to manipulate and adapt complex models such as RNNs, CNNs, and GANs to a variety of task…
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I'm getting crappy-looking samples from networks that seem to train properly. Loss converges nicely (see last screenshot), but samples don't compare with @hardmaru's results.
Here are some example…
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Hello,
I noticed a number of CTC implementations in pure Theano and even Lasagne adaptation:
https://github.com/skaae/Lasagne-CTC
Although it needs some fixes to be compatible with RNN API recently m…
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Hey, I want to better understand the performance of the mixed-bitwidth computatation setting in SiRNN and try to benchmark the extension/ truncation operations which i think is the basis for SIRNN.
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In some *state-less* `RNNBuilder` implementations (e.g. `SimpleRNNBuilder` or `GRUBuilder`) also have `get_s/set_s_impl` overridings, and they are basically coded as the redirect to `get_h/set_h_impl`…
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This issue makes part of #20 more concrete.
Recurrent Neural Networks, became an effective Neural Network architecture, that we would like to implement in Leaf as well. The operations could probably …
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Currently, in this repo, we have one data class, and all the implementations for different types of data generation or data reading are added to the same class. However, different problems needs dif…
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This issue collects a wishlist of de-novo implementations of torch based models.
Anyone can suggest models to implement, we will have to prioritize along a impact/cost analysis.
FYI @fnhirwa.
C…
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Hi @spro, i've read your implementation of luong attention in pytorch seq2seq translation tutorial and in the context calculation step, you're using rnn_output as input when calculating attn_weights …