Add modeling layer of BiDAF #11
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cgraywang
requested changes
Jul 20, 2018
| def __init__(self, prefix=None, params=None): | ||
| super(BiDAFModelingLayer, self).__init__(prefix=prefix, params=params) | ||
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| self._modeling_layer = LSTM(hidden_size=100, num_layers=2, bidirectional=True) |
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Can you specify the input_size to be 8*hidden_size=800, and add description?
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Can you specify the dropout=0.2 according to the paper?
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Can you set hidden_size=input_dim, and num_layer=nlayers, bidirectional=biflag? It will be more general.
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| layer = BiDAFModelingLayer() | ||
| # The model doesn't need to know the hidden states, so I don't hold variables for the states | ||
| layer.initialize(init.Xavier(magnitude=2.24)) |
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Use the default layer.initialize() which is default by Uniform
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Description
Add modeling layer of BiDAF: just 2-layer bi-LSTM and mimic data input from attention flow.
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