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Commit 393d5037 authored by Franck Dary's avatar Franck Dary
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Updated some machines for modular network

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...@@ -2,34 +2,17 @@ Name : Parser Machine ...@@ -2,34 +2,17 @@ Name : Parser Machine
Classifier : parser Classifier : parser
{ {
Transitions : {parser,data/parser.ts} Transitions : {parser,data/parser.ts}
Network type : LSTM Network type : Modular
Unknown value threshold : 1 Context : Unk{1} Buffer{-3 -2 -1 0 1 2} Stack{2 1 0} Columns{FORM UPOS} GRU{1 1 0.0 1} In{128} Out{512}
Buffer context : {-3 -2 -1 0 1 2} Focused : Column{ID} NbElem{1} Buffer{0} Stack{0} GRU{1 1 0.0 1} In{128} Out{256}
Stack context : {2 1 0} Focused : Column{EOS} NbElem{1} Buffer{-1 0} Stack{} GRU{1 1 0.0 1} In{128} Out{256}
Columns : {FORM UPOS} Focused : Column{FORM} NbElem{10} Buffer{-1 0} Stack{2 1 0} GRU{1 1 0.0 1} In{128} Out{256}
Focused buffer : {-1 0} Focused : Column{FEATS} NbElem{10} Buffer{-1 0} Stack{2 1 0} GRU{1 1 0.0 1} In{128} Out{256}
Focused stack : {2 1 0} Focused : Column{DEPREL} NbElem{1} Buffer{} Stack{2 1 0} GRU{1 1 0.0 1} In{128} Out{256}
Focused columns : {ID EOS FORM FEATS DEPREL} DepthLayerTree : Columns{DEPREL} Buffer{-1} Stack{2 1 0} LayerSizes{6} GRU{1 1 0.0 1} In{128} Out{128}
Max nb elements : {1 1 10 10 1} InputDropout : 0.3
Raw input left window : -1
Raw input right window : -1
Embeddings size : 128
MLP : {2048 0.3} MLP : {2048 0.3}
Context LSTM size : 512 End
Focused LSTM size : 256
Rawinput LSTM size : 32
Split trans LSTM size : 256
Num layers : 3
BiLSTM : true
LSTM dropout : 0.1
Total input dropout : 0.3
Embeddings dropout : 0.3
Dropout 2d : false
Tree embedding columns : {DEPREL}
Tree embedding buffer : {-1}
Tree embedding stack : {0 1 2}
Tree embedding nb : {6}
Tree embedding size : 128
Optimizer : Adam {0.0005 0.9 0.999 0.00000001 0.00001 true} Optimizer : Adam {0.0005 0.9 0.999 0.00000001 0.00001 true}
} }
Predictions : HEAD DEPREL EOS Predictions : HEAD DEPREL EOS
......
...@@ -2,34 +2,13 @@ Name : Tagger Machine ...@@ -2,34 +2,13 @@ Name : Tagger Machine
Classifier : tagger Classifier : tagger
{ {
Transitions : {tagger,data/tagger.ts} Transitions : {tagger,data/tagger.ts}
Network type : LSTM Network type : Modular
Unknown value threshold : 1 Context : Unk{1} Buffer{-3 -2 -1 0 1 2} Stack{} Columns{FORM UPOS} GRU{1 1 0.0 1} In{128} Out{512}
Buffer context : {-3 -2 -1 0 1 2} Focused : Column{ID} NbElem{1} Buffer{-1 0} Stack{} GRU{1 1 0.0 1} In{128} Out{256}
Stack context : {} Focused : Column{FORM} NbElem{10} Buffer{-1 0} Stack{} GRU{1 1 0.0 1} In{128} Out{256}
Columns : {FORM UPOS} InputDropout : 0.3
Focused buffer : {-1 0}
Focused stack : {}
Focused columns : {ID FORM}
Max nb elements : {1 10}
Raw input left window : -1
Raw input right window : -1
Embeddings size : 128
MLP : {2048 0.3} MLP : {2048 0.3}
Context LSTM size : 512 End
Focused LSTM size : 256
Rawinput LSTM size : 32
Split trans LSTM size : 256
Num layers : 3
BiLSTM : true
LSTM dropout : 0.1
Total input dropout : 0.3
Embeddings dropout : 0.3
Dropout 2d : false
Tree embedding columns : {}
Tree embedding buffer : {}
Tree embedding stack : {}
Tree embedding nb : {}
Tree embedding size : 0
Optimizer : Adam {0.0005 0.9 0.999 0.00000001 0.00001 true} Optimizer : Adam {0.0005 0.9 0.999 0.00000001 0.00001 true}
} }
Predictions : UPOS Predictions : UPOS
......
Name : Feats Machine
Classifier : morpho
{
Transitions : {tagger,data/tagger.ts morpho,data/morpho_parts.ts}
Network type : Modular
Context : Unk{1} Buffer{-3 -2 -1 0 1 2} Stack{} Columns{FORM UPOS} LSTM{1 1 0.0 1} In{128} Out{512}
Focused : Column{ID} NbElem{1} Buffer{-1 0} Stack{} LSTM{1 1 0.0 1} In{128} Out{256}
Focused : Column{FORM} NbElem{10} Buffer{-1 0} Stack{} LSTM{1 1 0.0 1} In{128} Out{256}
Focused : Column{FEATS} NbElem{10} Buffer{-1 0} Stack{} LSTM{1 1 0.0 1} In{128} Out{256}
InputDropout : 0.3
MLP : {2048 0.3}
End
Optimizer : Adam {0.0005 0.9 0.999 0.00000001 0.00001 true}
}
Predictions : UPOS FEATS
Strategy : sequential
tagger morpho 1
morpho morpho NOTHING 1
morpho morpho 0
...@@ -2,34 +2,15 @@ Name : Tokenizer Machine ...@@ -2,34 +2,15 @@ Name : Tokenizer Machine
Classifier : tokenizer Classifier : tokenizer
{ {
Transitions : {tokenizer,data/tokenizer.ts} Transitions : {tokenizer,data/tokenizer.ts}
Network type : LSTM Network type : Modular
Unknown value threshold : 1 Context : Unk{1} Buffer{-3 -2 -1} Stack{} Columns{FORM} GRU{1 1 0.0 1} In{128} Out{512}
Buffer context : {-3 -2 -1} Focused : Column{ID} NbElem{1} Buffer{-1 0} Stack{} GRU{1 1 0.0 1} In{128} Out{256}
Stack context : {} Focused : Column{FORM} NbElem{10} Buffer{-1 0} Stack{} GRU{1 1 0.0 1} In{128} Out{256}
Columns : {FORM} RawInput : Left{5} Right{5} GRU{1 1 0.0 1} In{32} Out{32}
Focused buffer : {-1 0} SplitTrans : GRU{1 1 0.0 1} In{128} Out{128}
Focused stack : {} InputDropout : 0.3
Focused columns : {ID FORM}
Max nb elements : {1 10}
Raw input left window : 5
Raw input right window : 5
Embeddings size : 128
MLP : {2048 0.3} MLP : {2048 0.3}
Context LSTM size : 512 End
Focused LSTM size : 256
Rawinput LSTM size : 32
Split trans LSTM size : 256
Num layers : 3
BiLSTM : true
LSTM dropout : 0.1
Total input dropout : 0.3
Embeddings dropout : 0.3
Dropout 2d : false
Tree embedding columns : {}
Tree embedding buffer : {}
Tree embedding stack : {}
Tree embedding nb : {}
Tree embedding size : 0
Optimizer : Adam {0.0005 0.9 0.999 0.00000001 0.00001 true} Optimizer : Adam {0.0005 0.9 0.999 0.00000001 0.00001 true}
} }
Splitwords : data/splitwords.ts Splitwords : data/splitwords.ts
......
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