From bf44c7fe27e20e9667e4dd6410e245eb6d1f8d6b Mon Sep 17 00:00:00 2001
From: Franck Dary <franck.dary@lis-lab.fr>
Date: Thu, 15 Apr 2021 20:07:07 +0200
Subject: [PATCH] Added way to decode model in main
---
Decode.py | 7 ++++++-
Train.py | 4 ++--
main.py | 2 +-
3 files changed, 9 insertions(+), 4 deletions(-)
diff --git a/Decode.py b/Decode.py
index 80b46ea..af8fc68 100644
--- a/Decode.py
+++ b/Decode.py
@@ -2,6 +2,7 @@ import random
import sys
from Transition import Transition, getMissingLinks, applyTransition
from Features import extractFeatures
+from Dicts import Dicts
import Config
import torch
@@ -65,7 +66,7 @@ def decodeModel(ts, strat, config, network, dicts, debug) :
################################################################################
################################################################################
-def decodeMode(debug, filename, type, network=None, dicts=None, output=sys.stdout) :
+def decodeMode(debug, filename, type, modelDir = None, network=None, dicts=None, output=sys.stdout) :
transitionSet = [Transition(elem) for elem in ["RIGHT", "LEFT", "SHIFT", "REDUCE"]]
strategy = {"RIGHT" : 1, "SHIFT" : 1, "LEFT" : 0, "REDUCE" : 0}
@@ -79,6 +80,10 @@ def decodeMode(debug, filename, type, network=None, dicts=None, output=sys.stdou
for config in sentences[1:] :
config.print(sys.stdout, header=False)
elif type == "model" :
+ if dicts is None :
+ dicts = Dicts()
+ dicts.load(modelDir+"/dicts.json")
+ network = torch.load(modelDir+"/network.pt")
for config in sentences :
decodeModel(transitionSet, strategy, config, network, dicts, debug)
sentences[0].print(output, header=True)
diff --git a/Train.py b/Train.py
index e16725f..6d19212 100644
--- a/Train.py
+++ b/Train.py
@@ -67,12 +67,12 @@ def trainModelOracle(debug, modelDir, filename, nbIter, batchSize, devFile, tran
examples = torch.stack(examples)
network = Networks.BaseNet(dicts, examples[0].size(0)-1, len(transitionSet))
- network.train()
optimizer = torch.optim.Adam(network.parameters(), lr=0.0001)
lossFct = torch.nn.CrossEntropyLoss()
bestLoss = None
bestScore = None
for iter in range(1,nbIter+1) :
+ network.train()
examples = examples.index_select(0, torch.randperm(examples.size(0)))
totalLoss = 0.0
nbEx = 0
@@ -98,7 +98,7 @@ def trainModelOracle(debug, modelDir, filename, nbIter, batchSize, devFile, tran
bestLoss = totalLoss if bestLoss is None else min(bestLoss, totalLoss)
if devFile is not None :
outFilename = modelDir+"/predicted_dev.conllu"
- Decode.decodeMode(debug, devFile, "model", network, dicts, open(outFilename, "w"))
+ Decode.decodeMode(debug, devFile, "model", modelDir, network, dicts, open(outFilename, "w"))
res = evaluate(load_conllu(open(devFile, "r")), load_conllu(open(outFilename, "r")), [])
UAS = res["UAS"][0].f1
score = UAS
diff --git a/main.py b/main.py
index 132f058..cf785b3 100755
--- a/main.py
+++ b/main.py
@@ -35,7 +35,7 @@ if __name__ == "__main__" :
if args.mode == "train" :
Train.trainMode(args.debug, args.corpus, args.type, args.model, int(args.iter), int(args.batchSize), args.dev, args.silent)
elif args.mode == "decode" :
- Decode.decodeMode(args.debug, args.corpus, args.type)
+ Decode.decodeMode(args.debug, args.corpus, args.type, args.model)
else :
print("ERROR : unknown mode '%s'"%args.mode, file=sys.stderr)
exit(1)
--
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