From 5ad5c3f9eb3a343e8c026df5477b9cb9c1962c28 Mon Sep 17 00:00:00 2001 From: CQY Date: Sat, 10 Dec 2016 16:21:45 +0800 Subject: [PATCH 1/3] add .gitignore --- .gitignore | 34 ++++++++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) create mode 100644 .gitignore diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..fd5d2c6 --- /dev/null +++ b/.gitignore @@ -0,0 +1,34 @@ +*~* +*.swap +*.pyc +*Rhistory +*RData +*.swp +screenlog* +*.ign +*.ignore +.nfs* +trash* +*.zip +*.rar +*.blg +*.bbl +*.aux +*.log +*.brf +*.nlo +*.out +*.dvi +*.ps +*.lof +*.toc +*.fls +*.fdb_latexmk +*.pdfsync +*.synctex.gz +*.ind +*.ilg +*.idx +nohup.out +*.pdf +.ipynb_checkpoints/* From 7a2ca0cdec88436b1c471f0fad5305827baf019e Mon Sep 17 00:00:00 2001 From: CQY Date: Sun, 11 Dec 2016 10:45:24 +0800 Subject: [PATCH 2/3] add silent --- rank/RankNet.py | 18 ++++++++++-------- 1 file changed, 10 insertions(+), 8 deletions(-) diff --git a/rank/RankNet.py b/rank/RankNet.py index 226ce77..86e2d71 100755 --- a/rank/RankNet.py +++ b/rank/RankNet.py @@ -61,14 +61,15 @@ class RankNet(NNfuncs.NN): Usage (Traininng): Model.fit(X, y) - + With options: Model.fit(X, y, batchsize=100, n_iter=5000, n_units1=512, n_units2=128, tv_ratio=0.95, optimizerAlgorithm="Adam", savefigName="result.pdf", savemodelName="RankNet.model") """ - def __init__(self, resumemodelName=None): + def __init__(self, resumemodelName=None, silent=False): self.resumemodelName = resumemodelName self.train_loss, self.test_loss = [], [] + self.silent = silent if resumemodelName is not None: print("load resume model!") self.loadModel(resumemodelName) @@ -108,16 +109,17 @@ def trainModel(self, x_train, y_train, x_test, y_test, n_iter): test_ndcg = self.ndcg(y_test, test_score) self.train_loss.append(train_ndcg) self.test_loss.append(test_ndcg) - print("step: {0}".format(step + 1)) - print("NDCG@100 | train: {0}, test: {1}".format(train_ndcg, test_ndcg)) + if not self.silent: + print("step: {0}".format(step + 1)) + print("NDCG@100 | train: {0}, test: {1}".format(train_ndcg, test_ndcg)) def fit(self, fit_X, fit_y, batchsize=100, n_iter=5000, n_units1=512, n_units2=128, tv_ratio=0.95, optimizerAlgorithm="Adam", savefigName="result.pdf", savemodelName="RankNet.model"): train_X, train_y, validate_X, validate_y = self.splitData(fit_X, fit_y, tv_ratio) - print("The number of data, train:", len(train_X), "validate:", len(validate_X)) + print("The number of data, train:", len(train_X), "validate:", len(validate_X)) if self.resumemodelName is None: self.initializeModel(Model, train_X, n_units1, n_units2, optimizerAlgorithm) - + self.trainModel(train_X, train_y, validate_X, validate_y, n_iter) plot_result.acc(self.train_loss, self.test_loss, savename=savefigName) @@ -211,9 +213,9 @@ def fit(self, fit_X, fit_y, batchsize=100, n_iter=5000, n_units1=512, n_units2=1 # # plot_result(train_loss, test_loss, savename=savefigName) # print('save the model') -# serializers.save_hdf5(savemodelName, model) +# serializers.save_hdf5(savemodelName, model) # print('save the optimizer') -# serializers.save_hdf5(savemodelName[:-5]+ 'state', optimizer) +# serializers.save_hdf5(savemodelName[:-5]+ 'state', optimizer) # return model From f311b4d5c5e9452f4aa3a0c99455153f04d694fb Mon Sep 17 00:00:00 2001 From: CQY Date: Sat, 27 May 2017 19:55:39 +0800 Subject: [PATCH 3/3] use verbose instead of silent --- rank/RankNet.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/rank/RankNet.py b/rank/RankNet.py index 86e2d71..cad906f 100755 --- a/rank/RankNet.py +++ b/rank/RankNet.py @@ -66,10 +66,10 @@ class RankNet(NNfuncs.NN): Model.fit(X, y, batchsize=100, n_iter=5000, n_units1=512, n_units2=128, tv_ratio=0.95, optimizerAlgorithm="Adam", savefigName="result.pdf", savemodelName="RankNet.model") """ - def __init__(self, resumemodelName=None, silent=False): + def __init__(self, resumemodelName=None, verbose=True): self.resumemodelName = resumemodelName self.train_loss, self.test_loss = [], [] - self.silent = silent + self._verbose = verbose if resumemodelName is not None: print("load resume model!") self.loadModel(resumemodelName) @@ -109,7 +109,7 @@ def trainModel(self, x_train, y_train, x_test, y_test, n_iter): test_ndcg = self.ndcg(y_test, test_score) self.train_loss.append(train_ndcg) self.test_loss.append(test_ndcg) - if not self.silent: + if self._verbose: print("step: {0}".format(step + 1)) print("NDCG@100 | train: {0}, test: {1}".format(train_ndcg, test_ndcg))