From 7a03bf30288810071243794546e54f007f351b1c Mon Sep 17 00:00:00 2001 From: TISU32 Date: Wed, 30 Jan 2019 15:30:33 -0500 Subject: [PATCH] minor changes --- cortex/_lib/train.py | 2 +- cortex/built_ins/models/classifier.py | 10 +++++----- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/cortex/_lib/train.py b/cortex/_lib/train.py index 35b0da5..670c3db 100644 --- a/cortex/_lib/train.py +++ b/cortex/_lib/train.py @@ -211,7 +211,7 @@ def main_loop(model, epochs=500, archive_every=10, save_on_best=None, total_time = 0. if eval_only: test_results, test_std = test_epoch( - 'Testing', eval_mode=True, mode=test_mode) + 'Testing', data_mode=test_mode) convert_to_numpy(test_results) convert_to_numpy(test_std) diff --git a/cortex/built_ins/models/classifier.py b/cortex/built_ins/models/classifier.py index d9b42ee..c3b5915 100644 --- a/cortex/built_ins/models/classifier.py +++ b/cortex/built_ins/models/classifier.py @@ -55,10 +55,10 @@ def routine(self, inputs, targets, if labeled.sum() > 0: correct = 100. * (labeled * predicted.eq( targets.data).float()).cpu().sum() / labeled.cpu().sum() - self.results.accuracy = correct + self.results.accuracy = correct.item() self.losses.classifier = loss - self.results.perc_labeled = labeled.mean() + self.results.perc_labeled = labeled.mean().item() def predict(self, inputs): classifier = self.nets.classifier @@ -107,9 +107,9 @@ def routine(self, inputs, attributes): correct = 100. * predicted.eq(attributes.data).cpu().sum(0) / attributes.size(0) self.losses.classifier = loss - self.results.accuracy = dict(mean=correct.float().mean(), - max=correct.max(), - min=correct.min()) + self.results.accuracy = dict(mean=correct.float().mean().item(), + max=correct.max().item(), + min=correct.min().item()) def predict(self, inputs): classifier = self.nets.classifier