From 7ce11aeeb247e59bcd5cbe4702838198785080f0 Mon Sep 17 00:00:00 2001
From: Neta Zmora <neta.zmora@intel.com>
Date: Tue, 8 May 2018 19:38:45 +0300
Subject: [PATCH] change the access to the data of 0-dimensional tensors
---
examples/classifier_compression/compress_classifier.py | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/examples/classifier_compression/compress_classifier.py b/examples/classifier_compression/compress_classifier.py
index 0f703c8..0d845de 100755
--- a/examples/classifier_compression/compress_classifier.py
+++ b/examples/classifier_compression/compress_classifier.py
@@ -362,13 +362,13 @@ def train(train_loader, model, criterion, optimizer, epoch,
# Measure accuracy and record loss
classerr.add(output.data, target)
- losses['objective_loss'].add(loss.data[0])
+ losses['objective_loss'].add(loss.item())
if compression_scheduler:
# Before running the backward phase, we add any regularization loss computed by the scheduler
regularizer_loss = compression_scheduler.before_backward_pass(epoch, train_step, steps_per_epoch, loss)
loss += regularizer_loss
- losses['regularizer_loss'].add(regularizer_loss.data[0])
+ losses['regularizer_loss'].add(regularizer_loss.item())
# Compute the gradient and do SGD step
optimizer.zero_grad()
@@ -446,7 +446,7 @@ def _validate(data_loader, model, criterion, loggers, print_freq, epoch=-1):
loss = criterion(output, target_var)
# measure accuracy and record loss
- losses['objective_loss'].add(loss.data[0])
+ losses['objective_loss'].add(loss.item())
classerr.add(output.data, target)
# if confusion:
# confusion.add(output.data, target)
--
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