xinyu-intel commented on a change in pull request #10391: [MXNET-139] Tutorial
for mixed precision training with float16
URL: https://github.com/apache/incubator-mxnet/pull/10391#discussion_r198707423
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File path: example/image-classification/benchmark_score.py
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@@ -74,11 +75,17 @@ def score(network, dev, batch_size, num_batches):
devs.append(mx.cpu())
batch_sizes = [1, 2, 4, 8, 16, 32]
-
for net in networks:
logging.info('network: %s', net)
for d in devs:
logging.info('device: %s', d)
for b in batch_sizes:
- speed = score(network=net, dev=d, batch_size=b, num_batches=10)
- logging.info('batch size %2d, image/sec: %f', b, speed)
+ for dtype in ['float32', 'float16']:
+ if d == mx.cpu() and dtype == 'float16':
+ #float16 is not supported on CPU
+ continue
+ elif net in ['inception-bn', 'alexnet'] and dt ==
'float16':
Review comment:
I guess this `dt` here doesn't work, please check again. By the way, it's
necessary to add a logging here to notice user what the dtype is.
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