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avoid per-batch blocking in metric #9636

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szha merged 1 commit into from
Jan 31, 2018
+6 −2
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avoid per-batch blocking in metric #9636

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8 changes: 6 additions & 2 deletions python/mxnet/metric.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,6 +28,7 @@
from .base import numeric_types, string_types
from . import ndarray
from . import registry
from .context import cpu


def check_label_shapes(labels, preds, shape=0):
Expand Down Expand Up @@ -388,6 +389,7 @@ def update(self, labels, preds):
"""
check_label_shapes(labels, preds)

results = []
for label, pred_label in zip(labels, preds):
if pred_label.shape != label.shape:
pred_label = ndarray.argmax(pred_label, axis=self.axis)
Expand All @@ -399,8 +401,10 @@ def update(self, labels, preds):
if pred_label.context != label.context:
pred_label = pred_label.as_in_context(label.context)

self.sum_metric += (pred_label.reshape((-1,)) == label.reshape((-1,))).sum().asscalar()
self.num_inst += numpy.prod(pred_label.shape)
self.num_inst += pred_label.size
results.append((pred_label.reshape((-1,)) == label.reshape((-1,)))
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@piiswrong piiswrong Jan 31, 2018 •
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why use add_n at the end instead of += on each iteration?

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@szha szha Jan 31, 2018

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this is for less kernel launch

.sum().as_in_context(cpu()))
self.sum_metric += ndarray.add_n(*results).asscalar()


@register
Expand Down