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m1.2.py
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m1.2.py
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#!/usr/bin/env python
import mxnet as mx
import logging
from reader import load_mnist
# Log to stdout for MXNet
logging.getLogger().setLevel(logging.DEBUG) # logging to stdout
print "Loading fashion-mnist data...",
test_images, test_labels = load_mnist(
path="/fashion-mnist", rows=70, cols=70, kind="t10k-70")
print "done"
# Do everything in a single batch
batch_size = len(test_images)
# Get iterators that cover the dataset
test_iter = mx.io.NDArrayIter(
test_images, test_labels, batch_size)
# Evaluate the network
print "Loading model...",
lenet_model = mx.mod.Module.load(
prefix='/models/baseline', epoch=2, context=mx.gpu())
lenet_model.bind(data_shapes=test_iter.provide_data,
label_shapes=test_iter.provide_label)
print "done"
print "New Inference"
acc = mx.metric.Accuracy()
lenet_model.score(test_iter, acc)
print(acc)