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@ -6,7 +6,7 @@ height = 227
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width = 227
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num_class = 1000
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batch_size = get_config_arg('batch_size', int, 128)
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use_mkldnn = get_config_arg('use_mkldnn', bool, False)
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gp = get_config_arg('layer_num', int, 1)
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is_infer = get_config_arg("is_infer", bool, False)
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num_samples = get_config_arg('num_samples', int, 2560)
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@ -41,12 +41,7 @@ net = img_pool_layer(input=net, pool_size=3, stride=2)
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# conv2
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net = img_conv_layer(
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input=net,
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filter_size=5,
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num_filters=256,
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stride=1,
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padding=2,
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groups=2 if use_mkldnn else 1)
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input=net, filter_size=5, num_filters=256, stride=1, padding=2, groups=gp)
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net = img_cmrnorm_layer(input=net, size=5, scale=0.0001, power=0.75)
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net = img_pool_layer(input=net, pool_size=3, stride=2)
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@ -55,21 +50,11 @@ net = img_conv_layer(
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input=net, filter_size=3, num_filters=384, stride=1, padding=1)
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# conv4
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net = img_conv_layer(
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input=net,
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filter_size=3,
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num_filters=384,
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stride=1,
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padding=1,
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groups=2 if use_mkldnn else 1)
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input=net, filter_size=3, num_filters=384, stride=1, padding=1, groups=gp)
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# conv5
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net = img_conv_layer(
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input=net,
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filter_size=3,
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num_filters=256,
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stride=1,
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padding=1,
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groups=2 if use_mkldnn else 1)
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input=net, filter_size=3, num_filters=256, stride=1, padding=1, groups=gp)
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net = img_pool_layer(input=net, pool_size=3, stride=2)
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net = fc_layer(
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@ -84,6 +69,9 @@ net = fc_layer(
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layer_attr=ExtraAttr(drop_rate=0.5))
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net = fc_layer(input=net, size=1000, act=SoftmaxActivation())
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lab = data_layer('label', num_class)
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loss = cross_entropy(input=net, label=lab)
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outputs(loss)
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if is_infer:
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outputs(net)
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else:
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lab = data_layer('label', num_class)
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loss = cross_entropy(input=net, label=lab)
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outputs(loss)
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