From 55d26ae8151846c5e8dc90b42064a1fadb51c40d Mon Sep 17 00:00:00 2001
From: Pariksheet Pinjari <pariksheet.pinjari@huawei.com>
Date: Thu, 25 Oct 2018 05:28:10 +0530
Subject: [PATCH] [Frontend][Darknet] L2 normalization support in darknet
(#1916)
* l2 normalization
* retrigger CI
---
nnvm/python/nnvm/frontend/darknet.py | 12 ++++++++++++
nnvm/python/nnvm/testing/darknet.py | 1 +
.../python/frontend/darknet/test_forward.py | 16 +++++++++++++++-
3 files changed, 28 insertions(+), 1 deletion(-)
diff --git a/nnvm/python/nnvm/frontend/darknet.py b/nnvm/python/nnvm/frontend/darknet.py
index bf3a16cdb..4da2e90bc 100644
--- a/nnvm/python/nnvm/frontend/darknet.py
+++ b/nnvm/python/nnvm/frontend/darknet.py
@@ -267,6 +267,13 @@ def _darknet_upsampling(inputs, attrs):
new_attrs['scale'] = attrs.get('scale', 1)
return _darknet_get_nnvm_op(op_name)(*inputs, **new_attrs), None
+def _darknet_l2normalize(inputs, attrs):
+ """Process the l2 normalization operation."""
+ op_name, new_attrs = 'l2_normalize', {}
+ new_attrs['eps'] = attrs.get('eps', 0)
+ new_attrs['axis'] = attrs.get('axis', 1)
+ return _darknet_get_nnvm_op(op_name)(*inputs, **new_attrs), None
+
def _darknet_softmax_output(inputs, attrs):
"""Process the softmax operation."""
temperature = attrs.get('temperature', 1)
@@ -370,6 +377,7 @@ _DARKNET_CONVERT_MAP = {
LAYERTYPE.REGION : _darknet_region,
LAYERTYPE.SHORTCUT : _darknet_shortcut,
LAYERTYPE.UPSAMPLE : _darknet_upsampling,
+ LAYERTYPE.L2NORM : _darknet_l2normalize,
LAYERTYPE.YOLO : _darknet_yolo,
LAYERTYPE.DETECTION : _darknet_op_not_support,
LAYERTYPE.CROP : _darknet_op_not_support,
@@ -630,6 +638,10 @@ class GraphProto(object):
elif LAYERTYPE.UPSAMPLE == layer.type:
attr.update({'scale' : layer.stride})
+
+ elif LAYERTYPE.L2NORM == layer.type:
+ pass
+
else:
err = "Darknet layer type {} is not supported in nnvm.".format(layer.type)
raise NotImplementedError(err)
diff --git a/nnvm/python/nnvm/testing/darknet.py b/nnvm/python/nnvm/testing/darknet.py
index d4d33a694..328ad2ae6 100644
--- a/nnvm/python/nnvm/testing/darknet.py
+++ b/nnvm/python/nnvm/testing/darknet.py
@@ -512,6 +512,7 @@ layer make_crnn_layer(int batch, int h, int w, int c, int hidden_filters, int ou
layer make_lstm_layer(int batch, int inputs, int outputs, int steps, int batch_normalize, int adam);
layer make_gru_layer(int batch, int inputs, int outputs, int steps, int batch_normalize, int adam);
layer make_upsample_layer(int batch, int w, int h, int c, int stride);
+layer make_l2norm_layer(int batch, int inputs);
void free_network(network *net);
"""
)
diff --git a/nnvm/tests/python/frontend/darknet/test_forward.py b/nnvm/tests/python/frontend/darknet/test_forward.py
index f836ca477..1f5e89c6e 100644
--- a/nnvm/tests/python/frontend/darknet/test_forward.py
+++ b/nnvm/tests/python/frontend/darknet/test_forward.py
@@ -107,7 +107,7 @@ def test_forward(net, build_dtype='float32'):
out.insert(0, attributes)
out.insert(0, _read_memory_buffer((layer.total*2, ), layer.biases))
out.insert(0, _read_memory_buffer((layer.n, ), layer.mask, dtype='int32'))
- layer_ou tshape = (layer.batch, layer.out_c,
+ layer_outshape = (layer.batch, layer.out_c,
layer.out_h, layer.out_w)
out.insert(0, _read_memory_buffer(layer_outshape, layer.output))
elif i == net.n-1:
@@ -361,6 +361,19 @@ def test_forward_upsample():
test_forward(net)
LIB.free_network(net)
+def test_forward_l2normalize():
+ '''test l2 normalization layer'''
+ net = LIB.make_network(1)
+ layer = LIB.make_l2norm_layer(1, 224*224*3)
+ layer.c = layer.out_c = 3
+ layer.h = layer.out_h = 224
+ layer.w = layer.out_w = 224
+ net.layers[0] = layer
+ net.w = net.h = 224
+ LIB.resize_network(net, 224, 224)
+ test_forward(net)
+ LIB.free_network(net)
+
def test_forward_elu():
'''test elu activation layer'''
net = LIB.make_network(1)
@@ -520,6 +533,7 @@ if __name__ == '__main__':
test_forward_region()
test_forward_yolo_op()
test_forward_upsample()
+ test_forward_l2normalize()
test_forward_elu()
test_forward_rnn()
test_forward_crnn()
--
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