[MXNET] LRN support in MXNET frontend (#1520)

nnvm/python/nnvm/frontend/mxnet.py

@@ -263,6 +263,15 @@ def _expand_dims(inputs, attrs):
     new_attrs['axis'] = _required_attr(attrs, 'axis')
     return _get_nnvm_op(op_name)(*inputs, **new_attrs)
 
+def _lrn(inputs, attrs):
+    op_name, new_attrs = "lrn", {}
+    new_attrs['alpha'] = attrs.get('alpha', 0.0001)
+    new_attrs['beta'] = attrs.get('beta', 0.75)
+    new_attrs['bias'] = attrs.get('knorm', 2)
+    # NCHW format and normalization along channel axis
+    new_attrs['axis'] = 1
+    new_attrs['size'] = _required_attr(attrs, 'nsize')
+    return _get_nnvm_op(op_name)(*inputs, **new_attrs)
 
 _identity_list = ['__add_scalar__', '__add_symbol__', '__div_scalar__',
                   '__div_symbol__', '__mul_scalar__', '__mul_symbol__',
@@ -314,7 +323,8 @@ _convert_map = {
     'sum_axis'      : _rename('sum'),
     'UpSampling'    : _upsampling,
     'clip'          : _clip,
-    'expand_dims'   : _expand_dims
+    'expand_dims'   : _expand_dims,
+    'LRN'           : _lrn
 }
 
 def _convert_symbol(op_name, inputs, attrs,

nnvm/tests/python/frontend/mxnet/test_forward.py

@@ -149,6 +149,11 @@ def test_forward_pooling():
     mx_sym = mx.sym.Pooling(data, kernel=(3, 3), pad=(1, 1), pool_type='max')
     verify_mxnet_frontend_impl(mx_sym, (1, 20, 8, 8), (1, 20, 8, 8))
 
+def test_forward_lrn():
+    data = mx.sym.var('data')
+    mx_sym = mx.sym.LRN(data, alpha=2, beta=2, knorm=1, nsize=5)
+    verify_mxnet_frontend_impl(mx_sym, (1, 10, 24, 24), (1, 10, 24, 24))
+
 if __name__ == '__main__':
     test_forward_mlp()
     test_forward_vgg()
@@ -163,3 +168,4 @@ if __name__ == '__main__':
     test_forward_split_squeeze()
     test_forward_expand_dims()
     test_forward_pooling()
+    test_forward_lrn()