def extract(cls, node):
attrs = get_mxnet_layer_attrs(node.symbol_dict)
act_type = attrs.str('act_type', 'leaky')
if act_type == 'prelu':
prelu_attrs = {
'channel_shared': 1,
'filler_type': 'constant',
'filler_value': 0,
'min': 0,
'max': 1,
'mean': 0,
'std': 0,
'sparse': -1,
'variance_norm': "caffe.FillerParameter.FAN_IN"
}
PReLU.update_node_stat(node, prelu_attrs)
elif act_type == 'elu':
alpha = attrs.float('slope', 0.25)
Elu.update_node_stat(node, {'alpha': alpha})
elif act_type == 'leaky':
negative_slope = attrs.float('slope', 0.25)
if negative_slope == 0:
ReLU.update_node_stat(node)
else:
LeakyReLU.update_node_stat(node,
{'negative_slope': negative_slope})
else:
raise Error(
"Operation '{}' not supported. Please register it as custom op. "
+ refer_to_faq_msg(86), act_type)
return LeakyReLUFrontExtractor.enabled
def extract(cls, node):
proto_layer = node.pb
pb_model = node.model_pb
param = proto_layer.prelu_param
update_attrs = {
'channel_shared': int(param.channel_shared)
}
variance_norm_caffe_map = {
0: 'caffe.FillerParameter.FAN_IN',
1: 'caffe.FillerParameter.FAN_OUT',
2: 'caffe.FillerParameter.AVERAGE'
}
if hasattr(param, 'filler'):
update_attrs.update({
'filler_type': param.filler.type,
'filler_value': int(param.filler.value),
'min': int(param.filler.min),
'max': int(param.filler.max),
'mean': int(param.filler.mean),
'std': int(param.filler.std),
'sparse': param.filler.sparse,
'variance_norm': variance_norm_caffe_map[param.filler.variance_norm]
})
mapping_rule = merge_attrs(param, update_attrs)
mapping_rule.update(weights_biases(False, pb_model))
mapping_rule.update(layout_attrs())
# update the attributes of the node
PReLU.update_node_stat(node, mapping_rule)
return cls.enabled