def proto_extractor(pb, model_pb, mapping, disable_omitting_optional,
enable_flattening_nested_params):
log.info("Custom extractor for layer {} with mapping {}".format(
pb.type, mapping))
log.debug('Found custom layer {}. Params are processed'.format(pb.name))
if mapping['hasParam'].lower() != 'true':
return {}
try:
native_attr = collect_attributes(
getattr(pb, mapping['protoParamName']),
disable_omitting_optional=disable_omitting_optional,
enable_flattening_nested_params=enable_flattening_nested_params)
except AttributeError as e:
error_message = 'Layer {} has no attribute {}'.format(
pb.type,
str(e).split(' ')[-1])
log.error(error_message)
raise ValueError(error_message)
keys = list(native_attr.keys())
obfuscate_special_attrs(native_attr, keys)
# avoid 'mo_caffe' appearing in param
for attr in native_attr:
if 'mo_caffe' in native_attr[attr]:
native_attr[attr] = native_attr[attr].replace('mo_caffe', 'caffe')
log.debug(str(keys))
log.debug(str(native_attr))
attrs = {
'IE': [('layer', [('id', lambda node: node.id), 'name',
'type'], [('data', keys, []), '@ports', '@consts'])]
}
attrs.update(native_attr)
return attrs
def extract(node):
param = node.pb.elu_param
attrs = collect_attributes(param)
attrs['operation'] = 'elu'
Activation.update_node_stat(node, attrs)
return ELUFrontExtractor.enabled
def extract(cls, node):
mapping_rule = collect_attributes(node.pb.shuffle_channel_param)
mapping_rule.update(layout_attrs())
# update the attributes of the node
ShuffleChannels.update_node_stat(node, mapping_rule)
return cls.enabled
def extract(node):
mapping_rule = collect_attributes(node.pb.shuffle_channel_param)
mapping_rule.update(layout_attrs())
# update the attributes of the node
Op.get_op_class_by_name(__class__.op).update_node_stat(
node, mapping_rule)
return __class__.enabled
def extract(cls, node):
proto_layer = node.pb
param = proto_layer.accum_param
attrs = collect_attributes(param)
# update the attributes of the node
AccumOp.update_node_stat(node, attrs)
return cls.enabled
def extract(node):
proto_layer = node.pb
param = proto_layer.accum_param
attrs = collect_attributes(param)
# update the attributes of the node
Op.get_op_class_by_name(__class__.op).update_node_stat(node, attrs)
return __class__.enabled
def extract(cls, node):
proto_layer = node.pb
param = proto_layer.power_file_param
attrs = collect_attributes(param)
# update the attributes of the node
PowerFileOp.update_node_stat(node, attrs)
return cls.enabled
def extract(node):
proto_layer = node.pb
param = proto_layer.norm_param
attrs = collect_attributes(param, enable_flattening_nested_params=True)
attrs.update(weights_biases(False, node.model_pb))
# update the attributes of the node
Op.get_op_class_by_name(__class__.op).update_node_stat(node, attrs)
return __class__.enabled
def extract(cls, node):
proto_layer = node.pb
param = proto_layer.norm_param
attrs = collect_attributes(param, enable_flattening_nested_params=True)
attrs.update(weights_biases(False, node.model_pb))
# update the attributes of the node
NormalizeOp.update_node_stat(node, attrs)
return cls.enabled
def extract(cls, node):
proto_layer = node.pb
param = proto_layer.mvn_param
attrs = collect_attributes(param)
if 'normalize_variance' not in attrs:
attrs['normalize_variance'] = 1
if 'across_channels' not in attrs:
attrs['across_channels'] = 0
# update the attributes of the node
MVNCaffe.update_node_stat(node, attrs)
return cls.enabled
def extract(cls, node):
param = node.pb.elu_param
attrs = collect_attributes(param)
Elu.update_node_stat(node, attrs)
return cls.enabled
