Esempio n. 1
0
 def extract(cls, node: Node):
     attrs = get_mxnet_layer_attrs(node.symbol_dict)
     Range.update_node_stat(node, {
         'start': attrs.int('start', 0),
         'stop': attrs.int('stop', 0),
         'repeat': attrs.int('repeat', 1),
         'step': attrs.float('step', 1),
         'dtype': np.dtype(attrs.str('dtype ', 'float32'))
     })
     return cls.enabled
Esempio n. 2
0
 def extract(cls, node: Node):
     Range.update_node_stat(node, {})
     return cls.enabled
Esempio n. 3
0
 def extract(cls, node: Node):
     Range.update_node_stat(
         node,
         {'output_type': tf_dtype_extractor(node.pb.attr['Tidx'].type)})
     return cls.enabled
Esempio n. 4
0
 def extract(cls, node: Node):
     # output_type attribute will be deduced during shape infer
     Range.update_node_stat(node, {})
     return cls.enabled