import copy class BiasOpt: def __init__(self): self.conv_layers = [ 'fluid.layers.conv2d', 'fluid.layers.conv2d_transpose' ] self.act_layers = [ 'fluid.layers.relu', 'fluid.layers.relu6', 'fluid.layers.sigmoid', 'fluid.layers.exp', 'fluid.layers.tanh', 'fluid.layers.softplus', 'fluid.layers.leaky_relu' ] def run(self, graph): layers = copy.deepcopy(graph.layers) for layer_id, layer in layers.items(): if layer.kernel in self.conv_layers or layer.kernel == "fluid.layers.transpose": if len(graph.edges_out.get(layer_id, [])) > 1: continue if layer.outputs[0] in graph.outputs: continue out_layer_id = graph.edges_out[layer_id][0] if graph.layers[ out_layer_id].kernel != "fluid.layers.elementwise_add": continue if graph.layers[out_layer_id].attrs.get('axis', -1) != -1: continue in_layer_id = graph.edges_in[out_layer_id] bias_layer_id = in_layer_id[1 - in_layer_id.index(layer_id)] if graph.layers[ bias_layer_id].kernel != "fluid.layers.create_parameter": continue bias_layer = graph.layers[bias_layer_id] if len(bias_layer.attrs['shape']) != 1: continue if len(graph.edges_out[bias_layer_id]) != 1: continue if layer.kernel == "fluid.layers.transpose": if layer.attrs['perm'] != [0, 2, 3, 1]: continue in_layer_id = graph.edges_in[layer_id][0] if graph.layers[in_layer_id].kernel not in self.conv_layers: continue if graph.layers[in_layer_id].attrs['bias_attr'] != False: continue if graph.layers[in_layer_id].outputs[0] in graph.outputs: continue if len(graph.edges_out[in_layer_id]) != 1: continue graph.layers[in_layer_id].attrs[ 'bias_attr'] = bias_layer.attrs['name'] else: graph.layers[layer_id].attrs[ 'bias_attr'] = bias_layer.attrs['name'] bias_add_outs = graph.edges_out.get(out_layer_id, []) bias_add_output = graph.layers[out_layer_id].outputs[0] graph.del_layer(bias_layer_id) graph.del_layer(out_layer_id) for out in bias_add_outs: for k, v in graph.layers[out].inputs.items(): if v == layer.outputs[0]: graph.layers[out].inputs[k] = bias_add_output graph.layers[layer_id].outputs[0] = bias_add_output if layer.kernel == "fluid.layers.transpose": in_layer_id = graph.edges_in[layer_id][0] graph.layers[in_layer_id].outputs[0] = bias_add_output graph.layers[layer_id].inputs['x'] = bias_add_output