tensorflow - 检查tensorflow keras模型中的下一层

Question

我有一个 keras层与层之间有捷径的模型。对于每一层，我想获得下一个连接层的名称(或索引)，因为简单地遍历所有 model.layers 不会告诉我该层是否连接到前一个层还是不是。

示例模型可以是:

model = tf.keras.applications.resnet50.ResNet50(
include_top=True, weights='imagenet', input_tensor=None,
input_shape=None, pooling=None, classes=1000)

Answer 1

可以这样提取dict格式的信息...

首先，定义一个效用函数并从每个 Functional 模型 ( code reference ) 中获取相关节点，如 model.summary() 方法中所做的那样

relevant_nodes = []
for v in model._nodes_by_depth.values():
    relevant_nodes += v

def get_layer_summary_with_connections(layer):
    
    info = {}
    connections = []
    for node in layer._inbound_nodes:
        if relevant_nodes and node not in relevant_nodes:
            # node is not part of the current network
            continue

        for inbound_layer, node_index, tensor_index, _ in node.iterate_inbound():
            connections.append(inbound_layer.name)
            
    name = layer.name
    info['type'] = layer.__class__.__name__
    info['parents'] = connections
            
    return info

其次，通过层迭代提取信息:

results = {}
layers = model.layers
for layer in layers:
    info = get_layer_summary_with_connections(layer)
    results[layer.name] = info

results 是一个嵌套的 dict，格式如下:

{
  'layer_name': {'type':'the layer type', 'parents':'list of the parent layers'},
  ...
  'layer_name': {'type':'the layer type', 'parents':'list of the parent layers'}
}

对于 ResNet50，它的结果是:

{
  'input_4': {'type': 'InputLayer', 'parents': []},
  'conv1_pad': {'type': 'ZeroPadding2D', 'parents': ['input_4']},
  'conv1_conv': {'type': 'Conv2D', 'parents': ['conv1_pad']},
  'conv1_bn': {'type': 'BatchNormalization', 'parents': ['conv1_conv']},
  ...
  'conv5_block3_out': {'type': 'Activation', 'parents': ['conv5_block3_add']},
  'avg_pool': {'type': 'GlobalAveragePooling2D', 'parents' ['conv5_block3_out']},
  'predictions': {'type': 'Dense', 'parents': ['avg_pool']}
}

另外，你可以修改get_layer_summary_with_connections返回所有你感兴趣的信息