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tensorflow - 检查tensorflow keras模型中的下一层

转载 作者:行者123 更新时间:2023-12-02 16:10:38 25 4
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我有一个 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)

最佳答案

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

关于tensorflow - 检查tensorflow keras模型中的下一层,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/68126965/

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