from tensorflow.python.framework.convert_to_constants import convert_variables_to_constants_v2from tensorflow.python.tools import optimize_for_inference_libloaded = tf.saved_model.load('models/mnist_test')infer = loaded.signatures['serving_default']f = tf.function(infer).get_concrete_function( flatten_input=tf.TensorSpec(shape=[None, 28, 28, 1], dtype=tf.float32)) # change this line for your own inputsf2 = convert_variables_to_constants_v2(f)graph_def = f2.graph.as_graph_def()if optimize : # Remove NoOp nodes for i in reversed(range(len(graph_def.node))): if graph_def.node[i].op == 'NoOp': del graph_def.node[i] for node in graph_def.node: for i in reversed(range(len(node.input))): if node.input[i][0] == '^': del node.input[i] # Parse graph's inputs/outputs graph_inputs = [x.name.rsplit(':')[0] for x in frozen_func.inputs] graph_outputs = [x.name.rsplit(':')[0] for x in frozen_func.outputs] graph_def = optimize_for_inference_lib.optimize_for_inference(graph_def, graph_inputs, graph_outputs, tf.float32.as_datatype_enum)# Export frozen graphwith tf.io.gfile.GFile('optimized_graph.pb', 'wb') as f: f.write(graph_def.SerializeToString())我有一個元組列表，比方說tuplist = [('a','b'),('a','c'),('e','f'),('f','c'),('d','z'),('z','x')]我正在嘗試獲得以下信息：('a','b','c','e','f'),('d','z','x')這是鏈接在一起的所有元素（就像圖論中的樹） 上述元組（也可以是列表）中的順序無關緊要。我已經設法獲得單個元素的所有鏈接的字典，但我正在努力以一種干凈有效的方式獲得最終結果......這是我到目前為止的代碼：ll=[('a','b'),('a','c'),('e','f'),('f','c'),('d','z'),('z','x')]total = {}total2={}final=[]for element in set([item for sublist in ll for item in sublist]):
2 回答
互換的青春
TA貢獻1797條經驗 獲得超6個贊
與這篇文章類似，您要查找的內容稱為圖的連接組件。一個簡單的方法是用 構建一個圖networkx，然后找到connected_components：
tuplist = [('a','b'),('a','c'),('e','f'),('f','c'),('d','z'),('z','x')]
import networkx as nx
G=nx.Graph()
G.add_edges_from(tuplist)
list(nx.connected_components(G))
# [{'a', 'b', 'c', 'e', 'f'}, {'d', 'x', 'z'}]
慕后森
TA貢獻1802條經驗 獲得超5個贊
可選的遞歸解決方案，雖然不像@yatu的解決方案那樣優雅networkx：
tuplist = [('a','b'),('a','c'),('e','f'),('f','c'),('d','z'),('z','x')]
def get_graphs(start, c = [], seen = []):
_r = [b for a, b in tuplist if a == start and b not in seen]+[a for a, b in tuplist if b == start and a not in seen]
if _r:
yield from [i for b in _r for i in get_graphs(b, c=c+[start, b, *_r], seen = seen+[start, b])]
else:
yield set(c)
_r = [a for a, _ in tuplist if a not in seen]
yield from ([] if not _r else get_graphs(_r[0], c = [], seen= seen))
result = list(get_graphs(tuplist[0][0]))
final_result = [a for i, a in enumerate(result) if all(all(k not in b for k in a) for b in result[i+1:])]
to_tuples = list(map(tuple, final_result))
輸出：
[('f', 'e', 'a', 'c', 'b'), ('z', 'd', 'x')]
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