def process_boosters(dag):
dag_nx = utils.dag_to_nx(dag)
processed_dag = dict()
sub_dags = []
for k, spec in dag.items():
if spec[1][0] == 'booBegin':
input_name = spec[0]
for node in nx.dfs_preorder_nodes(dag_nx, k):
node_type = dag[node][1][0]
if node == k:
continue
if node_type == 'booster':
sub_dags.append(dag[node][1][2])
if node_type == 'booEnd':
sub_dags = [normalize_dag(sd) for sd in sub_dags]
processed_dag[k] = (input_name, ['booster', {'sub_dags': sub_dags}], dag[node][2])
sub_dags = []
break
elif spec[1][0] in ['booster', 'booEnd']:
continue
else:
processed_dag[k] = spec
return processed_dag
def process_boosters(dag):
dag_nx = utils.dag_to_nx(dag)
processed_dag = dict()
sub_dags = []
for k, spec in dag.items():
if spec[1][0] == 'booBegin':
input_name = spec[0]
for node in nx.dfs_preorder_nodes(dag_nx, k):
node_type = dag[node][1][0]
if node == k:
continue
if node_type == 'booster':
sub_dags.append(dag[node][1][2])
if node_type == 'booEnd':
sub_dags = [normalize_dag(sd) for sd in sub_dags]
processed_dag[k] = (input_name,
['booster', {
'sub_dags': sub_dags
}], dag[node][2])
sub_dags = []
break
elif spec[1][0] in ['booster', 'booEnd']:
continue
else:
processed_dag[k] = spec
return processed_dag
def extract_subgraphs(dag, node):
out = []
dag_nx = utils.dag_to_nx(dag)
reverse_dag_nx = dag_nx.reverse()
for p in dag_nx.predecessors(node):
out.append({
k: v
for k, v in dag.items()
if k in list(nx.dfs_preorder_nodes(reverse_dag_nx, p))
})
common_nodes = [n for n in out[0] if all((n in o for o in out))]
toposort = list(nx.topological_sort(dag_nx))
sorted_common = sorted(common_nodes, key=lambda k: -toposort.index(k))
inputs = np.unique([
dag[n][0] for n in dag_nx.successors(sorted_common[0])
if any([n in o for o in out])
])
assert len(inputs) == 1
input_id = inputs[0]
remove_common = sorted_common
nout = []
for o in out:
no = dict()
no['input'] = ([], 'input', input_id)
for k, v in o.items():
if k in remove_common:
continue
ins = v[2]
if not isinstance(ins, list):
ins = [ins]
if ins[0] in dag[node][0]:
no[k] = v[0], v[1], 'output'
continue
no[k] = v
nout.append(no)
initial_dag = {k: v for k, v in dag.items() if k in common_nodes}
for k, v in initial_dag.items():
if isinstance(v[2], list) and input_id in v[2]:
initial_dag[k] = (v[0], v[1],
[x if x != input_id else 'output' for x in v[2]])
break
if v[2] == input_id:
initial_dag[k] = (v[0], v[1], 'output')
return nout, initial_dag, input_id
def extract_subgraphs(dag, node):
out = []
dag_nx = utils.dag_to_nx(dag)
reverse_dag_nx = dag_nx.reverse()
for p in dag_nx.predecessors(node):
out.append({k: v for k, v in dag.items() if k in list(nx.dfs_preorder_nodes(reverse_dag_nx, p))})
common_nodes = [n for n in out[0] if all((n in o for o in out))]
toposort = list(nx.topological_sort(dag_nx))
sorted_common = sorted(common_nodes, key=lambda k: -toposort.index(k))
inputs = np.unique([dag[n][0] for n in dag_nx.successors(sorted_common[0]) if any([n in o for o in out])])
assert len(inputs) == 1
input_id = inputs[0]
remove_common = sorted_common
nout = []
for o in out:
no = dict()
no['input'] = ([], 'input', input_id)
for k, v in o.items():
if k in remove_common:
continue
ins = v[2]
if not isinstance(ins, list):
ins = [ins]
if ins[0] in dag[node][0]:
no[k] = v[0], v[1], 'output'
continue
no[k] = v
nout.append(no)
initial_dag = {k: v for k, v in dag.items() if k in common_nodes}
for k, v in initial_dag.items():
if isinstance(v[2], list) and input_id in v[2]:
initial_dag[k] = (v[0], v[1], [x if x != input_id else 'output' for x in v[2]])
break
if v[2] == input_id:
initial_dag[k] = (v[0], v[1], 'output')
return nout, initial_dag, input_id