def get_structure_stats_dict(node):
node_types = dict(Counter([type(n) for n in get_nodes_by_type(node)]))
num_nodes = len(get_nodes_by_type(node, Node))
edges = get_number_of_edges(node)
layers = get_number_of_layers(node)
return {
'nodes': num_nodes,
'edges': edges,
'layers': layers
}.update(node_types)
def run_experiment(exp, spn, test_data, test_type, exp_lambda):
outprefix = path + "/spns/%s/" % (exp)
results_file = "%stime_test_%s_ll_%s.txt" % (outprefix, test_type, OS_name)
if os.path.isfile(results_file):
return
print(exp, test_data.shape, test_type)
ll, test_time = exp_lambda()
np.savetxt(results_file, ll, delimiter=";")
import cpuinfo
machine = cpuinfo.get_cpu_info()["brand"]
adds, muls = fpga_count_ops(spn)
test_n = test_data.shape[0]
results = OrderedDict()
results["Experiment"] = exp
results["OS"] = OS_name
results["machine"] = machine
results["test type"] = test_type
results["expected adds"] = adds
results["expected muls"] = muls
results["input rows"] = test_n
results["input cols"] = test_data.shape[1]
results["spn nodes"] = len(get_nodes_by_type(spn, Node))
results["spn sum nodes"] = len(get_nodes_by_type(spn, Sum))
results["spn prod nodes"] = len(get_nodes_by_type(spn, Product))
results["spn leaves"] = len(get_nodes_by_type(spn, Leaf))
results["spn edges"] = get_number_of_edges(spn)
results["spn layers"] = get_number_of_layers(spn)
results["time per task"] = test_time
results["time per instance"] = test_time / test_n
results["avg ll"] = np.mean(ll, dtype=np.float128)
results_file_name = "results.csv"
if not os.path.isfile(results_file_name):
results_file = open(results_file_name, "w")
results_file.write(";".join(results.keys()))
results_file.write("\n")
else:
results_file = open(results_file_name, "a")
results_file.write(";".join(map(str, results.values())))
results_file.write("\n")
results_file.close()
def get_structure_stats(node):
num_nodes = len(get_nodes_by_type(node, Node))
sum_nodes = len(get_nodes_by_type(node, Sum))
prod_nodes = len(get_nodes_by_type(node, Product))
leaf_nodes = len(get_nodes_by_type(node, Leaf))
edges = get_number_of_edges(node)
layers = get_number_of_layers(node)
return """---Structure Statistics---
# nodes %s
# sum nodes %s
# prod nodes %s
# leaf nodes %s
# edges %s
# layers %s""" % (num_nodes, sum_nodes, prod_nodes, leaf_nodes,
edges, layers)
def get_structure_stats_dict(node):
num_nodes = len(get_nodes_by_type(node, Node))
sum_nodes = len(
[s for s in get_nodes_by_type(node, Sum) if type(s) == Sum])
prod_nodes = len(get_nodes_by_type(node, Product))
leaf_nodes = len(get_nodes_by_type(node, Leaf))
param_leaf_nodes = len(get_nodes_by_type(node, Parametric))
type_leaf_nodes = len(get_nodes_by_type(node, TypeLeaf))
edges = get_number_of_edges(node)
layers = get_number_of_layers(node)
return {
'nodes': num_nodes,
'edges': edges,
'layers': layers,
'sum': sum_nodes,
'prod': prod_nodes,
'leaf': leaf_nodes,
'param-leaf': param_leaf_nodes,
'type-leaf': type_leaf_nodes
}