IshwaraK opened a new issue #4748: Segmentation Fault at Optimization level 2 and above URL: https://github.com/apache/incubator-tvm/issues/4748 The below reduced test-case shows segmentation fault in TVM compiler stack at the optimization level 2 and above. The problem is in call to 'lib.get_source()', as constant folding optimizes away whole graph and lib object becomes NULL. import tvm from tvm import relay from tvm.contrib import graph_runtime import numpy as np data_shape = (2, 2) matrix_x = relay.var('matrix_x', shape=data_shape, dtype='int32') matrix_y = relay.var('matrix_y', shape=data_shape, dtype='int32') add = relay.op.add(matrix_x, matrix_y) fun = relay.Function([matrix_x,matrix_y], add) relayMod = relay.Module({}) fname = relay.GlobalVar('main') relayMod.entry_func = fname relayMod[fname] = fun print("Relay Module:\n", relayMod) x_data = np.matrix('1 2; 3 4', dtype='int32') y_data = np.matrix('5 6; 7 8', dtype='int32') params = { "matrix_x" : x_data, "matrix_y" : y_data, } with relay.build_config(opt_level=3): graph, lib, params = relay.build(relayMod, "llvm", params=params) print("Model graph:\n", graph) print("\nModel parameters:") for item in params: print(item, ":\n", params[item]) print("\nOperator library:\n", lib.get_source()) mod = graph_runtime.create(graph, lib, ctx=tvm.cpu(0)) mod.set_input(**params) mod.run() res = mod.get_output(0).asnumpy() print("inference:\n", res)
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