arm_cpu compilation problem!
When the AI model are assigned to arm_cpu for compilation, the compiled model operators are scattered into multiple subgraphs instead of compiling into a complete graph (one operator compiled as one subgraph) . This seriously affects the speed of reasoning. Could you tell me how to solve this code? How can arm_cpu compile all operators into one graph instead of multiple subgraphs?
For example, in the mobilenetv2.onnx model, the operators in the model are compiled into arm_cpu. The json result of the model is as follows. The model operators are divided into many subgraphs of the class, resulting in slow running speed.
： { “nodes”: [ { “op”: “null”, “name”: “input”, “inputs”: [] }, { “op”: “null”, “name”: “p0”, “inputs”: [] }, { “op”: “null”, “name”: “p1”, “inputs”: [] }, { “op”: “tvm_op”, “name”: “tvmgen_default_fused_nn_conv2d_add_clip”, “attrs”: { “num_outputs”: “1”, “num_inputs”: “3”, “flatten_data”: “0”, “func_name”: “tvmgen_default_fused_nn_conv2d_add_clip”, “out_layout”: “”, “kernel_layout”: “OIHW”, “data_layout”: “NCHW”, “hash”: “2714b8eaaab95a1c” }, “inputs”: [ [ 0, 0, 0 ], [ 1, 0, 0 ], [ 2, 0, 0 ] ] }, { “op”: “null”, “name”: “p2”, “inputs”: [] }, { “op”: “null”, “name”: “p3”, “inputs”: [] }, { “op”: “tvm_op”, “name”: “tvmgen_default_fused_nn_conv2d_add_clip_1”, “attrs”: { “num_outputs”: “1”, “num_inputs”: “3”, “flatten_data”: “0”, “func_name”: “tvmgen_default_fused_nn_conv2d_add_clip_1”, “out_layout”: “”, “kernel_layout”: “OIHW”, “data_layout”: “NCHW”, “hash”: “1c02e3eebef4748c” }, “inputs”: [ [ 3, 0, 0 ], [ 4, 0, 0 ], [ 5, 0, 0 ] ] }, { “op”: “null”, “name”: “p4”, “inputs”: [] }, { “op”: “null”, “name”: “p5”, “inputs”: [] }, { “op”: “tvm_op”, “name”: “tvmgen_default_fused_nn_conv2d_add”, “attrs”: { “num_outputs”: “1”, “num_inputs”: “3”, “flatten_data”: “0”, “func_name”: “tvmgen_default_fused_nn_conv2d_add”, “out_layout”: “”, “kernel_layout”: “OIHW”, “data_layout”: “NCHW”, “hash”: “0a3ab8dc5430c9ad” }, “inputs”: [ [ 6, 0, 0 ], [ 7, 0, 0 ], [ 8, 0, 0 ] ] }, { “op”: “null”, “name”: “p6”, “inputs”: [] }, { “op”: “null”, “name”: “p7”, “inputs”: [] }, { “op”: “tvm_op”, “name”: “tvmgen_default_fused_nn_conv2d_add_clip_2”, “attrs”: { “num_outputs”: “1”, “num_inputs”: “3”, “flatten_data”: “0”, “func_name”: “tvmgen_default_fused_nn_conv2d_add_clip_2”, “out_layout”: “”, “kernel_layout”: “OIHW”, “data_layout”: “NCHW”, “hash”: “738375e0ba07c89e” }, …