python3 build.py Automatically configuring target: metal -keys=metal,gpu -max_function_args=31 -max_num_threads=256 -max_shared_memory_per_block=32768 -max_threads_per_block=1024 -thread_warp_size=32 Load cached module from dist/mod_cache_before_build.pkl and skip tracing. You can use --use-cache=0 to retrace Traceback (most recent call last): File "/Users/b03/Desktop/old/build.py", line 195, in <module> build(mod, ARGS) File "/Users/b03/Desktop/old/build.py", line 130, in build db = ms.database.create(work_dir=args.db_path) File "/opt/anaconda3/envs/web2/lib/python3.10/site-packages/tvm/meta_schedule/database/database.py", line 417, in create return JSONDatabase(*args, **kwargs) File "/opt/anaconda3/envs/web2/lib/python3.10/site-packages/tvm/meta_schedule/database/json_database.py", line 86, in __init__ self.__init_handle_by_constructor__( File "tvm/_ffi/_cython/./object.pxi", line 132, in tvm._ffi._cy3.core.ObjectBase.__init_handle_by_constructor__ File "tvm/_ffi/_cython/./packed_func.pxi", line 288, in tvm._ffi._cy3.core.ConstructorCall File "tvm/_ffi/_cython/./packed_func.pxi", line 277, in tvm._ffi._cy3.core.FuncCall File "tvm/_ffi/_cython/./base.pxi", line 182, in tvm._ffi._cy3.core.CHECK_CALL File "/opt/anaconda3/envs/web2/lib/python3.10/site-packages/tvm/_ffi/base.py", line 481, in raise_last_ffi_error raise py_err tvm._ffi.base.TVMError: Traceback (most recent call last): File "/Users/catalyst/Workspace/mlc-ai-package-self-runner/_work/package/package/tvm/src/support/parallel_for.cc", line 128 RuntimeError: parallel_for_dynamic error with [17:46:32] /Users/catalyst/Workspace/mlc-ai-package-self-runner/_work/package/package/tvm/src/meta_schedule/database/json_database.cc:198: ValueError: Unable to parse TuningRecord, on line 7 of file log_db/database_tuning_record.json. The workload is: # from tvm.script import ir as I # from tvm.script import tir as T @I.ir_module class Module: @T.prim_func def main(rxplaceholder: T.Buffer((T.int64(1), T.int64(4), T.int64(64), T.int64(64)), "float32"), T_multiply: T.Buffer((T.int64(1), T.int64(4), T.int64(64), T.int64(64)), "float32")): T.func_attr({"op_pattern": 0, "tir.noalias": T.bool(True)}) # with T.block("root"): for ax0, ax1, ax2, ax3 in T.grid(T.int64(1), T.int64(4), T.int64(64), T.int64(64)): with T.block("T_multiply"): v_ax0, v_ax1, v_ax2, v_ax3 = T.axis.remap("SSSS", [ax0, ax1, ax2, ax3]) T.reads(rxplaceholder[v_ax0, v_ax1, v_ax2, v_ax3]) T.writes(T_multiply[v_ax0, v_ax1, v_ax2, v_ax3]) T_multiply[v_ax0, v_ax1, v_ax2, v_ax3] = T.float32(0.041666667908430099) * rxplaceholder[v_ax0, v_ax1, v_ax2, v_ax3] The JSONObject of TuningRecord is: [T.int64(6), [[[["GetBlock", [], ["T_multiply", "main"], ["b0"]], ["GetLoops", ["b0"], [], ["l1", "l2", "l3", "l4"]], ["Fuse", ["l1", "l2", "l3", "l4"], [T.int64(1)], ["l5"]], ["SampleCategorical", [], [[T.int64(32), T.int64(64), T.int64(128), T.int64(256), T.int64(512), T.int64(1024)], [T.float64(0.16666666666666666), T.float64(0.16666666666666666), T.float64(0.16666666666666666), T.float64(0.16666666666666666), T.float64(0.16666666666666666), T.float64(0.16666666666666666)]], ["v6"]], ["Split", ["l5", "None", "v6"], [T.int64(1)], ["l7", "l8"]], ["Bind", ["l7"], ["blockIdx.x"], []], ["Bind", ["l8"], ["threadIdx.x"], []], ["EnterPostproc", [], [], []]], [[T.int64(3), T.int64(0)]]], [T.float64(2.767325769084694e-05)], {"thread_warp_size": T.int64(32), "host": {"mtriple": "arm64-apple-macos", "tag": "", "kind": "llvm", "mcpu": "apple-latest", "keys": ["arm_cpu", "cpu"]}, "max_threads_per_block": T.int64(1024), "max_function_args": T.int64(31), "max_num_threads": T.int64(256), "tag": "", "max_shared_memory_per_block": T.int64(32768), "kind": "metal", "keys": ["metal", "gpu"]}, [["TENSOR", "float32", [T.int64(1), T.int64(4), T.int64(64), T.int64(64)]], ["TENSOR", "float32", [T.int64(1), T.int64(4), T.int64(64), T.int64(64)]]]]] The error message is: [17:46:32] /Users/catalyst/Workspace/mlc-ai-package-self-runner/_work/package/package/tvm/src/meta_schedule/database/database.cc:167: ValueError: Unable to parse the JSON object: [[[["GetBlock", [], ["T_multiply", "main"], ["b0"]], ["GetLoops", ["b0"], [], ["l1", "l2", "l3", "l4"]], ["Fuse", ["l1", "l2", "l3", "l4"], [T.int64(1)], ["l5"]], ["SampleCategorical", [], [[T.int64(32), T.int64(64), T.int64(128), T.int64(256), T.int64(512), T.int64(1024)], [T.float64(0.16666666666666666), T.float64(0.16666666666666666), T.float64(0.16666666666666666), T.float64(0.16666666666666666), T.float64(0.16666666666666666), T.float64(0.16666666666666666)]], ["v6"]], ["Split", ["l5", "None", "v6"], [T.int64(1)], ["l7", "l8"]], ["Bind", ["l7"], ["blockIdx.x"], []], ["Bind", ["l8"], ["threadIdx.x"], []], ["EnterPostproc", [], [], []]], [[T.int64(3), T.int64(0)]]], [T.float64(2.767325769084694e-05)], {"thread_warp_size": T.int64(32), "host": {"mtriple": "arm64-apple-macos", "tag": "", "kind": "llvm", "mcpu": "apple-latest", "keys": ["arm_cpu", "cpu"]}, "max_threads_per_block": T.int64(1024), "max_function_args": T.int64(31), "max_num_threads": T.int64(256), "tag": "", "max_shared_memory_per_block": T.int64(32768), "kind": "metal", "keys": ["metal", "gpu"]}, [["TENSOR", "float32", [T.int64(1), T.int64(4), T.int64(64), T.int64(64)]], ["TENSOR", "float32", [T.int64(1), T.int64(4), T.int64(64), T.int64(64)]]]] The error is: [17:46:32] /Users/catalyst/Workspace/mlc-ai-package-self-runner/_work/package/package/tvm/src/tir/schedule/primitive/.././instruction_traits.h:387: InternalError: Check failed: kNumAttrs == attrs.size() (2 vs. 1) : ValueError: Incorrect kNumAttrs for instruction: Split