hi, I have build from source and cant do import python 
get next error:
when doing “import tvm”
I get next error:
Traceback (most recent call last):
File “”, line 1, in
File “/home/user/.local/lib/python3.6/site-packages/tvm-0.7.dev1-py3.6-linux-x86_64.egg/tvm/ init .py”, line 49, in
from . import target
File “/home/user/.local/lib/python3.6/site-packages/tvm-0.7.dev1-py3.6-linux-x86_64.egg/tvm/target/ init .py”, line 57, in
from .target import Target, create
File “/home/user/.local/lib/python3.6/site-packages/tvm-0.7.dev1-py3.6-linux-x86_64.egg/tvm/target/target.py”, line 28, in
class TargetKind(Object):
File “/home/user/.local/lib/python3.6/site-packages/tvm-0.7.dev1-py3.6-linux-x86_64.egg/tvm/_ffi/registry.py”, line 82, in register_object
return register(type_key)
File “/home/user/.local/lib/python3.6/site-packages/tvm-0.7.dev1-py3.6-linux-x86_64.egg/tvm/_ffi/registry.py”, line 68, in register
c_str(object_name), ctypes.byref(tidx)))
File “/home/user/.local/lib/python3.6/site-packages/tvm-0.7.dev1-py3.6-linux-x86_64.egg/tvm/_ffi/base.py”, line 334, in check_call
raise get_last_ffi_error()
tvm.ffi.base.TVMError: Traceback (most recent call last):
[bt] (2) /home/user/.local/lib/python3.6/site-packages/tvm-0.7.dev1-py3.6-linux-x86_64.egg/tvm/libtvm.so(TVMObjectTypeKey2Index+0x55) [0x7fc7f1ac4e75]
[bt] (1) /home/user/.local/lib/python3.6/site-packages/tvm-0.7.dev1-py3.6-linux-x86_64.egg/tvm/libtvm.so(tvm::runtime::Object::TypeKey2Index(std:: cxx11::basic_string<char, std::char_traits, std::allocator > const&)+0x214) [0x7fc7f1ac4dc4]
[bt] (0) /home/user/.local/lib/python3.6/site-packages/tvm-0.7.dev1-py3.6-linux-x86_64.egg/tvm/libtvm.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x82) [0x7fc7f0fbecd2]
File “/home/user/tvm/src/runtime/object.cc”, line 155
TVMError: Check failed: it != type_key2index .end(): Cannot find type TargetKind. Did you forget to register the node by TVM_REGISTER_NODE_TYPE ?
my cmake is:
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distributed with this work for additional information
regarding copyright ownership. The ASF licenses this file
to you under the Apache License, Version 2.0 (the
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with the License. You may obtain a copy of the License at
Apache License, Version 2.0
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software distributed under the License is distributed on an
“AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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specific language governing permissions and limitations
under the License.
#--------------------------------------------------------------------
Template custom cmake configuration for compiling
This file is used to override the build options in build.
If you want to change the configuration, please use the following
steps. Assume you are on the root directory. First copy the this
file so that any local changes will be ignored by git
$ mkdir build
$ cp cmake/config.cmake build
Next modify the according entries, and then compile by
$ cd build
$ cmake ..
Then build in parallel with 8 threads
$ make -j8
#--------------------------------------------------------------------
#---------------------------------------------
Backend runtimes.
#---------------------------------------------
Whether enable CUDA during compile,
Possible values:
- ON: enable CUDA with cmake’s auto search
- OFF: disable CUDA
- /path/to/cuda: use specific path to cuda toolkit
set(USE_CUDA OFF)
Whether enable ROCM runtime
Possible values:
- ON: enable ROCM with cmake’s auto search
- OFF: disable ROCM
- /path/to/rocm: use specific path to rocm
set(USE_ROCM OFF)
Whether enable SDAccel runtime
set(USE_SDACCEL OFF)
Whether enable Intel FPGA SDK for OpenCL (AOCL) runtime
set(USE_AOCL OFF)
Whether enable OpenCL runtime
set(USE_OPENCL ON)
Whether enable Metal runtime
set(USE_METAL OFF)
Whether enable Vulkan runtime
Possible values:
- ON: enable Vulkan with cmake’s auto search
- OFF: disable vulkan
- /path/to/vulkan-sdk: use specific path to vulkan-sdk
set(USE_VULKAN OFF)
Whether enable OpenGL runtime
set(USE_OPENGL OFF)
Whether enable MicroTVM runtime
set(USE_MICRO OFF)
Whether to enable SGX runtime
Possible values for USE_SGX:
- /path/to/sgxsdk: path to Intel SGX SDK
- OFF: disable SGX
SGX_MODE := HW|SIM
set(USE_SGX OFF) set(SGX_MODE “SIM”) set(RUST_SGX_SDK “/path/to/rust-sgx-sdk”)
Whether enable RPC runtime
set(USE_RPC ON)
Whether embed stackvm into the runtime
set(USE_STACKVM_RUNTIME OFF)
Whether enable tiny embedded graph runtime.
set(USE_GRAPH_RUNTIME ON)
Whether enable additional graph debug functions
set(USE_GRAPH_RUNTIME_DEBUG OFF)
Whether enable additional vm profiler functions
set(USE_VM_PROFILER OFF)
Whether enable uTVM standalone runtime
set(USE_MICRO_STANDALONE_RUNTIME OFF)
Whether build with LLVM support
Requires LLVM version >= 4.0
Possible values:
- ON: enable llvm with cmake’s find search
- OFF: disable llvm
- /path/to/llvm-config: enable specific LLVM when multiple llvm-dev is available.
set(USE_LLVM ON)
#---------------------------------------------
Contrib libraries
#---------------------------------------------
Whether use BLAS, choices: openblas, mkl, atlas, apple
set(USE_BLAS none)
/path/to/mkl: mkl root path when use mkl blas library
set(USE_MKL_PATH /opt/intel/mkl) for UNIX
set(USE_MKL_PATH ../IntelSWTools/compilers_and_libraries_2018/windows/mkl) for WIN32
set(USE_MKL_PATH ) if using pip install mkl
set(USE_MKL_PATH none)
Whether use MKLDNN library, choices: ON, OFF, path to mkldnn library
set(USE_MKLDNN OFF)
Whether use OpenMP thread pool, choices: gnu, intel
Note: “gnu” uses gomp library, “intel” uses iomp5 library
set(USE_OPENMP none)
Whether use contrib.random in runtime
set(USE_RANDOM OFF)
Whether use NNPack
set(USE_NNPACK OFF)
Possible values:
- ON: enable tflite with cmake’s find search
- OFF: disable tflite
- /path/to/libtensorflow-lite.a: use specific path to tensorflow lite library
set(USE_TFLITE /home/user/tensorflow/tensorflow/lite/tools/make/gen/linux_x86_64/lib/)
/path/to/tensorflow: tensorflow root path when use tflite library
set(USE_TENSORFLOW_PATH /home/user/tensorflow/)
Required for full builds with TFLite. Not needed for runtime with TFLite.
/path/to/flatbuffers: flatbuffers root path when using tflite library
set(USE_FLATBUFFERS_PATH /home/user/flatbuffers/)
Possible values:
- OFF: disable tflite support for edgetpu
- /path/to/edgetpu: use specific path to edgetpu library
set(USE_EDGETPU OFF)
Whether use CuDNN
set(USE_CUDNN OFF)
Whether use cuBLAS
set(USE_CUBLAS OFF)
Whether use MIOpen
set(USE_MIOPEN OFF)
Whether use MPS
set(USE_MPS OFF)
Whether use rocBlas
set(USE_ROCBLAS OFF)
Whether use contrib sort
set(USE_SORT ON)
Whether use MKL-DNN (DNNL) codegen
set(USE_DNNL_CODEGEN OFF)
Whether to use Arm Compute Library (ACL) codegen
We provide 2 separate flags since we cannot build the ACL runtime on x86.
This is useful for cases where you want to cross-compile a relay graph
on x86 then run on AArch.
An example of how to use this can be found here: docs/deploy/arm_compute_lib.rst.
USE_ARM_COMPUTE_LIB - Support for compiling a relay graph offloading supported
operators to Arm Compute Library. OFF/ON
USE_ARM_COMPUTE_LIB_GRAPH_RUNTIME - Run Arm Compute Library annotated functions via the ACL
runtime. OFF/ON/“path/to/ACL”
set(USE_ARM_COMPUTE_LIB OFF) set(USE_ARM_COMPUTE_LIB_GRAPH_RUNTIME OFF)
Build ANTLR parser for Relay text format
Possible values:
- ON: enable ANTLR by searching default locations (cmake find_program for antlr4 and /usr/local for jar)
- OFF: disable ANTLR
- /path/to/antlr-*-complete.jar: path to specific ANTLR jar file
set(USE_ANTLR OFF)
Whether use Relay debug mode
set(USE_RELAY_DEBUG OFF)
Whether to build fast VTA simulator driver
set(USE_VTA_FSIM OFF)
Whether to build cycle-accurate VTA simulator driver
set(USE_VTA_TSIM OFF)
Whether to build VTA FPGA driver (device side only)
set(USE_VTA_FPGA OFF)
Whether use Thrust
set(USE_THRUST OFF)
Whether to build the TensorFlow TVMDSOOp module
set(USE_TF_TVMDSOOP OFF)
Whether to use STL’s std::unordered_map or TVM’s POD compatible Map
set(USE_FALLBACK_STL_MAP OFF)
Whether to use hexagon device
set(USE_HEXAGON_DEVICE OFF) set(USE_HEXAGON_SDK /path/to/sdk)
Whether to use ONNX codegen
set(USE_TARGET_ONNX OFF)
Whether to compile the standalone C runtime.
set(USE_STANDALONE_CRT ON)