Before you open an issue, please make sure you have tried the following steps:

1. Make sure your environment is the same with (https://mace.readthedocs.io/en/latest/installation/env_requirement.html).
2. Have you ever read the document for your usage?
3. Check if your issue appears in HOW-TO-DEBUG or FAQ.
4. The form below must be filled.

System information

• OS Platform and Distribution Ubuntu 16.04:
• NDK version 16r:
• GCC version(5.4.0):
• MACE version (Use the command: git describe --long --tags):
• Python version(2.7):
• Bazel version (0.15.0):

Model deploy file (*.yml)

library_name: cpmCaffe
target_abis: [armeabi-v7a]
model_graph_format: file
model_data_format: file
models:
  openposecaffe: # model tag, which will be used in model loading and must be specific.
    platform: caffe
    # support local path, http:// and https://
    model_file_path: /media/long/data/android/PoseEstimationForMobile/caffemodel/new.prototxt 
    weight_file_path: /media/long/data/android/PoseEstimationForMobile/caffemodel/new.caffemodel
    # sha256_checksum of your model's graph and data files.
    # get the sha256_checksum: sha256sum path/to/your/file
    model_sha256_checksum: 9b335cbfb0acefe8d64237bda267180ec2fdfb24005386c99f01daa4bacf25e6
    weight_sha256_checksum: 6b382bcf12e75b51e635d166b909301c499debfefa4cb1ebf8f9a7c2ee1137cc
    # define your model's interface
    # if there multiple inputs or outputs, write like blow:
    subgraphs:
      - input_tensors:
          - data
        input_shapes:
          - 1,128,128,3
        output_tensors:
          - detection_out
        output_shapes:
          - 1,1,1,6
    runtime: cpu+gpu
    winograd: 0
````

### Describe the problem
A clear and concise description of what the bug is.

### To Reproduce
Steps to reproduce the problem:
```bash
python tools/converter.py convert --config=/media/long/data/android/PoseEstimationForMobile/release/mace_ymls/cpmCaffe.yml 
```

### Error information / logs
Please include the **full** log and/or traceback here.
```bash
![image](https://user-images.githubusercontent.com/30176962/56037277-77861e80-5d61-11e9-92e0-45fea5a972d1.png)

picture ,check the website.
```

### Additional context
Add any other context about the problem here, e.g., what you have modified about the code.

我在Android Demo的根目录下的mobilenet.yml增加了inception-v3、mobilenet-v2、resnet-v2-50，我想一次性编译多个模型，是否是支持的？

library_name: mobilenet
target_abis: [armeabi-v7a]
model_graph_format: code
model_data_format: code
models:
  mobilenet_v1:
    platform: tensorflow
    model_file_path: https://cnbj1.fds.api.xiaomi.com/mace/miai-models/mobilenet-v1/mobilenet-v1-1.0.pb
    model_sha256_checksum: 71b10f540ece33c49a7b51f5d4095fc9bd78ce46ebf0300487b2ee23d71294e6
    subgraphs:
      - input_tensors:
          - input
        input_shapes:
          - 1,224,224,3
        output_tensors:
          - MobilenetV1/Predictions/Reshape_1
        output_shapes:
          - 1,1001
    runtime: cpu+gpu
    limit_opencl_kernel_time: 0
    nnlib_graph_mode: 0
    obfuscate: 0
    winograd: 0

  mobilenet_v2:
    platform: tensorflow
    model_file_path: https://cnbj1.fds.api.xiaomi.com/mace/miai-models/mobilenet-v2/mobilenet-v2-1.0.pb
    model_sha256_checksum: 369f9a5f38f3c15b4311c1c84c032ce868da9f371b5f78c13d3ea3c537389bb4
    subgraphs:
      - input_tensors:
          - input
        input_shapes:
          - 1,224,224,3
        output_tensors:
          - MobilenetV2/Predictions/Reshape_1
        output_shapes:
          - 1,1001
    runtime: cpu+gpu
    limit_opencl_kernel_time: 0
    nnlib_graph_mode: 0
    obfuscate: 0
    winograd: 0

  inception_v3:
    platform: tensorflow
    model_file_path: https://cnbj1.fds.api.xiaomi.com/mace/miai-models/inception-v3/inception-v3.pb
    model_sha256_checksum: 632bb664547c846e7b4e44fe6a2ff9e35df277eb6440b80d9b559302baab1b8d
    subgraphs:
      - input_tensors:
          - input
        input_shapes:
          - 1,299,299,3
        output_tensors:
          - InceptionV3/Predictions/Reshape_1
        output_shapes:
          - 1,1001
    runtime: cpu+gpu
    limit_opencl_kernel_time: 0
    nnlib_graph_mode: 0
    obfuscate: 1
    winograd: 0

  resnet_v2_50:
    platform: tensorflow
    model_file_path: https://cnbj1.fds.api.xiaomi.com/mace/miai-models/resnet-v2-50/resnet-v2-50.pb
    model_sha256_checksum: 713c1a5cbe23d8113f4c013107c8296210b24720b365799023e033c1aa4f9360
    subgraphs:
      - input_tensors:
          - input
        output_tensors:
          - resnet_v2_50/predictions/Reshape_1
        input_shapes:
          - 1,299,299,3
        output_shapes:
          - 1,1001
    runtime: cpu+gpu
    limit_opencl_kernel_time: 0
    nnlib_graph_mode: 0
    obfuscate: 0
    winograd: 0

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ununtu16

• NDK version(e.g., 15c): 17

• GCC version(if compiling for host, e.g., 5.4.0):

• MACE version (Use the command: git describe --long --tags): master

• Python version(2.7): 2.7

• Bazel version (e.g., 0.13.0): 13.0

Model deploy file (*.yml)

......
# The name of library
library_name: libunitest
target_abis: [arm64-v8a]
model_graph_format: file
model_data_format: file
models:
  teacher: # model tag, which will be used in model loading and must be specific.
    platform: tensorflow
    # path to your tensorflow model's pb file. Support local path, http:// and https://
    model_file_path: /home/administrator/Code/share/mace/new_mace/sphereface-sphere_64_bggr_cosface_box_0-975000_features.pb
    # sha256_checksum of your model's pb file.
    # use this command to get the sha256_checksum: sha256sum path/to/your/pb/file
    model_sha256_checksum: f3bdc80bba9160b3344fbaefafff80ff1fc72ca533116b62f780baf258668cb8
    # define your model's interface
    # if there multiple inputs or outputs, write like blow:
    subgraphs:
      - input_tensors:
          - input
    #     - input1
        input_shapes:
          - 1,64,64,4
    #     - 1,224,224,3
        output_tensors:
          - Resface/Bottleneck/BatchNorm/FusedBatchNorm
    #      - output1
        output_shapes:
          - 1,1,1,512
    #      - 1,1001
    # cpu, gpu or cpu+gpu
    runtime: gpu
    obfuscate: 1
    winograd: 4

Describe the problem

I am running mace performance test on RK3399 GPU python3 tools/converter.py convert --config=/home/administrator/Code/share/mace/new_mace/FA_models_3.yml

python3 tools/converter.py run --config=/home/administrator/Code/share/mace/new_mace/FA_models_3.yml --round=10

And it failed to run on GPU!!!???

Error information / logs

python3 tools/converter.py run --config=/home/administrator/Code/share/mace/new_mace/FA_models_3.yml --round=100

• Build //mace/tools/validation:mace_run_static with ABI arm64-v8a WARNING: ignoring http_proxy in environment. WARNING: The major revision of the Android NDK referenced by android_ndk_repository rule 'androidndk' is 17. The major revisions supported by Bazel are [10, 11, 12, 13, 14, 15, 16]. Bazel will attempt to treat the NDK as if it was r16. This may cause compilation and linkage problems. Please download a supported NDK version. INFO: Analysed target //mace/tools/validation:mace_run_static (1 packages loaded). INFO: Found 1 target... Target //mace/tools/validation:mace_run_static up-to-date: bazel-bin/mace/tools/validation/mace_run_static INFO: Elapsed time: 1.407s, Critical Path: 0.03s INFO: 0 processes. INFO: Build completed successfully, 1 total action ('build', '//mace/tools/validation:mace_run_static', '--config', 'android', '--cpu=arm64-v8a', '--define', 'neon=true', '--define', 'openmp=false', '--define', 'opencl=true', '--define', 'quantize=false', '--define', 'hexagon=false', '--define', 'hta=false', '--define', 'apu=false', '--config', 'optimization', '--config', 'symbol_hidden') Build done!

      Run model teacher on Firefly-RK3399          

Generate input file: build/libunitest/_tmp/teacher/3e2b51b8ce4724bea30161fb3c936745/Firefly-RK3399_rk3399/arm64-v8a/model_input_input Generate input file done.

• Run 'teacher' with round=100, restart_round=1, tuning=False, out_of_range_check=False, omp_num_threads=(-1,), cpu_affinity_policy=(1,), gpu_perf_hint=(3,), gpu_priority_hint=(3,) Push build/libunitest/_tmp/teacher/3e2b51b8ce4724bea30161fb3c936745/Firefly-RK3399_rk3399/arm64-v8a/model_input_input to /data/local/tmp/mace_run Push build/libunitest/model/teacher.data to /data/local/tmp/mace_run Push build/libunitest/model/teacher.pb to /data/local/tmp/mace_run/teacher.pb Push build/libunitest/_tmp/arm64-v8a/mace_run_static to /data/local/tmp/mace_run Push /tmp/cmd_file-teacher-1568037556.1706104 to /data/local/tmp/mace_run/cmd_file-teacher-1568037556.1706104 I mace/tools/validation/mace_run.cc:462] model name: teacher I mace/tools/validation/mace_run.cc:463] mace version: v0.11.0-rc0-110-g03362fa I mace/tools/validation/mace_run.cc:464] input node: input I mace/tools/validation/mace_run.cc:465] input shape: 1,64,64,4 I mace/tools/validation/mace_run.cc:466] output node: Resface/Bottleneck/BatchNorm/FusedBatchNorm I mace/tools/validation/mace_run.cc:467] output shape: 1,1,1,512 I mace/tools/validation/mace_run.cc:468] input_file: /data/local/tmp/mace_run/model_input I mace/tools/validation/mace_run.cc:469] output_file: /data/local/tmp/mace_run/model_out I mace/tools/validation/mace_run.cc:470] model_data_file: /data/local/tmp/mace_run/teacher.data I mace/tools/validation/mace_run.cc:471] model_file: /data/local/tmp/mace_run/teacher.pb I mace/tools/validation/mace_run.cc:472] device: GPU I mace/tools/validation/mace_run.cc:473] round: 100 I mace/tools/validation/mace_run.cc:474] restart_round: 1 I mace/tools/validation/mace_run.cc:475] gpu_perf_hint: 3 I mace/tools/validation/mace_run.cc:476] gpu_priority_hint: 3 I mace/tools/validation/mace_run.cc:477] omp_num_threads: -1 I mace/tools/validation/mace_run.cc:478] cpu_affinity_policy: 1 I mace/libmace/mace.cc:430] Creating MaceEngine, MACE version: v0.11.0-rc0-110-g03362fa I mace/libmace/mace.cc:469] Initializing MaceEngine I mace/libmace/mace.cc:602] Destroying MaceEngine I mace/tools/validation/mace_run.cc:519] restart round 0 E ./mace/utils/tuner.h:170] Failed to read tuned param file: /data/local/tmp/mace_run/libunitest_tuned_opencl_parameter.Firefly-RK3399.rk3399.bin I mace/libmace/mace.cc:875] Create MaceEngine from model graph proto and weights data I mace/libmace/mace.cc:430] Creating MaceEngine, MACE version: v0.11.0-rc0-110-g03362fa E mace/core/kv_storage.cc:109] Failed to read kv store file: /data/local/tmp/mace_run/interior//mace_cl_compiled_program.bin W mace/core/runtime/opencl/opencl_runtime.cc:382] Load OpenCL cached compiled kernel file failed. Please make sure the storage directory exist and you have Write&Read permission I mace/libmace/mace.cc:469] Initializing MaceEngine I mace/core/net_def_adapter.cc:348] Op d019f091 fall back to CPU I mace/core/net_def_adapter.cc:348] Op 59ce7a42 fall back to CPU I mace/tools/validation/mace_run.cc:268] Create Mace Engine latency: 1891.87 ms I mace/tools/validation/mace_run.cc:275] Total init latency: 1892.24 ms acc in=65536 output_size =2048 I mace/tools/validation/mace_run.cc:326] Warm up run I mace/tools/validation/mace_run.cc:362] 1st warm up run latency: 2851.67 ms I mace/tools/validation/mace_run.cc:369] Run model I mace/tools/validation/mace_run.cc:420] Average latency: 785.491 ms ======================================================== capability(CPU) init warmup run_avg ======================================================== time 47.533 1892.243 2851.674 785.491 I mace/tools/validation/mace_run.cc:442] Write output file /data/local/tmp/mace_run/model_out_Resface_Bottleneck_BatchNorm_FusedBatchNorm with size 2048 done. I mace/libmace/mace.cc:602] Destroying MaceEngine Running finished!

Elapse time: 1.647197 minutes.

• Package libs for libunitest Start packaging 'libunitest' libs into build/libunitest/libmace_libunitest.tar.gz build/libunitest/model/ build/libunitest/model/teacher.pb build/libunitest/model/gpu/ build/libunitest/model/teacher.data Packaging Done!

Before you open an issue, please make sure you have tried the following steps:

1. Make sure your environment is the same with (https://mace.readthedocs.io/en/latest/installation/env_requirement.html).
2. Have you ever read the document for your usage?
3. Check if your issue appears in HOW-TO-DEBUG or FAQ.
4. The form below must be filled.

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 16.04
• NDK version(e.g., 15c): 18b
• GCC version(if compiling for host, e.g., 5.4.0): 5.4.0
• MACE version (Use the command: git describe --long --tags): 0.13.0
• Python version(2.7): 3.6
• Bazel version (e.g., 0.13.0): 0.16.0
• CMake version: 3.16.0

Model deploy file (*.yml)

# The name of library
library_name: FD
target_abis: [arm64-v8a]
model_graph_format: file
model_data_format: file
models:
  RF: # model tag, which will be used in model loading and must be specific.
    platform: caffe
    # path to your tensorflow model's pb file. Support local path, http:// and https://
    model_file_path: /models/model.prototxt
    weight_file_path: /models/model.caffemodel
    # sha256_checksum of your model's pb file.
    # use this command to get the sha256_checksum --> sha256sum path/to/your/pb/file
    model_sha256_checksum: 98f9b69a085e7d8f40704ac6b2fedae0fda876fff4658509dde3d74d883a9684
    weight_sha256_checksum: a9f5d4dfe944315511c6070e8556790409ae0f0bd9005c5db66b4fdd5c38b716
    subgraphs:
      - input_tensors:
          - data
        input_shapes:
          - 1,3,112,112
        input_data_formats:
          - NCHW
        output_tensors:
          - fc1
        output_shapes:
          - 1,1,1,512
    obfuscate: 0
    runtime: gpu
    winograd: 4

Describe the problem

• On kirin710 device, winograd: 4 is slower than winograd: 2. Why does this happen?
• kirin710 model output is different compared to the output obtained when running the same model on a different device (e.g. sdm845 or msmnile). Is WINOGRAD algorithm device-agnostic?

To Reproduce

Steps to reproduce the problem:

1. cd /path/to/mace
2. python tools/converter.py convert --config_file=/path/to/your/model_deployment_file
2. python tools/converter.py run --validate --disable_tuning --config_file=/path/to/your/model_deployment_file

Error information / logs

Please include the full log and/or traceback here.

Additional context

Model to reproduce the issue can be found here

Before you open an issue, please make sure you have tried the following steps:

1. Make sure your environment is the same with (https://mace.readthedocs.io/en/latest/installation/env_requirement.html).
2. Have you ever read the document for your usage?
3. The form below must be filled.

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
• NDK version(e.g., 15c):
• GCC version(if compiling for host, e.g., 5.4.0):
• MACE version (Use the command: git describe --long --tags):
• Python version(2.7):
• Bazel version (e.g., 0.13.0):

Model deploy file (*.yml)

......

Describe the problem

A clear and concise description of what the bug is.

To Reproduce

Steps to reproduce the problem:

1. cd /path/to/mace
2. python tools/converter.py convert --config_file=/path/to/your/model_deployment_file

Error information / logs

Please include the full log and/or traceback here.

LOGs

Additional context

Add any other context about the problem here, e.g., what you have modified about the code.

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu16.04 (MACE Docker image)
• NDK version(e.g., 15c): 18b
• GCC version(if compiling for host, e.g., 5.4.0): gcc (Ubuntu 5.4.0-6ubuntu1~16.04.11) 5.4.0 20160609
• MACE version (Use the command: git describe --long --tags): 0.12.0 (commit: 90d4b860d573fae8bcdcd986884861e18eec18c9)
• Python version(2.7): 3.6
• Bazel version (e.g., 0.13.0): [0.16.0]
• CMake version: 3.16.0

Model deploy file (*.yml)

......

Describe the problem

I have a question about a size of a compiled model library. The size of a model library compiled with v0.12.0 increases significantly by 4x-5x. 2 Caffe and 3 Tensorflow models are converted into the compiled library. Here is the table showing the size of libraries compiled with v0.12.0 and v0.11.0-rc0.

| Target ABI | Library size (v0.11.0-rc0) | Library size (v0.12.0) | |:-----------:|:--------------------------:|:----------------------:| | armeabi-v7a | 94M | 387M | | arm64-v8a | 96M | 504M |

Is it a normal result in v0.12.0?

PS. The compile libraries work fine.

Following issue https://github.com/XiaoMi/mace/issues/595 and specifically @lu229 suggestion https://github.com/XiaoMi/mace/issues/595#issuecomment-599338955, I've implemented a basic data layout transformation to get correct results from Reshape op on GPU when using a model with NCHW data format.

Using the model and yml file from https://github.com/XiaoMi/mace/issues/595#issuecomment-593762744, now validation is successful.

root@ds017:/mace# python tools/converter.py run --config /models/model/model_net3.yml --validate
CMD> bazel build //mace/proto:mace_py
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
Loading:
Loading: 0 packages loaded
Analyzing: target //mace/proto:mace_py (6 packages loaded)
INFO: Analysed target //mace/proto:mace_py (17 packages loaded).
INFO: Found 1 target...
[0 / 7] [-----] BazelWorkspaceStatusAction stable-status.txt
Target //mace/proto:mace_py up-to-date:
bazel-genfiles/mace/proto/mace_pb2.py
INFO: Elapsed time: 2.364s, Critical Path: 0.06s
INFO: 0 processes.
INFO: Build completed successfully, 1 total action
INFO: Build completed successfully, 1 total action

CMD> cp -f bazel-genfiles/mace/proto/mace_pb2.py tools/python/py_proto

CMD> bazel build //third_party/caffe:caffe_py
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
Loading:
Loading: 0 packages loaded
Analyzing: target //third_party/caffe:caffe_py (6 packages loaded)
INFO: Analysed target //third_party/caffe:caffe_py (17 packages loaded).
INFO: Found 1 target...
[0 / 1] [-----] BazelWorkspaceStatusAction stable-status.txt
Target //third_party/caffe:caffe_py up-to-date:
bazel-genfiles/third_party/caffe/caffe_pb2.py
INFO: Elapsed time: 2.337s, Critical Path: 0.05s
INFO: 0 processes.
INFO: Build completed successfully, 1 total action
INFO: Build completed successfully, 1 total action

CMD> cp -f bazel-genfiles/third_party/caffe/caffe_pb2.py tools/python/py_proto

* Build //mace/tools:mace_run_static with ABI arm64-v8a
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
WARNING: The major revision of the Android NDK referenced by android_ndk_repository rule 'androidndk' is 19. The major revisions supported by Bazel are [10, 11, 12, 13, 14, 15, 16]. Bazel will attempt to treat the NDK as if it was r16. This may cause compilation and linkage problems. Please download a supported NDK version.
INFO: Analysed target //mace/tools:mace_run_static (32 packages loaded).
INFO: Found 1 target...
Target //mace/tools:mace_run_static up-to-date:
  bazel-bin/mace/tools/mace_run_static
INFO: Elapsed time: 11.826s, Critical Path: 0.50s
INFO: 0 processes.
INFO: Build completed successfully, 1 total action
('build', '//mace/tools:mace_run_static', '--config', 'android', '--cpu=arm64-v8a', '--define', 'neon=true', '--define', 'openmp=false', '--define', 'opencl=true', '--define', 'quantize=false', '--define', 'hexagon=false', '--define', 'hta=false', '--define', 'apu=false', '--config', 'optimization', '--config', 'symbol_hidden')
Build done!

***********************************************
          Run model model on MI9          
***********************************************

Generate input file:  build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/MI9_msmnile/arm64-v8a/model_input_data
Generate input file done.
* Run 'model' with round=1, restart_round=1, tuning=False, out_of_range_check=False, omp_num_threads=(-1,), cpu_affinity_policy=(1,), gpu_perf_hint=(3,), gpu_priority_hint=(3,)
Push build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/MI9_msmnile/arm64-v8a/model_input_data to /data/local/tmp/mace_run
Push build/model/model/model.data to /data/local/tmp/mace_run
Push build/model/model/model.pb to /data/local/tmp/mace_run/model.pb
Push build/model/_tmp/arm64-v8a/mace_run_static to /data/local/tmp/mace_run
Push /tmp/cmd_file-model-1584697819.6052978 to /data/local/tmp/mace_run/cmd_file-model-1584697819.6052978
I mace/tools/mace_run.cc:527] model name: model
I mace/tools/mace_run.cc:528] mace version: v0.12.0-0-ga610d50
I mace/tools/mace_run.cc:529] input node: data
I mace/tools/mace_run.cc:530] input shape: 1,3,160,160
I mace/tools/mace_run.cc:531] output node: face_rpn_cls_prob_reshape_stride32,face_rpn_bbox_pred_stride32,face_rpn_landmark_pred_stride32,face_rpn_cls_prob_reshape_stride16,face_rpn_bbox_pred_stride16,face_rpn_landmark_pred_stride16,face_rpn_cls_prob_reshape_stride8,face_rpn_bbox_pred_stride8,face_rpn_landmark_pred_stride8
I mace/tools/mace_run.cc:532] output shape: 1,4,5,5:1,8,5,5:1,20,5,5:1,4,10,10:1,8,10,10:1,20,10,10:1,4,20,20:1,8,20,20:1,20,20,20
I mace/tools/mace_run.cc:533] input_file: /data/local/tmp/mace_run/model_input
I mace/tools/mace_run.cc:534] output_file: /data/local/tmp/mace_run/model_out
I mace/tools/mace_run.cc:535] input dir:
I mace/tools/mace_run.cc:536] output dir:
I mace/tools/mace_run.cc:537] model_data_file: /data/local/tmp/mace_run/model.data
I mace/tools/mace_run.cc:538] model_file: /data/local/tmp/mace_run/model.pb
I mace/tools/mace_run.cc:539] device: GPU
I mace/tools/mace_run.cc:540] round: 1
I mace/tools/mace_run.cc:541] restart_round: 1
I mace/tools/mace_run.cc:542] gpu_perf_hint: 3
I mace/tools/mace_run.cc:543] gpu_priority_hint: 3
I mace/tools/mace_run.cc:544] omp_num_threads: -1
I mace/tools/mace_run.cc:545] cpu_affinity_policy: 1
I mace/tools/mace_run.cc:548] limit_opencl_kernel_time: 0
I mace/tools/mace_run.cc:553] opencl_queue_window_size: 0
I mace/libmace/mace.cc:464] Creating MaceEngine, MACE version: v0.12.0-0-ga610d50
I mace/libmace/mace.cc:503] Initializing MaceEngine
I mace/libmace/mace.cc:636] Destroying MaceEngine
I mace/tools/mace_run.cc:596] restart round 0
W ./mace/utils/tuner.h:201] Failed to read tuned param file: /data/local/tmp/mace_run/model_tuned_opencl_parameter.MI9.msmnile.bin
I mace/libmace/mace.cc:911] Create MaceEngine from model graph proto and weights data
I mace/libmace/mace.cc:464] Creating MaceEngine, MACE version: v0.12.0-0-ga610d50
W mace/core/kv_storage.cc:109] Failed to read kv store file: /data/local/tmp/mace_run/interior//mace_cl_compiled_program.bin
W mace/core/runtime/opencl/opencl_runtime.cc:382] Load OpenCL cached compiled kernel file failed. Please make sure the storage directory exist and you have Write&Read permission
I mace/libmace/mace.cc:503] Initializing MaceEngine
I mace/tools/mace_run.cc:269] Create Mace Engine latency: 884.83 ms
I mace/tools/mace_run.cc:276] Total init latency: 884.993 ms
I mace/tools/mace_run.cc:370] Warm up run
I mace/tools/mace_run.cc:406] 1st warm up run latency: 1360.07 ms
I mace/tools/mace_run.cc:414] Run model
I mace/tools/mace_run.cc:476] Average latency: 11.777 ms
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride32 with size 400 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride32 with size 800 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride32 with size 2000 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride16 with size 1600 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride16 with size 3200 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride16 with size 8000 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride8 with size 6400 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride8 with size 12800 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride8 with size 32000 done.
========================================================
     capability(CPU)        init      warmup     run_avg
========================================================
time          19.788     884.993    1360.074      11.777
I mace/libmace/mace.cc:636] Destroying MaceEngine
Running finished!

* Validate with caffe
Pull /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride32 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride32 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride32 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride16 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride16 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride16 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride8 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride8 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride8 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/MI9_msmnile/arm64-v8a
face_rpn_cls_prob_reshape_stride32 MACE VS CAFFE similarity: 0.9999999920146434 , sqnr: 12416689.129010014 , pixel_accuracy: 0.8
******************************************
          Similarity Test Passed          
******************************************

face_rpn_bbox_pred_stride32 MACE VS CAFFE similarity: 0.9999543587571056 , sqnr: 10949.429334335218 , pixel_accuracy: 1.0
******************************************
          Similarity Test Passed          
******************************************

face_rpn_landmark_pred_stride32 MACE VS CAFFE similarity: 0.9999657541037306 , sqnr: 13611.449222524909 , pixel_accuracy: 1.0
******************************************
          Similarity Test Passed          
******************************************

face_rpn_cls_prob_reshape_stride16 MACE VS CAFFE similarity: 0.9999999900582555 , sqnr: 13540919.254218182 , pixel_accuracy: 0.775
******************************************
          Similarity Test Passed          
******************************************

face_rpn_bbox_pred_stride16 MACE VS CAFFE similarity: 0.9999490543979106 , sqnr: 9740.480377276486 , pixel_accuracy: 0.9625
******************************************
          Similarity Test Passed          
******************************************

face_rpn_landmark_pred_stride16 MACE VS CAFFE similarity: 0.9999721485332628 , sqnr: 17715.55990542613 , pixel_accuracy: 0.975
******************************************
          Similarity Test Passed          
******************************************

face_rpn_cls_prob_reshape_stride8 MACE VS CAFFE similarity: 0.9999999887438001 , sqnr: 13026576.736919338 , pixel_accuracy: 0.75
******************************************
          Similarity Test Passed          
******************************************

face_rpn_bbox_pred_stride8 MACE VS CAFFE similarity: 0.9998798908366177 , sqnr: 3858.796852940529 , pixel_accuracy: 0.95625
******************************************
          Similarity Test Passed          
******************************************

face_rpn_landmark_pred_stride8 MACE VS CAFFE similarity: 0.9999325048718496 , sqnr: 7404.160247931779 , pixel_accuracy: 0.97
******************************************
          Similarity Test Passed          
******************************************

Validation done!

Dana service is not available.
Elapse time: 0.439396 minutes.
* Build //mace/tools:mace_run_static with ABI arm64-v8a
WARNING: --batch mode is deprecated. Please instead explicitly shut down your Bazel server using the command "bazel shutdown".
WARNING: The major revision of the Android NDK referenced by android_ndk_repository rule 'androidndk' is 19. The major revisions supported by Bazel are [10, 11, 12, 13, 14, 15, 16]. Bazel will attempt to treat the NDK as if it was r16. This may cause compilation and linkage problems. Please download a supported NDK version.
INFO: Analysed target //mace/tools:mace_run_static (32 packages loaded).
INFO: Found 1 target...
Target //mace/tools:mace_run_static up-to-date:
  bazel-bin/mace/tools/mace_run_static
INFO: Elapsed time: 12.009s, Critical Path: 0.50s
INFO: 0 processes.
INFO: Build completed successfully, 1 total action
('build', '//mace/tools:mace_run_static', '--config', 'android', '--cpu=arm64-v8a', '--define', 'neon=true', '--define', 'openmp=false', '--define', 'opencl=true', '--define', 'quantize=false', '--define', 'hexagon=false', '--define', 'hta=false', '--define', 'apu=false', '--config', 'optimization', '--config', 'symbol_hidden')
Build done!

**************************************************
          Run model model on POCOF1          
**************************************************

Generate input file:  build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/POCOF1_sdm845/arm64-v8a/model_input_data
Generate input file done.
* Run 'model' with round=1, restart_round=1, tuning=False, out_of_range_check=False, omp_num_threads=(-1,), cpu_affinity_policy=(1,), gpu_perf_hint=(3,), gpu_priority_hint=(3,)
Push build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/POCOF1_sdm845/arm64-v8a/model_input_data to /data/local/tmp/mace_run
Push build/model/model/model.data to /data/local/tmp/mace_run
Push build/model/model/model.pb to /data/local/tmp/mace_run/model.pb
Push build/model/_tmp/arm64-v8a/mace_run_static to /data/local/tmp/mace_run
Push /tmp/cmd_file-model-1584697859.1764498 to /data/local/tmp/mace_run/cmd_file-model-1584697859.1764498
I mace/tools/mace_run.cc:527] model name: model
I mace/tools/mace_run.cc:528] mace version: v0.12.0-0-ga610d50
I mace/tools/mace_run.cc:529] input node: data
I mace/tools/mace_run.cc:530] input shape: 1,3,160,160
I mace/tools/mace_run.cc:531] output node: face_rpn_cls_prob_reshape_stride32,face_rpn_bbox_pred_stride32,face_rpn_landmark_pred_stride32,face_rpn_cls_prob_reshape_stride16,face_rpn_bbox_pred_stride16,face_rpn_landmark_pred_stride16,face_rpn_cls_prob_reshape_stride8,face_rpn_bbox_pred_stride8,face_rpn_landmark_pred_stride8
I mace/tools/mace_run.cc:532] output shape: 1,4,5,5:1,8,5,5:1,20,5,5:1,4,10,10:1,8,10,10:1,20,10,10:1,4,20,20:1,8,20,20:1,20,20,20
I mace/tools/mace_run.cc:533] input_file: /data/local/tmp/mace_run/model_input
I mace/tools/mace_run.cc:534] output_file: /data/local/tmp/mace_run/model_out
I mace/tools/mace_run.cc:535] input dir:
I mace/tools/mace_run.cc:536] output dir:
I mace/tools/mace_run.cc:537] model_data_file: /data/local/tmp/mace_run/model.data
I mace/tools/mace_run.cc:538] model_file: /data/local/tmp/mace_run/model.pb
I mace/tools/mace_run.cc:539] device: GPU
I mace/tools/mace_run.cc:540] round: 1
I mace/tools/mace_run.cc:541] restart_round: 1
I mace/tools/mace_run.cc:542] gpu_perf_hint: 3
I mace/tools/mace_run.cc:543] gpu_priority_hint: 3
I mace/tools/mace_run.cc:544] omp_num_threads: -1
I mace/tools/mace_run.cc:545] cpu_affinity_policy: 1
I mace/tools/mace_run.cc:548] limit_opencl_kernel_time: 0
I mace/tools/mace_run.cc:553] opencl_queue_window_size: 0
I mace/libmace/mace.cc:464] Creating MaceEngine, MACE version: v0.12.0-0-ga610d50
I mace/libmace/mace.cc:503] Initializing MaceEngine
I mace/libmace/mace.cc:636] Destroying MaceEngine
I mace/tools/mace_run.cc:596] restart round 0
W ./mace/utils/tuner.h:201] Failed to read tuned param file: /data/local/tmp/mace_run/model_tuned_opencl_parameter.POCOF1.sdm845.bin
I mace/libmace/mace.cc:911] Create MaceEngine from model graph proto and weights data
I mace/libmace/mace.cc:464] Creating MaceEngine, MACE version: v0.12.0-0-ga610d50
W mace/core/kv_storage.cc:109] Failed to read kv store file: /data/local/tmp/mace_run/interior//mace_cl_compiled_program.bin
W mace/core/runtime/opencl/opencl_runtime.cc:382] Load OpenCL cached compiled kernel file failed. Please make sure the storage directory exist and you have Write&Read permission
I mace/libmace/mace.cc:503] Initializing MaceEngine
I mace/tools/mace_run.cc:269] Create Mace Engine latency: 1204.28 ms
I mace/tools/mace_run.cc:276] Total init latency: 1204.47 ms
I mace/tools/mace_run.cc:370] Warm up run
I mace/tools/mace_run.cc:406] 1st warm up run latency: 1874.9 ms
I mace/tools/mace_run.cc:414] Run model
I mace/tools/mace_run.cc:476] Average latency: 12.42 ms
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride32 with size 400 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride32 with size 800 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride32 with size 2000 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride16 with size 1600 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride16 with size 3200 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride16 with size 8000 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride8 with size 6400 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride8 with size 12800 done.
I mace/tools/mace_run.cc:491] Write output file /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride8 with size 32000 done.
========================================================
     capability(CPU)        init      warmup     run_avg
========================================================
time          21.267    1204.469    1874.897      12.420
I mace/libmace/mace.cc:636] Destroying MaceEngine
Running finished!

* Validate with caffe
Pull /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride32 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/POCOF1_sdm845/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride32 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/POCOF1_sdm845/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride32 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/POCOF1_sdm845/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride16 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/POCOF1_sdm845/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride16 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/POCOF1_sdm845/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride16 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/POCOF1_sdm845/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride8 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/POCOF1_sdm845/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride8 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/POCOF1_sdm845/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride8 to build/model/_tmp/model/ff8ca0d5edb943c867518c604a0c575d/POCOF1_sdm845/arm64-v8a
face_rpn_cls_prob_reshape_stride32 MACE VS CAFFE similarity: 0.9999999923376746 , sqnr: 12761169.735631926 , pixel_accuracy: 0.75
******************************************
          Similarity Test Passed          
******************************************

face_rpn_bbox_pred_stride32 MACE VS CAFFE similarity: 0.9999559880321396 , sqnr: 11251.16938898572 , pixel_accuracy: 1.0
******************************************
          Similarity Test Passed          
******************************************

face_rpn_landmark_pred_stride32 MACE VS CAFFE similarity: 0.9999370739215658 , sqnr: 7828.408858784128 , pixel_accuracy: 0.98
******************************************
          Similarity Test Passed          
******************************************

face_rpn_cls_prob_reshape_stride16 MACE VS CAFFE similarity: 0.9999999903230272 , sqnr: 13382509.571867507 , pixel_accuracy: 0.75
******************************************
          Similarity Test Passed          
******************************************

face_rpn_bbox_pred_stride16 MACE VS CAFFE similarity: 0.9999496464497996 , sqnr: 9698.99300525273 , pixel_accuracy: 0.9625
******************************************
          Similarity Test Passed          
******************************************

face_rpn_landmark_pred_stride16 MACE VS CAFFE similarity: 0.9999721620823648 , sqnr: 17802.002994858874 , pixel_accuracy: 0.99
******************************************
          Similarity Test Passed          
******************************************

face_rpn_cls_prob_reshape_stride8 MACE VS CAFFE similarity: 0.9999999887525579 , sqnr: 12572009.393454924 , pixel_accuracy: 0.6875
******************************************
          Similarity Test Passed          
******************************************

face_rpn_bbox_pred_stride8 MACE VS CAFFE similarity: 0.999877265839963 , sqnr: 3695.563582568223 , pixel_accuracy: 0.91875
******************************************
          Similarity Test Passed          
******************************************

face_rpn_landmark_pred_stride8 MACE VS CAFFE similarity: 0.9999272805682087 , sqnr: 6862.242260144659 , pixel_accuracy: 0.95
******************************************
          Similarity Test Passed          
******************************************

Validation done!

Dana service is not available.
Elapse time: 0.444397 minutes.
* Package libs for model
Start packaging 'model' libs into build/model/libmace_model.tar.gz
build/model/model/
build/model/model/gpu/
build/model/model/model.data
build/model/model/model.pb
Packaging Done!

--------------------------------------------------------------
                           Library                            
--------------------------------------------------------------
|          key           |               value               |
==============================================================
| MACE Model package Path| build/model/libmace_model.tar.gz|
--------------------------------------------------------------

Code isn't complete yet, indeed I'm not very familiar with MACE project classes and I don't know how to assess if a model requires this data layout transformation or not. Namely, how can I get the model data format (ǸCHW, NHWC) from within mace/ops/opencl/image/reshape.cc? So that we can apply the transformation only if needed.

One additional point is related to performance. I noticed that adding this data layout transformation, of course, takes some time during inference. Maybe there's a better and more performing way to implement it?

@lu229 I hope this helps, please tag anyone else that might be interested in contributing

Before you open an issue, please make sure you have tried the following steps:

1. Make sure your environment is the same with (https://mace.readthedocs.io/en/latest/installation/env_requirement.html).
2. Have you ever read the document for your usage?
3. Check if your issue appears in HOW-TO-DEBUG or FAQ.
4. The form below must be filled.

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 16.04
• NDK version(e.g., 15c): 18b
• GCC version(if compiling for host, e.g., 5.4.0): 5.4.0
• MACE version (Use the command: git describe --long --tags): 0.11.0-rc0
• Python version(2.7): 2.7
• Bazel version (e.g., 0.13.0): 0.16.0

Model deploy file (*.yml)

# The name of library
library_name: model
target_abis: [arm64-v8a]
model_graph_format: file
model_data_format: file
models:
  sp: # model tag, which will be used in model loading and must be specific.
    platform: caffe
    # path to your tensorflow model's pb file. Support local path, http:// and https://
    model_file_path: /models/sp/model-nofc.prototxt
    weight_file_path: /models/sp/model-nofc.caffemodel
    # sha256_checksum of your model's pb file.
    # use this command to get the sha256_checksum --> sha256sum path/to/your/pb/file
    model_sha256_checksum: 54479f5ec821884f5bfcc03cb1f4558275541c6e80d9f33f65cc58562fffe91b 
    weight_sha256_checksum: e9599be0e9d5a5f08b85f9b98d2a76b55463ecb6820efc3bcdbc3ea0050f62a0 
    subgraphs:
      - input_tensors:
          - data
        input_shapes:
          - 1,3,112,112
        input_data_formats:
          - NCHW
        output_tensors:
          - fc1bn
        output_shapes:
          - 1,1,1,512
    obfuscate: 0
    quantize: 1
    quantize_range_file: /mace/overall_range
    runtime: cpu # cpu, gpu or cpu+gpu or dsp
    winograd: 0

Describe the problem

Segmentation fault happens when running quantized depthwise conv2d.

To Reproduce

Steps to reproduce the problem:

1. cd /path/to/mace
2. python tools/converter.py convert --config_file=/path/to/your/model_deployment_file
2. python tools/converter.py run --config_file=/path/to/your/model_deployment_file

Error information / logs

Please include the full log and/or traceback here. https://gist.github.com/gasgallo/619eb23800d7caf46e6e97ed23bfc38a

Additional context

Models runs fine w/o quantization.

我把一个onnx模型转换成mace时，在onnx_converter.py 197行 "to": lambda x: data_type.onnx2tf(x) onnx_attr_translator = { "axis": lambda x: int(x), "axes": lambda x: [int(a) for a in x], "dtype": lambda x: data_type.onnx2tf(x), "keepdims": lambda x: bool(x), "to": lambda x: data_type.onnx2tf(x), } 中遇到 “global name 'data_type' is not defined”这个错误，请问如何解决？

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu16.04 (MACE Docker image)
• NDK version(e.g., 15c): 18b
• GCC version(if compiling for host, e.g., 5.4.0): gcc (Ubuntu 5.4.0-6ubuntu1~16.04.11) 5.4.0 20160609
• MACE version (Use the command: git describe --long --tags): 0.12.0
• Python version(2.7): 3.6
• Bazel version (e.g., 0.13.0): [0.16.0]
• CMake version: 3.16.0

Model deploy file (*.yml)

# The name of library
library_name: libretinanet
target_abis: [arm64-v8a]
model_graph_format: code
model_data_format: code
models:
  retinanet:
    platform: caffe
    model_file_path: /models/retinanet/retinanet3.prototxt
    weight_file_path: /models/retinanet/retinanet3.caffemodel
    model_sha256_checksum: 638e05fc466737c3b8fc36261adaaff40cbd4de5a8c72a46b37f2b00f01180e1
    weight_sha256_checksum: 6222910a773c693c23b4765baba4ed8427e9f3c11781060918e6282a297a7437
    subgraphs:
      - input_tensors:
          - data
        input_shapes:
          - 1,3,320,320
        input_data_formats:
          - NCHW
        output_tensors:
          - face_rpn_cls_prob_reshape_stride32
          - face_rpn_bbox_pred_stride32
          - face_rpn_landmark_pred_stride32
          - face_rpn_cls_prob_reshape_stride16
          - face_rpn_bbox_pred_stride16
          - face_rpn_landmark_pred_stride16
          - face_rpn_cls_prob_reshape_stride8
          - face_rpn_bbox_pred_stride8
          - face_rpn_landmark_pred_stride8
        output_shapes:
          - 1,4,10,10
          - 1,8,10,10
          - 1,20,10,10
          - 1,4,20,20
          - 1,8,20,20
          - 1,20,20,20
          - 1,4,40,40
          - 1,8,40,40
          - 1,20,40,40
        output_data_formats:
          - NCHW
          - NCHW
          - NCHW
          - NCHW
          - NCHW
          - NCHW
          - NCHW
          - NCHW
          - NCHW
    obfuscate: 0
    runtime: gpu
    winograd: 4

Describe the problem

With MACE v0.12.0, the output of converted model is significantly different. As a result, it fails to run in validation mode. In addition, I tried to run unit tests on Andorid Studio and found the output difference. However, with MACE v0.11.0-rc1, the output is fine and the validation runs successfully.

========================================================
     capability(CPU)        init      warmup     run_avg
========================================================
time           7.484     877.331    1323.142      16.371
I mace/libmace/mace.cc:636] Destroying MaceEngine
Running finished!

* Validate with caffe
Pull /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride32 to build/libretinanet/_tmp/retinanet/14a062bf9f488e2a38c1fb60b18a80de/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride32 to build/libretinanet/_tmp/retinanet/14a062bf9f488e2a38c1fb60b18a80de/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride32 to build/libretinanet/_tmp/retinanet/14a062bf9f488e2a38c1fb60b18a80de/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride16 to build/libretinanet/_tmp/retinanet/14a062bf9f488e2a38c1fb60b18a80de/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride16 to build/libretinanet/_tmp/retinanet/14a062bf9f488e2a38c1fb60b18a80de/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride16 to build/libretinanet/_tmp/retinanet/14a062bf9f488e2a38c1fb60b18a80de/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_cls_prob_reshape_stride8 to build/libretinanet/_tmp/retinanet/14a062bf9f488e2a38c1fb60b18a80de/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_bbox_pred_stride8 to build/libretinanet/_tmp/retinanet/14a062bf9f488e2a38c1fb60b18a80de/MI9_msmnile/arm64-v8a
Pull /data/local/tmp/mace_run/model_out_face_rpn_landmark_pred_stride8 to build/libretinanet/_tmp/retinanet/14a062bf9f488e2a38c1fb60b18a80de/MI9_msmnile/arm64-v8a
Traceback (most recent call last):
  File "/mace/validate.py", line 459, in <module>
face_rpn_cls_prob_reshape_stride32 MACE VS CAFFE similarity: 0.7051022200187764 , sqnr: 1.988659806883121 , pixel_accuracy: 0.4
    FLAGS.log_file)
  File "/mace/validate.py", line 371, in validate
    validation_threshold, log_file)
  File "/mace/validate.py", line 262, in validate_caffe_model
    value, validation_threshold, log_file)
  File "/mace/validate.py", line 113, in compare_output
    "", common.StringFormatter.block("Similarity Test Failed"))
TypeError: summary() takes exactly 1 argument (2 given)
Traceback (most recent call last):
  File "tools/converter.py", line 1151, in <module>
    flags.func(flags)
  File "tools/converter.py", line 938, in run_mace
    device.run_specify_abi(flags, configs, target_abi)
  File "/mace/tools/device.py", line 782, in run_specify_abi
    log_file=log_file,
  File "/mace/tools/sh_commands.py", line 756, in validate_model
    _fg=True)
  File "/root/.pyenv/versions/3.6.3/lib/python3.6/site-packages/sh.py", line 1413, in __call__
    raise exc
sh.ErrorReturnCode_1: 

  RAN: /usr/bin/docker exec mace_caffe_lastest_validator python -u /mace/validate.py --platform=caffe --model_file=/mace/retinanet3.prototxt --weight_file=/mace/retinanet3.caffemodel --input_file=/mace/model_input --mace_out_file=/mace/model_out --device_type=GPU --input_node=data --output_node=face_rpn_cls_prob_reshape_stride32,face_rpn_bbox_pred_stride32,face_rpn_landmark_pred_stride32,face_rpn_cls_prob_reshape_stride16,face_rpn_bbox_pred_stride16,face_rpn_landmark_pred_stride16,face_rpn_cls_prob_reshape_stride8,face_rpn_bbox_pred_stride8,face_rpn_landmark_pred_stride8 --input_shape=1,3,320,320 --output_shape=1,4,10,10:1,8,10,10:1,20,10,10:1,4,20,20:1,8,20,20:1,20,20,20:1,4,40,40:1,8,40,40:1,20,40,40 --input_data_format=NCHW --output_data_format=NCHW,NCHW,NCHW,NCHW,NCHW,NCHW,NCHW,NCHW,NCHW --validation_threshold=0.995000 --input_data_type=float32 --backend=tensorflow --validation_outputs_data= --log_file=

  STDOUT:


  STDERR:

To Reproduce

Steps to reproduce the problem:

1. cd /path/to/mace
2. python tools/converter.py convert --config_file=/models/retinanet/retinanet3.yml
2. python tools/converter.py run --validate --config_file=/models/retinanet/retinanet3.yml

Error information / logs

Please refer to this gist link for full conversion and validation log: MACE v0.12.0 Error log - validation failed · GitHub

Additional context

For MACE v0.12.0, I followed a workaround from the last answer of this issue https://github.com/XiaoMi/mace/issues/560

diff --git a/tools/python/transform/transformer.py b/tools/python/transform/transformer.py
index bb9154f..bbf14b4 100644
--- a/tools/python/transform/transformer.py
+++ b/tools/python/transform/transformer.py
@@ -1353,7 +1353,7 @@ class Transformer(base_converter.ConverterInterface):
         visited = set()
         sorted_nodes = []
 
-        output_nodes = self._option.check_nodes.keys()
+        output_nodes = list(self._option.check_nodes.keys())
         if not self._quantize_activation_info:
             output_nodes.extend(self._option.output_nodes)
         for output_node in output_nodes:

Before you open an issue, please make sure you have tried the following steps:

1. Make sure your environment is the same with (https://mace.readthedocs.io/en/latest/installation/env_requirement.html).
2. Have you ever read the document for your usage?
3. Check if your issue appears in HOW-TO-DEBUG or FAQ.
4. The form below must be filled.

System information

• **OS Platform and Distribution (e.g., Linux Ubuntu 16.04)：Centos7
• NDK version(e.g., 15c):17b
• GCC version(if compiling for host, e.g., 5.4.0):
• **MACE version (Use the command: git describe --long --tags):v0.11.0-rc0-0-g2d650b6
• **Python version(2.7):2.7
• **Bazel version (e.g., 0.13.0):0.13.0

Model deploy file (*.yml)

library_name: yolo-v3 target_abis: [armeabi-v7a, arm64-v8a] model_graph_format: code model_data_format: code models: yolo_v3: platform: tensorflow model_file_path: /MACE/mace-models/yolo-v3/frozen_darknet_yolov3_model.pb model_sha256_checksum: 90d96d1e07340bce8e250dd66bbcb05e2965bad7e22d0f875aa65d97e11113f1 subgraphs: - input_tensors: - inputs:0 input_shapes: - 1,416,416,3 output_tensors: - detector/yolo-v3/Conv_6/BiasAdd:0 - detector/yolo-v3/Conv_14/BiasAdd:0 - detector/yolo-v3/Conv_22/BiasAdd:0 output_shapes: - 1,13,13,42 - 1,26,26,42 - 1,52,52,42 runtime: cpu+gpu limit_opencl_kernel_time: 0 nnlib_graph_mode: 0 obfuscate: 0 winograd: 0

Describe the problem

问题1：通过GPU运行的，CPU总是崩溃 问题2：有没有解析yolo3输出结果的例子呢？ 问题3：GPU运行模型后，输出的数据都是类似下方的样子， NaN NaN 0.0 0.0 -4.25229E-39 1.8E-44 -1.4E-45 0.0 0.0 -1.4E-45 0.0 0.0 -1.4E-45 0.0 0.0 -1.4E-45 0.0

To Reproduce

Steps to reproduce the problem:

1. cd /path/to/mace
2. python tools/converter.py convert --config_file=/path/to/your/model_deployment_file

Error information / logs

日志信息： 06-21 15:21:21.144 29261-29261/? I/art: Late-enabling -Xcheck:jni 06-21 15:21:21.174 29261-29267/? I/art: Debugger is no longer active 06-21 15:21:21.204 29261-29261/? W/ActivityThread: Application com.xiaomi.mace.demo is waiting for the debugger on port 8100... 06-21 15:21:21.204 29261-29261/? I/System.out: Sending WAIT chunk 06-21 15:21:25.494 29261-29267/com.xiaomi.mace.demo I/art: Debugger is active 06-21 15:21:25.684 29261-29261/com.xiaomi.mace.demo I/System.out: Debugger has connected 06-21 15:21:25.684 29261-29261/com.xiaomi.mace.demo I/System.out: waiting for debugger to settle... 06-21 15:21:25.884 29261-29261/com.xiaomi.mace.demo I/System.out: waiting for debugger to settle... 06-21 15:21:26.084 29261-29261/com.xiaomi.mace.demo I/System.out: waiting for debugger to settle... 06-21 15:21:26.284 29261-29261/com.xiaomi.mace.demo I/System.out: waiting for debugger to settle... 06-21 15:21:26.494 29261-29261/com.xiaomi.mace.demo I/System.out: waiting for debugger to settle... 06-21 15:21:26.694 29261-29261/com.xiaomi.mace.demo I/System.out: waiting for debugger to settle... 06-21 15:21:26.894 29261-29261/com.xiaomi.mace.demo I/System.out: waiting for debugger to settle... 06-21 15:21:27.094 29261-29261/com.xiaomi.mace.demo I/System.out: waiting for debugger to settle... 06-21 15:21:27.294 29261-29261/com.xiaomi.mace.demo I/System.out: debugger has settled (1451) 06-21 15:21:27.904 29261-29261/com.xiaomi.mace.demo I/InstantRun: starting instant run server: is main process 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = person 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = bicycle 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = car 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = motorbike 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = aeroplane 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = bus 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = train 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = truck 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = boat 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = traffic light 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = fire hydrant 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = stop sign 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = parking meter 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = bench 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = bird 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = cat 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = dog 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = horse 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = sheep 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = cow 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = elephant 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = bear 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = zebra 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = giraffe 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = backpack 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = umbrella 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = handbag 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = tie 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = suitcase 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = frisbee 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = skis 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = snowboard 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = sports ball 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = kite 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = baseball bat 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = baseball glove 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = skateboard 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = surfboard 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = tennis racket 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = bottle 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = wine glass 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = cup 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = fork 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = knife 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = spoon 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = bowl 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = banana 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = apple 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = sandwich 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = orange 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = broccoli 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = carrot 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = hot dog 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = pizza 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = donut 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = cake 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = chair 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = sofa 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = pottedplant 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = bed 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = diningtable 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = toilet 06-21 15:21:27.964 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = tvmonitor 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = laptop 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = mouse 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = remote 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = keyboard 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = cell phone 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = microwave 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = oven 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = toaster 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = sink 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = refrigerator 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = book 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = clock 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = vase 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = scissors 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = teddy bear 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = hair drier 06-21 15:21:27.974 29261-29313/com.xiaomi.mace.demo D/labelCache: readLine = toothbrush 06-21 15:21:27.994 29261-29261/com.xiaomi.mace.demo D/PhoneWindow: DEBUG_SYSTEMUI:origin statusbar style 06-21 15:21:27.994 29261-29261/com.xiaomi.mace.demo D/PhoneWindow: DEBUG_SYSTEMUI:windowDrawsFlag set 06-21 15:21:27.994 29261-29261/com.xiaomi.mace.demo D/PhoneWindow: DEBUG_SYSTEMUI:IconColor=1 06-21 15:21:27.994 29261-29261/com.xiaomi.mace.demo D/PhoneWindow: DEBUG_SYSTEMUI:StatusBarColor final set ff303f9f 06-21 15:21:28.064 29261-29314/com.xiaomi.mace.demo W/linker: /data/app/com.xiaomi.mace.demo-1/lib/arm/libmace_mobile_jni.so: unused DT entry: type 0x1d arg 0x1e0aa 06-21 15:21:28.474 29261-29314/com.xiaomi.mace.demo I/APPModel: maceMobilenetCreateGPUContext result = 0 06-21 15:21:28.474 29261-29314/com.xiaomi.mace.demo I/image_classify attrs: gpu perf: 3, priority: 3 06-21 15:21:28.474 29261-29314/com.xiaomi.mace.demo I/image_classify attrs: device: 2 06-21 15:21:28.494 29261-29314/com.xiaomi.mace.demo E/MACE: env.cc:86 failed to open /sys/devices/system/cpu/cpu0/cpufreq/cpuinfo_max_freq 06-21 15:21:28.494 29261-29314/com.xiaomi.mace.demo I/MACE: env.cc:97 LinuxBaseEnv::GetCPUMaxFreq(max_freqs) failed with error: Runtime error 06-21 15:21:28.494 29261-29314/com.xiaomi.mace.demo E/MACE: thread_pool.cc:140 Fail to get cpu max frequencies 06-21 15:21:28.494 29261-29314/com.xiaomi.mace.demo E/MACE: thread_pool.cc:79 CPU core is empty 06-21 15:21:28.494 29261-29314/com.xiaomi.mace.demo I/MACE: mace.cc:431 Creating MaceEngine, MACE version: v0.11.0-rc1-0-gd9406dd 06-21 15:21:28.494 29261-29314/com.xiaomi.mace.demo E/MACE: env.cc:86 failed to open /sys/devices/system/cpu/cpu0/cpufreq/cpuinfo_max_freq 06-21 15:21:28.494 29261-29314/com.xiaomi.mace.demo I/MACE: env.cc:97 LinuxBaseEnv::GetCPUMaxFreq(max_freqs) failed with error: Runtime error 06-21 15:21:28.494 29261-29314/com.xiaomi.mace.demo I/MACE: cpu_runtime.cc:99 GetCPUMaxFreq(&cpu_max_freqs) failed with error: Runtime error 06-21 15:21:28.504 29261-29315/com.xiaomi.mace.demo D/OpenGLRenderer: Use EGL_SWAP_BEHAVIOR_PRESERVED: true 06-21 15:21:29.714 29261-29315/com.xiaomi.mace.demo I/Adreno: QUALCOMM build : 31f65f7, Ia3ef73d9d4 Build Date : 12/16/16 OpenGL ES Shader Compiler Version: XE031.08.00.00 Local Branch : Remote Branch : Remote Branch : Reconstruct Branch : 06-21 15:21:30.014 29261-29315/com.xiaomi.mace.demo I/OpenGLRenderer: Initialized EGL, version 1.4 06-21 15:21:30.304 29261-29261/com.xiaomi.mace.demo I/Choreographer: Skipped 68 frames! The application may be doing too much work on its main thread. 06-21 15:21:30.664 29261-29314/com.xiaomi.mace.demo I/MACE: mace.cc:470 Initializing MaceEngine 06-21 15:21:31.064 29261-29314/com.xiaomi.mace.demo E/MACE: env.cc:86 failed to open /sys/devices/system/cpu/cpu0/cpufreq/cpuinfo_max_freq 06-21 15:21:31.064 29261-29314/com.xiaomi.mace.demo I/MACE: env.cc:97 LinuxBaseEnv::GetCPUMaxFreq(max_freqs) failed with error: Runtime error 06-21 15:21:31.064 29261-29314/com.xiaomi.mace.demo I/MACE: cpu_runtime.cc:99 GetCPUMaxFreq(&cpu_max_freqs) failed with error: Runtime error 06-21 15:21:31.064 29261-29314/com.xiaomi.mace.demo I/MACE: net_def_adapter.cc:348 Op detector/transpose fall back to CPU 06-21 15:21:31.064 29261-29314/com.xiaomi.mace.demo I/MACE: net_def_adapter.cc:348 Op detector/truediv fall back to CPU 06-21 15:21:31.094 29261-29314/com.xiaomi.mace.demo I/MACE: net_def_adapter.cc:348 Op detector/yolo-v3/transpose_1 fall back to CPU 06-21 15:21:31.094 29261-29314/com.xiaomi.mace.demo I/MACE: net_def_adapter.cc:348 Op detector/yolo-v3/ResizeNearestNeighbor fall back to CPU 06-21 15:21:31.094 29261-29314/com.xiaomi.mace.demo I/MACE: net_def_adapter.cc:348 Op detector/yolo-v3/transpose_2 fall back to CPU 06-21 15:21:31.094 29261-29314/com.xiaomi.mace.demo I/MACE: net_def_adapter.cc:348 Op detector/yolo-v3/concat_3 fall back to CPU 06-21 15:21:31.094 29261-29314/com.xiaomi.mace.demo I/MACE: net_def_adapter.cc:348 Op detector/yolo-v3/transpose_4 fall back to CPU 06-21 15:21:31.094 29261-29314/com.xiaomi.mace.demo I/MACE: net_def_adapter.cc:348 Op detector/yolo-v3/ResizeNearestNeighbor_1 fall back to CPU 06-21 15:21:31.094 29261-29314/com.xiaomi.mace.demo I/MACE: net_def_adapter.cc:348 Op detector/yolo-v3/transpose_5 fall back to CPU 06-21 15:21:31.094 29261-29314/com.xiaomi.mace.demo I/MACE: net_def_adapter.cc:348 Op detector/yolo-v3/concat_7 fall back to CPU 06-21 15:21:31.104 29261-29314/com.xiaomi.mace.demo E/MACE: env.cc:86 failed to open /sys/devices/system/cpu/cpu0/cpufreq/cpuinfo_max_freq 06-21 15:21:31.104 29261-29314/com.xiaomi.mace.demo I/MACE: env.cc:97 LinuxBaseEnv::GetCPUMaxFreq(max_freqs) failed with error: Runtime error 06-21 15:21:31.104 29261-29314/com.xiaomi.mace.demo I/MACE: cpu_runtime.cc:99 GetCPUMaxFreq(&cpu_max_freqs) failed with error: Runtime error 06-21 15:21:31.534 29261-29314/com.xiaomi.mace.demo I/image_classify attrs: create result: Success: Success: Success,input:1,output:3 06-21 15:21:31.534 29261-29314/com.xiaomi.mace.demo I/APPModel: maceMobilenetCreateEngine result = 0 06-21 15:21:34.584 29261-29261/com.xiaomi.mace.demo D/PhoneWindow: DEBUG_SYSTEMUI:origin statusbar style 06-21 15:21:34.584 29261-29261/com.xiaomi.mace.demo D/PhoneWindow: DEBUG_SYSTEMUI:IconColor=1 06-21 15:21:34.584 29261-29261/com.xiaomi.mace.demo D/PhoneWindow: DEBUG_SYSTEMUI:StatusBarColor final set ff303f9f 06-21 15:21:34.594 29261-29261/com.xiaomi.mace.demo D/yuan: onVisibilityChanged----android.widget.ListView{ede1ff3 VFED.VC.. ......I. 0,0-0,0 #7f070047 app:id/list_menu} 06-21 15:21:35.624 29261-29314/com.xiaomi.mace.demo I/image_classify attrs: device: 0 06-21 15:21:35.634 29261-29314/com.xiaomi.mace.demo E/MACE: env.cc:86 failed to open /sys/devices/system/cpu/cpu0/cpufreq/cpuinfo_max_freq 06-21 15:21:35.634 29261-29314/com.xiaomi.mace.demo I/MACE: env.cc:97 LinuxBaseEnv::GetCPUMaxFreq(max_freqs) failed with error: Runtime error 06-21 15:21:35.634 29261-29314/com.xiaomi.mace.demo E/MACE: thread_pool.cc:140 Fail to get cpu max frequencies 06-21 15:21:35.634 29261-29314/com.xiaomi.mace.demo E/MACE: thread_pool.cc:79 CPU core is empty 06-21 15:21:35.634 29261-29314/com.xiaomi.mace.demo I/MACE: mace.cc:431 Creating MaceEngine, MACE version: v0.11.0-rc1-0-gd9406dd 06-21 15:21:35.634 29261-29314/com.xiaomi.mace.demo E/MACE: env.cc:86 failed to open /sys/devices/system/cpu/cpu0/cpufreq/cpuinfo_max_freq 06-21 15:21:35.634 29261-29314/com.xiaomi.mace.demo I/MACE: env.cc:97 LinuxBaseEnv::GetCPUMaxFreq(max_freqs) failed with error: Runtime error 06-21 15:21:35.634 29261-29314/com.xiaomi.mace.demo I/MACE: cpu_runtime.cc:99 GetCPUMaxFreq(&cpu_max_freqs) failed with error: Runtime error 06-21 15:21:35.634 29261-29314/com.xiaomi.mace.demo I/MACE: mace.cc:603 Destroying MaceEngine 06-21 15:21:35.764 29261-29314/com.xiaomi.mace.demo I/MACE: mace.cc:470 Initializing MaceEngine 06-21 15:21:36.834 29261-29315/com.xiaomi.mace.demo D/OpenGLRenderer: endAllStagingAnimators on 0x80018598 (RippleDrawable) with handle 0x800fbc68 06-21 15:21:36.964 29261-29314/com.xiaomi.mace.demo E/MACE: env.cc:86 failed to open /sys/devices/system/cpu/cpu0/cpufreq/cpuinfo_max_freq 06-21 15:21:36.964 29261-29314/com.xiaomi.mace.demo I/MACE: env.cc:97 LinuxBaseEnv::GetCPUMaxFreq(max_freqs) failed with error: Runtime error 06-21 15:21:36.964 29261-29314/com.xiaomi.mace.demo I/MACE: cpu_runtime.cc:99 GetCPUMaxFreq(&cpu_max_freqs) failed with error: Runtime error 06-21 15:21:37.004 29261-29314/com.xiaomi.mace.demo E/MACE: env.cc:86 failed to open /sys/devices/system/cpu/cpu0/cpufreq/cpuinfo_max_freq 06-21 15:21:37.004 29261-29314/com.xiaomi.mace.demo I/MACE: env.cc:97 LinuxBaseEnv::GetCPUMaxFreq(max_freqs) failed with error: Runtime error 06-21 15:21:37.004 29261-29314/com.xiaomi.mace.demo I/MACE: cpu_runtime.cc:99 GetCPUMaxFreq(&cpu_max_freqs) failed with error: Runtime error 06-21 15:21:37.664 29261-29314/com.xiaomi.mace.demo I/image_classify attrs: create result: Success: Success: Success,input:1,output:3 06-21 15:21:37.664 29261-29314/com.xiaomi.mace.demo I/APPModel: maceMobilenetCreateEngine result = 0 06-21 15:21:41.474 29261-29261/com.xiaomi.mace.demo I/Choreographer: Skipped 104 frames! The application may be doing too much work on its main thread. 06-21 15:21:41.474 29261-29314/com.xiaomi.mace.demo I/image_classify: output:detector/yolo-v3/Conv_6/BiasAdd:0,size:1 06-21 15:21:41.474 29261-29314/com.xiaomi.mace.demo I/image_classify: output:detector/yolo-v3/Conv_14/BiasAdd:0,size:2 06-21 15:21:41.474 29261-29314/com.xiaomi.mace.demo I/image_classify: output:detector/yolo-v3/Conv_22/BiasAdd:0,size:3 06-21 15:21:41.484 29261-29315/com.xiaomi.mace.demo I/Adreno: QUALCOMM build : 31f65f7, Ia3ef73d9d4 Build Date : 12/16/16 OpenGL ES Shader Compiler Version: XE031.08.00.00 Local Branch : Remote Branch : Remote Branch : Reconstruct Branch : 06-21 15:21:41.794 29261-29315/com.xiaomi.mace.demo I/OpenGLRenderer: Initialized EGL, version 1.4 bt

CPU崩溃信息 A/libc: Fatal signal 11 (SIGSEGV), code 2 (SEGV_ACCERR), fault addr 0xc8300000 in tid 20169 (jniThread), pid 20098 (iaomi.mace.demo) std::__ndk1::__function::__func<mace::ops::arm::fp32::Conv2dGeneral::Compute(mace::OpContext const*, mace::Tensor const*, mace::Tensor const*, mace::Tensor*)::$_0, std::__ndk1::allocator<mace::ops::arm::fp32::Conv2dGeneral::Compute(mace::OpContext const*, mace::Tensor const*, mace::Tensor const*, mace::Tensor*)::$_0>, void (long long, long long, long long, long long, long long, long long)>::operator()(long long&&, long long&&, long long&&, long long&&, long long&&, long long&&) 0x000000009aa0df22 mace::utils::ThreadPool::Compute2D(std::__ndk1::function<void (long long, long long, long long, long long, long long, long long)> const&, long long, long long, long long, long long, long long, long long, long long, long long, int) 0x000000009aa57ae8 mace::ops::arm::fp32::Conv2dGeneral::Compute(mace::OpContext const*, mace::Tensor const*, mace::Tensor const*, mace::Tensor*) 0x000000009aa0d890 mace::ops::Conv2dOp<(mace::DeviceType)0, float>::Run(mace::OpContext*) 0x000000009a9ba16a mace::SerialNet::Run(mace::RunMetadata*) 0x000000009aa42642 mace::MaceEngine::Impl::Run(std::__ndk1::map<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator >, mace::MaceTensor, std::__ndk1::less<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator > >, std::__ndk1::allocator<std::__ndk1::pair<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator > const, mace::MaceTensor> > > const&, std::__ndk1::map<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator >, mace::MaceTensor, std::__ndk1::less<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator > >, std::__ndk1::allocator<std::__ndk1::pair<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator > const, mace::MaceTensor> > >, mace::RunMetadata) 0x000000009a8febd4 mace::MaceEngine::Run(std::__ndk1::map<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator >, mace::MaceTensor, std::__ndk1::less<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator > >, std::__ndk1::allocator<std::__ndk1::pair<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator > const, mace::MaceTensor> > > const&, std::__ndk1::map<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator >, mace::MaceTensor, std::__ndk1::less<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator > >, std::__ndk1::allocator<std::__ndk1::pair<std::__ndk1::basic_string<char, std::__ndk1::char_traits, std::__ndk1::allocator > const, mace::MaceTensor> > >*) 0x000000009a8ff16c ::Java_com_xiaomi_mace_JniMaceUtils_maceMobilenetClassify(JNIEnv *, jclass, jfloatArray) image_classify.cc:345 art_quick_generic_jni_trampoline 0x00000000b3d67d1a art_quick_invoke_stub_internal 0x00000000b3d63622 art_quick_invoke_static_stub 0x00000000b406a628

求问，给安卓系统用，不算神经网络本身，就是mace的基础框架库多大呢？

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
• NDK version(e.g., 15c):
• GCC version(if compiling for host, e.g., 5.4.0):
• MACE version (Use the command: git describe --long --tags):
• Python version(2.7):
• Bazel version (e.g., 0.13.0):

Model deploy file (*.yml)

......

Describe the problem

A clear and concise description of what the bug is.

To Reproduce

Steps to reproduce the problem:

1. cd /path/to/mace
2. python tools/converter.py convert --config_file=/path/to/your/model_deployment_file

Error information / logs

Please include the full log and/or traceback here.

LOGs

Additional context

Add any other context about the problem here, e.g., what you have modified about the code.

将onnx模型转mace models时，一个conv op转换失败，报错如下: Traceback (most recent call last): File "tools/converter.py", line 1334, in flags.func(flags) File "tools/converter.py", line 926, in convert_func convert.convert(configs, MODEL_CODEGEN_DIR, flags.enable_micro) File "tools/python/convert.py", line 89, in convert net_def_with_Data = convert_net(net_name, net_conf, enable_micro) File "tools/python/convert.py", line 235, in convert_net output_graph_def, converter_info = converter.run() File "tools/python/transform/onnx_converter.py", line 565, in run self.convert_ops(graph_def) File "tools/python/transform/onnx_converter.py", line 649, in convert_ops self._op_convertersnode.op_type File "tools/python/transform/onnx_converter.py", line 937, in convert_conv2d filter_shape = self._graph_shapes_dict[node.inputs[1]] KeyError: '819' 而其中，这个op打印如下： { input: "540" input: "819" input: "820" output: "818" name: "Conv_12" op_type: "Conv" attribute { name: "dilations" ints: 1 ints: 1 type: INTS } attribute { name: "group" i: 32 type: INT } attribute { name: "kernel_shape" ints: 3 ints: 3 type: INTS } attribute { name: "pads" ints: 1 ints: 1 ints: 1 ints: 1 type: INTS } attribute { name: "strides" ints: 2 ints: 2 type: INTS } } 顺着代码看了下，报错那行代码中试图从self._graph_shapes_dict中读取shape，这个self._graph_shapes_dict是通过读取图中tensor得到的，可819号其实是参数W，所以没有出现在self._graph_shapes_dict中，导致报错。请问这个符合预期吗？