mace: CL_INVALID_KERNEL_ARGS

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.

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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: test
target_abis: [arm64-v8a]
model_graph_format: code
model_data_format: code
models:
  FE: # 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/FE.prototxt
    weight_file_path: /models/FE.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
    limit_opencl_kernel_time: 1
    runtime: cpu+gpu
    winograd: 4

  FD:
    platform: caffe
    model_file_path: /models/FD.prototxt
    weight_file_path: /models/FD.caffemodel
    model_sha256_checksum: 213d764bd605d02b1630740969ab7110a2ee0111e3f8200ce02304cf72fbd42a
    weight_sha256_checksum: c83d575645daf8541867a63197de6bfd44a7fb3bf9bf4c876cde8165c23fac0c
    subgraphs:
      - input_tensors:
          - data
        input_shapes:
          - 1,3,160,160
        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:
          - 1,4,5,5
          - 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
        output_data_formats:
          - NCHW
          - NCHW
          - NCHW
          - NCHW
          - NCHW
          - NCHW
          - NCHW
          - NCHW
          - NCHW
    obfuscate: 0
    runtime: cpu+gpu
    winograd: 0

Describe the problem

• When integrating compiled mace library and model into and android app, I get CL_INVALID_KERNEL_ARGS error at runtime, followed by some Out of resources errors.

Any clue about what can cause this kind of error?

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
3. run android app

Error information / logs

Please include the full log and/or traceback here.

E/MACE: helper.cc:201 error: CL_INVALID_KERNEL_ARGS
E/MACE: helper.cc:246 error: CL_INVALID_KERNEL_ARGS
I/MACE: activation.cc:113 TuningOrRun3DKernel(runtime, kernel_, tuning_key, gws, lws, context->future()) failed with error: Out of resources
I/MACE: net.cc:152 op->Run(&context) failed with error: Out of resources
I/MACE: mace.cc:890 net_->Run(run_metadata) failed with error: Out of resources

Additional context

Model to reproduce the issue can be found here