[OpBugFix]support OpenCL fc shape size >2 and in_num_col_dims > 1 #8465
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Thanks for your contribution! |
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| } else { | ||
| output.y = 0.0f; |
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需要改为支持half的情况，output.y = (CL_DTYPE)0;
| output.z = input2.w; | ||
| } | ||
| } else { | ||
| output.z = 0.0f; |
| output.w = input3.w; | ||
| } | ||
| } else { | ||
| output.w = 0.0f; |
| output.w = input3.w; | ||
| } | ||
| } else { | ||
| output.w = 0.0f; |
| } | ||
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| } else { | ||
| output.y = 0.0f; |
| output.z = input2.w; | ||
| } | ||
| } else { | ||
| output.z = 0.0f; |
| @@ -53,6 +53,8 @@ class FcImageCompute : public KernelLite<TARGET(kOpenCL), | |||
| // convert weights from cpu to gpu | |||
| auto w_cpu_t = std::unique_ptr<Tensor>(new Tensor); | |||
| w_gpu_t_ = std::unique_ptr<Tensor>(new Tensor); | |||
| layout_input_image_ = std::unique_ptr<Tensor>(new Tensor); | |||
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将这两行代码放在后面的if判断中吧，当输入是2维数据时，不用执行。
| @@ -170,22 +173,113 @@ class FcImageCompute : public KernelLite<TARGET(kOpenCL), | |||
| kernel_key << kernel_func_name_ << build_options_ << time_stamp_; | |||
| kernel_ = context.cl_context()->GetKernel(kernel_key.str()); | |||
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| context.cl_context()->AddKernel( | |||
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建议这两个kernel编译也放在if判断中
| auto x_dims = param.input->dims(); | ||
| auto out_dims = param.output->dims(); | ||
| cl::Image2D* x_img_src = DATA_GPU(param.input); | ||
| cl::NDRange layout_gws; |
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layout_gws 变量放在 Line 200 if 判断内
| cl::NDRange layout_gws; | ||
| if (x_dims.size() > 2 && x_dims.size() <= 4) { | ||
| int in_num_col_dims = param.in_num_col_dims; | ||
| std::vector<size_t> new_dims = {1, 1, 1, 1}; |
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对原始维度扩展为4维，这个函数挺常用， 已经在 image_helfer.h 中定义了，可以直接调用auto new_dims = Broadcast2GpuShape(x_dims);
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支持fc中shape size > 2和in_num_col_dims > 1