@@ -209,10 +209,10 @@ class ConcatComputeImage : public KernelLite<TARGET(kOpenCL),
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int arg_cnt = 0 ;
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for (auto & input : inputs) {
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auto * input_image_p = GET_DATA_GPU (input);
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- kernel.setArg (arg_cnt++, *input_image_p);
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+ status = kernel.setArg (arg_cnt++, *input_image_p);
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CL_CHECK_FATAL (status);
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}
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- kernel.setArg (arg_cnt++, *output_image_p);
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+ status = kernel.setArg (arg_cnt++, *output_image_p);
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CL_CHECK_FATAL (status);
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for (auto & input : inputs) {
@@ -221,15 +221,15 @@ class ConcatComputeImage : public KernelLite<TARGET(kOpenCL),
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in_shape.s [4 - input->dims ().size () + j] = input->dims ()[j];
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}
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in_shape.s [1 ] = UP_DIV (in_shape.s [1 ], 4 );
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- kernel.setArg (arg_cnt++, in_shape);
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+ status = kernel.setArg (arg_cnt++, in_shape);
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CL_CHECK_FATAL (status);
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}
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cl_int4 out_shape = {1 , 1 , 1 , 1 };
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for (auto j = 0 ; j < output_tensor_dims.size (); ++j) {
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out_shape.s [4 - output_tensor_dims.size () + j] = output_tensor_dims[j];
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}
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out_shape.s [1 ] = UP_DIV (out_shape.s [1 ], 4 );
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- kernel.setArg (arg_cnt++, out_shape);
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+ status = kernel.setArg (arg_cnt++, out_shape);
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CL_CHECK_FATAL (status);
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status = EnqueueNDRangeKernel (context,
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