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authorMichalis Spyrou <michalis.spyrou@arm.com>2018-11-21 15:44:55 +0000
committerMichalis Spyrou <michalis.spyrou@arm.com>2018-11-21 17:32:46 +0000
commit3112e33d8d0b987e85107390a0350bd5988f5f01 (patch)
tree050c8400608caaa216305611ca2de1d8163e462b /src/core/CL
parentedf26ea4921fd0c162abb962fc4863846e73f53f (diff)
downloadComputeLibrary-3112e33d8d0b987e85107390a0350bd5988f5f01.tar.gz
COMPMID-1451 Change PriorBox output to NCHw
Output of Priorbox should be independent of the input data layout and should always be in NCHW format Change-Id: Ie80cd4e51c78945b158c0db1af1923bdf8d7ea7b
Diffstat (limited to 'src/core/CL')
-rw-r--r--src/core/CL/CLKernelLibrary.cpp1
-rw-r--r--src/core/CL/cl_kernels/prior_box_layer.cl117
-rw-r--r--src/core/CL/kernels/CLPriorBoxLayerKernel.cpp82
3 files changed, 13 insertions, 187 deletions
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index ff4803e79c..33e66705e3 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -355,7 +355,6 @@ const std::map<std::string, std::string> CLKernelLibrary::_kernel_program_map =
{ "pooling_layer_MxN_quantized_nhwc", "pooling_layer_quantized.cl" },
{ "pooling_layer_MxN_quantized_nchw", "pooling_layer_quantized.cl" },
{ "prior_box_layer_nchw", "prior_box_layer.cl" },
- { "prior_box_layer_nhwc", "prior_box_layer.cl" },
{ "quantization_layer", "quantization_layer.cl" },
{ "reduction_operation_x", "reduction_operation.cl" },
{ "reduction_operation_quantized_x", "reduction_operation.cl" },
diff --git a/src/core/CL/cl_kernels/prior_box_layer.cl b/src/core/CL/cl_kernels/prior_box_layer.cl
index be072ecb1d..046151bca4 100644
--- a/src/core/CL/cl_kernels/prior_box_layer.cl
+++ b/src/core/CL/cl_kernels/prior_box_layer.cl
@@ -104,88 +104,6 @@ inline int calculate_min_nchw(Image *out, __global float *max, __global float *a
return idx;
}
-
-/** Compute prior boxes and clip (NHWC)
- *
- * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F32
- * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
- * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
- * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor
- * @param[in] idx Index to write to
- * @param[in] center_x Center value of the x axis
- * @param[in] center_y Center value of the y axis
- * @param[in] box_width Prior box width
- * @param[in] box_height Prior box height
- *
- */
-inline void calculate_xy_min_max_nhwc(Tensor3D *out, int idx, float center_x, float center_y, float box_width, float box_height)
-{
- float xmin = (center_x - box_width / 2.f) / WIDTH;
- float ymin = (center_y - box_height / 2.f) / HEIGHT;
- float xmax = (center_x + box_width / 2.f) / WIDTH;
- float ymax = (center_y + box_height / 2.f) / HEIGHT;
-
-#if defined(CLIP)
- xmin = clamp(xmin, 0.f, 1.f);
- ymin = clamp(ymin, 0.f, 1.f);
- xmax = clamp(xmax, 0.f, 1.f);
- ymax = clamp(ymax, 0.f, 1.f);
-#endif // defined(CLIP)
-
- *((__global DATA_TYPE *)tensor3D_offset(out, 0, idx + 0, 0)) = xmin;
- *((__global DATA_TYPE *)tensor3D_offset(out, 0, idx + 1, 0)) = ymin;
- *((__global DATA_TYPE *)tensor3D_offset(out, 0, idx + 2, 0)) = xmax;
- *((__global DATA_TYPE *)tensor3D_offset(out, 0, idx + 3, 0)) = ymax;
-}
-
-/** Compute prior boxes (NHWC)
- *
- * @param[in,out] out Tensor output
- * @param[in] max The maximum values
- * @param[in] aspect_ratios The aspect ratio values
- * @param[in] max_size The maximum values values size
- * @param[in] aspect_ratios_size The aspect ratio values size
- * @param[in] min_size The minimum values size
- * @param[in] min_idx Index of the min vector
- * @param[in] idx Index to write to
- *
- * @return The updated index
- */
-inline int calculate_min_nhwc(Tensor3D *out, __global float *max, __global float *aspect_ratios, int max_size, int aspect_ratios_size, float min_size, int min_idx, int idx)
-{
- const float center_x = ((float)(get_global_id(1) % LAYER_WIDTH) + OFFSET) * STEP_X;
- const float center_y = ((float)(get_global_id(1) / LAYER_WIDTH) + OFFSET) * STEP_Y;
-
- float box_width = min_size;
- float box_height = min_size;
-
- calculate_xy_min_max_nhwc(out, idx, center_x, center_y, box_width, box_height);
- idx += 4;
- if(max_size > 0)
- {
- box_width = sqrt(min_size * max[min_idx]);
- box_height = box_width;
- calculate_xy_min_max_nhwc(out, idx, center_x, center_y, box_width, box_height);
- idx += 4;
- }
- for(unsigned int i = 0; i < aspect_ratios_size; ++i)
- {
- if(fabs(aspect_ratios[i] - 1.f) < 1e-6f)
- {
- continue;
- }
- box_width = min_size * sqrt(aspect_ratios[i]);
- box_height = min_size * rsqrt(aspect_ratios[i]);
-
- calculate_xy_min_max_nhwc(out, idx, center_x, center_y, box_width, box_height);
- idx += 4;
- }
-
- return idx;
-}
-
/** Calculate prior boxes with NCHW format.
*
* @param[out] output_ptr Pointer to the destination tensor. Supported data types: F32
@@ -218,39 +136,4 @@ __kernel void prior_box_layer_nchw(IMAGE_DECLARATION(output), __global float *mi
vstore4((VEC_DATA_TYPE(DATA_TYPE, 4))(VARIANCE_0, VARIANCE_1, VARIANCE_2, VARIANCE_3), 0, ((__global DATA_TYPE *)offset(&out, i, 1)));
}
}
-
-/** Calculate prior boxes with NHWC format.
- *
- * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F32
- * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
- * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
- * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor
- * @param[in] min The minimum values
- * @param[in] max The maximum_values
- * @param[in] aspect_ratios The aspect ratio values
- * @param[in] min_size The minimum values size
- * @param[in] max_size The maximum_values values size
- * @param[in] aspect_ratios_size The aspect ratio values size
- */
-__kernel void prior_box_layer_nhwc(TENSOR3D_DECLARATION(output), __global float *min, __global float *max, __global float *aspect_ratios, unsigned int min_size, unsigned int max_size,
- unsigned int aspect_ratios_size)
-{
- Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
-
- int idx = 0;
- for(unsigned int i = 0; i < min_size; ++i)
- {
- idx = calculate_min_nhwc(&out, max, aspect_ratios, max_size, aspect_ratios_size, min[i], i, idx);
- }
-
- for(int i = 0; i < (NUM_PRIORS * 4); i += 4)
- {
- *((__global DATA_TYPE *)tensor3D_offset(&out, 0, i + 0, 1)) = VARIANCE_0;
- *((__global DATA_TYPE *)tensor3D_offset(&out, 0, i + 1, 1)) = VARIANCE_1;
- *((__global DATA_TYPE *)tensor3D_offset(&out, 0, i + 2, 1)) = VARIANCE_2;
- *((__global DATA_TYPE *)tensor3D_offset(&out, 0, i + 3, 1)) = VARIANCE_3;
- }
-}
#endif /* defined(DATA_TYPE) && defined(WIDTH) && defined(HEIGHT) && defined(LAYER_WIDTH) && defined(LAYER_HEIGHT) && defined(OFFSET) && defined(STEP_X) && defined(STEP_Y) && defined(NUM_PRIORS) && defined(VARIANCE_0) && defined(VARIANCE_1) && defined(VARIANCE_2) && defined(VARIANCE_3) */
diff --git a/src/core/CL/kernels/CLPriorBoxLayerKernel.cpp b/src/core/CL/kernels/CLPriorBoxLayerKernel.cpp
index 63e745ed10..c76d839551 100644
--- a/src/core/CL/kernels/CLPriorBoxLayerKernel.cpp
+++ b/src/core/CL/kernels/CLPriorBoxLayerKernel.cpp
@@ -73,8 +73,7 @@ Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2,
if(output != nullptr && output->total_size() != 0)
{
- ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(get_data_layout_dimension_index(input1->data_layout(), DataLayoutDimension::HEIGHT)) != 2);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input1, output);
+ ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) != 2);
}
return Status{};
@@ -87,29 +86,11 @@ std::pair<Status, Window> validate_and_configure_window(const ITensorInfo *input
TensorShape output_shape = compute_prior_box_shape(*input1, info);
auto_init_if_empty(*output, output_shape, 1, input1->data_type());
- Window win{};
- bool window_changed = false;
-
- switch(input1->data_layout())
- {
- case DataLayout::NCHW:
- {
- const unsigned int num_elems_processed_per_iteration = 4 * num_priors;
-
- win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
- AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
- window_changed = update_window_and_padding(win, output_access);
- break;
- }
- case DataLayout::NHWC:
- {
- win = calculate_max_window(*output, Steps());
- break;
- }
- default:
- ARM_COMPUTE_ERROR("Not implemented");
- };
- Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ const unsigned int num_elems_processed_per_iteration = 4 * num_priors;
+ Window win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration));
+ AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration);
+ bool window_changed = update_window_and_padding(win, output_access);
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
return std::make_pair(err, win);
}
} // namespace
@@ -188,25 +169,8 @@ void CLPriorBoxLayerKernel::configure(const ICLTensor *input1, const ICLTensor *
}
}
- unsigned int idx = 0;
- // Create kernel
- switch(data_layout)
- {
- case DataLayout::NCHW:
- {
- idx = num_arguments_per_2D_tensor();
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("prior_box_layer_nchw", build_opts.options()));
- break;
- }
- case DataLayout::NHWC:
- {
- idx = num_arguments_per_3D_tensor();
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("prior_box_layer_nhwc", build_opts.options()));
- break;
- }
- default:
- ARM_COMPUTE_ERROR("Not implemented");
- }
+ unsigned int idx = num_arguments_per_2D_tensor();
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("prior_box_layer_nchw", build_opts.options()));
_kernel.setArg(idx++, *_min);
_kernel.setArg(idx++, *_max);
@@ -245,31 +209,11 @@ void CLPriorBoxLayerKernel::run(const Window &window, cl::CommandQueue &queue)
queue.enqueueWriteBuffer(*_max, CL_TRUE, 0, _info.max_sizes().size() * sizeof(float), _info.max_sizes().data());
}
- switch(_input1->info()->data_layout())
- {
- case DataLayout::NCHW:
- {
- Window slice = window.first_slice_window_2D();
- slice.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 2));
+ Window slice = window.first_slice_window_2D();
+ slice.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 2));
- unsigned int idx = 0;
- add_2D_tensor_argument(idx, _output, slice);
- enqueue(queue, *this, slice);
- break;
- }
- case DataLayout::NHWC:
- {
- Window slice = window.first_slice_window_3D();
- slice.set(Window::DimY, Window::Dimension(0, _output->info()->dimension(1), 4 * _num_priors));
- slice.set(Window::DimZ, Window::Dimension(0, _output->info()->dimension(2), 2));
-
- unsigned int idx = 0;
- add_3D_tensor_argument(idx, _output, slice);
- enqueue(queue, *this, slice);
- break;
- }
- default:
- ARM_COMPUTE_ERROR("Not implemented");
- }
+ unsigned int idx = 0;
+ add_2D_tensor_argument(idx, _output, slice);
+ enqueue(queue, *this, slice);
}
} // namespace arm_compute