COMPMID-1635: Optimize CLDeconvolutionLayer - Part III
Change-Id: Id2661e093a669ef3eaf2a5116cd278a80c1d5a89
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/935
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Comments-Addressed: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Isabella Gottardi <isabella.gottardi@arm.com>
Comments-Addressed: Isabella Gottardi <isabella.gottardi@arm.com>
Tested-by: Isabella Gottardi <isabella.gottardi@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/cl_kernels/deconvolution_layer.cl b/src/core/CL/cl_kernels/deconvolution_layer.cl
index e5169f9..ea2455c 100644
--- a/src/core/CL/cl_kernels/deconvolution_layer.cl
+++ b/src/core/CL/cl_kernels/deconvolution_layer.cl
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -52,3 +52,79 @@
// Store result
*((__global DATA_TYPE *)dst.ptr) = *((__global DATA_TYPE *)src.ptr);
}
+
+#if defined(FILTER_WIDTH) && defined(FILTER_HEIGHT) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DATA_TYPE)
+/** This kernel reshapes the deconvolution output tensor before returning the result of the Deconvolution. The decovnolution output tensor
+ * is the result of a @ref CLGEMM operation between the deconvolution input and the deconvolution filter
+ *
+ * @note Data type should be given as a preprocessor argument using -DDATA_TYPE=type, e.g., -DDATA_TYPE=F32
+ * @note The width of the filter should be given as a preprocessor argument using -DFILTER_WIDTH=width, e.g., -DFILTER_WIDTH=2
+ * @note The height of the filter should be given as a preprocessor argument using -DFILTER_HEIGHT=height, e.g., -DFILTER_HEIGHT=2
+ * @note The width of the input should be given as a preprocessor argument using -DSRC_WIDTH=width, e.g., -DSRC_WIDTH=10
+ * @note The height of the input should be given as a preprocessor argument using -DSRC_HEIGHT=width, e.g., -DSRC_HEIGHT=10
+ * @note The output data layout is NHWC if the preprocessor argument NUM_FILTERS is defined, NCHW if NUM_FILTERS is not defined
+ *
+ * @param[in] src_ptr Pointer to the source image. Supported data types: QASYMM8/F16/F32
+ * @param[in] src_stride_x Stride of the source image in X dimension (in bytes)
+ * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] src_stride_y Stride of the source image in Y dimension (in bytes)
+ * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source image
+ * @param[out] dst_ptr Pointer to the destination image. Supported data types: same as @p src_ptr
+ * @param[in] dst_stride_x Stride of the destination image in X dimension (in bytes)
+ * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] dst_stride_y Stride of the destination image in Y dimension (in bytes)
+ * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] dst_stride_z Stride of the source tensor in Z dimension (in bytes)
+ * @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes)
+ * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination image
+ * @param[in] bias_ptr (Optional) Pointer to the biases vector. Supported data types: F16/F32/S32
+ * @param[in] bias_stride_x (Optional) Stride of the biases vector in X dimension (in bytes)
+ * @param[in] bias_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] bias_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector
+ */
+__kernel void deconvolution_reshape(
+ TENSOR3D_DECLARATION(src),
+ TENSOR3D_DECLARATION(dst)
+#if defined(ADD_BIAS)
+ ,
+ VECTOR_DECLARATION(bias)
+#endif // defined(ADD_BIAS)
+)
+{
+#define FILTER_AREA ((FILTER_WIDTH) * (FILTER_HEIGHT))
+
+ Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src);
+ Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(dst);
+ const DATA_TYPE data = *(__global DATA_TYPE *)src.ptr;
+
+ // Store result
+ const int x_in = get_global_id(0);
+ const int y_in = get_global_id(1);
+ const int z_in = get_global_id(2);
+
+#if defined(NUM_FILTERS)
+ const int bias_index = x_in / (FILTER_AREA);
+ const int z_out = bias_index + (NUM_FILTERS) * (z_in / (SRC_HEIGHT));
+ const int x_out = x_in % (FILTER_WIDTH) + y_in * (FILTER_WIDTH);
+ const int y_out = (FILTER_HEIGHT) * (z_in % (SRC_HEIGHT)) + ((x_in % (FILTER_AREA)) / (FILTER_WIDTH));
+#else // defined(NUM_FILTERS)
+ const int x_out = x_in / (FILTER_AREA);
+ const int y_out = x_in % (FILTER_WIDTH) + y_in * (FILTER_WIDTH);
+ const int z_out = (FILTER_HEIGHT) * z_in + ((x_in % (FILTER_AREA)) / (FILTER_WIDTH));
+ const int bias_index = x_out;
+#endif // defined(NUM_FILTERS)
+
+#if defined(ADD_BIAS)
+ Vector bias = CONVERT_TO_VECTOR_STRUCT_NO_STEP(bias);
+ const DATA_TYPE bias_val = *(__global DATA_TYPE *)vector_offset(&bias, bias_index);
+ *((__global DATA_TYPE *)tensor3D_offset(&dst, x_out, y_out, z_out)) = data + bias_val;
+#else // defined(ADD_BIAS)
+ *((__global DATA_TYPE *)tensor3D_offset(&dst, x_out, y_out, z_out)) = data;
+#endif // defined(ADD_BIAS)
+
+#undef FILTER_AREA
+}
+#endif // defined(FILTER_WIDTH) && defined(FILTER_HEIGHT) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DATA_TYPE)