COMPMID-2599: Implement a new and generic depthwise convolution on OpenCL (Fp32/FP16-NHWC)
Part 1
Change-Id: I5e1d27a7006199e9229e455a1df9bfc2ed4e8341
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1898
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/cl_kernels/depthwise_convolution.cl b/src/core/CL/cl_kernels/depthwise_convolution.cl
index fb4a0fc..1b2f5cc 100644
--- a/src/core/CL/cl_kernels/depthwise_convolution.cl
+++ b/src/core/CL/cl_kernels/depthwise_convolution.cl
@@ -21,7 +21,6 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
-
#include "helpers.h"
#include "activation_float_helpers.h"
@@ -1479,7 +1478,7 @@
//3x3 Convolution of elements starting in 0th row
pixels0 = convolution_3x3_dilation_stridex2_stridey2_bifrost_f16(src_addr, src.stride_x, src.stride_y, 0, weights_addr, weights_stride_y);
//3x3 Convolution of elements starting in 2nd row
- pixels1 = convolution_3x3_dilation_stridex2_stridey2_bifrost_f16(src_addr, src.stride_x, src.stride_y, 2, weights_addr, weights_stride_y);
+ pixels1 = convolution_3x3_dilation_stridex2_stridey2_bifrost_f16(src_addr, src.stride_x, src.stride_y, 2, weights_addr, weights_stride_y);
#endif /* DILATION_X==1 && DILATION_Y==1 */
#ifdef HAS_BIAS
@@ -1492,6 +1491,153 @@
}
#endif // defined(ARM_COMPUTE_OPENCL_FP16_ENABLED) && defined(DEPTH_MULTIPLIER) && defined(DST_CHANNELS) && defined(IS_F16)
+#if defined(SRC_DIM1) && defined(SRC_DIM2) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(N0) && defined(DATA_TYPE) && defined(DILATION_X) && defined(DILATION_Y) && defined(CONV_STRIDE_X) && defined(CONV_STRIDE_Y) && defined(CONV_PAD_LEFT) && defined(CONV_PAD_TOP)
+/** This function computes the depthwise convolution for NHWC data layout. This kernel assumes that the weights tensor is NOT reshaped
+ *
+ * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float
+ * @note The number of elements processed must be passed at compile time using -DN0 (e.g. -DN0=2)
+ * @note The depth multiplier must be passed at compile time using -DDEPTH_MULTIPLIER (e.g. -DDEPTH_MULTIPLIER=1)
+ * @note The first dimension of the input tensor must be passed at compile time using -DSRC_DIM1 (e.g. -DSRC_DIM1=112)
+ * @note The second dimension of the input tensor must be passed at compile time using -DSRC_DIM2 (e.g. -DSRC_DIM2=80)
+ * @note The kernel width must be passed at compile time using -DKERNEL_WIDTH (e.g. -DKERNEL_WIDTH=5)
+ * @note The kernel height must be passed at compile time using -DKERNEL_HEIGHT (e.g. -DKERNEL_HEIGHT=5)
+ * @note The convolution pad top must be passed at compile time using -DCONV_PAD_TOP (e.g. -DCONV_PAD_TOP=1)
+ * @note The convolution pad top must be passed at compile time using -DCONV_PAD_LEFT (e.g. -DCONV_PAD_LEFT=1)
+ * @note The convolution stride along the width must be passed at compile time using -DCONV_STRIDE_X (e.g. -DCONV_STRIDE_Y=X)
+ * @note The convolution stride along the height must be passed at compile time using -DCONV_STRIDE_Y (e.g. -DCONV_STRIDE_Y=1)
+ * @note It is possible to select the activation function to apply using -DACTIVATION_TYPE e.g. -DACTIVATION_TYPE=relu
+ * @note A, B variables required by some activation functions are set using -DA_VAL= and -DB_VAL= respectively
+ *
+ * @param[in] src_ptr Pointer to the source tensor. Supported data types: F16/F32
+ * @param[in] src_stride_x Stride of the source tensor 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 tensor 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_y * number of elements along Z processed per workitem(in bytes)
+ * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes)
+ * @param[in] src_step_w src_stride_w * number of elements along W processed per workitem(in bytes)
+ * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor
+ * @param[in] dst_ptr Pointer to the destination tensor. Supported data types: same as src_ptr
+ * @param[in] dst_stride_x Stride of the destination tensor 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 tensor 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 destination tensor in Z dimension (in bytes)
+ * @param[in] dst_step_z dst_stride_z * number of elements along Y processed per workitem(in bytes)
+ * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes)
+ * @param[in] dst_step_w dst_stride_w * number of elements along W processed per workitem(in bytes)
+ * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor
+ * @param[in] weights_ptr Pointer to the weights tensor. Supported data types: F16/F32
+ * @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes)
+ * @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes)
+ * @param[in] weights_step_y weights_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes)
+ * @param[in] weights_step_z weights_stride_z * number of elements along Y processed per workitem(in bytes)
+ * @param[in] weights_offset_first_element_in_bytes The offset of the first element in the weights tensor
+ * @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: same as src_ptr
+ * @param[in] biases_stride_x (Optional) Stride of the biases vector in X dimension (in bytes)
+ * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector
+ */
+__kernel void dwc_MxN_native_fp_nhwc(
+ TENSOR4D_DECLARATION(src),
+ TENSOR4D_DECLARATION(dst),
+ TENSOR3D_DECLARATION(weights),
+#if defined(HAS_BIAS)
+ VECTOR_DECLARATION(biases)
+#endif // defined(HAS_BIAS)
+)
+{
+ int x = get_global_id(0); // channels
+ int y = get_global_id(1); // spatial coordinate x
+#if defined(DST_DEPTH)
+ int z = get_global_id(2) % (int)DST_DEPTH; // spatial coordinate y
+ int b = get_global_id(2) / (int)DST_DEPTH; // batch
+#else // defined(DST_DEPTH)
+ int z = get_global_id(2); // spatial coordinate y
+#endif // defined(DST_DEPTH)
+
+ __global uchar *s_addr = src_ptr + src_offset_first_element_in_bytes +
+ x * sizeof(DATA_TYPE) * (int)N0;
+
+ __global uchar *d_addr = dst_ptr + dst_offset_first_element_in_bytes +
+ x * sizeof(DATA_TYPE) * (int)DEPTH_MULTIPLIER * (int)N0 +
+ y * dst_stride_y +
+ z * dst_stride_z;
+
+ __global uchar *w_addr = weights_ptr + weights_offset_first_element_in_bytes +
+ x * sizeof(DATA_TYPE) * (int)DEPTH_MULTIPLIER * (int)N0;
+
+#if defined(HAS_BIAS)
+ __global uchar *b_addr = biases_ptr + biases_offset_first_element_in_bytes +
+ x * sizeof(DATA_TYPE) * (int)DEPTH_MULTIPLIER * (int)N0;
+#endif // defined(HAS_BIAS)
+
+#if defined(DST_DEPTH)
+ s_addr += b * src_stride_w;
+ d_addr += b * dst_stride_w;
+#endif // defined(DST_DEPTH)
+
+ for(int d = 0; d < (int)DEPTH_MULTIPLIER; ++d)
+ {
+ // Each work-item computes N0x1x1 elements
+ VEC_DATA_TYPE(DATA_TYPE, N0)
+ res = 0;
+
+ int x_coord = y * CONV_STRIDE_X - (int)CONV_PAD_LEFT;
+ int y_coord = z * CONV_STRIDE_Y - (int)CONV_PAD_TOP;
+
+ for(int yk = 0; yk < KERNEL_HEIGHT; ++yk)
+ {
+ if(y_coord >= 0 && y_coord < SRC_DIM2)
+ {
+ int x_coord_tmp = x_coord;
+
+ for(int xk = 0; xk < KERNEL_WIDTH; ++xk)
+ {
+ if(x_coord_tmp >= 0 && x_coord_tmp < SRC_DIM1)
+ {
+ int s_offset = x_coord_tmp * (int)src_stride_y + y_coord * (int)src_stride_z;
+ int w_offset = xk * weights_stride_y + yk * weights_stride_z;
+
+ // Load input and weights values
+ VEC_DATA_TYPE(DATA_TYPE, N0)
+ i = VLOAD(N0)(0, (__global DATA_TYPE *)(s_addr + s_offset));
+ VEC_DATA_TYPE(DATA_TYPE, N0)
+ w = VLOAD(N0)(0, (__global DATA_TYPE *)(w_addr + w_offset));
+
+#if GPU_ARCH == GPU_ARCH_MIDGARD
+ res += i * w;
+#else // GPU_ARCH == GPU_ARCH_MIDGARD
+ res = fma(i, w, res);
+#endif // GPU_ARCH == GPU_ARCH_MIDGARD
+ }
+ x_coord_tmp += DILATION_X;
+ }
+ }
+ y_coord += DILATION_Y;
+ }
+
+#if defined(HAS_BIAS)
+ res += VLOAD(N0)(0, (__global DATA_TYPE *)(b_addr));
+#endif // defined(HAS_BIAS)
+
+ res = ACTIVATION(ACTIVATION_TYPE, DATA_TYPE, res, A_VAL, B_VAL);
+
+ VSTORE(N0)
+ (res, 0, (__global DATA_TYPE *)(d_addr));
+
+ w_addr += sizeof(DATA_TYPE);
+ d_addr += sizeof(DATA_TYPE);
+#if defined(HAS_BIAS)
+ b_addr += sizeof(DATA_TYPE);
+#endif // defined(HAS_BIAS)
+ }
+}
+#endif // defined(SRC_DIM1) && defined(SRC_DIM2) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defiend(N0) && defined(DATA_TYPE) && defined(DILATION_X) && defined(DILATION_Y) && defined(CONV_STRIDE_X) && defined(CONV_STRIDE_Y) && defined(CONV_PAD_LEFT) && defined(CONV_PAD_TOP)
+
#if defined(VEC_SIZE) && defined(SRC_DIM_2) && defined(CONV_PAD_TOP) && defined(CONV_PAD_LEFT) && defined(DATA_TYPE)
#if DATA_TYPE != float || DATA_TYPE != half
@@ -1501,6 +1647,7 @@
#define VEC_FLOAT VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
#if defined(CONV_STRIDE_X) && defined(CONV_STRIDE_Y)
+
/** This function computes the depthwise convolution for NHWC data layout when the stride along the width or height is not 1.
*
* @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float