COMPMID-2047: Add support for dilation in CLDepthwiseConvolution.
Change-Id: I3106aa34bd168985a56791613d95072756be6e9b
Signed-off-by: Usama Arif <usama.arif@arm.com>
Reviewed-on: https://review.mlplatform.org/c/958
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Pablo Marquez <pablo.tello@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 4f6fdfa..8ee0185 100644
--- a/src/core/CL/cl_kernels/depthwise_convolution.cl
+++ b/src/core/CL/cl_kernels/depthwise_convolution.cl
@@ -51,13 +51,18 @@
const float middle_coeff,
const float right_coeff)
{
+#if(DILATION_X == 1 && DILATION_Y == 1)
float4 temp = vload4(0, (__global float *)left_pixel);
float2 left = CONVERT(temp.s01, float2);
float2 middle = CONVERT(temp.s12, float2);
float2 right = CONVERT(temp.s23, float2);
-
return left * (float2)left_coeff + middle * (float2)middle_coeff + right * (float2)right_coeff;
+#else /* DILATION_X==1 && DILATION_Y==1 */
+ return vload2(0, (__global float *)left_pixel) * (float2)left_coeff
+ + vload2(0, (__global float *)(left_pixel) + DILATION_X) * (float2)middle_coeff
+ + vload2(0, (__global float *)(left_pixel) + 2 * DILATION_X) * (float2)right_coeff;
+#endif /* DILATION_X==1 && DILATION_Y==1 */
}
/** Compute a 1D horizontal convolution of size 3 and stride 2 for floating point type.
@@ -74,6 +79,7 @@
const float middle_coeff,
const float right_coeff)
{
+#if(DILATION_X == 1 && DILATION_Y == 1)
float4 temp0 = vload4(0, (__global float *)left_pixel);
float temp1 = *((__global float *)(left_pixel + 4 * sizeof(float)));
@@ -82,6 +88,14 @@
float2 right = CONVERT((float2)(temp0.s2, temp1), float2);
return left * (float2)left_coeff + middle * (float2)middle_coeff + right * (float2)right_coeff;
+#else /* DILATION_X==1 && DILATION_Y==1 */
+ __global float *left_pixel_float = (__global float *)left_pixel;
+
+ return vload4(0, left_pixel_float).s02 * (float2)left_coeff
+ + vload4(0, left_pixel_float + DILATION_X).s02 * (float2)middle_coeff
+ + vload4(0, left_pixel_float + DILATION_X * 2).s02 * (float2)right_coeff;
+
+#endif /* DILATION_X==1 && DILATION_Y==1 */
}
/** Compute a 1D horizontal convolution of size 3 and stride 3 for floating point type.
@@ -98,6 +112,7 @@
const float middle_coeff,
const float right_coeff)
{
+#if(DILATION_X == 1 && DILATION_Y == 1)
float4 temp0 = vload4(0, (__global float *)left_pixel);
float2 temp1 = vload2(0, (__global float *)(left_pixel + 4 * sizeof(float)));
@@ -106,6 +121,13 @@
float2 right = CONVERT((float2)(temp0.s2, temp1.s1), float2);
return left * (float2)left_coeff + middle * (float2)middle_coeff + right * (float2)right_coeff;
+#else /* DILATION_X==1 && DILATION_Y==1 */
+ __global float *left_pixel_float = (__global float *)left_pixel;
+
+ return (float2)(*left_pixel_float, *(left_pixel_float + 3)) * (float2)left_coeff
+ + (float2)(*(left_pixel_float + DILATION_X), *(left_pixel_float + DILATION_X + 3)) * (float2)middle_coeff
+ + (float2)(*(left_pixel_float + DILATION_X * 2), *(left_pixel_float + DILATION_X * 2 + 3)) * (float2)right_coeff;
+#endif /* DILATION_X==1 && DILATION_Y==1 */
}
/** Apply a 3x3 convolution matrix to a single channel F32 input image and return the result.
@@ -139,8 +161,8 @@
float2 pixels;
pixels = convolution1x3(offset(src, 0, 0), mat0, mat1, mat2);
- pixels += convolution1x3(offset(src, 0, 1), mat3, mat4, mat5);
- pixels += convolution1x3(offset(src, 0, 2), mat6, mat7, mat8);
+ pixels += convolution1x3(offset(src, 0, DILATION_Y), mat3, mat4, mat5);
+ pixels += convolution1x3(offset(src, 0, DILATION_Y * 2), mat6, mat7, mat8);
return pixels;
}
@@ -216,6 +238,8 @@
}
#endif //defined(CONV_STRIDE_X)
+#if(DILATION_X == 1 && DILATION_Y == 1)
+
#define CONVOLUTION1x3_BIFROST2X1_STRIDE1(acc, src0, weights_row0) \
({ \
acc.s0 = fma(src0.s0, weights_row0.s0, acc.s0); \
@@ -268,6 +292,227 @@
acc.s3 = fma(src1.s0, weights_row0.s2, acc.s3); \
})
+#else /* DILATION_X==1 && DILATION_Y==1 */
+
+#define CONVOLUTION1x3_BIFROST2X1_STRIDE1(acc, src0_left, src0_mid, src0_right, weights_row0) \
+ ({ \
+ acc.s0 = fma(src0_left.s0, weights_row0.s0, acc.s0); \
+ acc.s0 = fma(src0_mid.s0, weights_row0.s1, acc.s0); \
+ acc.s0 = fma(src0_right.s0, weights_row0.s2, acc.s0); \
+ acc.s1 = fma(src0_left.s1, weights_row0.s0, acc.s1); \
+ acc.s1 = fma(src0_mid.s1, weights_row0.s1, acc.s1); \
+ acc.s1 = fma(src0_right.s1, weights_row0.s2, acc.s1); \
+ })
+
+#define CONVOLUTION1x3_BIFROST2X1_STRIDE2(acc, src0_left, src0_mid, src0_right, weights_row0) \
+ ({ \
+ acc.s0 = fma(src0_left.s0, weights_row0.s0, acc.s0); \
+ acc.s0 = fma(src0_mid.s0, weights_row0.s1, acc.s0); \
+ acc.s0 = fma(src0_right.s0, weights_row0.s2, acc.s0); \
+ acc.s1 = fma(src0_left.s2, weights_row0.s0, acc.s1); \
+ acc.s1 = fma(src0_mid.s2, weights_row0.s1, acc.s1); \
+ acc.s1 = fma(src0_right.s2, weights_row0.s2, acc.s1); \
+ })
+
+#define CONVOLUTION1x3_BIFROST4X1_STRIDE1(acc, src0_left, src0_mid, src0_right, weights_row0) \
+ ({ \
+ acc.s0 = fma(src0_left.s0, weights_row0.s0, acc.s0); \
+ acc.s0 = fma(src0_mid.s0, weights_row0.s1, acc.s0); \
+ acc.s0 = fma(src0_right.s0, weights_row0.s2, acc.s0); \
+ acc.s1 = fma(src0_left.s1, weights_row0.s0, acc.s1); \
+ acc.s1 = fma(src0_mid.s1, weights_row0.s1, acc.s1); \
+ acc.s1 = fma(src0_right.s1, weights_row0.s2, acc.s1); \
+ acc.s2 = fma(src0_left.s2, weights_row0.s0, acc.s2); \
+ acc.s2 = fma(src0_mid.s2, weights_row0.s1, acc.s2); \
+ acc.s2 = fma(src0_right.s2, weights_row0.s2, acc.s2); \
+ acc.s3 = fma(src0_left.s3, weights_row0.s0, acc.s3); \
+ acc.s3 = fma(src0_mid.s3, weights_row0.s1, acc.s3); \
+ acc.s3 = fma(src0_right.s3, weights_row0.s2, acc.s3); \
+ })
+
+#define CONVOLUTION1x3_BIFROST4X1_STRIDE2(acc, src0_left, src0_mid, src0_right, weights_row0) \
+ ({ \
+ acc.s0 = fma(src0_left.s0, weights_row0.s0, acc.s0); \
+ acc.s0 = fma(src0_mid.s0, weights_row0.s1, acc.s0); \
+ acc.s0 = fma(src0_right.s0, weights_row0.s2, acc.s0); \
+ acc.s1 = fma(src0_left.s2, weights_row0.s0, acc.s1); \
+ acc.s1 = fma(src0_mid.s2, weights_row0.s1, acc.s1); \
+ acc.s1 = fma(src0_right.s2, weights_row0.s2, acc.s1); \
+ acc.s2 = fma(src0_left.s4, weights_row0.s0, acc.s2); \
+ acc.s2 = fma(src0_mid.s4, weights_row0.s1, acc.s2); \
+ acc.s2 = fma(src0_right.s4, weights_row0.s2, acc.s2); \
+ acc.s3 = fma(src0_left.s6, weights_row0.s0, acc.s3); \
+ acc.s3 = fma(src0_mid.s6, weights_row0.s1, acc.s3); \
+ acc.s3 = fma(src0_right.s6, weights_row0.s2, acc.s3); \
+ })
+
+/** Get the pointer position at a certain offset in x and y direction.
+ *
+ * @param[in] ptr Pointer to the starting position of the buffer
+ * @param[in] x Relative X position
+ * @param[in] y Relative Y position
+ * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
+ */
+inline __global uchar *ptr_offset(__global uchar *ptr, const int x, const int y, const int stride_x, const int stride_y)
+{
+ return ptr + x * stride_x + y * stride_y;
+}
+
+/** Perform 3x3 convolution for stride_x=1 and stride_y=1 when DILATION_X>1 and DILATION_Y>1 for F32
+ *
+ * @param[in] src_addr Pointer to the starting position of where to perform the convolution
+ * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
+ * @param[in] y_offset Offset from the source tensor from which to start convolution
+ * @param[in] weights_addr Pointer from where to get weights
+ * @param[in] weights_stride_y Stride of weights tesnsor in Y dimension
+ */
+inline float2 convolution_3x3_dilation_stridex1_stridey1_bifrost_f32(__global uchar *src_addr, const int stride_x_bytes, const int stride_y_bytes,
+ const int y_offset, __global uchar *weights_addr, const int weights_stride_y)
+{
+ // Load the weights
+ float3 weights_row0 = vload3(0, (__global float *)(weights_addr + 0 * weights_stride_y));
+ float3 weights_row1 = vload3(0, (__global float *)(weights_addr + 1 * weights_stride_y));
+ float3 weights_row2 = vload3(0, (__global float *)(weights_addr + 2 * weights_stride_y));
+
+ float2 pixels0 = 0.0f;
+
+ float2 src00_left = vload2(0, (__global float *)ptr_offset(src_addr, 0, y_offset, stride_x_bytes, stride_y_bytes)); // Row0
+ float2 src00_mid = vload2(0, (__global float *)ptr_offset(src_addr, DILATION_X, y_offset, stride_x_bytes, stride_y_bytes));
+ float2 src00_right = vload2(0, (__global float *)ptr_offset(src_addr, 2 * DILATION_X, y_offset, stride_x_bytes, stride_y_bytes));
+
+ float2 src10_left = vload2(0, (__global float *)ptr_offset(src_addr, 0, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes)); // Row1
+ float2 src10_mid = vload2(0, (__global float *)ptr_offset(src_addr, DILATION_X, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes));
+ float2 src10_right = vload2(0, (__global float *)ptr_offset(src_addr, 2 * DILATION_X, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes));
+
+ float2 src20_left = vload2(0, (__global float *)ptr_offset(src_addr, 0, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes)); // Row2
+ float2 src20_mid = vload2(0, (__global float *)ptr_offset(src_addr, DILATION_X, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes));
+ float2 src20_right = vload2(0, (__global float *)ptr_offset(src_addr, 2 * DILATION_X, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes));
+
+ CONVOLUTION1x3_BIFROST2X1_STRIDE1(pixels0, src00_left, src00_mid, src00_right, weights_row0);
+ CONVOLUTION1x3_BIFROST2X1_STRIDE1(pixels0, src10_left, src10_mid, src10_right, weights_row1);
+ CONVOLUTION1x3_BIFROST2X1_STRIDE1(pixels0, src20_left, src20_mid, src20_right, weights_row2);
+
+ return pixels0;
+}
+
+/** Perform 3x3 convolution for stride_x=2 and stride_y=2 when DILATION_X>1 and DILATION_Y>1 for F32
+ *
+ * @param[in] src_addr Pointer to the starting position of where to perform the convolution
+ * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
+ * @param[in] y_offset Offset from the source tensor from which to start convolution
+ * @param[in] weights_addr Pointer from where to get weights
+ * @param[in] weights_stride_y Stride of weights tesnsor in Y dimension
+ */
+inline float2 convolution_3x3_dilation_stridex2_stridey2_bifrost_f32(__global uchar *src_addr, const int stride_x_bytes, const int stride_y_bytes,
+ const int y_offset, __global uchar *weights_addr, const int weights_stride_y)
+{
+ // Load the weights
+ float3 weights_row0 = vload3(0, (__global float *)(weights_addr + 0 * weights_stride_y));
+ float3 weights_row1 = vload3(0, (__global float *)(weights_addr + 1 * weights_stride_y));
+ float3 weights_row2 = vload3(0, (__global float *)(weights_addr + 2 * weights_stride_y));
+
+ float2 pixels0 = 0.0f;
+
+ float3 src00_left = vload3(0, (__global float *)ptr_offset(src_addr, 0, y_offset, stride_x_bytes, stride_y_bytes)); // Row0
+ float3 src00_mid = vload3(0, (__global float *)ptr_offset(src_addr, DILATION_X, y_offset, stride_x_bytes, stride_y_bytes));
+ float3 src00_right = vload3(0, (__global float *)ptr_offset(src_addr, 2 * DILATION_X, y_offset, stride_x_bytes, stride_y_bytes));
+
+ float3 src10_left = vload3(0, (__global float *)ptr_offset(src_addr, 0, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes)); // Row1
+ float3 src10_mid = vload3(0, (__global float *)ptr_offset(src_addr, DILATION_X, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes));
+ float3 src10_right = vload3(0, (__global float *)ptr_offset(src_addr, 2 * DILATION_X, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes));
+
+ float3 src20_left = vload3(0, (__global float *)ptr_offset(src_addr, 0, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes)); // Row2
+ float3 src20_mid = vload3(0, (__global float *)ptr_offset(src_addr, DILATION_X, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes));
+ float3 src20_right = vload3(0, (__global float *)ptr_offset(src_addr, 2 * DILATION_X, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes));
+
+ CONVOLUTION1x3_BIFROST2X1_STRIDE2(pixels0, src00_left, src00_mid, src00_right, weights_row0);
+ CONVOLUTION1x3_BIFROST2X1_STRIDE2(pixels0, src10_left, src10_mid, src10_right, weights_row1);
+ CONVOLUTION1x3_BIFROST2X1_STRIDE2(pixels0, src20_left, src20_mid, src20_right, weights_row2);
+
+ return pixels0;
+}
+
+/** Perform 3x3 convolution for stride_x=1 and stride_y=1 when DILATION_X>1 and DILATION_Y>1 for f16
+ *
+ * @param[in] src_addr Pointer to the starting position of where to perform the convolution
+ * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
+ * @param[in] y_offset Offset from the source tensor from which to start convolution
+ * @param[in] weights_addr Pointer from where to get weights
+ * @param[in] weights_stride_y Stride of weights tesnsor in Y dimension
+ */
+inline half4 convolution_3x3_dilation_stridex1_stridey1_bifrost_f16(__global uchar *src_addr, const int stride_x_bytes, const int stride_y_bytes,
+ const int y_offset, __global uchar *weights_addr, const int weights_stride_y)
+{
+ // Load the weights
+ half3 weights_row0 = vload3(0, (__global half *)(weights_addr + 0 * weights_stride_y));
+ half3 weights_row1 = vload3(0, (__global half *)(weights_addr + 1 * weights_stride_y));
+ half3 weights_row2 = vload3(0, (__global half *)(weights_addr + 2 * weights_stride_y));
+
+ half4 pixels0 = 0.0f;
+
+ half4 src00_left = vload4(0, (__global half *)ptr_offset(src_addr, 0, y_offset, stride_x_bytes, stride_y_bytes)); // Row0
+ half4 src00_mid = vload4(0, (__global half *)ptr_offset(src_addr, DILATION_X, y_offset, stride_x_bytes, stride_y_bytes));
+ half4 src00_right = vload4(0, (__global half *)ptr_offset(src_addr, 2 * DILATION_X, y_offset, stride_x_bytes, stride_y_bytes));
+
+ half4 src10_left = vload4(0, (__global half *)ptr_offset(src_addr, 0, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes)); // Row1
+ half4 src10_mid = vload4(0, (__global half *)ptr_offset(src_addr, DILATION_X, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes));
+ half4 src10_right = vload4(0, (__global half *)ptr_offset(src_addr, 2 * DILATION_X, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes));
+
+ half4 src20_left = vload4(0, (__global half *)ptr_offset(src_addr, 0, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes)); // Row2
+ half4 src20_mid = vload4(0, (__global half *)ptr_offset(src_addr, DILATION_X, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes));
+ half4 src20_right = vload4(0, (__global half *)ptr_offset(src_addr, 2 * DILATION_X, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes));
+
+ CONVOLUTION1x3_BIFROST4X1_STRIDE1(pixels0, src00_left, src00_mid, src00_right, weights_row0);
+ CONVOLUTION1x3_BIFROST4X1_STRIDE1(pixels0, src10_left, src10_mid, src10_right, weights_row1);
+ CONVOLUTION1x3_BIFROST4X1_STRIDE1(pixels0, src20_left, src20_mid, src20_right, weights_row2);
+
+ return pixels0;
+}
+
+/** Perform 3x3 convolution for stride_x=2 and stride_y=2 when DILATION_X>1 and DILATION_Y>1 for F16
+ *
+ * @param[in] src_addr Pointer to the starting position of where to perform the convolution
+ * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes)
+ * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes)
+ * @param[in] y_offset Offset from the source tensor from which to start convolution
+ * @param[in] weights_addr Pointer from where to get weights
+ * @param[in] weights_stride_y Stride of weights tesnsor in Y dimension
+ */
+inline half4 convolution_3x3_dilation_stridex2_stridey2_bifrost_f16(__global uchar *src_addr, const int stride_x_bytes, const int stride_y_bytes,
+ const int y_offset, __global uchar *weights_addr, const int weights_stride_y)
+{
+ // Load the weights
+ half3 weights_row0 = vload3(0, (__global half *)(weights_addr + 0 * weights_stride_y));
+ half3 weights_row1 = vload3(0, (__global half *)(weights_addr + 1 * weights_stride_y));
+ half3 weights_row2 = vload3(0, (__global half *)(weights_addr + 2 * weights_stride_y));
+
+ half4 pixels0 = 0.0f;
+
+ half8 src00_left = vload8(0, (__global half *)ptr_offset(src_addr, 0, y_offset, stride_x_bytes, stride_y_bytes)); // Row0
+ half8 src00_mid = vload8(0, (__global half *)ptr_offset(src_addr, DILATION_X, y_offset, stride_x_bytes, stride_y_bytes));
+ half8 src00_right = vload8(0, (__global half *)ptr_offset(src_addr, 2 * DILATION_X, y_offset, stride_x_bytes, stride_y_bytes));
+
+ half8 src10_left = vload8(0, (__global half *)ptr_offset(src_addr, 0, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes)); // Row1
+ half8 src10_mid = vload8(0, (__global half *)ptr_offset(src_addr, DILATION_X, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes));
+ half8 src10_right = vload8(0, (__global half *)ptr_offset(src_addr, 2 * DILATION_X, y_offset + DILATION_Y, stride_x_bytes, stride_y_bytes));
+
+ half8 src20_left = vload8(0, (__global half *)ptr_offset(src_addr, 0, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes)); // Row2
+ half8 src20_mid = vload8(0, (__global half *)ptr_offset(src_addr, DILATION_X, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes));
+ half8 src20_right = vload8(0, (__global half *)ptr_offset(src_addr, 2 * DILATION_X, y_offset + DILATION_Y * 2, stride_x_bytes, stride_y_bytes));
+
+ CONVOLUTION1x3_BIFROST4X1_STRIDE2(pixels0, src00_left, src00_mid, src00_right, weights_row0);
+ CONVOLUTION1x3_BIFROST4X1_STRIDE2(pixels0, src10_left, src10_mid, src10_right, weights_row1);
+ CONVOLUTION1x3_BIFROST4X1_STRIDE2(pixels0, src20_left, src20_mid, src20_right, weights_row2);
+
+ return pixels0;
+}
+
+#endif /* DILATION_X==1 && DILATION_Y==1 */
+
/** This OpenCL kernel is optimized for Bifrost architectures and computes the depthwise convolution 3x3 when both
* stride_x and stride_y are equal to 1
*
@@ -326,6 +571,7 @@
__global uchar *weights_addr = weights.ptr + get_global_id(0) * weights_step_x + get_global_id(1) * weights_step_y + channel * weights_step_z;
__global uchar *src_addr = src.ptr - batch * (DST_CHANNELS / DEPTH_MULTIPLIER) * (DEPTH_MULTIPLIER - 1) * src_step_z - (channel - (channel / DEPTH_MULTIPLIER)) * src_step_z;
+#if(DILATION_X == 1 && DILATION_Y == 1)
// Load the weights
float3 weights_row0 = vload3(0, (__global float *)(weights_addr + 0 * weights_stride_y));
float3 weights_row1 = vload3(0, (__global float *)(weights_addr + 1 * weights_stride_y));
@@ -352,6 +598,19 @@
CONVOLUTION1x3_BIFROST2X1_STRIDE1(pixels3, src40, weights_row1);
CONVOLUTION1x3_BIFROST2X1_STRIDE1(pixels3, src50, weights_row2);
+#else /* DILATION_X==1 && DILATION_Y==1 */
+
+ //3x3 Convolution of elements starting in 0th row
+ pixels0 = convolution_3x3_dilation_stridex1_stridey1_bifrost_f32(src_addr, src.stride_x, src.stride_y, 0, weights_addr, weights_stride_y);
+ //3x3 Convolution of elements starting in 1st row
+ pixels1 = convolution_3x3_dilation_stridex1_stridey1_bifrost_f32(src_addr, src.stride_x, src.stride_y, 1, weights_addr, weights_stride_y);
+ //3x3 Convolution of elements starting in 2nd row
+ pixels2 = convolution_3x3_dilation_stridex1_stridey1_bifrost_f32(src_addr, src.stride_x, src.stride_y, 2, weights_addr, weights_stride_y);
+ //3x3 Convolution of elements starting in 3rd row
+ pixels3 = convolution_3x3_dilation_stridex1_stridey1_bifrost_f32(src_addr, src.stride_x, src.stride_y, 3, weights_addr, weights_stride_y);
+
+#endif /* DILATION_X==1 && DILATION_Y==1 */
+
#ifdef HAS_BIAS
Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
@@ -425,6 +684,8 @@
__global uchar *weights_addr = weights.ptr + get_global_id(0) * weights_step_x + get_global_id(1) * weights_step_y + channel * weights_step_z;
__global uchar *src_addr = src.ptr - batch * (DST_CHANNELS / DEPTH_MULTIPLIER) * (DEPTH_MULTIPLIER - 1) * src_step_z - (channel - (channel / DEPTH_MULTIPLIER)) * src_step_z;
+#if(DILATION_X == 1 && DILATION_Y == 1)
+
// Load the weights
float3 weights_row0 = vload3(0, (__global float *)(weights_addr + 0 * weights_stride_y));
float3 weights_row1 = vload3(0, (__global float *)(weights_addr + 1 * weights_stride_y));
@@ -449,6 +710,14 @@
CONVOLUTION1x3_BIFROST2X1_STRIDE2(pixels1, src30, src31, weights_row1);
CONVOLUTION1x3_BIFROST2X1_STRIDE2(pixels1, src40, src41, weights_row2);
+#else /* DILATION_X==1 && DILATION_Y==1 */
+
+ //3x3 Convolution of elements starting in 0th row
+ pixels0 = convolution_3x3_dilation_stridex2_stridey2_bifrost_f32(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_f32(src_addr, src.stride_x, src.stride_y, 2, weights_addr, weights_stride_y);
+#endif /* DILATION_X==1 && DILATION_Y==1 */
+
#ifdef HAS_BIAS
Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases);
@@ -632,11 +901,12 @@
}
#endif //defined(SRC_WIDTH) && defined(DATA_TYPE)
-#if defined(STRIDE_X) && defined(STRIDE_Y) && defined(PAD_LEFT) && defined(PAD_TOP) && defined(PAD_RIGHT) && defined(PAD_BOTTOM) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DATA_TYPE) && defined(PAD_VALUE) && defined(DEPTH_MULTIPLIER)
+#if defined(STRIDE_X) && defined(STRIDE_Y) && defined(PAD_LEFT) && defined(PAD_TOP) && defined(PAD_RIGHT) && defined(PAD_BOTTOM) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(DATA_TYPE) && defined(PAD_VALUE) && defined(DEPTH_MULTIPLIER) && defined(DILATION_X) && defined(DILATION_Y)
/** This kernel performs a reshaping of the input tensor to a tensor used to perform depthwise convolution using vector to matrix multiplication.
*
* @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float
* @note The convolution information must be passed at compile time using -DSTRIDE_X, -DSTRIDE_Y, -DPAD_LEFT, -DPAD_TOP, -DPAD_RIGHT, -DPAD_BOTTOM, -DKERNEL_WIDHT, -DKERNEL_HEIGHT, -DSRC_WIDTH, -DSRC_HEIGHT, -DDEPTH_MULTIPLIER
+ * @note The dilation_x and dilation_y must be passed at compile time using -DDILATION_X and -DDILATION_Y: e.g. -DDILATION_X=1, -DDILATION_Y=1
*
* @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)
@@ -661,7 +931,7 @@
const int src_pixel_linear = get_global_id(1) * STRIDE_X;
const int full_length = SRC_WIDTH + PAD_LEFT + PAD_RIGHT;
- const int max_initial_x = STRIDE_X * (((full_length - KERNEL_WIDTH) / STRIDE_X) + 1);
+ const int max_initial_x = STRIDE_X * (((full_length - (KERNEL_WIDTH + (KERNEL_WIDTH - 1) * (DILATION_X - 1))) / STRIDE_X) + 1);
const int src_x = -PAD_LEFT + src_pixel_linear % max_initial_x;
const int src_y = -PAD_TOP + src_pixel_linear / max_initial_x * STRIDE_Y;
@@ -670,9 +940,9 @@
__global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + src_z * in_stride_z;
__global DATA_TYPE *output_ptr = ((__global DATA_TYPE *)(dst.ptr));
- for(int y = src_y; y < src_y + KERNEL_HEIGHT; ++y)
+ for(int y = src_y; y < src_y + KERNEL_HEIGHT + (KERNEL_HEIGHT - 1) * (DILATION_Y - 1); y += DILATION_Y)
{
- for(int x = src_x; x < src_x + KERNEL_WIDTH; ++x, ++output_ptr)
+ for(int x = src_x; x < src_x + KERNEL_WIDTH + (KERNEL_WIDTH - 1) * (DILATION_X - 1); x += DILATION_X, ++output_ptr)
{
if(x < 0 || x >= SRC_WIDTH || y < 0 || y >= SRC_HEIGHT)
{
@@ -754,6 +1024,8 @@
const half middle_coeff,
const half right_coeff)
{
+#if(DILATION_X == 1 && DILATION_Y == 1)
+
half8 temp = vload8(0, (__global half *)left_pixel);
half4 left = CONVERT(temp.s0123, half4);
@@ -761,6 +1033,12 @@
half4 right = CONVERT(temp.s2345, half4);
return left * (half4)left_coeff + middle * (half4)middle_coeff + right * (half4)right_coeff;
+#else /* DILATION_X==1 && DILATION_Y==1 */
+ return vload4(0, (__global half *)left_pixel) * (half4)left_coeff
+ + vload4(0, (__global half *)(left_pixel) + DILATION_X) * (half4)middle_coeff
+ + vload4(0, (__global half *)(left_pixel) + 2 * DILATION_X) * (half4)right_coeff;
+
+#endif /* DILATION_X==1 && DILATION_Y==1 */
}
/** Compute a 1D horizontal convolution of size 3 and stride 2 for 16bit floating point type.
@@ -777,6 +1055,8 @@
const half middle_coeff,
const half right_coeff)
{
+#if(DILATION_X == 1 && DILATION_Y == 1)
+
half8 temp0 = vload8(0, (__global half *)left_pixel);
half temp1 = *((__global half *)(left_pixel + 8 * sizeof(half)));
@@ -785,6 +1065,15 @@
half4 right = CONVERT((half4)(temp0.s246, temp1), half4);
return left * (half4)left_coeff + middle * (half4)middle_coeff + right * (half4)right_coeff;
+#else /* DILATION_X==1 && DILATION_Y==1 */
+
+ __global half *left_pixel_float = (__global half *)left_pixel;
+
+ return (half4)(*left_pixel_float, *(left_pixel_float + 2), *(left_pixel_float + 4), *(left_pixel_float + 6)) * (half4)left_coeff
+ + (half4)(*(left_pixel_float + DILATION_X), *(left_pixel_float + DILATION_X + 2), *(left_pixel_float + DILATION_X + 4), *(left_pixel_float + DILATION_X + 6)) * (half4)middle_coeff
+ + (half4)(*(left_pixel_float + DILATION_X * 2), *(left_pixel_float + DILATION_X * 2 + 2), *(left_pixel_float + DILATION_X * 2 + 4), *(left_pixel_float + DILATION_X * 2 + 6)) * (half4)right_coeff;
+
+#endif /* DILATION_X==1 && DILATION_Y==1 */
}
/** Compute a 1D horizontal convolution of size 3 and stride 3 for 16bit floating point type.
@@ -801,6 +1090,8 @@
const half middle_coeff,
const half right_coeff)
{
+#if(DILATION_X == 1 && DILATION_Y == 1)
+
half16 temp0 = vload16(0, (__global half *)left_pixel);
half4 left = CONVERT(temp0.s0369, half4);
@@ -808,6 +1099,15 @@
half4 right = CONVERT(temp0.s258B, half4);
return left * (half4)left_coeff + middle * (half4)middle_coeff + right * (half4)right_coeff;
+#else /* DILATION_X==1 && DILATION_Y==1 */
+
+ __global half *left_pixel_float = (__global half *)left_pixel;
+
+ return (half4)(*left_pixel_float, *(left_pixel_float + 3), *(left_pixel_float + 6), *(left_pixel_float + 9)) * (half4)left_coeff
+ + (half4)(*(left_pixel_float + DILATION_X), *(left_pixel_float + DILATION_X + 3), *(left_pixel_float + DILATION_X + 6), *(left_pixel_float + DILATION_X + 9)) * (half4)middle_coeff
+ + (half4)(*(left_pixel_float + DILATION_X * 2), *(left_pixel_float + DILATION_X * 2 + 3), *(left_pixel_float + DILATION_X * 2 + 6), *(left_pixel_float + DILATION_X * 2 + 9)) * (half4)right_coeff;
+
+#endif /* DILATION_X==1 && DILATION_Y==1 */
}
/** Apply a 3x3 convolution matrix to a single channel F16 input image and return the result.
@@ -841,8 +1141,8 @@
half4 pixels;
pixels = convolution1x3_f16(offset(src, 0, 0), mat0, mat1, mat2);
- pixels += convolution1x3_f16(offset(src, 0, 1), mat3, mat4, mat5);
- pixels += convolution1x3_f16(offset(src, 0, 2), mat6, mat7, mat8);
+ pixels += convolution1x3_f16(offset(src, 0, DILATION_Y), mat3, mat4, mat5);
+ pixels += convolution1x3_f16(offset(src, 0, DILATION_Y * 2), mat6, mat7, mat8);
return pixels;
}
@@ -986,6 +1286,7 @@
__global uchar *weights_addr = weights.ptr + get_global_id(0) * weights_step_x + get_global_id(1) * weights_step_y + channel * weights_step_z;
__global uchar *src_addr = src.ptr - batch * (DST_CHANNELS / DEPTH_MULTIPLIER) * (DEPTH_MULTIPLIER - 1) * src_step_z - (channel - (channel / DEPTH_MULTIPLIER)) * src_step_z;
+#if(DILATION_X == 1 && DILATION_Y == 1)
// Load the weights
half3 weights_row0 = vload3(0, (__global half *)(weights_addr + 0 * weights_stride_y));
half3 weights_row1 = vload3(0, (__global half *)(weights_addr + 1 * weights_stride_y));
@@ -1012,6 +1313,19 @@
CONVOLUTION1x3_BIFROST4X1_STRIDE1(pixels3, src40, weights_row1);
CONVOLUTION1x3_BIFROST4X1_STRIDE1(pixels3, src50, weights_row2);
+#else /* DILATION_X==1 && DILATION_Y==1 */
+
+ //3x3 Convolution of elements starting in 0th row
+ pixels0 = convolution_3x3_dilation_stridex1_stridey1_bifrost_f16(src_addr, src.stride_x, src.stride_y, 0, weights_addr, weights_stride_y);
+ //3x3 Convolution of elements starting in 1st row
+ pixels1 = convolution_3x3_dilation_stridex1_stridey1_bifrost_f16(src_addr, src.stride_x, src.stride_y, 1, weights_addr, weights_stride_y);
+ //3x3 Convolution of elements starting in 2nd row
+ pixels2 = convolution_3x3_dilation_stridex1_stridey1_bifrost_f16(src_addr, src.stride_x, src.stride_y, 2, weights_addr, weights_stride_y);
+ //3x3 Convolution of elements starting in 3rd row
+ pixels3 = convolution_3x3_dilation_stridex1_stridey1_bifrost_f16(src_addr, src.stride_x, src.stride_y, 3, weights_addr, weights_stride_y);
+
+#endif /* DILATION_X==1 && DILATION_Y==1 */
+
#ifdef HAS_BIAS
pixels0 += (half4)bias;
pixels1 += (half4)bias;
@@ -1088,6 +1402,8 @@
__global uchar *weights_addr = weights.ptr + get_global_id(0) * weights_step_x + get_global_id(1) * weights_step_y + channel * weights_step_z;
__global uchar *src_addr = src.ptr - batch * (DST_CHANNELS / DEPTH_MULTIPLIER) * (DEPTH_MULTIPLIER - 1) * src_step_z - (channel - (channel / DEPTH_MULTIPLIER)) * src_step_z;
+#if(DILATION_X == 1 && DILATION_Y == 1)
+
// Load the weights
half3 weights_row0 = vload3(0, (__global half *)(weights_addr + 0 * weights_stride_y));
half3 weights_row1 = vload3(0, (__global half *)(weights_addr + 1 * weights_stride_y));
@@ -1112,6 +1428,13 @@
CONVOLUTION1x3_BIFROST4X1_STRIDE2(pixels1, src30, src31, weights_row1);
CONVOLUTION1x3_BIFROST4X1_STRIDE2(pixels1, src40, src41, weights_row2);
+#else /* DILATION_X==1 && DILATION_Y==1 */
+ //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);
+#endif /* DILATION_X==1 && DILATION_Y==1 */
+
#ifdef HAS_BIAS
pixels0 += (half4)bias;
pixels1 += (half4)bias;
@@ -1189,9 +1512,9 @@
#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)
+#else // defined(DST_DEPTH)
+ int z = get_global_id(2); // spatial coordinate y
+#endif // defined(DST_DEPTH)
Vector weights = CONVERT_TO_VECTOR_STRUCT(weights);
@@ -1203,7 +1526,7 @@
int z_coord = 0;
int4 offset = 0;
- int4 y_offset = ((int4)(y * CONV_STRIDE_X) + (int4)(0, 1, 2, 3) - CONV_PAD_LEFT) * (int4)src_stride_y;
+ int4 y_offset = ((int4)(y * CONV_STRIDE_X) + (int4)(0, DILATION_X * 1, DILATION_X * 2, DILATION_X * 3) - CONV_PAD_LEFT) * (int4)src_stride_y;
// We compute 2x1x1 [C,W,H] elements
VEC_FLOAT acc = 0;
@@ -1236,16 +1559,16 @@
// z == 1
// z_coord can be only negative for z = 0 so we do not need to clamp it
// Moreover z_coord cannot be out-of-bound for z = 1 so we do not need to clamp the offset
- z_coord = z * CONV_STRIDE_Y - (int)CONV_PAD_TOP + 1;
+ z_coord = z * CONV_STRIDE_Y - (int)CONV_PAD_TOP + DILATION_Y;
offset = y_offset + (int4)(z_coord * src_stride_z);
VEC_FLOAT values3 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_FLOAT values4 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
VEC_FLOAT values5 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s2));
// z == 2
- // After z = 1 we can simply add src_stride_z to offset without updating z_coord
- // However offset can be out-of-bound so we need to check if it is greater than max_offset
- offset += (int4)src_stride_z;
+ // Offset can be out-of-bound so we need to check if it is greater than max_offset
+ z_coord = z * CONV_STRIDE_Y - (int)CONV_PAD_TOP + DILATION_Y * 2;
+ offset = y_offset + (int4)(z_coord * src_stride_z);
offset = min(offset, (int4)max_offset);
VEC_FLOAT values6 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s0));
VEC_FLOAT values7 = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)(src_addr + offset.s1));
@@ -1338,9 +1661,9 @@
#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)
+#else // defined(DST_DEPTH)
+ int z = get_global_id(2); // spatial coordinate y
+#endif // defined(DST_DEPTH)
Vector weights = CONVERT_TO_VECTOR_STRUCT(weights);
diff --git a/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl b/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl
index 503aa7e..8d145a0 100644
--- a/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl
+++ b/src/core/CL/cl_kernels/depthwise_convolution_quantized.cl
@@ -53,6 +53,8 @@
#if !(defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8))
+#if DILATION_X == 1
+
#if CONV_STRIDE_X == 1
#define GET_VALUES(first_value, left, middle, right) \
({ \
@@ -85,6 +87,46 @@
})
#endif /* CONV_STRIDE_X */
+#else /* DILATION_X == 1 */
+
+#if CONV_STRIDE_X == 1
+#define GET_VALUES(first_value, left, middle, right) \
+ ({ \
+ left = CONVERT(vload8(0, first_value), int8); \
+ middle = CONVERT(vload8(0, first_value + DILATION_X * sizeof(uchar)), int8); \
+ right = CONVERT(vload8(0, first_value + 2 * DILATION_X * sizeof(uchar)), int8); \
+ })
+#elif CONV_STRIDE_X == 2
+#define GET_VALUES(first_value, left, middle, right) \
+ ({ \
+ int16 temp0 = CONVERT(vload16(0, first_value), int16); \
+ left = CONVERT(temp0.s02468ace, int8); \
+ \
+ temp0 = CONVERT(vload16(0, first_value + DILATION_X * sizeof(uchar)), int16); \
+ middle = CONVERT(temp0.s02468ace, int8); \
+ \
+ temp0 = CONVERT(vload16(0, first_value + 2 * DILATION_X * sizeof(uchar)), int16); \
+ right = CONVERT(temp0.s02468ace, int8); \
+ })
+#else /* CONV_STRIDE_X */
+#define GET_VALUES(first_value, left, middle, right) \
+ ({ \
+ int16 temp0 = CONVERT(vload16(0, first_value), int16); \
+ int8 temp1 = CONVERT(vload8(0, (first_value + 16 * sizeof(uchar))), int8); \
+ left = CONVERT((int8)(temp0.s0369, temp0.scf, temp1.s25), int8); \
+ \
+ temp0 = CONVERT(vload16(0, first_value + DILATION_X * sizeof(uchar)), int16); \
+ temp1 = CONVERT(vload8(0, (first_value + (16 + DILATION_X) * sizeof(uchar))), int8); \
+ middle = CONVERT((int8)(temp0.s0369, temp0.scf, temp1.s25), int8); \
+ \
+ temp0 = CONVERT(vload16(0, first_value + 2 * DILATION_X * sizeof(uchar)), int16); \
+ temp1 = CONVERT(vload8(0, (first_value + (16 + 2 * DILATION_X) * sizeof(uchar))), int8); \
+ right = CONVERT((int8)(temp0.s0369, temp0.scf, temp1.s25), int8); \
+ })
+
+#endif /* CONV_STRIDE_X */
+#endif /* DILATION_X==1 */
+
/** This function computes the depthwise convolution quantized.
*
* @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8
@@ -151,10 +193,10 @@
int8 values0 = 0;
int8 sum0 = 0;
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
int8 values1 = 0;
int8 sum1 = 0;
-#endif /* CONV_STRIDE_Y */
+#endif /* CONV_STRIDE_Y &&DILATION_Y==1 */
// Row0
int8 left, middle, right;
@@ -168,44 +210,44 @@
#endif /* WEIGHTS_OFFSET != 0 */
// Row1
- GET_VALUES(src.ptr + 1 * src_stride_y, left, middle, right);
+ GET_VALUES(src.ptr + DILATION_Y * src_stride_y, left, middle, right);
values0 += left * (int8)(w1.s0);
values0 += middle * (int8)(w1.s1);
values0 += right * (int8)(w1.s2);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += left * (int8)(w0.s0);
values1 += middle * (int8)(w0.s1);
values1 += right * (int8)(w0.s2);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y && DILATION_Y== 1 */
#if WEIGHTS_OFFSET != 0
int8 tmp = left + middle + right;
sum0 += tmp;
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
sum1 += tmp;
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y &&DILATION_Y== 1 */
#endif /* WEIGHTS_OFFSET != 0 */
// Row2
- GET_VALUES(src.ptr + 2 * src_stride_y, left, middle, right);
+ GET_VALUES(src.ptr + 2 * DILATION_Y * src_stride_y, left, middle, right);
values0 += left * (int8)(w2.s0);
values0 += middle * (int8)(w2.s1);
values0 += right * (int8)(w2.s2);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += left * (int8)(w1.s0);
values1 += middle * (int8)(w1.s1);
values1 += right * (int8)(w1.s2);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y &&DILATION_Y == 1 */
#if WEIGHTS_OFFSET != 0
tmp = left + middle + right;
sum0 += tmp;
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
sum1 += tmp;
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1 */
#endif /* WEIGHTS_OFFSET != 0 */
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
// Row3
GET_VALUES(src.ptr + 3 * src_stride_y, left, middle, right);
values1 += left * (int8)(w2.s0);
@@ -215,20 +257,20 @@
#if WEIGHTS_OFFSET != 0
sum1 += left + middle + right;
#endif /* WEIGHTS_OFFSET != 0 */
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y && DILATION_Y == 1 */
#if defined(HAS_BIAS)
values0 += (int8)(bias_value);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += (int8)(bias_value);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y & &DILATION_Y == 1 */
#endif //defined(HAS_BIAS)
#if WEIGHTS_OFFSET != 0
values0 += sum0 * (int8)(WEIGHTS_OFFSET);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += sum1 * (int8)(WEIGHTS_OFFSET);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1 */
#endif /* WEIGHTS_OFFSET != 0 */
#if INPUT_OFFSET != 0
@@ -236,16 +278,16 @@
ushort3 tmp_we = convert_ushort3(w0) + convert_ushort3(w1) + convert_ushort3(w2);
sum_weights += tmp_we.s0 + tmp_we.s1 + tmp_we.s2;
values0 += sum_weights * (int8)(INPUT_OFFSET);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += sum_weights * (int8)(INPUT_OFFSET);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1 */
#endif /* INPUT_OFFSET != 0 */
#if K_OFFSET != 0
values0 += (int8)(K_OFFSET);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += (int8)(K_OFFSET);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1*/
#endif /* K_OFFSET != 0 */
#if defined(REAL_MULTIPLIER)
@@ -264,7 +306,7 @@
res0 = min(res0, (uchar8)255);
vstore8(ACTIVATION_FUNC(res0), 0, dst.ptr);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
#if defined(REAL_MULTIPLIER)
values1 = CONVERT(round(CONVERT(values1, float8) * (float8)REAL_MULTIPLIER), int8);
@@ -281,11 +323,11 @@
res1 = min(res1, (uchar8)255);
vstore8(ACTIVATION_FUNC(res1), 0, dst.ptr + dst_stride_y);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1*/
}
#else // !(defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8))
-
+#if DILATION_X == 1
#if CONV_STRIDE_X == 1
#define GET_VALUES(first_value, left, middle, right) \
({ \
@@ -317,6 +359,43 @@
right = (uchar8)(temp0.s258b, temp0.se, temp1.s147); \
})
#endif /* CONV_STRIDE_X */
+#else /*DILATION_X==1*/
+
+#if CONV_STRIDE_X == 1
+#define GET_VALUES(first_value, left, middle, right) \
+ ({ \
+ left = vload8(0, first_value); \
+ middle = vload8(0, first_value + DILATION_X * sizeof(uchar)); \
+ right = vload8(0, first_value + 2 * DILATION_X * sizeof(uchar)); \
+ })
+#elif CONV_STRIDE_X == 2
+#define GET_VALUES(first_value, left, middle, right) \
+ ({ \
+ uchar16 temp0 = vload16(0, first_value); \
+ left = temp0.s02468ace; \
+ temp0 = vload16(0, first_value + DILATION_X * sizeof(uchar)); \
+ middle = temp0.s02468ace; \
+ temp0 = vload16(0, first_value + 2 * DILATION_X * sizeof(uchar)); \
+ right = temp0.s02468ace; \
+ })
+#else /* CONV_STRIDE_X */
+#define GET_VALUES(first_value, left, middle, right) \
+ ({ \
+ uchar16 temp0 = vload16(0, first_value); \
+ uchar8 temp1 = vload8(0, (first_value + 16 * sizeof(uchar))); \
+ left = (uchar8)(temp0.s0369, temp0.scf, temp1.s25); \
+ \
+ temp0 = vload16(0, first_value + DILATION_X * sizeof(uchar)); \
+ temp1 = vload8(0, (first_value + (16 + DILATION_X) * sizeof(uchar))); \
+ middle = (uchar8)(temp0.s0369, temp0.scf, temp1.s25); \
+ \
+ temp0 = vload16(0, first_value + 2 * DILATION_X * sizeof(uchar)); \
+ temp1 = vload8(0, (first_value + (16 + 2 * DILATION_X) * sizeof(uchar))); \
+ right = (uchar8)(temp0.s0369, temp0.scf, temp1.s25); \
+ })
+
+#endif /* CONV_STRIDE_X */
+#endif /*DILATION_X==1*/
/** This function computes the depthwise convolution quantized using dot product when the data layout is NCHW.
*
* @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8
@@ -389,8 +468,8 @@
int8 sum0 = 0;
GET_VALUES(src.ptr + 0 * src_stride_y, left0, middle0, right0);
- GET_VALUES(src.ptr + 1 * src_stride_y, left1, middle1, right1);
- GET_VALUES(src.ptr + 2 * src_stride_y, left2, middle2, right2);
+ GET_VALUES(src.ptr + DILATION_Y * src_stride_y, left1, middle1, right1);
+ GET_VALUES(src.ptr + 2 * DILATION_Y * src_stride_y, left2, middle2, right2);
#if WEIGHTS_OFFSET != 0
sum0 += convert_int8(left0) + convert_int8(middle0) + convert_int8(right0);
@@ -398,7 +477,7 @@
sum0 += convert_int8(left2) + convert_int8(middle2) + convert_int8(right2);
#endif /* WEIGHTS_OFFSET != 0 */
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
// If conv_stride_y is equals to 1, we compute two output rows
uchar8 left3, middle3, right3;
@@ -412,7 +491,7 @@
sum1 += convert_int8(left2) + convert_int8(middle2) + convert_int8(right2);
sum1 += convert_int8(left3) + convert_int8(middle3) + convert_int8(right3);
#endif /* WEIGHTS_OFFSET != 0 */
-#endif // CONV_STRIDE_Y == 1
+#endif // CONV_STRIDE_Y == 1 && DILATION_Y==1
ARM_DOT((uchar4)(left0.s0, middle0.s0, right0.s0, left1.s0), (uchar4)(w0.s0, w0.s1, w0.s2, w1.s0), values0.s0);
ARM_DOT((uchar4)(middle1.s0, right1.s0, left2.s0, middle2.s0), (uchar4)(w1.s1, w1.s2, w2.s0, w2.s1), values0.s0);
@@ -446,7 +525,7 @@
ARM_DOT((uchar4)(middle1.s7, right1.s7, left2.s7, middle2.s7), (uchar4)(w1.s1, w1.s2, w2.s0, w2.s1), values0.s7);
values0.s7 += right2.s7 * w2.s2;
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
ARM_DOT((uchar4)(left1.s0, middle1.s0, right1.s0, left2.s0), (uchar4)(w0.s0, w0.s1, w0.s2, w1.s0), values1.s0);
ARM_DOT((uchar4)(middle2.s0, right2.s0, left3.s0, middle3.s0), (uchar4)(w1.s1, w1.s2, w2.s0, w2.s1), values1.s0);
values1.s0 += right3.s0 * w2.s2;
@@ -478,20 +557,20 @@
ARM_DOT((uchar4)(left1.s7, middle1.s7, right1.s7, left2.s7), (uchar4)(w0.s0, w0.s1, w0.s2, w1.s0), values1.s7);
ARM_DOT((uchar4)(middle2.s7, right2.s7, left3.s7, middle3.s7), (uchar4)(w1.s1, w1.s2, w2.s0, w2.s1), values1.s7);
values1.s7 += right3.s7 * w2.s2;
-#endif // CONV_STRIDE_Y == 1
+#endif // CONV_STRIDE_Y == 1 && DILATION_Y==1
#if defined(HAS_BIAS)
values0 += (int8)(bias_value);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += (int8)(bias_value);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1 */
#endif //defined(HAS_BIAS)
#if WEIGHTS_OFFSET != 0
values0 += sum0 * (int8)(WEIGHTS_OFFSET);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += sum1 * (int8)(WEIGHTS_OFFSET);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1 */
#endif /* WEIGHTS_OFFSET != 0 */
#if INPUT_OFFSET != 0
@@ -499,16 +578,16 @@
ushort3 tmp_we = convert_ushort3(w0) + convert_ushort3(w1) + convert_ushort3(w2);
sum_weights += tmp_we.s0 + tmp_we.s1 + tmp_we.s2;
values0 += sum_weights * (int8)(INPUT_OFFSET);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += sum_weights * (int8)(INPUT_OFFSET);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1*/
#endif /* INPUT_OFFSET != 0 */
#if K_OFFSET != 0
values0 += (int8)(K_OFFSET);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
values1 += (int8)(K_OFFSET);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1*/
#endif /* K_OFFSET != 0 */
#if defined(REAL_MULTIPLIER)
@@ -527,7 +606,7 @@
res0 = min(res0, (uchar8)255);
vstore8(ACTIVATION_FUNC(res0), 0, dst.ptr);
-#if CONV_STRIDE_Y == 1
+#if CONV_STRIDE_Y == 1 && DILATION_Y == 1
#if defined(REAL_MULTIPLIER)
@@ -545,7 +624,7 @@
res1 = min(res1, (uchar8)255);
vstore8(ACTIVATION_FUNC(res1), 0, dst.ptr + dst_stride_y);
-#endif /* CONV_STRIDE_Y == 1 */
+#endif /* CONV_STRIDE_Y == 1 && DILATION_Y==1*/
}
#endif // defined(ARM_COMPUTE_OPENCL_DOT8_ENABLED) && defined(cl_arm_integer_dot_product_int8)
@@ -669,7 +748,7 @@
int z_coord = 0;
int4 offset = 0;
- int4 y_coord = ((int4)(y * CONV_STRIDE_X) + (int4)(0, 1, 2, 3)) - (int)CONV_PAD_LEFT;
+ int4 y_coord = ((int4)(y * CONV_STRIDE_X) + (int4)(0, DILATION_X * 1, DILATION_X * 2, DILATION_X * 3)) - (int)CONV_PAD_LEFT;
// Only for y = 0 we can have a negative coordinate. If so, we convert it to SRC_DIM_1
y_coord.s0 = min((uint)y_coord.s0, (uint)SRC_DIM_1);
@@ -720,16 +799,16 @@
// z == 1
// z_coord can be only negative for z = 0 so we do not need to clamp it
// Moreover z_coord cannot be out-of-bound for z = 1 so we do not need to clamp the offset
- z_coord = z * (int)CONV_STRIDE_Y - (int)CONV_PAD_TOP + 1;
+ z_coord = z * (int)CONV_STRIDE_Y - (int)CONV_PAD_TOP + DILATION_Y;
offset = y_offset + (int4)(z_coord * src_stride_z);
VEC_UCHAR values3 = VLOAD(VEC_SIZE)(0, src_addr + offset.s0);
VEC_UCHAR values4 = VLOAD(VEC_SIZE)(0, src_addr + offset.s1);
VEC_UCHAR values5 = VLOAD(VEC_SIZE)(0, src_addr + offset.s2);
// z == 2
- // After z = 1 we can simply add src_stride_z to offset without updating z_coord
- // However offset can be out-of-bound so we need to check if it is greater than max_offset
- offset += (int4)src_stride_z;
+ // Offset can be out-of-bound so we need to check if it is greater than max_offset
+ z_coord = z * (int)CONV_STRIDE_Y - (int)CONV_PAD_TOP + DILATION_Y * 2;
+ offset = y_offset + (int4)(z_coord * src_stride_z);
offset = min(offset, (int4)max_offset);
VEC_UCHAR values6 = VLOAD(VEC_SIZE)(0, src_addr + offset.s0);
VEC_UCHAR values7 = VLOAD(VEC_SIZE)(0, src_addr + offset.s1);
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp
index 83fac16..ec27e41 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NCHWKernel.cpp
@@ -43,7 +43,7 @@
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier,
- const ActivationLayerInfo &act_info)
+ const ActivationLayerInfo &act_info, const Size2D dilation)
{
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
@@ -56,6 +56,8 @@
ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(0) != 3 || weights->dimension(1) != 3);
ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1 || conv_info.stride().first > 3);
+ ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || (dilation.y() < 1));
+
const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
if(biases != nullptr)
@@ -74,7 +76,7 @@
if(output->total_size() != 0)
{
- const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier);
+ const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
}
@@ -82,10 +84,10 @@
}
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier,
- GPUTarget gpu_target, std::string &kernel_name)
+ GPUTarget gpu_target, std::string &kernel_name, const Size2D dilation)
{
// Output auto inizialitation if not yet initialized
- const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier);
+ const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation);
auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape));
const unsigned int conv_stride_x = conv_info.stride().first;
@@ -176,10 +178,12 @@
kernel_name += (is_qasymm ? "_nchw" : "");
num_elems_written_per_iteration_x = 8 / data_size_from_type(input->data_type());
- num_elems_written_per_iteration_y = (is_qasymm && conv_stride_y == 1) ? 2 : 1;
+ num_elems_written_per_iteration_y = (is_qasymm && conv_stride_y == 1 && dilation.y() == 1) ? 2 : 1;
num_elems_read_per_iteration_x = 3 + (num_elems_written_per_iteration_x - 1) * conv_stride_x;
num_elems_read_per_iteration_y = num_elems_written_per_iteration_y + 2;
}
+ num_elems_read_per_iteration_x += (num_elems_read_per_iteration_x - 1) * (dilation.x() - 1);
+ num_elems_read_per_iteration_y += (num_elems_read_per_iteration_y - 1) * (dilation.y() - 1);
// Create window and update padding
Window win = calculate_max_window(*output, Steps(num_elems_written_per_iteration_x, num_elems_written_per_iteration_y));
@@ -210,10 +214,10 @@
}
void CLDepthwiseConvolutionLayer3x3NCHWKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier, ActivationLayerInfo act_info)
+ unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info, dilation));
bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type());
@@ -231,7 +235,7 @@
std::string kernel_name;
const GPUTarget gpu_target = get_target();
- auto win_config = validate_and_configure_window(input->info(), weights->info(), output->info(), conv_info, depth_multiplier, gpu_target, kernel_name);
+ auto win_config = validate_and_configure_window(input->info(), weights->info(), output->info(), conv_info, depth_multiplier, gpu_target, kernel_name, dilation);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
@@ -240,6 +244,8 @@
build_opts.add_option("-DDST_CHANNELS=" + support::cpp11::to_string(_output->info()->tensor_shape().z()));
build_opts.add_option("-DDEPTH_MULTIPLIER=" + support::cpp11::to_string(depth_multiplier));
build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(_conv_stride_x));
+ build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x()));
+ build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y()));
build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS");
if(is_qasymm)
@@ -292,12 +298,11 @@
}
Status CLDepthwiseConvolutionLayer3x3NCHWKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier,
- ActivationLayerInfo act_info, GPUTarget gpu_target)
+ unsigned int depth_multiplier, ActivationLayerInfo act_info, GPUTarget gpu_target, const Size2D &dilation)
{
std::string kernel_name;
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info));
- ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), output->clone().get(), conv_info, depth_multiplier, gpu_target, kernel_name).first);
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(), output->clone().get(), conv_info, depth_multiplier, gpu_target, kernel_name, dilation).first);
return Status{};
}
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
index 431039c..86d186b 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
@@ -42,7 +42,7 @@
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier,
- const ActivationLayerInfo &act_info)
+ const ActivationLayerInfo &act_info, const Size2D &dilation)
{
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32, DataType::QASYMM8);
@@ -57,6 +57,8 @@
ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1);
ARM_COMPUTE_RETURN_ERROR_ON(std::max(conv_info.pad_top(), conv_info.pad_bottom()) > 1);
+ ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || (dilation.y() < 1));
+
const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
const size_t weights_width = 3;
const size_t weights_height = 3;
@@ -89,7 +91,8 @@
if(output->total_size() != 0)
{
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, weights_width, weights_height, conv_info, depth_multiplier);
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(
+ *input, TensorInfo(TensorShape(weights_width, weights_height), 1, weights->data_type()).set_data_layout(DataLayout::NCHW), conv_info, depth_multiplier, dilation);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
}
@@ -97,13 +100,14 @@
}
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output,
- const PadStrideInfo &conv_info, unsigned int depth_multiplier)
+ const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
{
const size_t weights_width = 3;
const size_t weights_height = 3;
// Get convolved dimensions
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, weights_width, weights_height, conv_info, depth_multiplier);
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(
+ *input, TensorInfo(TensorShape(weights_width, weights_height), 1, weights->data_type()).set_data_layout(DataLayout::NCHW), conv_info, depth_multiplier, dilation);
// Output auto inizialitation if not yet initialized
auto_init_if_empty(*output,
@@ -112,10 +116,10 @@
input->data_type(),
input->quantization_info());
- const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
- const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1));
+ const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
+ const bool is_stride_1_dilation_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1) && dilation.x() == 1 && dilation.y() == 1);
- const unsigned int num_rows_processed_per_iteration = is_stride_1 ? 2 : 1;
+ const unsigned int num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1;
const unsigned int num_elems_accessed_per_iteration = is_qasymm ? 4 : (8 / input->element_size());
const unsigned int num_rows_read_per_iteration = num_rows_processed_per_iteration + 2;
const unsigned int num_rows_written_per_iteration = std::ceil(num_rows_processed_per_iteration / static_cast<float>(conv_info.stride().first));
@@ -166,15 +170,17 @@
}
void CLDepthwiseConvolutionLayer3x3NHWCKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier, ActivationLayerInfo act_info)
+ unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info));
- auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier);
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info, dilation));
+ auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, dilation);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
- const bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type());
- const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1));
+ const bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type());
+ const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1));
+ const bool is_stride_1_dilation_1 = (is_stride_1 && dilation.x() == 1 && dilation.y() == 1);
+
const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device());
_input = input;
@@ -182,8 +188,8 @@
_weights = weights;
_biases = biases;
_conv_stride_y = conv_info.stride().second;
- _num_rows_processed_per_iteration = is_stride_1 ? 2 : 1;
- _num_planes_processed_per_iteration = is_stride_1 ? 2 : 1;
+ _num_rows_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1;
+ _num_planes_processed_per_iteration = is_stride_1_dilation_1 ? 2 : 1;
// If QASYMM8 and the 8 bit dot product is available, force _num_planes_processed_per_iteration to 1
if(is_dot8_supported && is_qasymm)
@@ -201,6 +207,8 @@
build_opts.add_option("-DSRC_DIM_2=" + support::cpp11::to_string(_input->info()->dimension(2)));
build_opts.add_option("-DCONV_PAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
build_opts.add_option("-DCONV_PAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()));
+ build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x()));
+ build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y()));
if(is_qasymm)
{
@@ -238,7 +246,7 @@
build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(_input->info()->data_type()));
}
- if(is_stride_1)
+ if(is_stride_1_dilation_1)
{
build_opts.add_option("-DNUM_ROWS_PROCESSED=" + support::cpp11::to_string(_num_rows_processed_per_iteration));
build_opts.add_option("-DNUM_PLANES_PROCESSED=" + support::cpp11::to_string(_num_planes_processed_per_iteration));
@@ -257,14 +265,14 @@
if(is_qasymm)
{
kernel_name = std::string("dwc_3x3_reshaped_qasymm8");
- kernel_name += (is_dot8_supported && is_stride_1 ? "_dot8" : "");
- kernel_name += (is_stride_1 ? "_stride1" : "");
+ kernel_name += (is_dot8_supported && is_stride_1_dilation_1 ? "_dot8" : "");
+ kernel_name += (is_stride_1_dilation_1 ? "_stride1" : "");
kernel_name += "_nhwc";
}
else
{
kernel_name = std::string("depthwise_convolution_3x3_nhwc");
- kernel_name += (is_stride_1 ? "_stride1" : "");
+ kernel_name += (is_stride_1_dilation_1 ? "_stride1" : "");
}
ICLKernel::configure_internal(win_config.second);
@@ -287,13 +295,12 @@
}
Status CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
- unsigned int depth_multiplier,
- ActivationLayerInfo act_info)
+ unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation)
{
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(),
biases != nullptr ? biases->clone().get() : nullptr,
- output->clone().get(), conv_info, depth_multiplier)
+ output->clone().get(), conv_info, depth_multiplier, dilation)
.first);
return Status{};
diff --git a/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp b/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp
index beff7ae..28d4ff2 100644
--- a/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp
@@ -44,7 +44,8 @@
namespace
{
-Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier)
+Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier,
+ const Size2D &dilation)
{
const size_t idx_c = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL);
@@ -55,16 +56,18 @@
ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_asymmetric(input->data_type()) && has_bias);
ARM_COMPUTE_RETURN_ERROR_ON((input->dimension(idx_c) * depth_multiplier) != output->dimension(2));
ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) != (kernel_dims.width * kernel_dims.height + ((has_bias) ? 1 : 0)));
+ ARM_COMPUTE_RETURN_ERROR_ON((dilation.x() < 1) || dilation.y() < 1);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output);
return Status{};
}
} // namespace
-void CLDepthwiseIm2ColKernel::configure(const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier)
+void CLDepthwiseIm2ColKernel::configure(const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier,
+ const Size2D &dilation)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), kernel_dims, conv_info, has_bias, depth_multiplier));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), kernel_dims, conv_info, has_bias, depth_multiplier, dilation));
_input = input;
_output = output;
@@ -88,6 +91,8 @@
build_opts.add_option("-DKERNEL_WIDTH=" + support::cpp11::to_string(kernel_dims.width));
build_opts.add_option("-DKERNEL_HEIGHT=" + support::cpp11::to_string(kernel_dims.height));
build_opts.add_option("-DDEPTH_MULTIPLIER=" + support::cpp11::to_string(depth_multiplier));
+ build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x()));
+ build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y()));
build_opts.add_option("-D" + string_from_data_layout(input->info()->data_layout()));
build_opts.add_option_if(has_bias, "-DHAS_BIAS");
build_opts.add_option_if_else(is_data_type_quantized_asymmetric(input->info()->data_type()),
@@ -104,9 +109,10 @@
ICLKernel::configure_internal(win);
}
-Status CLDepthwiseIm2ColKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier)
+Status CLDepthwiseIm2ColKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias, unsigned int depth_multiplier,
+ const Size2D &dilation)
{
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, kernel_dims, conv_info, has_bias, depth_multiplier));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, kernel_dims, conv_info, has_bias, depth_multiplier, dilation));
return Status{};
}