From 172e57028ef14f2f8d6c56edc53c5c85f97e07cd Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Mon, 26 Jun 2017 14:18:47 +0100 Subject: COMPMID-425 Port CLBatchnormalization to support QS8/QS16 Change-Id: I46c93305f377666ea0915ff789b7dfdfff596087 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/78862 Reviewed-by: Anthony Barbier Tested-by: Kaizen --- src/core/CL/cl_kernels/batchnormalization_layer.cl | 69 +++++++++++++++------- src/core/CL/cl_kernels/fixed_point.h | 12 ++++ .../CL/kernels/CLBatchNormalizationLayerKernel.cpp | 25 +++++--- 3 files changed, 76 insertions(+), 30 deletions(-) (limited to 'src') diff --git a/src/core/CL/cl_kernels/batchnormalization_layer.cl b/src/core/CL/cl_kernels/batchnormalization_layer.cl index 13e6702334..cb4d0c8947 100644 --- a/src/core/CL/cl_kernels/batchnormalization_layer.cl +++ b/src/core/CL/cl_kernels/batchnormalization_layer.cl @@ -21,11 +21,31 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ + #include "helpers.h" +#if defined(FIXED_POINT_POSITION) +#include "fixed_point.h" + +#define ADD_OP(a, b) ADD_SAT_OP_EXPAND((a), (b), DATA_TYPE, VEC_SIZE) +#define SUB_OP(a, b) SUB_SAT_OP_EXPAND((a), (b), DATA_TYPE, VEC_SIZE) +#define MUL_OP(a, b) MUL_SAT_OP_EXPAND((a), (b), DATA_TYPE, VEC_SIZE, FIXED_POINT_POSITION) +#define INVSQRT_OP(a) INVSQRT_OP_EXPAND((a), DATA_TYPE, VEC_SIZE, FIXED_POINT_POSITION) +#define SQCVT_SAT(a) SQCVT_SAT_OP_EXPAND((a), DATA_TYPE, FIXED_POINT_POSITION) + +#else /* FIXED_POINT_POSITION */ + +#define ADD_OP(a, b) ((a) + (b)) +#define SUB_OP(a, b) ((a) - (b)) +#define MUL_OP(a, b) ((a) * (b)) +#define INVSQRT_OP(a) rsqrt((a)) +#define SQCVT_SAT(a) (a) + +#endif /* FIXED_POINT_POSITION */ + /** Apply batch normalization. * - * @param[in] input_ptr Pointer to the first source tensor. Supported data types: F32 + * @param[in] input_ptr Pointer to the first source tensor. Supported data types: QS8/QS16/F32 * @param[in] input_stride_x Stride of the first source tensor in X dimension (in bytes) * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] input_stride_y Stride of the first source tensor in Y dimension (in bytes) @@ -33,7 +53,7 @@ * @param[in] input_stride_z Stride of the first source tensor in Z dimension (in bytes) * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source tensor - * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F32 + * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr * @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) @@ -41,19 +61,19 @@ * @param[in] output_stride_z Stride of the destination tensor in Z dimension (in bytes) * @param[in] output_step_z output_stride_z * number of elements along Z 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] mean_ptr Pointer to the mean source tensor. Supported data types: F32 + * @param[in] mean_ptr Pointer to the mean source tensor. Supported data types: same as @p input_ptr * @param[in] mean_stride_x Stride of the mean source tensor in X dimension (in bytes) * @param[in] mean_step_x mean_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] mean_offset_first_element_in_bytes The offset of the first element in the mean source tensor - * @param[in] var_ptr Pointer to the var tensor. Supported data types: F32 + * @param[in] var_ptr Pointer to the var tensor. Supported data types: same as @p input_ptr * @param[in] var_stride_x Stride of the var tensor in X dimension (in bytes) * @param[in] var_step_x var_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] var_offset_first_element_in_bytes The offset of the first element in the var source tensor - * @param[in] beta_ptr Pointer to the beta source tensor. Supported data types: F32 + * @param[in] beta_ptr Pointer to the beta source tensor. Supported data types: same as @p input_ptr * @param[in] beta_stride_x Stride of the beta source tensor in X dimension (in bytes) * @param[in] beta_step_x beta_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] beta_offset_first_element_in_bytes The offset of the first element in the beta source tensor - * @param[in] gamma_ptr Pointer to the gamma source tensor. Supported data types: F32 + * @param[in] gamma_ptr Pointer to the gamma source tensor. Supported data types: same as @p input_ptr * @param[in] gamma_stride_x Stride of the gamma source tensor in X dimension (in bytes) * @param[in] gamma_step_x gamma_stride_x * number of elements along X processed per workitem(in bytes) * @param[in] gamma_offset_first_element_in_bytes The offset of the first element in the gamma source tensor @@ -74,26 +94,33 @@ __kernel void batchnormalization_layer(TENSOR3D_DECLARATION(input), Vector beta = CONVERT_TO_VECTOR_STRUCT(beta); Vector gamma = CONVERT_TO_VECTOR_STRUCT(gamma); - float4 _in = 0; - float4 denominator = 0; - float4 numerator = 0; - float4 x_bar = 0; - float4 gamma_vec = 0; - float4 beta_vec = 0; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + _in = 0; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + denominator = 0; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + numerator = 0; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + x_bar = 0; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + gamma_vec = 0; + VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE) + beta_vec = 0; const int current_slice = get_global_id(2); - _in = vload4(0, (__global float *)in.ptr); - denominator = *((__global float *)(var.ptr + current_slice * var.stride_x)); - denominator = rsqrt(denominator + epsilon); + _in = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)in.ptr); + denominator = *((__global DATA_TYPE *)(var.ptr + current_slice * var.stride_x)); + denominator = INVSQRT_OP(ADD_OP(denominator, SQCVT_SAT(epsilon))); // Calculate x bar and store results - numerator = *((__global float *)(mean.ptr + current_slice * mean.stride_x)); - numerator = _in - numerator; - x_bar = numerator * denominator; + numerator = *((__global DATA_TYPE *)(mean.ptr + current_slice * mean.stride_x)); + numerator = SUB_OP(_in, numerator); + x_bar = MUL_OP(numerator, denominator); - gamma_vec = *((__global float *)(gamma.ptr + current_slice * beta.stride_x)); - beta_vec = *((__global float *)(beta.ptr + current_slice * beta.stride_x)); + gamma_vec = *((__global DATA_TYPE *)(gamma.ptr + current_slice * beta.stride_x)); + beta_vec = *((__global DATA_TYPE *)(beta.ptr + current_slice * beta.stride_x)); - vstore4(gamma_vec * x_bar + beta_vec, 0, (__global float *)out.ptr); + VSTORE(VEC_SIZE) + (ADD_OP(MUL_OP(gamma_vec, x_bar), beta_vec), 0, (__global DATA_TYPE *)out.ptr); } diff --git a/src/core/CL/cl_kernels/fixed_point.h b/src/core/CL/cl_kernels/fixed_point.h index bb534f5a51..4de7fc576b 100644 --- a/src/core/CL/cl_kernels/fixed_point.h +++ b/src/core/CL/cl_kernels/fixed_point.h @@ -471,4 +471,16 @@ CONVERTQ_DOWN_SAT_IMPL(float16, qs16x16) CONVERTQ_UP_IMPL(qs8x16, float16) CONVERTQ_UP_IMPL(qs16x16, float16) +#define SQCVT_SAT_IMPL(type) \ + inline type sqcvt_##type##_sat(float a, int fixed_point_position) \ + { \ + return CONVERT_SAT((a * (1 << fixed_point_position) + ((a < 0) ? -0.5f : 0.5f)), type); \ + } + +SQCVT_SAT_IMPL(qs8) +SQCVT_SAT_IMPL(qs16) + +#define SQCVT_SAT_OP_EXPAND_STR(a, type, position) sqcvt_##type##_sat((a), (position)) +#define SQCVT_SAT_OP_EXPAND(a, type, position) SQCVT_SAT_OP_EXPAND_STR((a), type, position) + #endif // ARM_COMPUTE_FIXED_POINT_H diff --git a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp index 85d8ab7cb4..02bf35a860 100644 --- a/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp +++ b/src/core/CL/kernels/CLBatchNormalizationLayerKernel.cpp @@ -26,12 +26,15 @@ #include "arm_compute/core/CL/CLHelpers.h" #include "arm_compute/core/CL/CLKernelLibrary.h" #include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/FixedPoint.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" +#include "support/ToolchainSupport.h" + using namespace arm_compute; CLBatchNormalizationLayerKernel::CLBatchNormalizationLayerKernel() @@ -42,7 +45,7 @@ CLBatchNormalizationLayerKernel::CLBatchNormalizationLayerKernel() void CLBatchNormalizationLayerKernel::configure(const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon) { - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F32); ARM_COMPUTE_ERROR_ON_NULLPTR(output); // Output tensor auto initialization if not yet initialized @@ -54,10 +57,6 @@ void CLBatchNormalizationLayerKernel::configure(const ICLTensor *input, ICLTenso ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(mean, var, beta, gamma); ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) != mean->info()->dimension(0)); - // Set build options - std::set build_opts; - build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()))); - _input = input; _output = output; _mean = mean; @@ -66,17 +65,25 @@ void CLBatchNormalizationLayerKernel::configure(const ICLTensor *input, ICLTenso _gamma = gamma; _epsilon = epsilon; + const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); + + // Set build options + std::set build_opts; + build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()))); + build_opts.emplace(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration))); + if(is_data_type_fixed_point(input->info()->data_type())) + { + build_opts.emplace("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position())); + } + // Create kernel - std::string kernel_name = "batchnormalization_layer"; - _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts)); + _kernel = static_cast(CLKernelLibrary::get().create_kernel("batchnormalization_layer", build_opts)); // Set kernel static arguments unsigned int idx = 2 * num_arguments_per_3D_tensor() + 4 * num_arguments_per_1D_tensor(); // Skip the input and output parameters _kernel.setArg(idx++, _epsilon); // Configure kernel window - const unsigned int num_elems_processed_per_iteration = 4; - Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); -- cgit v1.2.1