cavis/libnd4j/include/loops/cuda/transform/transform_any.cu

/* ******************************************************************************
 *
 *
 * This program and the accompanying materials are made available under the
 * terms of the Apache License, Version 2.0 which is available at
 * https://www.apache.org/licenses/LICENSE-2.0.
 *
 *  See the NOTICE file distributed with this work for additional
 *  information regarding copyright ownership.
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
 * License for the specific language governing permissions and limitations
 * under the License.
 *
 * SPDX-License-Identifier: Apache-2.0
 ******************************************************************************/

//
// @author raver119@gmail.com
//

#include <system/Environment.h>
#include <loops/transform_any.h>
#include <types/types.h>
#include <system/op_boilerplate.h>

#include <loops/legacy_ops.h>
#include <helpers/DebugHelper.h>

using namespace simdOps;


template <typename X, typename Z, typename OpType>
__global__ void transformAnySimple(
        const void *x, const Nd4jLong *xShapeInfo, int xRank,
        void *params,
        void *z, const Nd4jLong *zShapeInfo, int zRank,
        int *allocationPointer, void *reductionPointer,
        const Nd4jLong *tadShapeInfo, const Nd4jLong *tadOffsets) {

	functions::transform::TransformAny<X,Z>::template transformCuda<OpType>(x,xShapeInfo,params,z,zShapeInfo,allocationPointer,reductionPointer,tadShapeInfo, tadOffsets);
}


namespace functions {
    namespace transform {

        template<typename X, typename Y>
        _CUDA_H void TransformAny<X,Y>::executeTransformShaped(
                dim3 launchDims, cudaStream_t *stream,
                const int opNum,
                const void *x, const Nd4jLong *xShape, int xRank,
                void *extraParams,
                void *z, const Nd4jLong *zShape, int zRank,
                int *allocationPointer, void *reductionPointer,
                const Nd4jLong *tadShapeInfo, const Nd4jLong *tadOffsets) {
			DISPATCH_BY_OPNUM_TT(intermediateShaped, PARAMS(launchDims, stream, x, xShape, xRank, extraParams, z, zShape, zRank, allocationPointer, reductionPointer, tadShapeInfo, tadOffsets), TRANSFORM_ANY_OPS);

            DEBUG_KERNEL(stream, opNum);
        }


        template<typename X, typename Z>
        template <typename OpType>
        __device__ void TransformAny<X,Z>::transformCuda(
                const void *vx, const Nd4jLong *xShapeInfo,
                void *vparams,
                void *vz, const Nd4jLong *zShapeInfo,
                int *allocationPointer, void *vreductionPointer,
                const Nd4jLong *tadShapeInfo, const Nd4jLong *tadOffsets) {

        	auto x = reinterpret_cast<const X*>(vx);
		    auto z = reinterpret_cast<Z*>(vz);
		    auto params = reinterpret_cast<X*>(vparams);
		    auto reductionPointer = reinterpret_cast<Z*>(vreductionPointer);

		    __shared__ Nd4jLong xEws;
    	    __shared__ Nd4jLong zEws;
        	__shared__ char xOrder;
            __shared__ char zOrder;
            __shared__ Nd4jLong length;

	        if (threadIdx.x == 0) {

        		xEws = shape::elementWiseStride(xShapeInfo);
            	zEws = shape::elementWiseStride(zShapeInfo);
                xOrder = shape::order(xShapeInfo);
				zOrder = shape::order(zShapeInfo);
				length = shape::length(xShapeInfo);
            }
            __syncthreads();

	    	auto tid = blockIdx.x * blockDim.x + threadIdx.x;
			int totalThreads = gridDim.x * blockDim.x;

		    if(xEws > 0 && zEws > 0 && xOrder == zOrder && xOrder == 'c') {

				for (int i = tid; i < length; i += totalThreads)
					z[i * zEws] = OpType::op(x[i * xEws], params);
		    }
		    else {
				if(vx == vz) {
					for (Nd4jLong i = tid; i < length; i+= totalThreads) {
						auto xOffset = shape::getIndexOffset(i, xShapeInfo);
	    		    	z[xOffset] = OpType::op(x[xOffset], params);
		    	   	}
				}
				else {
		    	   	for (Nd4jLong i = tid; i < length; i+= totalThreads) {
						auto xOffset = shape::getIndexOffset(i, xShapeInfo);
						auto zOffset = shape::getIndexOffset(i, zShapeInfo);
	    		    	z[zOffset] = OpType::op(x[xOffset], params);
		    	   	}
		    	}
		    }
	    };


		template<typename X, typename Z>
		template <typename OpType>
		_CUDA_H void TransformAny<X,Z>::intermediateShaped(
		        dim3 launchDims, cudaStream_t *stream,
                const void *x, const Nd4jLong *xShape, int xRank,
                void *extraParams,
                void *z, const Nd4jLong *zShape, int zRank,
                int *allocationPointer, void *reductionPointer,
                const Nd4jLong *tadShapeInfo, const Nd4jLong *tadOffsets) {

			transformAnySimple<X, Z, OpType><<<launchDims.x, launchDims.y, launchDims.z, *stream>>>(x, xShape, xRank, extraParams, z, zShape, zRank, allocationPointer, reductionPointer, tadShapeInfo, tadOffsets);

			sd::DebugHelper::checkErrorCode(stream, "transformAny(...) failed");
		}

        BUILD_DOUBLE_TEMPLATE(template class ND4J_EXPORT TransformAny, , LIBND4J_TYPES, LIBND4J_TYPES);
    }
}