117 lines
5.7 KiB
Plaintext
117 lines
5.7 KiB
Plaintext
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author George A. Shulinok <sgazeos@gmail.com>
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//
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#include <ops/declarable/helpers/matrix_band.h>
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#include <helpers/TAD.h>
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#include <exceptions/cuda_exception.h>
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#include <helpers/ShapeUtils.h>
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#include <helpers/ConstantTadHelper.h>
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namespace sd {
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namespace ops {
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namespace helpers {
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////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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// matrix band kernel
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//
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// inputBuffer - buffer of input tensor
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// inputShape - shape of input tensor
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// outputBuffer - buffer of output tensor
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// outputShape - shape of output tensor
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// lowerBand - lower band of matrix
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// upperBand - upper band of matrix
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// tadOnlyInputShapeInfo - TAD shape for input
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// tadInputOffsets - TAD offsets for input
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// tadOnlyOutputShapeInfo - TAD output shape
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// tadOutputOffsets - TAD output offsets
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// numTads - number of subarrays
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// inputLength - input subarray length
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//
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template <typename T>
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static __global__ void matrixBandKernel(const void* inputBuffer, const Nd4jLong* inputShape,
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void* outputBuffer, const Nd4jLong* outputShape,
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Nd4jLong lowerBand, Nd4jLong upperBand,
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const Nd4jLong* tadOnlyInputShapeInfo, const Nd4jLong* tadInputOffsets,
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const Nd4jLong* tadOnlyOutputShapeInfo, const Nd4jLong* tadOutputOffsets,
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Nd4jLong numTads,
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Nd4jLong inputLength) {
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int totalThreads = blockDim.x;
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Nd4jLong rows = shape::sizeAt(inputShape, -2);
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Nd4jLong cols = shape::sizeAt(inputShape, -1);
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for (Nd4jLong e = blockIdx.x; e < numTads; e += gridDim.x) {
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auto yOffset = tadInputOffsets[e];
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auto xOffset = tadOutputOffsets[e];
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for (Nd4jLong i = blockIdx.y; i < rows; i += gridDim.y) {
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for (Nd4jLong j = threadIdx.x; j < cols; j += totalThreads) {
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Nd4jLong coords[2] = {i, j};
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Nd4jLong tadOffsetOut = shape::getOffset(tadOnlyOutputShapeInfo, coords);
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Nd4jLong tadOffsetIn = shape::getOffset(tadOnlyInputShapeInfo, coords);
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if (i >= j) { // check lower diagonals
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if (lowerBand > 0) {
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if ((i - j) > lowerBand)
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*(reinterpret_cast<T *>(outputBuffer) + xOffset + tadOffsetOut) = T(0);
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else
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*(reinterpret_cast<T *>(outputBuffer) + xOffset + tadOffsetOut) = *(
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reinterpret_cast<T const *>(inputBuffer) + yOffset + tadOffsetIn);
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}
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} else if (j > i) {
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if (upperBand > 0)
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if ((j - i) > upperBand)
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*(reinterpret_cast<T *>(outputBuffer) + xOffset + tadOffsetOut) = T(0);
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else
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*(reinterpret_cast<T *>(outputBuffer) + xOffset + tadOffsetOut) = *(
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reinterpret_cast<T const *>(inputBuffer) + yOffset + tadOffsetIn);
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}
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}
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}
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}
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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// matrixBandPart_ - main algorithm caller
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//
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template <typename T>
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void matrixBandPart_(sd::LaunchContext * context, NDArray* input, NDArray* output, Nd4jLong lowerBand, Nd4jLong upperBand) {
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dim3 launchDims(256, 512, 8192);
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auto stream = context->getCudaStream();
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std::vector<int> lastDims({input->rankOf() - 2, input->rankOf() - 1});
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std::vector<int> dimsToExclude = ShapeUtils::evalDimsToExclude(input->rankOf(), lastDims);
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auto packX = sd::ConstantTadHelper::getInstance().tadForDimensions(input->shapeInfo(), lastDims);
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auto packZ = sd::ConstantTadHelper::getInstance().tadForDimensions(output->shapeInfo(), lastDims);
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const Nd4jLong numTads = packX.numberOfTads();
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NDArray::prepareSpecialUse({output}, {input});
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matrixBandKernel<T><<<launchDims.x, launchDims.y, launchDims.z, *stream>>>(input->specialBuffer(),
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input->specialShapeInfo(), output->specialBuffer(), output->specialShapeInfo(),
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lowerBand, upperBand, packX.specialShapeInfo(), packX.specialOffsets(), packZ.specialShapeInfo(), packZ.specialOffsets(), numTads, input->lengthOf());
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NDArray::registerSpecialUse({output}, {input});
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
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void matrixBandPart(sd::LaunchContext * context, NDArray* input, NDArray* output, Nd4jLong lowerBand, Nd4jLong upperBand) {
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BUILD_SINGLE_SELECTOR(input->dataType(), matrixBandPart_, (context, input, output, lowerBand, upperBand), FLOAT_TYPES);
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}
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}
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}
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}
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