wehub-resource-sync
150 lines
4.9 KiB
C++
150 lines
4.9 KiB
C++
/* ******************************************************************************
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*
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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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* See the NOTICE file distributed with this work for additional
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* information regarding copyright ownership.
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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 raver119@gmail.com
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//
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#include <system/op_boilerplate.h>
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#if NOT_EXCLUDED(OP_cumsum)
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#include <ops/declarable/CustomOperations.h>
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#include <ops/declarable/helpers/prefix.h>
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namespace sd {
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namespace ops {
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CONFIGURABLE_OP_IMPL(cumsum, 1, 1, true, 0, 2) {
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auto input = INPUT_VARIABLE(0);
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auto output = OUTPUT_VARIABLE(0);
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const bool exclusive = INT_ARG(0) == 1;
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const bool reverse = INT_ARG(1) == 1;
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REQUIRE_TRUE(input->dataType() == output->dataType(), 0, "CumSum: input and output data types must be equal");
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if (input->isEmpty()) {
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// No-op
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return sd::Status::OK;
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}
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if (block.getIArguments()->size() == 2 && block.width() == 1) {
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// all at once case
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sd::ops::helpers::prefix(block.launchContext(), scalar::Add, input, output, exclusive, reverse);
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} else {
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std::vector<sd::LongType> dims(block.numI() - 2);
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if (block.width() == 1) {
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for (size_t e = 0; e < block.numI() - 2; e++) dims[e] = INT_ARG(e + 2);
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} else {
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auto ax = INPUT_VARIABLE(1);
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dims = ax->template asVectorT<sd::LongType>();
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}
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for (size_t e = 0; e < dims.size(); e++)
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if (dims[e] < 0) dims[e] += input->rankOf();
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sd::ops::helpers::prefix(block.launchContext(), scalar::Add, input, output, dims, exclusive, reverse);
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}
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return sd::Status::OK;
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}
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DECLARE_TYPES(cumsum) {
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getOpDescriptor()
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->setAllowedInputTypes(0, {ALL_FLOATS, ALL_INTS})
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->setAllowedInputTypes(1, {ALL_FLOATS,ALL_INTS})
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->setAllowedOutputTypes({ALL_FLOATS})
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->setSameMode(false);
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}
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CUSTOM_OP_IMPL(cumsum_bp, 2, -1, true, 0, 2) {
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auto input = INPUT_VARIABLE(0);
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auto axis = block.width() == 3 ? INPUT_VARIABLE(1) : nullptr;
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auto gradOut = block.width() == 3 ? INPUT_VARIABLE(2) : INPUT_VARIABLE(1);
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auto output = OUTPUT_VARIABLE(0);
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const bool exclusive = INT_ARG(0) == 1;
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const bool reverse = INT_ARG(1) == 1;
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std::vector<sd::LongType> dims;
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if (block.width() > 2) {
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dims = axis->template asVectorT<sd::LongType>();
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float one = 1.f;
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OUTPUT_VARIABLE(1)->assign(one);
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} else if (int newSize = (block.numI() - 2)) {
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dims.resize(newSize);
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for (int e = 0; e < newSize; e++) dims[e] = INT_ARG(e + 2);
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}
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if (!exclusive && !reverse) {
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if (dims.size())
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sd::ops::helpers::prefix(block.launchContext(), scalar::Add, gradOut, output, dims, false, true);
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else
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sd::ops::helpers::prefix(block.launchContext(), scalar::Add, gradOut, output, false, true);
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} else if (!exclusive && reverse) {
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if (dims.size())
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sd::ops::helpers::prefix(block.launchContext(), scalar::Add, gradOut, output, dims, false, false);
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else
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sd::ops::helpers::prefix(block.launchContext(), scalar::Add, gradOut, output, false, false);
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} else if (exclusive && !reverse) {
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if (dims.size())
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sd::ops::helpers::prefix(block.launchContext(), scalar::Add, gradOut, output, dims, true, true);
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else
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sd::ops::helpers::prefix(block.launchContext(), scalar::Add, gradOut, output, true, true);
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} else {
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if (dims.size())
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sd::ops::helpers::prefix(block.launchContext(), scalar::Add, gradOut, output, dims, true, false);
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else
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sd::ops::helpers::prefix(block.launchContext(), scalar::Add, gradOut, output, true, false);
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}
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return sd::Status::OK;
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}
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DECLARE_TYPES(cumsum_bp) {
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getOpDescriptor()->setAllowedInputTypes(0, {ALL_FLOATS, ALL_INTS});
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getOpDescriptor()->setAllowedInputTypes(1, {ALL_FLOATS, ALL_INTS}); // axes can be set as the second param
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getOpDescriptor()->setAllowedInputTypes(2, {ALL_FLOATS});
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getOpDescriptor()->setAllowedOutputTypes(0, {ALL_FLOATS});
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}
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DECLARE_SHAPE_FN(cumsum_bp) {
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auto inp = inputShape->at(0);
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sd::LongType *newShapeX = nullptr;
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COPY_SHAPE(inp, newShapeX);
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if (block.width() == 2) {
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auto result = CONSTANT(newShapeX);
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delete[] newShapeX;
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return SHAPELIST(result);
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} else {
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sd::LongType *newShapeA = nullptr;
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COPY_SHAPE(inputShape->at(1), newShapeA);
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auto resultX = CONSTANT(newShapeX);
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auto resultA = CONSTANT(newShapeA);
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delete[] newShapeX;
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delete[] newShapeA;
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return SHAPELIST(resultX, resultA);
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}
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}
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} // namespace ops
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} // namespace sd
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#endif
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