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* initial commit Signed-off-by: raver119 <raver119@gmail.com> * - gruCell_bp further Signed-off-by: Yurii <yurii@skymind.io> * - further work on gruCell_bp Signed-off-by: Yurii <yurii@skymind.io> * Inverse matrix cublas implementation. Partial working revision. * Separation of segment ops helpers. Max separation. * Separated segment_min ops. * Separation of segment_mean/sum/prod/sqrtN ops heleprs. * Fixed diagonal processing with LUP decomposition. * Modified inversion approach using current state of LU decomposition. * Implementation of matrix_inverse op with cuda kernels. Working revision. * Implemented sequence_mask cuda helper. Eliminated waste printf with matrix_inverse implementation. Added proper tests. * - further work on gruCell_bp (ff/cuda) Signed-off-by: Yurii <yurii@skymind.io> * comment one test for gruCell_bp Signed-off-by: Yurii <yurii@skymind.io> * - provide cuda static_rnn Signed-off-by: Yurii <yurii@skymind.io> * Refactored random_shuffle op to use new random generator. * Refactored random_shuffle op helper. * Fixed debug tests with random ops tests. * Implement random_shuffle op cuda kernel helper and tests. * - provide cuda scatter_update Signed-off-by: Yurii <yurii@skymind.io> * Implementation of random_shuffle for linear case with cuda kernels and tests. * Implemented random_shuffle with cuda kernels. Final revision. * - finally gruCell_bp is completed Signed-off-by: Yurii <yurii@skymind.io> * Dropout op cuda helper implementation. * Implemented dropout_bp cuda helper. * Implemented alpha_dropout_bp with cuda kernel helpers. * Refactored helper. * Implementation of suppresion helper with cuda kernels. * - provide cpu code fot hsvToRgb, rgbToHsv, adjustHue Signed-off-by: Yurii <yurii@skymind.io> * Using sort by value method. * Implementation of image.non_max_suppression op cuda-based helper. * - correcting and testing adjust_hue, adjust_saturation cpu/cuda code Signed-off-by: Yurii <yurii@skymind.io> * Added cuda device prefixes to declarations. * Implementation of hashcode op with cuda helper. Initital revision. * rnn cu impl removed Signed-off-by: raver119 <raver119@gmail.com>
71 lines
2.2 KiB
C++
71 lines
2.2 KiB
C++
/*******************************************************************************
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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 raver119@gmail.com
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//
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#ifndef DEV_TESTS_HASHCODE_H
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#define DEV_TESTS_HASHCODE_H
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#include "helpers.h"
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namespace nd4j {
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namespace ops {
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namespace helpers {
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template <typename T>
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FORCEINLINE _CUDA_HD Nd4jLong longBytes(T value);
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template <>
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FORCEINLINE _CUDA_HD Nd4jLong longBytes(float value) {
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int intie = *(int *)&value;
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return static_cast<Nd4jLong>(intie);
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}
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template <>
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FORCEINLINE _CUDA_HD Nd4jLong longBytes(double value) {
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Nd4jLong longie = *(Nd4jLong *)&value;
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return longie;
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}
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template <>
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FORCEINLINE _CUDA_HD Nd4jLong longBytes(float16 value) {
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return longBytes<float>((float) value);
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}
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template <>
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FORCEINLINE _CUDA_HD Nd4jLong longBytes(Nd4jLong value) {
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return value;
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}
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template <>
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FORCEINLINE _CUDA_HD Nd4jLong longBytes(bfloat16 value) {
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return longBytes<float>((float) value);
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}
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template <typename T>
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FORCEINLINE _CUDA_HD Nd4jLong longBytes(T value) {
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return longBytes<Nd4jLong>((Nd4jLong) value);
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}
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void hashCode(LaunchContext *context, NDArray &array, NDArray &result);
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}
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}
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}
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#endif //DEV_TESTS_HASHCODE_H
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