[WIP] HSV,RGB color model conversions (#125)
* CUDA implementation for hsv_to_rgb and rgb_to_hsv Signed-off-by: raver119 <raver119@gmail.com> * hsv_to_rgb and rgb_to_hsv operations Test coverage: c order 1d, 2d, 3d array Signed-off-by: Abdelrauf <rauf@konduit.ai> * Index check Signed-off-by: Abdelrauf <rauf@konduit.ai> * Suppress Msvc floating point errors Signed-off-by: Abdelrauf <rauf@konduit.ai> * Added Index Check for adjust_saturation and adjust_hue Signed-off-by: Abdelrauf <rauf@konduit.ai> * minor fix Signed-off-by: raver119 <raver119@gmail.com> * Fixes missed Msvc floating narrowing errors Signed-off-by: Abdelrauf <rauf@konduit.ai>master
Abdelrauf
raver119
parent
bfd9e3692a
commit
e0a9cb6c08
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@ -12,6 +12,21 @@
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"cmakeCommandArgs": " -DCUDA_BLAS=true -DLIBND4J_NAME=nd4jcuda -DMSVC_DEV=true -DCOMPUTE=61 -DBUILD_TESTS=true",
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"buildCommandArgs": "-v",
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"ctestCommandArgs": ""
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},
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{
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"name": "WSL-GCC-Debug",
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"generator": "Unix Makefiles",
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"configurationType": "Debug",
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"buildRoot": "${projectDir}\\out\\build\\${name}",
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"installRoot": "${projectDir}\\out\\install\\${name}",
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"cmakeExecutable": "/usr/bin/cmake",
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"cmakeCommandArgs": "-DLIBND4J_ALL_OPS=true -DCMAKE_BUILD_TYPE=Debug -DCPU_BLAS=true -DLIBND4J_NAME=nd4jcpu -DBUILD_TESTS=ON -DCMAKE_BUILD_TYPE=Debug -DOPENBLAS_PATH=/usr/lib/openblas-base/ -DEXTENSION=avx2 ",
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"buildCommandArgs": "-j 4",
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"ctestCommandArgs": "",
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"inheritEnvironments": [ "linux_x64" ],
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"wslPath": "${defaultWSLPath}",
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"addressSanitizerRuntimeFlags": "detect_leaks=0",
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"variables": []
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}
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]
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}
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@ -41,6 +41,7 @@
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#include <ops/declarable/headers/tests.h>
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#include <ops/declarable/headers/kernels.h>
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#include <ops/declarable/headers/BarnesHutTsne.h>
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#include <ops/declarable/headers/color_models.h>
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#include <dll.h>
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#include <helpers/shape.h>
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#include <helpers/TAD.h>
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@ -0,0 +1,85 @@
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/*******************************************************************************
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* Copyright (c) 2019 Konduit K.K.
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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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#include <ops/declarable/headers/color_models.h>
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#include <ops/declarable/CustomOperations.h>
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#include <helpers/ConstantTadHelper.h>
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#include <execution/Threads.h>
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namespace nd4j {
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namespace ops {
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CONFIGURABLE_OP_IMPL(hsv_to_rgb, 1, 1, false, 0, 0) {
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auto input = INPUT_VARIABLE(0);
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auto output = OUTPUT_VARIABLE(0);
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if (input->isEmpty())
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return Status::OK();
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const int rank = input->rankOf();
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const int arg_size = block.getIArguments()->size();
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const int dimC = arg_size > 0 ? (INT_ARG(0) >= 0 ? INT_ARG(0) : INT_ARG(0) + rank) : rank - 1;
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REQUIRE_TRUE(rank >= 1, 0, "HSVtoRGB: Fails to meet the rank requirement: %i >= 1 ", rank);
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if (arg_size > 0) {
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REQUIRE_TRUE(dimC >= 0 && dimC < rank, 0, "Index of the Channel dimension out of range: %i not in [%i,%i) ", INT_ARG(0), -rank, rank);
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}
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REQUIRE_TRUE(input->sizeAt(dimC) == 3, 0, "HSVtoRGB: operation expects 3 channels (H, S, V), but got %i instead", input->sizeAt(dimC));
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helpers::transform_hsv_rgb(block.launchContext(), input, output, dimC);
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return Status::OK();
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}
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CONFIGURABLE_OP_IMPL(rgb_to_hsv, 1, 1, false, 0, 0) {
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auto input = INPUT_VARIABLE(0);
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auto output = OUTPUT_VARIABLE(0);
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if (input->isEmpty())
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return Status::OK();
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const int rank = input->rankOf();
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const int arg_size = block.getIArguments()->size();
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const int dimC = arg_size > 0 ? (INT_ARG(0) >= 0 ? INT_ARG(0) : INT_ARG(0) + rank) : rank - 1;
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REQUIRE_TRUE(rank >= 1, 0, "RGBtoHSV: Fails to meet the rank requirement: %i >= 1 ", rank);
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if (arg_size > 0) {
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REQUIRE_TRUE(dimC >= 0 && dimC < rank, 0, "Index of the Channel dimension out of range: %i not in [%i,%i) ", INT_ARG(0), -rank, rank);
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}
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REQUIRE_TRUE(input->sizeAt(dimC) == 3, 0, "RGBtoHSV: operation expects 3 channels (H, S, V), but got %i instead", input->sizeAt(dimC));
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helpers::transform_rgb_hsv(block.launchContext(), input, output, dimC);
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return Status::OK();
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}
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DECLARE_TYPES(hsv_to_rgb) {
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getOpDescriptor()->setAllowedInputTypes({ ALL_FLOATS })
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->setSameMode(true);
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}
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DECLARE_TYPES(rgb_to_hsv) {
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getOpDescriptor()->setAllowedInputTypes({ ALL_FLOATS })
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->setSameMode(true);
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}
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}
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}
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@ -39,10 +39,14 @@ CONFIGURABLE_OP_IMPL(adjust_hue, 1, 1, true, 0, 0) {
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return Status::OK();
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const int rank = input->rankOf();
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const int dimC = block.getIArguments()->size() > 0 ? (INT_ARG(0) >= 0 ? INT_ARG(0) : INT_ARG(0) + rank) : rank - 1;
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const int arg_size = block.getIArguments()->size();
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const int dimC = arg_size > 0 ? (INT_ARG(0) >= 0 ? INT_ARG(0) : INT_ARG(0) + rank) : rank - 1;
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REQUIRE_TRUE(block.numT() > 0 || block.width() > 1, 0, "ADJUST_HUE: delta factor is required !");
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REQUIRE_TRUE(rank >= 3, 0, "ADJUST_HUE: op expects rank of input array to be >= 3, but got %i instead", rank);
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if (arg_size > 0) {
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REQUIRE_TRUE(dimC >= 0 && dimC < rank, 0, "Index of the Channel dimension out of range: %i not in [%i,%i) ", INT_ARG(0), -rank, rank);
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}
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REQUIRE_TRUE(input->sizeAt(dimC) == 3, 0, "ADJUST_HUE: operation expects image with 3 channels (R, G, B), but got %i instead", input->sizeAt(dimC));
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NDArray* delta = nullptr;
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@ -38,9 +38,13 @@ CONFIGURABLE_OP_IMPL(adjust_saturation, 1, 1, true, 0, 0) {
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return Status::OK();
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const int rank = input->rankOf();
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const int dimC = block.getIArguments()->size() > 0 ? (INT_ARG(0) >= 0 ? INT_ARG(0) : INT_ARG(0) + rank) : rank - 1;
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const int arg_size = block.getIArguments()->size();
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const int dimC = arg_size > 0 ? (INT_ARG(0) >= 0 ? INT_ARG(0) : INT_ARG(0) + rank) : rank - 1;
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REQUIRE_TRUE(rank >= 3, 0, "ADJUST_SATURATION: op expects rank of input array to be >= 3, but got %i instead", rank);
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if (arg_size > 0) {
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REQUIRE_TRUE(dimC >= 0 && dimC < rank, 0, "Index of the Channel dimension out of range: %i not in [%i,%i) ", INT_ARG(0), -rank, rank);
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}
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REQUIRE_TRUE(input->sizeAt(dimC) == 3, 0, "ADJUST_SATURATION: operation expects image with 3 channels (R, G, B), but got %i instead", input->sizeAt(dimC));
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REQUIRE_TRUE(block.numT() > 0 || block.width() > 1, 0, "ADJUST_SATURATION: scale factor is required !");
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@ -0,0 +1,56 @@
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/*******************************************************************************
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* Copyright (c) 2019 Konduit K.K.
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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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#ifndef LIBND4J_HEADERS_COLOR_MODELS_H
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#define LIBND4J_HEADERS_COLOR_MODELS_H
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#include <ops/declarable/headers/common.h>
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#include <ops/declarable/CustomOperations.h>
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#include <helpers/ConstantTadHelper.h>
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#include <execution/Threads.h>
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#include <ops/declarable/helpers/color_models_conv.h>
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namespace nd4j {
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namespace ops {
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/**
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* Rgb To Hsv
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* Input arrays:
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* 0 - input array with rank >= 1, must have at least one dimension equal 3, that is dimension containing channels.
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* Int arguments:
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* 0 - optional argument, corresponds to dimension with 3 channels
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*/
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#if NOT_EXCLUDED(OP_rgb_to_hsv)
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DECLARE_CONFIGURABLE_OP(rgb_to_hsv, 1, 1, false, 0, 0);
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#endif
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/**
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* Hsv To Rgb
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* Input arrays:
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* 0 - input array with rank >= 1, must have at least one dimension equal 3, that is dimension containing channels.
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* Int arguments:
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* 0 - optional argument, corresponds to dimension with 3 channels
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*/
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#if NOT_EXCLUDED(OP_hsv_to_rgb)
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DECLARE_CONFIGURABLE_OP(hsv_to_rgb, 1, 1, false, 0, 0);
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#endif
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}
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}
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#endif
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@ -0,0 +1,30 @@
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/*******************************************************************************
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* Copyright (c) 2019 Konduit K.K.
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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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#include <op_boilerplate.h>
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#include <templatemath.h>
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#include <NDArray.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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void transform_hsv_rgb(nd4j::LaunchContext* context, const NDArray* input, NDArray* output, const int dimC);
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void transform_rgb_hsv(nd4j::LaunchContext* context, const NDArray* input, NDArray* output, const int dimC);
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}
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}
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}
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@ -0,0 +1,90 @@
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/*******************************************************************************
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* Copyright (c) 2019 Konduit K.K.
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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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#include <ops/declarable/helpers/adjust_hue.h>
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#include <ops/declarable/helpers/color_models_conv.h>
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#include <helpers/ConstantTadHelper.h>
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#include <execution/Threads.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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//local
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template <typename T, typename Op>
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FORCEINLINE static void triple_transformer(const NDArray* input, NDArray* output, const int dimC, Op op) {
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const int rank = input->rankOf();
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const T* x = input->bufferAsT<T>();
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T* z = output->bufferAsT<T>();
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if (dimC == rank - 1 && input->ews() == 1 && output->ews() == 1 && input->ordering() == 'c' && output->ordering() == 'c') {
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auto func = PRAGMA_THREADS_FOR{
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for (auto i = start; i < stop; i += increment) {
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op(x[i], x[i + 1], x[i + 2], z[i], z[i + 1], z[i + 2]);
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}
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};
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samediff::Threads::parallel_for(func, 0, input->lengthOf(), 3);
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}
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else {
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auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(input->getShapeInfo(), dimC);
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auto packZ = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(output->getShapeInfo(), dimC);
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const Nd4jLong numOfTads = packX.numberOfTads();
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const Nd4jLong xDimCstride = input->stridesOf()[dimC];
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const Nd4jLong zDimCstride = output->stridesOf()[dimC];
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auto func = PRAGMA_THREADS_FOR{
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for (auto i = start; i < stop; i += increment) {
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const T* xTad = x + packX.platformOffsets()[i];
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T* zTad = z + packZ.platformOffsets()[i];
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op(xTad[0], xTad[xDimCstride], xTad[2 * xDimCstride], zTad[0], zTad[zDimCstride], zTad[2 * zDimCstride]);
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}
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};
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samediff::Threads::parallel_tad(func, 0, numOfTads);
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}
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}
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template <typename T>
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FORCEINLINE static void hsv_rgb(const NDArray* input, NDArray* output, const int dimC) {
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auto op = nd4j::ops::helpers::hsvToRgb<T>;
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return triple_transformer<T>(input, output, dimC, op);
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}
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template <typename T>
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FORCEINLINE static void rgb_hsv(const NDArray* input, NDArray* output, const int dimC) {
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auto op = nd4j::ops::helpers::rgbToHsv<T>;
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return triple_transformer<T>(input, output, dimC, op);
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}
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void transform_hsv_rgb(nd4j::LaunchContext* context, const NDArray* input, NDArray* output, const int dimC) {
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BUILD_SINGLE_SELECTOR(input->dataType(), hsv_rgb, (input, output, dimC), FLOAT_TYPES);
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}
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void transform_rgb_hsv(nd4j::LaunchContext* context, const NDArray* input, NDArray* output, const int dimC) {
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BUILD_SINGLE_SELECTOR(input->dataType(), rgb_hsv, (input, output, dimC), FLOAT_TYPES);
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}
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}
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}
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}
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@ -0,0 +1,139 @@
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/*******************************************************************************
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* Copyright (c) 2019 Konduit K.K.
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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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#include <ops/declarable/helpers/color_models_conv.h>
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#include <ops/declarable/helpers/adjust_hue.h>
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#include <ops/declarable/helpers/adjust_saturation.h>
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#include <helpers/ConstantTadHelper.h>
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#include <PointersManager.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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static void _CUDA_G rgbToHsvCuda(const void* vx, const Nd4jLong* xShapeInfo, const Nd4jLong* xTadOffsets,
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void* vz, const Nd4jLong *zShapeInfo, const Nd4jLong* zTadOffsets,
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const Nd4jLong numOfTads, const int dimC) {
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const T* x = reinterpret_cast<const T*>(vx);
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T* z = reinterpret_cast<T*>(vz);
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__shared__ int rank;
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__shared__ Nd4jLong xDimCstride, zDimCstride;
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if (threadIdx.x == 0) {
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rank = shape::rank(xShapeInfo);
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xDimCstride = shape::stride(xShapeInfo)[dimC];
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zDimCstride = shape::stride(zShapeInfo)[dimC];
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}
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__syncthreads();
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const auto tid = blockIdx.x * blockDim.x + threadIdx.x;
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for (Nd4jLong i = tid; i < numOfTads; i += gridDim.x * blockDim.x) {
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const T* xTad = x + xTadOffsets[i];
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T* zTad = z + zTadOffsets[i];
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rgbToHsv<T>(xTad[0], xTad[xDimCstride], xTad[2 * xDimCstride], zTad[0], zTad[zDimCstride], zTad[2 * zDimCstride]);
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}
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}
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template <typename T>
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static void _CUDA_G hsvToRgbCuda(const void* vx, const Nd4jLong* xShapeInfo, const Nd4jLong* xTadOffsets,
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void* vz, const Nd4jLong *zShapeInfo, const Nd4jLong* zTadOffsets,
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const Nd4jLong numOfTads, const int dimC) {
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const T* x = reinterpret_cast<const T*>(vx);
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T* z = reinterpret_cast<T*>(vz);
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__shared__ int rank;
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__shared__ Nd4jLong xDimCstride, zDimCstride;
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if (threadIdx.x == 0) {
|
||||
rank = shape::rank(xShapeInfo);
|
||||
xDimCstride = shape::stride(xShapeInfo)[dimC];
|
||||
zDimCstride = shape::stride(zShapeInfo)[dimC];
|
||||
}
|
||||
__syncthreads();
|
||||
|
||||
const auto tid = blockIdx.x * blockDim.x + threadIdx.x;
|
||||
|
||||
for (Nd4jLong i = tid; i < numOfTads; i += gridDim.x * blockDim.x) {
|
||||
const T* xTad = x + xTadOffsets[i];
|
||||
T* zTad = z + zTadOffsets[i];
|
||||
|
||||
hsvToRgb<T>(xTad[0], xTad[xDimCstride], xTad[2 * xDimCstride], zTad[0], zTad[zDimCstride], zTad[2 * zDimCstride]);
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////////////////////////////////////////////////
|
||||
template<typename T>
|
||||
static _CUDA_H void hsvToRgbCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const cudaStream_t *stream,
|
||||
const void* vx, const Nd4jLong* xShapeInfo, const Nd4jLong* xTadOffsets,
|
||||
void* vz, const Nd4jLong* zShapeInfo, const Nd4jLong* zTadOffsets,
|
||||
const Nd4jLong numOfTads, const int dimC) {
|
||||
|
||||
hsvToRgbCuda<T><<<blocksPerGrid, threadsPerBlock, 256, *stream>>>(vx, xShapeInfo, xTadOffsets, vz, zShapeInfo, zTadOffsets, numOfTads, dimC);
|
||||
}
|
||||
|
||||
template<typename T>
|
||||
static _CUDA_H void rgbToHsvCudaLauncher(const int blocksPerGrid, const int threadsPerBlock, const cudaStream_t *stream,
|
||||
const void* vx, const Nd4jLong* xShapeInfo, const Nd4jLong* xTadOffsets,
|
||||
void* vz, const Nd4jLong* zShapeInfo, const Nd4jLong* zTadOffsets,
|
||||
const Nd4jLong numOfTads, const int dimC) {
|
||||
|
||||
rgbToHsvCuda<T><<<blocksPerGrid, threadsPerBlock, 256, *stream>>>(vx, xShapeInfo, xTadOffsets, vz, zShapeInfo, zTadOffsets, numOfTads, dimC);
|
||||
}
|
||||
|
||||
|
||||
void transform_hsv_rgb(nd4j::LaunchContext* context, const NDArray* input, NDArray* output, const int dimC) {
|
||||
auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(input->getShapeInfo(), {dimC});
|
||||
auto packZ = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(output->getShapeInfo(), {dimC});
|
||||
|
||||
const Nd4jLong numOfTads = packX.numberOfTads();
|
||||
|
||||
const int threadsPerBlock = MAX_NUM_THREADS / 2;
|
||||
const int blocksPerGrid = (numOfTads + threadsPerBlock - 1) / threadsPerBlock;
|
||||
|
||||
PointersManager manager(context, "hsv_to_rgb");
|
||||
|
||||
NDArray::prepareSpecialUse({output}, {input});
|
||||
BUILD_SINGLE_SELECTOR(input->dataType(), hsvToRgbCudaLauncher, (blocksPerGrid, threadsPerBlock, context->getCudaStream(), input->getSpecialBuffer(), input->getSpecialShapeInfo(), packX.platformOffsets(), output->specialBuffer(), output->specialShapeInfo(), packZ.platformOffsets(), numOfTads, dimC), FLOAT_TYPES);
|
||||
NDArray::registerSpecialUse({output}, {input});
|
||||
|
||||
manager.synchronize();
|
||||
}
|
||||
|
||||
void transform_rgb_hsv(nd4j::LaunchContext* context, const NDArray* input, NDArray* output, const int dimC) {
|
||||
auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(input->getShapeInfo(), {dimC});
|
||||
auto packZ = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(output->getShapeInfo(), {dimC});
|
||||
|
||||
const Nd4jLong numOfTads = packX.numberOfTads();
|
||||
|
||||
const int threadsPerBlock = MAX_NUM_THREADS / 2;
|
||||
const int blocksPerGrid = (numOfTads + threadsPerBlock - 1) / threadsPerBlock;
|
||||
|
||||
PointersManager manager(context, "rgb_to_hsv");
|
||||
|
||||
NDArray::prepareSpecialUse({output}, {input});
|
||||
BUILD_SINGLE_SELECTOR(input->dataType(), rgbToHsvCudaLauncher, (blocksPerGrid, threadsPerBlock, context->getCudaStream(), input->getSpecialBuffer(), input->getSpecialShapeInfo(), packX.platformOffsets(), output->specialBuffer(), output->specialShapeInfo(), packZ.platformOffsets(), numOfTads, dimC), FLOAT_TYPES);
|
||||
NDArray::registerSpecialUse({output}, {input});
|
||||
|
||||
manager.synchronize();
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -1,240 +1,695 @@
|
|||
/*******************************************************************************
|
||||
* Copyright (c) 2015-2019 Skymind, Inc.
|
||||
*
|
||||
* 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.
|
||||
*
|
||||
* 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 "testlayers.h"
|
||||
#include <ops/declarable/CustomOperations.h>
|
||||
#include <NDArray.h>
|
||||
#include <ops/ops.h>
|
||||
#include <GradCheck.h>
|
||||
#include <array>
|
||||
|
||||
|
||||
using namespace nd4j;
|
||||
|
||||
|
||||
class DeclarableOpsTests16 : public testing::Test {
|
||||
public:
|
||||
|
||||
DeclarableOpsTests16() {
|
||||
printf("\n");
|
||||
fflush(stdout);
|
||||
}
|
||||
};
|
||||
|
||||
TEST_F(DeclarableOpsTests16, scatter_upd_1) {
|
||||
auto x = NDArrayFactory::create<float>('c', {3}, {1.f, 1.f, 1.f});
|
||||
auto y = NDArrayFactory::create<int>(0);
|
||||
auto w = NDArrayFactory::create<float>(3.0f);
|
||||
auto e = NDArrayFactory::create<float>('c', {3}, {3.f, 1.f, 1.f});
|
||||
|
||||
nd4j::ops::scatter_upd op;
|
||||
auto result = op.execute({&x, &y, &w}, {}, {});
|
||||
ASSERT_EQ(Status::OK(), result->status());
|
||||
|
||||
auto z = result->at(0);
|
||||
|
||||
ASSERT_EQ(e, *z);
|
||||
|
||||
delete result;
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, scatter_upd_2) {
|
||||
|
||||
NDArray x('c', {10, 3}, nd4j::DataType::FLOAT32);
|
||||
NDArray indices('c', {2}, {2,5}, nd4j::DataType::INT32);
|
||||
NDArray updates('c', {2, 3}, {100,101,102, 200,201,202}, nd4j::DataType::FLOAT32);
|
||||
NDArray e('c', {10, 3}, {1,2,3, 4,5,6, 100,101,102, 10,11,12, 13,14,15, 200,201,202, 19,20,21, 22,23,24, 25,26,27, 28,29,30}, nd4j::DataType::FLOAT32);
|
||||
|
||||
x.linspace(1);
|
||||
|
||||
nd4j::ops::scatter_upd op;
|
||||
auto result = op.execute({&x, &indices, &updates}, {}, {});
|
||||
ASSERT_EQ(Status::OK(), result->status());
|
||||
|
||||
auto z = result->at(0);
|
||||
|
||||
ASSERT_EQ(e, *z);
|
||||
|
||||
delete result;
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, scatter_upd_3) {
|
||||
|
||||
NDArray x('c', {10, 3}, nd4j::DataType::FLOAT32);
|
||||
NDArray indices('c', {2}, {20,5}, nd4j::DataType::INT32);
|
||||
NDArray updates('c', {2, 3}, {100,101,102, 200,201,202}, nd4j::DataType::FLOAT32);
|
||||
NDArray output('c', {10, 3}, nd4j::DataType::FLOAT32);
|
||||
|
||||
nd4j::ops::scatter_upd op;
|
||||
ASSERT_ANY_THROW(op.execute({&x, &indices, &updates}, {&output}, {}, {}, {true, true}));
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_size_dtype_1) {
|
||||
auto x = NDArrayFactory::create<float>('c', {3}, {1, 1, 1});
|
||||
auto z = NDArrayFactory::create<float>(0.0f);
|
||||
auto e = NDArrayFactory::create<float>(3.0f);
|
||||
|
||||
nd4j::ops::size op;
|
||||
auto status = op.execute({&x}, {&z}, {}, {}, {});
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
|
||||
ASSERT_EQ(e, z);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_empty_noop_1) {
|
||||
auto z = NDArrayFactory::empty<Nd4jLong>();
|
||||
|
||||
nd4j::ops::noop op;
|
||||
auto status = op.execute({}, {&z}, {}, {}, {});
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_empty_noop_2) {
|
||||
auto z = NDArrayFactory::empty<Nd4jLong>();
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setOutputArray(0, z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo());
|
||||
|
||||
nd4j::ops::noop op;
|
||||
auto status = op.execute(&ctx);
|
||||
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_svd_1) {
|
||||
auto x = NDArrayFactory::create<float>('c', {3, 3}, {0.7787856f, 0.80119777f, 0.72437465f, 0.23089433f, 0.72714126f, 0.18039072f,0.50563407f, 0.89252293f, 0.5461209f});
|
||||
auto z = NDArrayFactory::create<float>('c', {3});
|
||||
|
||||
nd4j::ops::svd op;
|
||||
auto status = op.execute({&x}, {&z}, {}, {0, 0, 16}, {});
|
||||
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_hamming_distance_1) {
|
||||
auto x = NDArrayFactory::create<Nd4jLong>({37, 37, 37});
|
||||
auto y = NDArrayFactory::create<Nd4jLong>({8723, 8723, 8723});
|
||||
auto e = NDArrayFactory::create<Nd4jLong>(18);
|
||||
|
||||
nd4j::ops::bits_hamming_distance op;
|
||||
auto result = op.execute({&x, &y}, {}, {});
|
||||
ASSERT_EQ(Status::OK(), result->status());
|
||||
|
||||
auto z = result->at(0);
|
||||
|
||||
ASSERT_EQ(e, *z);
|
||||
|
||||
delete result;
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_knn_mindistance_1) {
|
||||
auto input = NDArrayFactory::create<float>('c', {512});
|
||||
auto low = NDArrayFactory::create<float>('c', {512});
|
||||
auto high = NDArrayFactory::create<float>('c', {512});
|
||||
|
||||
auto output = NDArrayFactory::create<float>(0.0f);
|
||||
|
||||
input.linspace(1.0);
|
||||
low.linspace(1.0);
|
||||
high.linspace(1.0);
|
||||
|
||||
nd4j::ops::knn_mindistance op;
|
||||
auto result = op.execute({&input, &low, &high}, {&output}, {}, {}, {});
|
||||
ASSERT_EQ(Status::OK(), result);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_empty_cast_1) {
|
||||
auto x = NDArrayFactory::create<bool>('c', {1, 0, 2});
|
||||
auto e = NDArrayFactory::create<Nd4jLong>('c', {1, 0, 2});
|
||||
|
||||
nd4j::ops::cast op;
|
||||
auto result = op.execute({&x}, {}, {10});
|
||||
ASSERT_EQ(Status::OK(), result->status());
|
||||
ASSERT_EQ(e, *result->at(0));
|
||||
|
||||
delete result;
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_range_1) {
|
||||
nd4j::ops::range op;
|
||||
auto z = NDArrayFactory::create<float>('c', {200});
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setTArguments({-1.0, 1.0, 0.01});
|
||||
ctx.setOutputArray(0, &z);
|
||||
|
||||
auto status = op.execute(&ctx);
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_range_2) {
|
||||
nd4j::ops::range op;
|
||||
auto z = NDArrayFactory::create<float>('c', {200});
|
||||
|
||||
double tArgs[] = {-1.0, 1.0, 0.01};
|
||||
|
||||
auto shapes = ::calculateOutputShapes2(nullptr, op.getOpHash(), nullptr, nullptr, 0, tArgs, 3, nullptr, 0, nullptr, 0);
|
||||
shape::printShapeInfoLinear("Result", shapes->at(0));
|
||||
ASSERT_TRUE(shape::shapeEquals(z.shapeInfo(), shapes->at(0)));
|
||||
|
||||
delete shapes;
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_reverse_1) {
|
||||
std::vector<Nd4jLong> rows = {3, 5, 7, 8, 9, 10, 119, 211};
|
||||
std::vector<Nd4jLong> columns = {6, 5, 10, 100, 153, 171, 635};
|
||||
|
||||
for (auto r : rows) {
|
||||
for (auto c : columns) {
|
||||
//nd4j_printf("Trying [%i, %i]\n", r, c);
|
||||
auto array = NDArrayFactory::create<float>('c', {r, c});
|
||||
auto exp = NDArrayFactory::create<float>('c', {r, c});
|
||||
auto reversed = NDArrayFactory::create<float>('c', {r, c});
|
||||
|
||||
auto rowOriginal = NDArrayFactory::create<float>('c', {c});
|
||||
auto rowReversed = NDArrayFactory::create<float>('c', {c});
|
||||
|
||||
for (int e = 0; e < c; e++) {
|
||||
rowOriginal.p(e, (float) e);
|
||||
rowReversed.p(c - e - 1, (float) e);
|
||||
}
|
||||
|
||||
|
||||
auto listI = array.allTensorsAlongDimension({1});
|
||||
auto listE = exp.allTensorsAlongDimension({1});
|
||||
|
||||
for (int e = 0; e < r; e++) {
|
||||
listI->at(e)->assign(rowOriginal);
|
||||
listE->at(e)->assign(rowReversed);
|
||||
}
|
||||
|
||||
delete listI;
|
||||
delete listE;
|
||||
|
||||
nd4j::ops::reverse op;
|
||||
Nd4jLong axis = 1;
|
||||
auto status = op.execute({&array}, {&reversed}, {}, {axis}, {});
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
|
||||
ASSERT_EQ(exp, reversed);
|
||||
}
|
||||
}
|
||||
/*******************************************************************************
|
||||
* Copyright (c) 2015-2019 Skymind, Inc.
|
||||
*
|
||||
* 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.
|
||||
*
|
||||
* 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 "testlayers.h"
|
||||
#include <ops/declarable/CustomOperations.h>
|
||||
#include <NDArray.h>
|
||||
#include <ops/ops.h>
|
||||
#include <GradCheck.h>
|
||||
#include <array>
|
||||
|
||||
|
||||
using namespace nd4j;
|
||||
|
||||
|
||||
class DeclarableOpsTests16 : public testing::Test {
|
||||
public:
|
||||
|
||||
DeclarableOpsTests16() {
|
||||
printf("\n");
|
||||
fflush(stdout);
|
||||
}
|
||||
};
|
||||
|
||||
TEST_F(DeclarableOpsTests16, scatter_upd_1) {
|
||||
auto x = NDArrayFactory::create<float>('c', { 3 }, { 1.f, 1.f, 1.f });
|
||||
auto y = NDArrayFactory::create<int>(0);
|
||||
auto w = NDArrayFactory::create<float>(3.0f);
|
||||
auto e = NDArrayFactory::create<float>('c', { 3 }, { 3.f, 1.f, 1.f });
|
||||
|
||||
nd4j::ops::scatter_upd op;
|
||||
auto result = op.execute({ &x, &y, &w }, {}, {});
|
||||
ASSERT_EQ(Status::OK(), result->status());
|
||||
|
||||
auto z = result->at(0);
|
||||
|
||||
ASSERT_EQ(e, *z);
|
||||
|
||||
delete result;
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, scatter_upd_2) {
|
||||
|
||||
NDArray x('c', { 10, 3 }, nd4j::DataType::FLOAT32);
|
||||
NDArray indices('c', { 2 }, { 2,5 }, nd4j::DataType::INT32);
|
||||
NDArray updates('c', { 2, 3 }, { 100,101,102, 200,201,202 }, nd4j::DataType::FLOAT32);
|
||||
NDArray e('c', { 10, 3 }, { 1,2,3, 4,5,6, 100,101,102, 10,11,12, 13,14,15, 200,201,202, 19,20,21, 22,23,24, 25,26,27, 28,29,30 }, nd4j::DataType::FLOAT32);
|
||||
|
||||
x.linspace(1);
|
||||
|
||||
nd4j::ops::scatter_upd op;
|
||||
auto result = op.execute({ &x, &indices, &updates }, {}, {});
|
||||
ASSERT_EQ(Status::OK(), result->status());
|
||||
|
||||
auto z = result->at(0);
|
||||
|
||||
ASSERT_EQ(e, *z);
|
||||
|
||||
delete result;
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, scatter_upd_3) {
|
||||
|
||||
NDArray x('c', { 10, 3 }, nd4j::DataType::FLOAT32);
|
||||
NDArray indices('c', { 2 }, { 20,5 }, nd4j::DataType::INT32);
|
||||
NDArray updates('c', { 2, 3 }, { 100,101,102, 200,201,202 }, nd4j::DataType::FLOAT32);
|
||||
NDArray output('c', { 10, 3 }, nd4j::DataType::FLOAT32);
|
||||
|
||||
nd4j::ops::scatter_upd op;
|
||||
ASSERT_ANY_THROW(op.execute({ &x, &indices, &updates }, { &output }, {}, {}, { true, true }));
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_size_dtype_1) {
|
||||
auto x = NDArrayFactory::create<float>('c', { 3 }, { 1, 1, 1 });
|
||||
auto z = NDArrayFactory::create<float>(0.0f);
|
||||
auto e = NDArrayFactory::create<float>(3.0f);
|
||||
|
||||
nd4j::ops::size op;
|
||||
auto status = op.execute({ &x }, { &z }, {}, {}, {});
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
|
||||
ASSERT_EQ(e, z);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_empty_noop_1) {
|
||||
auto z = NDArrayFactory::empty<Nd4jLong>();
|
||||
|
||||
nd4j::ops::noop op;
|
||||
auto status = op.execute({}, { &z }, {}, {}, {});
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_empty_noop_2) {
|
||||
auto z = NDArrayFactory::empty<Nd4jLong>();
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setOutputArray(0, z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo());
|
||||
|
||||
nd4j::ops::noop op;
|
||||
auto status = op.execute(&ctx);
|
||||
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_svd_1) {
|
||||
auto x = NDArrayFactory::create<float>('c', { 3, 3 }, { 0.7787856f, 0.80119777f, 0.72437465f, 0.23089433f, 0.72714126f, 0.18039072f,0.50563407f, 0.89252293f, 0.5461209f });
|
||||
auto z = NDArrayFactory::create<float>('c', { 3 });
|
||||
|
||||
nd4j::ops::svd op;
|
||||
auto status = op.execute({ &x }, { &z }, {}, { 0, 0, 16 }, {});
|
||||
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_hamming_distance_1) {
|
||||
auto x = NDArrayFactory::create<Nd4jLong>({ 37, 37, 37 });
|
||||
auto y = NDArrayFactory::create<Nd4jLong>({ 8723, 8723, 8723 });
|
||||
auto e = NDArrayFactory::create<Nd4jLong>(18);
|
||||
|
||||
nd4j::ops::bits_hamming_distance op;
|
||||
auto result = op.execute({ &x, &y }, {}, {});
|
||||
ASSERT_EQ(Status::OK(), result->status());
|
||||
|
||||
auto z = result->at(0);
|
||||
|
||||
ASSERT_EQ(e, *z);
|
||||
|
||||
delete result;
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_knn_mindistance_1) {
|
||||
auto input = NDArrayFactory::create<float>('c', { 512 });
|
||||
auto low = NDArrayFactory::create<float>('c', { 512 });
|
||||
auto high = NDArrayFactory::create<float>('c', { 512 });
|
||||
|
||||
auto output = NDArrayFactory::create<float>(0.0f);
|
||||
|
||||
input.linspace(1.0);
|
||||
low.linspace(1.0);
|
||||
high.linspace(1.0);
|
||||
|
||||
nd4j::ops::knn_mindistance op;
|
||||
auto result = op.execute({ &input, &low, &high }, { &output }, {}, {}, {});
|
||||
ASSERT_EQ(Status::OK(), result);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_empty_cast_1) {
|
||||
auto x = NDArrayFactory::create<bool>('c', { 1, 0, 2 });
|
||||
auto e = NDArrayFactory::create<Nd4jLong>('c', { 1, 0, 2 });
|
||||
|
||||
nd4j::ops::cast op;
|
||||
auto result = op.execute({ &x }, {}, { 10 });
|
||||
ASSERT_EQ(Status::OK(), result->status());
|
||||
ASSERT_EQ(e, *result->at(0));
|
||||
|
||||
delete result;
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_range_1) {
|
||||
nd4j::ops::range op;
|
||||
auto z = NDArrayFactory::create<float>('c', { 200 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setTArguments({ -1.0, 1.0, 0.01 });
|
||||
ctx.setOutputArray(0, &z);
|
||||
|
||||
auto status = op.execute(&ctx);
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_range_2) {
|
||||
nd4j::ops::range op;
|
||||
auto z = NDArrayFactory::create<float>('c', { 200 });
|
||||
|
||||
double tArgs[] = { -1.0, 1.0, 0.01 };
|
||||
|
||||
auto shapes = ::calculateOutputShapes2(nullptr, op.getOpHash(), nullptr, nullptr, 0, tArgs, 3, nullptr, 0, nullptr, 0);
|
||||
shape::printShapeInfoLinear("Result", shapes->at(0));
|
||||
ASSERT_TRUE(shape::shapeEquals(z.shapeInfo(), shapes->at(0)));
|
||||
|
||||
delete shapes;
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_reverse_1) {
|
||||
std::vector<Nd4jLong> rows = { 3, 5, 7, 8, 9, 10, 119, 211 };
|
||||
std::vector<Nd4jLong> columns = { 6, 5, 10, 100, 153, 171, 635 };
|
||||
|
||||
for (auto r : rows) {
|
||||
for (auto c : columns) {
|
||||
//nd4j_printf("Trying [%i, %i]\n", r, c);
|
||||
auto array = NDArrayFactory::create<float>('c', { r, c });
|
||||
auto exp = NDArrayFactory::create<float>('c', { r, c });
|
||||
auto reversed = NDArrayFactory::create<float>('c', { r, c });
|
||||
|
||||
auto rowOriginal = NDArrayFactory::create<float>('c', { c });
|
||||
auto rowReversed = NDArrayFactory::create<float>('c', { c });
|
||||
|
||||
for (int e = 0; e < c; e++) {
|
||||
rowOriginal.p(e, (float)e);
|
||||
rowReversed.p(c - e - 1, (float)e);
|
||||
}
|
||||
|
||||
|
||||
auto listI = array.allTensorsAlongDimension({ 1 });
|
||||
auto listE = exp.allTensorsAlongDimension({ 1 });
|
||||
|
||||
for (int e = 0; e < r; e++) {
|
||||
listI->at(e)->assign(rowOriginal);
|
||||
listE->at(e)->assign(rowReversed);
|
||||
}
|
||||
|
||||
delete listI;
|
||||
delete listE;
|
||||
|
||||
nd4j::ops::reverse op;
|
||||
Nd4jLong axis = 1;
|
||||
auto status = op.execute({ &array }, { &reversed }, {}, { axis }, {});
|
||||
ASSERT_EQ(Status::OK(), status);
|
||||
|
||||
ASSERT_EQ(exp, reversed);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_rgb_to_hsv_1) {
|
||||
/*
|
||||
test case generated by python colorsys and scaled to suit our needs
|
||||
from colorsys import *
|
||||
from random import *
|
||||
import numpy as np
|
||||
rgbs = np.array([randint(0,255) for x in range(0,3*4*5)]).reshape([5,4,3])
|
||||
hsvs=np.apply_along_axis(lambda x: np.array(rgb_to_hsv(x[0]/255,x[1]/255,x[2]/255))*np.array([360,1,1]),2,rgbs)
|
||||
rgbs.ravel()
|
||||
hsvs.ravel()
|
||||
*/
|
||||
auto rgbs = NDArrayFactory::create<float>('c', { 5, 4, 3 },
|
||||
{
|
||||
213.f, 220.f, 164.f, 121.f, 180.f, 180.f, 18.f, 245.f, 75.f, 235.f, 76.f, 74.f, 168.f,
|
||||
50.f, 233.f, 191.f, 132.f, 100.f, 207.f, 37.f, 245.f, 77.f, 250.f, 182.f, 111.f, 52.f,
|
||||
59.f, 193.f, 147.f, 137.f, 168.f, 103.f, 121.f, 48.f, 191.f, 187.f, 53.f, 82.f, 239.f,
|
||||
156.f, 37.f, 118.f, 244.f, 90.f, 7.f, 221.f, 98.f, 243.f, 12.f, 209.f, 192.f, 2.f,
|
||||
115.f, 205.f, 79.f, 247.f, 32.f, 70.f, 152.f, 180.f
|
||||
});
|
||||
auto expected = NDArrayFactory::create<float>('c', { 5, 4, 3 },
|
||||
{
|
||||
6.75000000e+01f, 2.54545455e-01f, 8.62745098e-01f, 1.80000000e+02f,
|
||||
3.27777778e-01f, 7.05882353e-01f, 1.35066079e+02f, 9.26530612e-01f,
|
||||
9.60784314e-01f, 7.45341615e-01f, 6.85106383e-01f, 9.21568627e-01f,
|
||||
2.78688525e+02f, 7.85407725e-01f, 9.13725490e-01f, 2.10989011e+01f,
|
||||
4.76439791e-01f, 7.49019608e-01f, 2.89038462e+02f, 8.48979592e-01f,
|
||||
9.60784314e-01f, 1.56416185e+02f, 6.92000000e-01f, 9.80392157e-01f,
|
||||
3.52881356e+02f, 5.31531532e-01f, 4.35294118e-01f, 1.07142857e+01f,
|
||||
2.90155440e-01f, 7.56862745e-01f, 3.43384615e+02f, 3.86904762e-01f,
|
||||
6.58823529e-01f, 1.78321678e+02f, 7.48691099e-01f, 7.49019608e-01f,
|
||||
2.30645161e+02f, 7.78242678e-01f, 9.37254902e-01f, 3.19159664e+02f,
|
||||
7.62820513e-01f, 6.11764706e-01f, 2.10126582e+01f, 9.71311475e-01f,
|
||||
9.56862745e-01f, 2.90896552e+02f, 5.96707819e-01f, 9.52941176e-01f,
|
||||
1.74822335e+02f, 9.42583732e-01f, 8.19607843e-01f, 2.06600985e+02f,
|
||||
9.90243902e-01f, 8.03921569e-01f, 1.06883721e+02f, 8.70445344e-01f,
|
||||
9.68627451e-01f, 1.95272727e+02f, 6.11111111e-01f, 7.05882353e-01f
|
||||
});
|
||||
|
||||
|
||||
auto actual = NDArrayFactory::create<float>('c', { 5,4,3 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, &rgbs);
|
||||
ctx.setOutputArray(0, &actual);
|
||||
|
||||
nd4j::ops::rgb_to_hsv op;
|
||||
auto status = op.execute(&ctx);
|
||||
#if 0
|
||||
//visual check
|
||||
rgbs.printBuffer("rgbs ");
|
||||
actual.printBuffer("HSV ");
|
||||
expected.printBuffer("exp");
|
||||
#endif
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_rgb_to_hsv_2) {
|
||||
/*
|
||||
swapped_rgbs=rgbs.swapaxes(1,2).ravel()
|
||||
swapped_hsvs=hsvs.swapaxes(1,2).ravel()
|
||||
*/
|
||||
auto rgbs = NDArrayFactory::create<float>('c', { 5,3,4 },
|
||||
{
|
||||
213.f, 121.f, 18.f, 235.f, 220.f, 180.f, 245.f, 76.f, 164.f, 180.f, 75.f, 74.f, 168.f,
|
||||
191.f, 207.f, 77.f, 50.f, 132.f, 37.f, 250.f, 233.f, 100.f, 245.f, 182.f, 111.f, 193.f,
|
||||
168.f, 48.f, 52.f, 147.f, 103.f, 191.f, 59.f, 137.f, 121.f, 187.f, 53.f, 156.f, 244.f,
|
||||
221.f, 82.f, 37.f, 90.f, 98.f, 239.f, 118.f, 7.f, 243.f, 12.f, 2.f, 79.f, 70.f,
|
||||
209.f, 115.f, 247.f, 152.f, 192.f, 205.f, 32.f, 180.f
|
||||
});
|
||||
auto expected = NDArrayFactory::create<float>('c', { 5,3,4 },
|
||||
{
|
||||
6.75000000e+01f, 1.80000000e+02f, 1.35066079e+02f, 7.45341615e-01f,
|
||||
2.54545455e-01f, 3.27777778e-01f, 9.26530612e-01f, 6.85106383e-01f,
|
||||
8.62745098e-01f, 7.05882353e-01f, 9.60784314e-01f, 9.21568627e-01f,
|
||||
2.78688525e+02f, 2.10989011e+01f, 2.89038462e+02f, 1.56416185e+02f,
|
||||
7.85407725e-01f, 4.76439791e-01f, 8.48979592e-01f, 6.92000000e-01f,
|
||||
9.13725490e-01f, 7.49019608e-01f, 9.60784314e-01f, 9.80392157e-01f,
|
||||
3.52881356e+02f, 1.07142857e+01f, 3.43384615e+02f, 1.78321678e+02f,
|
||||
5.31531532e-01f, 2.90155440e-01f, 3.86904762e-01f, 7.48691099e-01f,
|
||||
4.35294118e-01f, 7.56862745e-01f, 6.58823529e-01f, 7.49019608e-01f,
|
||||
2.30645161e+02f, 3.19159664e+02f, 2.10126582e+01f, 2.90896552e+02f,
|
||||
7.78242678e-01f, 7.62820513e-01f, 9.71311475e-01f, 5.96707819e-01f,
|
||||
9.37254902e-01f, 6.11764706e-01f, 9.56862745e-01f, 9.52941176e-01f,
|
||||
1.74822335e+02f, 2.06600985e+02f, 1.06883721e+02f, 1.95272727e+02f,
|
||||
9.42583732e-01f, 9.90243902e-01f, 8.70445344e-01f, 6.11111111e-01f,
|
||||
8.19607843e-01f, 8.03921569e-01f, 9.68627451e-01f, 7.05882353e-01f
|
||||
});
|
||||
|
||||
|
||||
auto actual = NDArrayFactory::create<float>('c', { 5,3,4 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, &rgbs);
|
||||
ctx.setOutputArray(0, &actual);
|
||||
ctx.setIArguments({ 1 });
|
||||
nd4j::ops::rgb_to_hsv op;
|
||||
auto status = op.execute(&ctx);
|
||||
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_rgb_to_hsv_3) {
|
||||
/*
|
||||
2D
|
||||
*/
|
||||
auto rgbs = NDArrayFactory::create<float>('c', { 8,3 },
|
||||
{ 130.f, 61.f, 239.f, 117.f, 16.f, 168.f, 181.f, 223.f, 0.f, 49.f, 195.f, 195.f, 131.f,
|
||||
153.f, 78.f, 86.f, 21.f, 209.f, 101.f, 14.f, 107.f, 191.f, 98.f, 210.f });
|
||||
auto expected = NDArrayFactory::create<float>('c', { 8,3 },
|
||||
{ 263.25842697f, 0.74476987f, 0.9372549f, 279.86842105f,
|
||||
0.9047619f, 0.65882353f, 71.30044843f, 1.f,
|
||||
0.8745098f, 180.f, 0.74871795f, 0.76470588f,
|
||||
77.6f, 0.49019608f, 0.6f, 260.74468085f,
|
||||
0.89952153f, 0.81960784f, 296.12903226f, 0.86915888f,
|
||||
0.41960784f, 289.82142857f, 0.53333333f, 0.82352941f });
|
||||
|
||||
|
||||
auto actual = NDArrayFactory::create<float>('c', { 8,3 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, &rgbs);
|
||||
ctx.setOutputArray(0, &actual);
|
||||
|
||||
nd4j::ops::rgb_to_hsv op;
|
||||
auto status = op.execute(&ctx);
|
||||
#if 0
|
||||
//visual check
|
||||
rgbs.printBuffer("rgbs ");
|
||||
actual.printBuffer("HSV ");
|
||||
expected.printBuffer("exp");
|
||||
#endif
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_rgb_to_hsv_4) {
|
||||
/*
|
||||
2D
|
||||
*/
|
||||
auto rgbs = NDArrayFactory::create<float>('c', { 3,8 },
|
||||
{ 130.f, 117.f, 181.f, 49.f, 131.f, 86.f, 101.f, 191.f, 61.f, 16.f, 223.f, 195.f, 153.f,
|
||||
21.f, 14.f, 98.f, 239.f, 168.f, 0.f, 195.f, 78.f, 209.f, 107.f, 210.f });
|
||||
auto expected = NDArrayFactory::create<float>('c', { 3, 8 },
|
||||
{ 263.25842697f, 279.86842105f, 71.30044843f, 180.f,
|
||||
77.6f, 260.74468085f, 296.12903226f, 289.82142857f,
|
||||
0.74476987f, 0.9047619f, 1.f, 0.74871795f,
|
||||
0.49019608f, 0.89952153f, 0.86915888f, 0.53333333f,
|
||||
0.9372549f, 0.65882353f, 0.8745098f, 0.76470588f,
|
||||
0.6f, 0.81960784f, 0.41960784f, 0.82352941f });
|
||||
|
||||
|
||||
auto actual = NDArrayFactory::create<float>('c', { 3, 8 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, &rgbs);
|
||||
ctx.setOutputArray(0, &actual);
|
||||
ctx.setIArguments({ 0 });
|
||||
nd4j::ops::rgb_to_hsv op;
|
||||
auto status = op.execute(&ctx);
|
||||
#if 0
|
||||
//visual check
|
||||
rgbs.printBuffer("rgbs ");
|
||||
actual.printBuffer("HSV ");
|
||||
expected.printBuffer("exp");
|
||||
#endif
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_rgb_to_hsv_5) {
|
||||
/*
|
||||
|
||||
*/
|
||||
auto rgbs = NDArrayFactory::create<float>('c', { 3 },
|
||||
{ 213.f, 220.f, 164.f });
|
||||
auto expected = NDArrayFactory::create<float>('c', { 3 },
|
||||
{ 6.75000000e+01f, 2.54545455e-01f, 8.62745098e-01f });
|
||||
|
||||
|
||||
auto actual = NDArrayFactory::create<float>('c', { 3 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, &rgbs);
|
||||
ctx.setOutputArray(0, &actual);
|
||||
|
||||
nd4j::ops::rgb_to_hsv op;
|
||||
auto status = op.execute(&ctx);
|
||||
#if 0
|
||||
//visual check
|
||||
rgbs.printBuffer("rgbs ");
|
||||
actual.printBuffer("HSV ");
|
||||
expected.printBuffer("exp");
|
||||
#endif
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_rgb_to_hsv_6) {
|
||||
/*
|
||||
|
||||
*/
|
||||
auto rgbs = NDArrayFactory::create<float>('c', { 3,8 },
|
||||
{ 130.f, 117.f, 181.f, 49.f, 131.f, 86.f, 101.f, 191.f, 61.f, 16.f, 223.f, 195.f, 153.f,
|
||||
21.f, 14.f, 98.f, 239.f, 168.f, 0.f, 195.f, 78.f, 209.f, 107.f, 210.f });
|
||||
|
||||
auto expected = NDArrayFactory::create<float>('c', { 3 },
|
||||
{ 263.25842697f, 0.74476987f, 0.9372549f });
|
||||
|
||||
//get subarray
|
||||
std::unique_ptr<NDArray> subArrRgbs(rgbs.subarray({ NDIndex::all(), NDIndex::point(0) }));
|
||||
subArrRgbs->reshapei({ 3 });
|
||||
#if 0
|
||||
//[RANK][SHAPE][STRIDES][OPTIONS][EWS][ORDER]
|
||||
subArrRgbs->printShapeInfo("subArrRgbs");
|
||||
#endif
|
||||
auto actual = NDArrayFactory::create<float>('c', { 3 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, subArrRgbs.get());
|
||||
ctx.setOutputArray(0, &actual);
|
||||
ctx.setIArguments({ 0 });
|
||||
nd4j::ops::rgb_to_hsv op;
|
||||
auto status = op.execute(&ctx);
|
||||
#if 0
|
||||
//visual check
|
||||
subArrRgbs->printBuffer("subArrRgbs ");
|
||||
actual.printBuffer("HSV ");
|
||||
expected.printBuffer("exp");
|
||||
#endif
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_hsv_to_rgb_1) {
|
||||
/*
|
||||
using the same numbers of rgb_to_hsv_1 test
|
||||
*/
|
||||
auto expected = NDArrayFactory::create<float>('c', { 5,4,3 },
|
||||
{ 213.f, 220.f, 164.f, 121.f, 180.f, 180.f, 18.f, 245.f, 75.f, 235.f, 76.f, 74.f, 168.f,
|
||||
50.f, 233.f, 191.f, 132.f, 100.f, 207.f, 37.f, 245.f, 77.f, 250.f, 182.f, 111.f, 52.f,
|
||||
59.f, 193.f, 147.f, 137.f, 168.f, 103.f, 121.f, 48.f, 191.f, 187.f, 53.f, 82.f, 239.f,
|
||||
156.f, 37.f, 118.f, 244.f, 90.f, 7.f, 221.f, 98.f, 243.f, 12.f, 209.f, 192.f, 2.f,
|
||||
115.f, 205.f, 79.f, 247.f, 32.f, 70.f, 152.f, 180.f }
|
||||
);
|
||||
auto hsvs = NDArrayFactory::create<float>('c', { 5,4,3 },
|
||||
{
|
||||
6.75000000e+01f, 2.54545455e-01f, 8.62745098e-01f, 1.80000000e+02f,
|
||||
3.27777778e-01f, 7.05882353e-01f, 1.35066079e+02f, 9.26530612e-01f,
|
||||
9.60784314e-01f, 7.45341615e-01f, 6.85106383e-01f, 9.21568627e-01f,
|
||||
2.78688525e+02f, 7.85407725e-01f, 9.13725490e-01f, 2.10989011e+01f,
|
||||
4.76439791e-01f, 7.49019608e-01f, 2.89038462e+02f, 8.48979592e-01f,
|
||||
9.60784314e-01f, 1.56416185e+02f, 6.92000000e-01f, 9.80392157e-01f,
|
||||
3.52881356e+02f, 5.31531532e-01f, 4.35294118e-01f, 1.07142857e+01f,
|
||||
2.90155440e-01f, 7.56862745e-01f, 3.43384615e+02f, 3.86904762e-01f,
|
||||
6.58823529e-01f, 1.78321678e+02f, 7.48691099e-01f, 7.49019608e-01f,
|
||||
2.30645161e+02f, 7.78242678e-01f, 9.37254902e-01f, 3.19159664e+02f,
|
||||
7.62820513e-01f, 6.11764706e-01f, 2.10126582e+01f, 9.71311475e-01f,
|
||||
9.56862745e-01f, 2.90896552e+02f, 5.96707819e-01f, 9.52941176e-01f,
|
||||
1.74822335e+02f, 9.42583732e-01f, 8.19607843e-01f, 2.06600985e+02f,
|
||||
9.90243902e-01f, 8.03921569e-01f, 1.06883721e+02f, 8.70445344e-01f,
|
||||
9.68627451e-01f, 1.95272727e+02f, 6.11111111e-01f, 7.05882353e-01f
|
||||
});
|
||||
|
||||
|
||||
auto actual = NDArrayFactory::create<float>('c', { 5,4,3 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, &hsvs);
|
||||
ctx.setOutputArray(0, &actual);
|
||||
|
||||
nd4j::ops::hsv_to_rgb op;
|
||||
auto status = op.execute(&ctx);
|
||||
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_hsv_to_rgb_2) {
|
||||
/*
|
||||
using the same numbers of hsv_to_rgb_2
|
||||
*/
|
||||
auto expected = NDArrayFactory::create<float>('c', { 5,3,4 },
|
||||
{ 213.f, 121.f, 18.f, 235.f, 220.f, 180.f, 245.f, 76.f, 164.f, 180.f, 75.f, 74.f, 168.f,
|
||||
191.f, 207.f, 77.f, 50.f, 132.f, 37.f, 250.f, 233.f, 100.f, 245.f, 182.f, 111.f, 193.f,
|
||||
168.f, 48.f, 52.f, 147.f, 103.f, 191.f, 59.f, 137.f, 121.f, 187.f, 53.f, 156.f, 244.f,
|
||||
221.f, 82.f, 37.f, 90.f, 98.f, 239.f, 118.f, 7.f, 243.f, 12.f, 2.f, 79.f, 70.f,
|
||||
209.f, 115.f, 247.f, 152.f, 192.f, 205.f, 32.f, 180.f }
|
||||
);
|
||||
auto hsvs = NDArrayFactory::create<float>('c', { 5,3,4 },
|
||||
{
|
||||
6.75000000e+01f, 1.80000000e+02f, 1.35066079e+02f, 7.45341615e-01f,
|
||||
2.54545455e-01f, 3.27777778e-01f, 9.26530612e-01f, 6.85106383e-01f,
|
||||
8.62745098e-01f, 7.05882353e-01f, 9.60784314e-01f, 9.21568627e-01f,
|
||||
2.78688525e+02f, 2.10989011e+01f, 2.89038462e+02f, 1.56416185e+02f,
|
||||
7.85407725e-01f, 4.76439791e-01f, 8.48979592e-01f, 6.92000000e-01f,
|
||||
9.13725490e-01f, 7.49019608e-01f, 9.60784314e-01f, 9.80392157e-01f,
|
||||
3.52881356e+02f, 1.07142857e+01f, 3.43384615e+02f, 1.78321678e+02f,
|
||||
5.31531532e-01f, 2.90155440e-01f, 3.86904762e-01f, 7.48691099e-01f,
|
||||
4.35294118e-01f, 7.56862745e-01f, 6.58823529e-01f, 7.49019608e-01f,
|
||||
2.30645161e+02f, 3.19159664e+02f, 2.10126582e+01f, 2.90896552e+02f,
|
||||
7.78242678e-01f, 7.62820513e-01f, 9.71311475e-01f, 5.96707819e-01f,
|
||||
9.37254902e-01f, 6.11764706e-01f, 9.56862745e-01f, 9.52941176e-01f,
|
||||
1.74822335e+02f, 2.06600985e+02f, 1.06883721e+02f, 1.95272727e+02f,
|
||||
9.42583732e-01f, 9.90243902e-01f, 8.70445344e-01f, 6.11111111e-01f,
|
||||
8.19607843e-01f, 8.03921569e-01f, 9.68627451e-01f, 7.05882353e-01f
|
||||
});
|
||||
|
||||
|
||||
auto actual = NDArrayFactory::create<float>('c', { 5,3,4 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, &hsvs);
|
||||
ctx.setOutputArray(0, &actual);
|
||||
ctx.setIArguments({ 1 });
|
||||
nd4j::ops::hsv_to_rgb op;
|
||||
auto status = op.execute(&ctx);
|
||||
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_hsv_to_rgb_3) {
|
||||
/*
|
||||
2D
|
||||
*/
|
||||
auto expected = NDArrayFactory::create<float>('c', { 8,3 },
|
||||
{ 130.f, 61.f, 239.f, 117.f, 16.f, 168.f, 181.f, 223.f, 0.f, 49.f, 195.f, 195.f, 131.f,
|
||||
153.f, 78.f, 86.f, 21.f, 209.f, 101.f, 14.f, 107.f, 191.f, 98.f, 210.f });
|
||||
auto hsvs = NDArrayFactory::create<float>('c', { 8,3 },
|
||||
{ 263.25842697f, 0.74476987f, 0.9372549f, 279.86842105f,
|
||||
0.9047619f, 0.65882353f, 71.30044843f, 1.f,
|
||||
0.8745098f, 180.f, 0.74871795f, 0.76470588f,
|
||||
77.6f, 0.49019608f, 0.6f, 260.74468085f,
|
||||
0.89952153f, 0.81960784f, 296.12903226f, 0.86915888f,
|
||||
0.41960784f, 289.82142857f, 0.53333333f, 0.82352941f });
|
||||
|
||||
|
||||
auto actual = NDArrayFactory::create<float>('c', { 8,3 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, &hsvs);
|
||||
ctx.setOutputArray(0, &actual);
|
||||
|
||||
nd4j::ops::hsv_to_rgb op;
|
||||
auto status = op.execute(&ctx);
|
||||
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_hsv_to_rgb_4) {
|
||||
/*
|
||||
2D
|
||||
*/
|
||||
auto expected = NDArrayFactory::create<float>('c', { 3,8 },
|
||||
{ 130.f, 117.f, 181.f, 49.f, 131.f, 86.f, 101.f, 191.f, 61.f, 16.f, 223.f, 195.f, 153.f,
|
||||
21.f, 14.f, 98.f, 239.f, 168.f, 0.f, 195.f, 78.f, 209.f, 107.f, 210.f });
|
||||
auto hsvs = NDArrayFactory::create<float>('c', { 3,8 },
|
||||
{ 263.25842697f, 279.86842105f, 71.30044843f, 180.f,
|
||||
77.6f, 260.74468085f, 296.12903226f, 289.82142857f,
|
||||
0.74476987f, 0.9047619f, 1.f, 0.74871795f,
|
||||
0.49019608f, 0.89952153f, 0.86915888f, 0.53333333f,
|
||||
0.9372549f, 0.65882353f, 0.8745098f, 0.76470588f,
|
||||
0.6f, 0.81960784f, 0.41960784f, 0.82352941f });
|
||||
|
||||
|
||||
auto actual = NDArrayFactory::create<float>('c', { 3,8 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, &hsvs);
|
||||
ctx.setOutputArray(0, &actual);
|
||||
ctx.setIArguments({ 0 });
|
||||
nd4j::ops::hsv_to_rgb op;
|
||||
auto status = op.execute(&ctx);
|
||||
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_hsv_to_rgb_5) {
|
||||
/*
|
||||
|
||||
*/
|
||||
auto expected = NDArrayFactory::create<float>('c', { 3 },
|
||||
{ 213.f, 220.f, 164.f });
|
||||
auto hsvs = NDArrayFactory::create<float>('c', { 3 },
|
||||
{ 6.75000000e+01f, 2.54545455e-01f, 8.62745098e-01f });
|
||||
|
||||
|
||||
auto actual = NDArrayFactory::create<float>('c', { 3 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, &hsvs);
|
||||
ctx.setOutputArray(0, &actual);
|
||||
|
||||
nd4j::ops::hsv_to_rgb op;
|
||||
auto status = op.execute(&ctx);
|
||||
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
|
||||
TEST_F(DeclarableOpsTests16, test_hsv_to_rgb_6) {
|
||||
|
||||
auto expected = NDArrayFactory::create<double>('c', { 3 },
|
||||
{ 130.0, 61.0, 239.0 });
|
||||
auto hsvs = NDArrayFactory::create<double>('c', { 3,8 },
|
||||
{ 263.25842697, 279.86842105, 71.30044843, 180,
|
||||
77.6, 260.74468085, 296.12903226, 289.82142857,
|
||||
0.74476987, 0.9047619, 1., 0.74871795,
|
||||
0.49019608, 0.89952153, 0.86915888, 0.53333333,
|
||||
0.9372549, 0.65882353, 0.8745098, 0.76470588,
|
||||
0.6, 0.81960784, 0.41960784, 0.82352941
|
||||
});
|
||||
|
||||
//get subarray
|
||||
std::unique_ptr<NDArray> subArrHsvs(hsvs.subarray({ NDIndex::all(), NDIndex::point(0) }));
|
||||
subArrHsvs->reshapei({ 3 });
|
||||
#if 0
|
||||
//[RANK][SHAPE][STRIDES][OPTIONS][EWS][ORDER]
|
||||
subArrHsvs->printShapeInfo("subArrHsvs");
|
||||
#endif
|
||||
auto actual = NDArrayFactory::create<double>('c', { 3 });
|
||||
|
||||
Context ctx(1);
|
||||
ctx.setInputArray(0, subArrHsvs.get());
|
||||
ctx.setOutputArray(0, &actual);
|
||||
nd4j::ops::hsv_to_rgb op;
|
||||
auto status = op.execute(&ctx);
|
||||
#if 0
|
||||
//visual check
|
||||
subArrHsvs->printBuffer("subArrHsvs ");
|
||||
actual.printBuffer("rgb ");
|
||||
expected.printBuffer("exp");
|
||||
#endif
|
||||
ASSERT_EQ(ND4J_STATUS_OK, status);
|
||||
ASSERT_TRUE(expected.equalsTo(actual));
|
||||
|
||||
}
|
||||
Loading…
Reference in New Issue