1934 lines
86 KiB
C++
1934 lines
86 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2019 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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// Created by raver on 8/4/2018.
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//
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#include "testlayers.h"
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#include <ops/declarable/CustomOperations.h>
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#include <NDArray.h>
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#include <ops/ops.h>
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#include <GradCheck.h>
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using namespace nd4j;
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class DeclarableOpsTests13 : public testing::Test {
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public:
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DeclarableOpsTests13() {
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//printf("\n");
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//fflush(stdout);
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}
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};
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TEST_F(DeclarableOpsTests13, test_pow_1) {
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auto x = NDArrayFactory::create<float>('c', {2, 2}, {2.f, 2.f, 2.f, 2.f});
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auto y = NDArrayFactory::create<int>('c', {2}, {3, 3});
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auto e = NDArrayFactory::create<float>('c', {2, 2}, {8.f, 8.f, 8.f, 8.f});
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nd4j::ops::Pow op;
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auto result = op.execute({&x, &y}, {}, {});
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ASSERT_EQ(Status::OK(), result->status());
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auto z = result->at(0);
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ASSERT_EQ(e, *z);
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delete result;
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}
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TEST_F(DeclarableOpsTests13, test_empty_range_1) {
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auto start = NDArrayFactory::create<int>(0);
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auto limit = NDArrayFactory::create<int>(0);
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nd4j::ops::range op;
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auto result = op.execute({&start, &limit}, {}, {});
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ASSERT_EQ(Status::OK(), result->status());
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auto z = result->at(0);
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ASSERT_TRUE(z->isEmpty());
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delete result;
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}
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TEST_F(DeclarableOpsTests13, test_empty_range_2) {
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nd4j::ops::range op;
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auto result = op.execute({}, {1.0, 1.0}, {});
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ASSERT_EQ(Status::OK(), result->status());
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auto z = result->at(0);
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ASSERT_TRUE(z->isEmpty());
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delete result;
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}
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TEST_F(DeclarableOpsTests13, test_empty_range_3) {
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nd4j::ops::range op;
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auto result = op.execute({}, {}, {1, 1});
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ASSERT_EQ(Status::OK(), result->status());
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auto z = result->at(0);
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ASSERT_TRUE(z->isEmpty());
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delete result;
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}
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TEST_F(DeclarableOpsTests13, test_argmax_edge_1) {
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auto ctx = new Context(1);
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auto arr = NDArrayFactory::create_<float>('c', {1024,1});
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ctx->setInputArray(0, arr, true);
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ctx->setOutputArray(0, NDArrayFactory::create_<Nd4jLong >('c', {1}), true);
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ctx->setInputArray(1, NDArrayFactory::create_<Nd4jLong >(0), true); //Axis 0
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nd4j::ops::argmax op;
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auto result = op.execute(ctx);
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ASSERT_EQ(Status::OK(), result);
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//nd4j_printf("Done\n","");
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delete ctx;
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}
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TEST_F(DeclarableOpsTests13, test_add_1) {
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auto x = NDArrayFactory::create<float>('c', {1, 768});
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auto y = NDArrayFactory::create<float>('c', {768});
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auto e = NDArrayFactory::create<float>('c', {1, 768});;
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y. assign(1.0f);
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e.assign(1.0f);
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x += y;
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ASSERT_EQ(e, x);
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}
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TEST_F(DeclarableOpsTests13, test_listdiff_1) {
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auto x = NDArrayFactory::create<int>('c', {4}, {0, 1, 2, 3});
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auto y = NDArrayFactory::create<int>('c', {2}, {3, 1});
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auto od = NDArrayFactory::create<int>('c', {2});
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auto oi = NDArrayFactory::create<int>('c', {2});
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nd4j::ops::listdiff op;
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auto result = op.execute({&x, &y}, {&od, &oi}, {}, {}, {});
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ASSERT_EQ(Status::OK(), result);
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}
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TEST_F(DeclarableOpsTests13, test_greater_1) {
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auto x = NDArrayFactory::create<float>('c', {3, 1});
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auto y = NDArrayFactory::create<float>('c', {1, 4});
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nd4j::ops::greater op;
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auto result = op.execute({&x, &y}, {}, {});
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ASSERT_EQ(Status::OK(), result->status());
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delete result;
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}
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TEST_F(DeclarableOpsTests13, test_eval_reduction_shape_1) {
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Nd4jLong axis = 0L;
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auto x = NDArrayFactory::create<Nd4jLong>('c', {2}, {4, 2});
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auto y = NDArrayFactory::create<Nd4jLong>('c', {1}, {axis});
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auto exp = NDArrayFactory::create<Nd4jLong>('c', {2}, {1, 2});
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nd4j::ops::evaluate_reduction_shape op;
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auto result = op.execute({&x, &y}, {}, {}, {true});
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ASSERT_EQ(Status::OK(), result->status());
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auto z = result->at(0);
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ASSERT_EQ(exp, *z);
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delete result;
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}
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TEST_F(DeclarableOpsTests13, test_or_1) {
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NDArray x('c', {4}, {false, true, false, true}, nd4j::DataType::BOOL);
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NDArray y('c', {4}, {false, false, true, true}, nd4j::DataType::BOOL);
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NDArray e('c', {4}, {false, true, true, true}, nd4j::DataType::BOOL);
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NDArray z('c', {4}, nd4j::DataType::BOOL);
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x.applyPairwiseTransform(pairwise::Or, &y, &z, nullptr);
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ASSERT_EQ(e, z);
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}
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TEST_F(DeclarableOpsTests13, test_and_1) {
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auto x = NDArrayFactory::create<bool>('c', {4}, {false, true, false, true});
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auto y = NDArrayFactory::create<bool>('c', {4}, {false, false, true, true});
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auto e = NDArrayFactory::create<bool>('c', {4}, {false, false, false, true});
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auto z = NDArrayFactory::create<bool>('c', {4});
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x.applyPairwiseTransform(pairwise::And, &y, &z, nullptr);
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ASSERT_EQ(e, z);
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}
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TEST_F(DeclarableOpsTests13, test_xor_1) {
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auto x = NDArrayFactory::create<bool>('c', {4}, {false, true, false, true});
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auto y = NDArrayFactory::create<bool>('c', {4}, {false, false, true, true});
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auto e = NDArrayFactory::create<bool>('c', {4}, {false, true, true, false});
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auto z = NDArrayFactory::create<bool>('c', {4});
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x.applyPairwiseTransform(pairwise::Xor, &y, &z, nullptr);
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ASSERT_EQ(e, z);
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}
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TEST_F(DeclarableOpsTests13, BarnesHutTsne_GainsTest_1) {
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auto x = NDArrayFactory::create<double>('c', {2,3}, {1,2,3, 4, 5, 6});
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auto y = NDArrayFactory::create<double>('c', {2,3}, {1,-2,3, -4, 5, -6});
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auto eps = NDArrayFactory::create<double>('c', {2,3}, {-0.1, 0.2, -0.3, 0.4, -0.5, 0.6});
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auto exp = NDArrayFactory::create<double>('c', {2,3}, {1.2,2.2,3.2,4.2,5.2,6.2});
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nd4j::ops::barnes_gains op;
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auto result = op.execute({&x, &y, &eps}, {}, {});
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ASSERT_EQ(result->status(), Status::OK());
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//result->at(0)->printBuffer("Gains out");
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ASSERT_TRUE(exp.equalsTo(result->at(0)));
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delete result;
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}
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TEST_F(DeclarableOpsTests13, BarnesHutTsne_GainsTest_2) {
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auto x = NDArrayFactory::create<double>('c', {2,3}, {1, -2, 3, -4, 5, -6});
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auto y = NDArrayFactory::create<double>('c', {2,3}, {1, -2, 3, -4, 5, -6});
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auto eps = NDArrayFactory::create<double>('c', {2,3}, {-0.1, 0.2, -0.3, 0.4, -0.5, 0.6});
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auto exp = NDArrayFactory::create<double>('c', {2,3}, {1.2, 0.01, 3.2, 0.01, 5.2, 0.01});
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nd4j::ops::barnes_gains op;
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auto result = op.execute({&x, &y, &eps}, {}, {});
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ASSERT_EQ(result->status(), Status::OK());
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//result->at(0)->printBuffer("Gains out");
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ASSERT_TRUE(exp.equalsTo(result->at(0)));
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//ASSERT_EQ(e, z);
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delete result;
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}
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TEST_F(DeclarableOpsTests13, BarnesHutTsne_GainsTest_3) {
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auto x = NDArrayFactory::create<double>('c', {2,3}, {-1, 2, -3, 4, -5, 6});
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auto y = NDArrayFactory::create<double>('c', {2,3}, {-0.1,-2,3, -4, -0.5, -6});
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auto eps = NDArrayFactory::create<double>('c', {2,3}, {-0.1, 0.2, -0.3, 0.4, -0.5, 0.6});
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auto exp = NDArrayFactory::create<double>('c', {2,3}, {0.01, 2.2, 0.01, 4.2, 0.01, 6.2});
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nd4j::ops::barnes_gains op;
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auto result = op.execute({&x, &y, &eps}, {}, {});
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ASSERT_EQ(result->status(), Status::OK());
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//result->at(0)->printBuffer("Gains out");
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ASSERT_TRUE(exp.equalsTo(result->at(0)));
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delete result;
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}
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TEST_F(DeclarableOpsTests13, BarnesHutTsne_EdgeForceTest_1) {
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auto data = NDArrayFactory::create<double>('c', {5,4});
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auto rows = NDArrayFactory::create<int>('c', {2}, {2, 3});
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auto cols = NDArrayFactory::create<int>('c', {5}, {0, 2, 1, 4, 3});
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auto vals = NDArrayFactory::create<double>('c', {5}, {10., 20., 30., 40., 50.});
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//auto buf = NDArrayFactory::create<double>('c', {4});
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auto exp1 = NDArrayFactory::create<double>('c', {5,4}, {-1.846154, -1.846154, -1.846154, -1.846154, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.});
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//auto exp2 = NDArrayFactory::create<double>({-4., -4., -4., -4.
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//std::vector<NDArray*> exp({&exp1, &exp2});
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data.linspace(1);
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// auto y = NDArrayFactory::create<double>('c', {2,3}, {-0.1,-2,3, -4, -0.5, -6});
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// auto eps = NDArrayFactory::create<double>('c', {2,3}, {-0.1, 0.2, -0.3, 0.4, -0.5, 0.6});
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// auto exp = NDArrayFactory::create<double>('c', {2,3}, {1, 2, 1, 2, 2, 2});
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nd4j::ops::barnes_edge_forces op;
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auto result = op.execute({&rows, &cols, &vals, &data}, {}, {1});
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ASSERT_EQ(result->status(), Status::OK());
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//result->at(0)->printBuffer("Output");
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ASSERT_TRUE(exp1.equalsTo(result->at(0)));
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delete result;
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}
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TEST_F(DeclarableOpsTests13, BarnesHutTsne_EdgeForceTest_2) {
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auto data = NDArrayFactory::create<double>('c', {5,4});
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auto rows = NDArrayFactory::create<int>('c', {3}, {1,2,3});
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auto cols = NDArrayFactory::create<int>('c', {5}, {1, 2, 0, 4, 3});
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auto vals = NDArrayFactory::create<double>('c', {5}, {10., 20., 30., 40., 50.});
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//auto buf = NDArrayFactory::create<double>('c', {4});
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auto exp = NDArrayFactory::create<double>('c', {5,4}, {-0.622568, -0.622568, -0.622568, -0.622568, 1.846154, 1.846154, 1.846154, 1.846154, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.});
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//auto exp2 = NDArrayFactory::create<double>({-4., -4., -4., -4.
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//std::vector<NDArray*> exp({&exp1, &exp2});
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data.linspace(1);
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// auto y = NDArrayFactory::create<double>('c', {2,3}, {-0.1,-2,3, -4, -0.5, -6});
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// auto eps = NDArrayFactory::create<double>('c', {2,3}, {-0.1, 0.2, -0.3, 0.4, -0.5, 0.6});
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// auto exp = NDArrayFactory::create<double>('c', {2,3}, {1, 2, 1, 2, 2, 2});
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nd4j::ops::barnes_edge_forces op;
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auto result = op.execute({&rows, &cols, &vals, &data}, {}, {2});
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ASSERT_EQ(result->status(), Status::OK());
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//result->at(0)->printBuffer("Output");
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ASSERT_TRUE(exp.equalsTo(result->at(0)));
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delete result;
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}
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TEST_F(DeclarableOpsTests13, BarnesHutTsne_EdgeForceTest_3) {
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auto data = NDArrayFactory::create<double>('c', {11, 5}, {0.3, 0.2625, 0.2674, 0.8604, 0.4803, 0.1096, 0.795, 0.5918, 0.2738, 0.952, 0.969, 0.8586, 0.8088, 0.5338, 0.5961, 0.7187, 0.463, 0.0867, 0.7748, 0.4802, 0.2493, 0.3227, 0.3064, 0.698, 0.7977, 0.7674, 0.168, 0.3107, 0.0217, 0.138, 0.8619, 0.8413, 0.5285, 0.9703, 0.6774, 0.2624, 0.4374, 0.1569, 0.1107, 0.0601, 0.4094, 0.9564, 0.5994, 0.8279, 0.3859, 0.6202, 0.7604, 0.0788, 0.0865, 0.7445, 0.6548, 0.3385, 0.0582, 0.6249, 0.7432});
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auto rows = NDArrayFactory::create<int>({0, 9, 18, 27, 36, 45, 54, 63, 72, 81, 90, 99});
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auto cols = NDArrayFactory::create<int>({4, 3, 10, 8, 6, 7, 1, 5, 9, 4, 9, 8, 10, 2, 0, 6, 7, 3, 6, 8, 3, 9, 10, 1, 4, 0, 5, 10, 0, 4, 6, 8, 9, 2, 5, 7, 0, 10, 3, 1, 8, 9, 6, 7, 2, 7, 9, 3, 10, 0, 4, 2, 8, 1, 2, 8, 3, 10, 0, 4, 9, 1, 5, 5, 9, 0, 3, 10, 4, 8, 1, 2, 6, 2, 0, 3, 4, 1, 10, 9, 7, 10, 1, 3, 7, 4, 5, 2, 8, 6, 3, 4, 0, 9, 6, 5, 8, 7, 1});
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auto vals = NDArrayFactory::create<double>({0.6199614579042966, 0.19644097697184246, 0.13824979367331638, 0.01949900138247239, 0.008923198738222747, 0.008392793826291798, 0.0033348224714784204, 0.0026246189757042166, 0.0025733360563748838, 0.5877136110798608, 0.28250257562439585, 0.08098135424273815, 0.014862718272075049, 0.01219187321450782, 0.01152346362368888, 0.004243137936786281, 0.0034626999030188577, 0.0025185661029283168, 0.6777005651521399, 0.18321248222489303, 0.04018202465629351, 0.02941935889988646, 0.02164146250842832, 0.019898422145651618, 0.011683461395713935, 0.008439076090480863, 0.007823146926512332, 0.6770900431883232, 0.16617511239723026, 0.06039349887686468, 0.04650913399744179, 0.016886531410284355, 0.014591049666869658, 0.006407638669806174, 0.006074413005122801, 0.0058725787880570205, 0.6278185083409108, 0.235127797795446, 0.07023700015217448, 0.030885483448633774, 0.01229522088606573, 0.009238279699136107, 0.008219511168822047, 0.004303744819835723, 0.0018744536889749907, 0.7122603898978483, 0.07862620103245824, 0.07061257369349086, 0.06721483653169834, 0.028957853952131768, 0.01778978123182596, 0.01481713955181034, 0.005492728917348627, 0.0042284951913875955, 0.5266844101016999, 0.3304104787383107, 0.10930017433210941, 0.018514917515240075, 0.006969360999637938, 0.0063776901975396, 0.0010590388116165708, 6.526830884629785E-4, 3.1246215383067865E-5, 0.7176179284835663, 0.08741734015883978, 0.05927699083866909, 0.04663169573956976, 0.03287576269194147, 0.02993912340339554, 0.013365238657916641, 0.010616858763291145, 0.002259061262810172, 0.6891905160321706, 0.1397658294110526, 0.05438284759722162, 0.05437184733708826, 0.028683289714498808, 0.020986120697576355, 0.007218358114741088, 0.0032834770669826364, 0.002117714028667893, 0.6823873496503976, 0.1345267083671607, 0.08712863515505885, 0.04286621088946242, 0.02544804597749639, 0.01689343932533317, 0.007219134659004873, 0.0019232929717404616, 0.0016071830043453991, 0.6425809622897437, 0.18474464886441516, 0.10897036475298316, 0.03466939253836615, 0.013288054277817787, 0.005149178177380355, 0.0037974063158903518, 0.0037851733015991287, 0.0030148194818042273});
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//auto buf = NDArrayFactory::create<double>('c', {4});
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auto exp = NDArrayFactory::create<double>('c', {11, 5}, {-0.080205, -0.085862, 0.024045, 0.133551, -0.199896, -0.170597, 0.187301, 0.205824, -0.165268, 0.131228, 0.155135, 0.021446, 0.217583, -0.262873, -0.021075, 0.114537, 0.088023, -0.039205, 0.087984, -0.179565, -0.132683, 0.003677, 0.072081, -0.068737, 0.204481, 0.287223, -0.193989, 0.104569, -0.123401, -0.036368, 0.086745, 0.002961, -0.091327, 0.234853, 0.120270, -0.304006, 0.128305, -0.084867, -0.017550, -0.130837, -0.288569, 0.124679, 0.054078, -0.034187, -0.192599, 0.033196, 0.228182, -0.044972, -0.314217, 0.020287, 0.054427, -0.078887, -0.078246, -0.104543, 0.169803});
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//auto exp2 = NDArrayFactory::create<double>({-4., -4., -4., -4.
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//std::vector<NDArray*> exp({&exp1, &exp2});
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//data.assign(1.0); //linspace(1);
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// auto y = NDArrayFactory::create<double>('c', {2,3}, {-0.1,-2,3, -4, -0.5, -6});
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// auto eps = NDArrayFactory::create<double>('c', {2,3}, {-0.1, 0.2, -0.3, 0.4, -0.5, 0.6});
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// auto exp = NDArrayFactory::create<double>('c', {2,3}, {1, 2, 1, 2, 2, 2});
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nd4j::ops::barnes_edge_forces op;
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auto result = op.execute({&rows, &cols, &vals, &data}, {}, {11});
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//nd4j_printf("rows %lld, cols %lld, vals %lld, res full %lld\n", rows.lengthOf(), cols.lengthOf(), vals.lengthOf(), exp1.lengthOf());
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ASSERT_EQ(result->status(), Status::OK());
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//result->at(0)->printBuffer("Output");
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//exp.printBuffer("Expect");
|
|
//result->at(0)->printShapeInfo("Shape output");
|
|
ASSERT_TRUE(exp.equalsTo(result->at(0)));
|
|
delete result;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests13, BarnesHutTsne_symmetrized_1) {
|
|
// auto data = NDArrayFactory::create<double>('c', {5,4});
|
|
auto rows = NDArrayFactory::create<int>('c', {2}, {0, 1});
|
|
auto cols = NDArrayFactory::create<int>('c', {4}, {0, 1, 1, 0});
|
|
auto vals = NDArrayFactory::create<double>('c', {4}, {20., 30., 40., 50.});
|
|
auto exp = NDArrayFactory::create<double>('c', {1,1}, {20.});
|
|
// data.linspace(1);
|
|
|
|
// auto y = NDArrayFactory::create<double>('c', {2,3}, {-0.1,-2,3, -4, -0.5, -6});
|
|
// auto eps = NDArrayFactory::create<double>('c', {2,3}, {-0.1, 0.2, -0.3, 0.4, -0.5, 0.6});
|
|
// auto exp = NDArrayFactory::create<double>('c', {2,3}, {1, 2, 1, 2, 2, 2});
|
|
nd4j::ops::barnes_symmetrized op;
|
|
auto result = op.execute({&rows, &cols, &vals}, {}, {1});
|
|
ASSERT_EQ(result->status(), Status::OK());
|
|
//result->at(2)->printBuffer("Symmetrized1");
|
|
ASSERT_TRUE(exp.equalsTo(result->at(2)));
|
|
|
|
delete result;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests13, BarnesHutTsne_symmetrized_2) {
|
|
auto rows = NDArrayFactory::create<int>('c', {4}, {0, 2, 2, 3});
|
|
auto cols = NDArrayFactory::create<int>('c', {8}, {0, 1, 1, 0, 0, 1, 1, 1});
|
|
auto vals = NDArrayFactory::create<double>('c', {8}, {20., 30., 40., 50., 120., 130., 140., 150.});
|
|
auto exp = NDArrayFactory::create<double>('c', {1,5}, {20., 15., 15., 20., 20.});
|
|
// data.linspace(1);
|
|
|
|
// auto y = NDArrayFactory::create<double>('c', {2,3}, {-0.1,-2,3, -4, -0.5, -6});
|
|
// auto eps = NDArrayFactory::create<double>('c', {2,3}, {-0.1, 0.2, -0.3, 0.4, -0.5, 0.6});
|
|
// auto exp = NDArrayFactory::create<double>('c', {2,3}, {1, 2, 1, 2, 2, 2});
|
|
nd4j::ops::barnes_symmetrized op;
|
|
auto result = op.execute({&rows, &cols, &vals}, {}, {3});
|
|
ASSERT_EQ(result->status(), Status::OK());
|
|
//result->at(2)->printBuffer("Symmetrized2");
|
|
// ASSERT_TRUE(exp[i]->equalsTo(result->at(i)));
|
|
ASSERT_TRUE(exp.equalsTo(result->at(2)));
|
|
delete result;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests13, BarnesHutTsne_symmetrized_3) {
|
|
auto rows = NDArrayFactory::create<int>('c', {12}, {0, 2, 3, 5, 7, 8, 9, 11, 12, 14, 18, 21});
|
|
auto cols = NDArrayFactory::create<int>('c', {24}, {0, 1, 2, 3, 4, 5, 4, 3, 2, 1, 0, 1, 0, 2, 4, 3, 2, 1, 0, 1, 2, 3, 4, 5});
|
|
auto vals = NDArrayFactory::create<double>('c', {24}, {20., 30., 40., 50., 120., 130., 140., 150.,220., 230., 240., 250., 2120., 2130., 2140., 2150., 320., 330., 340., 350., 3120., 3130., 3140., 3150.});
|
|
auto exp = NDArrayFactory::create<double>('c', {1, 39}, {15.000000, 0.000000, 0.000000, 65.000000, 60.000000, 145.000000, 20.000000, 25.000000, 65.000000, 145.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000});
|
|
// data.linspace(1);
|
|
|
|
// auto y = NDArrayFactory::create<double>('c', {2,3}, {-0.1,-2,3, -4, -0.5, -6});
|
|
// auto eps = NDArrayFactory::create<double>('c', {2,3}, {-0.1, 0.2, -0.3, 0.4, -0.5, 0.6});
|
|
// auto exp = NDArrayFactory::create<double>('c', {2,3}, {1, 2, 1, 2, 2, 2});
|
|
nd4j::ops::barnes_symmetrized op;
|
|
auto result = op.execute({&rows, &cols, &vals}, {}, {11});
|
|
ASSERT_EQ(result->status(), Status::OK());
|
|
//result->at(2)->printBuffer("Symmetrized3");
|
|
//exp.printBuffer("EXPect symm3");
|
|
// ASSERT_TRUE(exp[i]->equalsTo(result->at(i)));
|
|
//ASSERT_TRUE(exp.equalsTo(result->at(0)));
|
|
delete result;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests13, BarnesHutTsne_symmetrized_4) {
|
|
auto rows = NDArrayFactory::create<int>({0, 9, 18, 27, 36, 45, 54, 63, 72, 81, 90, 99});
|
|
auto cols = NDArrayFactory::create<int>({4, 3, 10, 8, 6, 7, 1, 5, 9, 4, 9, 8, 10, 2, 0, 6, 7, 3, 6, 8, 3, 9, 10, 1, 4, 0, 5, 10, 0, 4, 6, 8, 9, 2, 5, 7, 0, 10, 3, 1, 8, 9, 6, 7, 2, 7, 9, 3, 10, 0, 4, 2, 8, 1, 2, 8, 3, 10, 0, 4, 9, 1, 5, 5, 9, 0, 3, 10, 4, 8, 1, 2, 6, 2, 0, 3, 4, 1, 10, 9, 7, 10, 1, 3, 7, 4, 5, 2, 8, 6, 3, 4, 0, 9, 6, 5, 8, 7, 1});
|
|
auto vals = NDArrayFactory::create<double>( {0.6200, 0.1964, 0.1382, 0.0195, 0.0089, 0.0084, 0.0033, 0.0026, 0.0026, 0.5877, 0.2825, 0.0810, 0.0149, 0.0122, 0.0115, 0.0042, 0.0035, 0.0025, 0.6777, 0.1832, 0.0402, 0.0294, 0.0216, 0.0199, 0.0117, 0.0084, 0.0078, 0.6771, 0.1662, 0.0604, 0.0465, 0.0169, 0.0146, 0.0064, 0.0061, 0.0059, 0.6278, 0.2351, 0.0702, 0.0309, 0.0123, 0.0092, 0.0082, 0.0043, 0.0019, 0.7123, 0.0786, 0.0706, 0.0672, 0.0290, 0.0178, 0.0148, 0.0055, 0.0042, 0.5267, 0.3304, 0.1093, 0.0185, 0.0070, 0.0064, 0.0011, 0.0007, 3.1246e-5, 0.7176, 0.0874, 0.0593, 0.0466, 0.0329, 0.0299, 0.0134, 0.0106, 0.0023, 0.6892, 0.1398, 0.0544, 0.0544, 0.0287, 0.0210, 0.0072, 0.0033, 0.0021, 0.6824, 0.1345, 0.0871, 0.0429, 0.0254, 0.0169, 0.0072, 0.0019, 0.0016, 0.6426, 0.1847, 0.1090, 0.0347, 0.0133, 0.0051, 0.0038, 0.0038, 0.0030});
|
|
//auto exp = NDArrayFactory::create<double>('c', {1, 39}, {15.000000, 0.000000, 0.000000, 65.000000, 60.000000, 145.000000, 20.000000, 25.000000, 65.000000, 145.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000});
|
|
// data.linspace(1);
|
|
auto exp4 = NDArrayFactory::create<double>('c', {1, 108}, {0.6239, 0.1813, 0.1236, 0.03695, 0.00795, 0.03385, 0.0074, 0.0158, 0.0013, 0.0042, 0.0074, 0.3093, 0.2085, 0.051, 0.00895, 0.01605, 0.00245, 0.00705, 0.00125, 0.0021, 0.01605, 0.6022, 0.1615, 0.0233,
|
|
0.0183, 0.0108, 0.0068, 0.0042, 0.0113, 0.00115, 0.1813, 0.00125, 0.0233, 0.65985, 0.0653, 0.0779, 0.03565, 0.05085, 0.03835, 0.02625, 0.6239, 0.3093, 0.0068, 0.0653, 0.2099, 0.0205, 0.0173, 0.0073,
|
|
0.0171, 0.0089, 0.0158, 0.0113, 0.03835, 0.71495, 0.04775, 0.03615, 0.0089, 0.00275, 0.0021, 1.5623E-5, 0.00795, 0.00245, 0.6022, 0.0779, 0.0073, 0.5098, 0.0159, 0.00135, 1.5623E-5, 0.03385, 0.00705,
|
|
0.02625, 0.0171, 0.71495, 0.06515, 0.01835, 0.00775, 0.00115, 0.03695, 0.051, 0.1615, 0.03565, 0.0205, 0.00275, 0.5098, 0.00775, 0.0055, 0.0026, 0.0013, 0.2085, 0.0183, 0.05085, 0.0173, 0.04775,
|
|
0.00135, 0.06515, 0.0026, 0.35855, 0.1236, 0.00895, 0.0108, 0.65985, 0.2099, 0.03615, 0.0159, 0.01835, 0.0055, 0.35855});
|
|
// auto y = NDArrayFactory::create<double>('c', {2,3}, {-0.1,-2,3, -4, -0.5, -6});
|
|
// auto eps = NDArrayFactory::create<double>('c', {2,3}, {-0.1, 0.2, -0.3, 0.4, -0.5, 0.6});
|
|
// auto exp = NDArrayFactory::create<double>('c', {2,3}, {1, 2, 1, 2, 2, 2});
|
|
nd4j::ops::barnes_symmetrized op;
|
|
auto result = op.execute({&rows, &cols, &vals}, {}, {11});
|
|
ASSERT_EQ(result->status(), Status::OK());
|
|
auto res = result->at(2);
|
|
// res->printBuffer("Symmetrized4");
|
|
// exp4.printBuffer("Expected sym");
|
|
// nd4j_printf("Total res is {1, %lld}\n", res->lengthOf());
|
|
// nd4j_printf("Expected is {1, %lld}\n", exp4.lengthOf());
|
|
|
|
//exp.printBuffer("EXPect symm3");
|
|
// ASSERT_TRUE(exp[i]->equalsTo(result->at(i)));
|
|
ASSERT_TRUE(exp4.equalsTo(res));
|
|
delete result;
|
|
}
|
|
|
|
TEST_F(DeclarableOpsTests13, CellContains_test_1) {
|
|
|
|
auto corners = NDArrayFactory::create<double>( {0.5384, 0.5640, 0.3449, 0.5257, 0.5505});
|
|
auto width = NDArrayFactory::create<double>({0.4306, 0.3960, 0.4639, 0.5040, 0.4904});
|
|
auto point = NDArrayFactory::create<double>({0.3000, 0.2625, 0.2674, 0.8604, 0.4803});
|
|
//auto exp = NDArrayFactory::create<double>('c', {1, 39}, {15.000000, 0.000000, 0.000000, 65.000000, 60.000000, 145.000000, 20.000000, 25.000000, 65.000000, 145.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000});
|
|
// data.linspace(1);
|
|
|
|
// auto y = NDArrayFactory::create<double>('c', {2,3}, {-0.1,-2,3, -4, -0.5, -6});
|
|
// auto eps = NDArrayFactory::create<double>('c', {2,3}, {-0.1, 0.2, -0.3, 0.4, -0.5, 0.6});
|
|
// auto exp = NDArrayFactory::create<double>('c', {2,3}, {1, 2, 1, 2, 2, 2});
|
|
nd4j::ops::cell_contains op;
|
|
auto result = op.execute({&corners, &width, &point}, {}, {5});
|
|
ASSERT_EQ(result->status(), Status::OK());
|
|
ASSERT_TRUE(result->at(0)->e<bool>(0));
|
|
//result->at(2)->printBuffer("Symmetrized3");
|
|
//exp.printBuffer("EXPect symm3");
|
|
// ASSERT_TRUE(exp[i]->equalsTo(result->at(i)));
|
|
//ASSERT_TRUE(exp.equalsTo(result->at(0)));
|
|
delete result;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, adjustHue_1) {
|
|
|
|
NDArray input('c', {2,2,3}, {0,100,56, 17,220,5, 150,97,230, 255,2,13}, nd4j::DataType::FLOAT32);
|
|
NDArray exp ('c', {2,2,3}, {100,0,44, 208,5,220, 177,230,97, 2,255,244}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::adjust_hue op;
|
|
auto results = op.execute({&input}, {0.5}, {2});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer();
|
|
|
|
ASSERT_TRUE(exp.isSameShape(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, adjustHue_2) {
|
|
|
|
NDArray input('c', {2,2,3}, {0,100,56, 17,220,5, 150,97,230, 255,2,13}, nd4j::DataType::FLOAT32);
|
|
NDArray exp ('c', {2,2,3}, {4,100,0, 146,220,5, 97,123.8,230, 255,2,164.8}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::adjust_hue op;
|
|
auto results = op.execute({&input}, {0.9}, {2});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, adjustHue_3) {
|
|
|
|
NDArray input('c', {2,2,3}, {0,100,56, 17,220,5, 150,97,230, 255,2,13}, nd4j::DataType::FLOAT32);
|
|
NDArray exp ('c', {2,2,3}, {0.,84.,100., 5.,220.,122.0001, 229.8,97.,230., 255.,142.8002,2.}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::adjust_hue op;
|
|
auto results = op.execute({&input}, {-0.9}, {2});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, adjustHue_4) {
|
|
|
|
NDArray input('c', {2,3,2}, {0,17, 100,220, 56,5, 150,255, 97,2, 230,13}, nd4j::DataType::FLOAT32);
|
|
NDArray exp ('c', {2,3,2}, {100,208, 0,5, 44,220, 177,2, 230,255, 97,244}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::adjust_hue op;
|
|
auto results = op.execute({&input}, {0.5}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, adjustHue_5) {
|
|
|
|
NDArray input('c', {3,2,2}, {0,17, 150,255, 100,220, 97,2, 56,5, 230,13}, nd4j::DataType::FLOAT32);
|
|
NDArray exp ('c', {3,2,2}, {100,208, 177,2, 0,5, 230,255, 44,220, 97,244}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::adjust_hue op;
|
|
auto results = op.execute({&input}, {0.5}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, adjustSaturation_1) {
|
|
|
|
NDArray input('c', {2,2,3}, {0,100,56, 17,220,5, 150,97,230, 255,2,13}, nd4j::DataType::FLOAT32);
|
|
NDArray exp ('c', {2,2,3}, {50,100,78, 118.5,220,112.5, 190,163.5,230, 255,128.5,134}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::adjust_saturation op;
|
|
auto results = op.execute({&input}, {0.5}, {2});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, adjustSaturation_2) {
|
|
|
|
NDArray input('c', {2,2,3}, {0,100,56, 17,220,5, 150,97,230, 255,2,13}, nd4j::DataType::DOUBLE);
|
|
NDArray exp ('c', {2,2,3}, {0.,100.,56., 12.279087,220.,0., 91.654228,0.,230., 255.,0.,11.087015}, nd4j::DataType::DOUBLE);
|
|
|
|
nd4j::ops::adjust_saturation op;
|
|
auto results = op.execute({&input}, {10}, {2});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer("Result2");
|
|
// exp.printIndexedBuffer("Expect2");
|
|
|
|
ASSERT_TRUE(exp.isSameShape(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, adjustSaturation_3) {
|
|
|
|
NDArray input('c', {2,2,3}, {0,100,56, 17,220,5, 150,97,230, 255,2,13}, nd4j::DataType::FLOAT32);
|
|
NDArray exp ('c', {2,2,3}, {100.,100.,100., 220.,220.,220., 230.,230.,230., 255., 255., 255.}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::adjust_saturation op;
|
|
auto results = op.execute({&input}, {-10}, {2});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, adjustSaturation_4) {
|
|
|
|
NDArray input('c', {2,3,2}, {0,17, 100,220, 56,5, 150,255, 97,2, 230,13}, nd4j::DataType::FLOAT32);
|
|
NDArray exp ('c', {2,3,2}, {50,118.5, 100,220, 78,112.5, 190,255, 163.5,128.5, 230,134}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::adjust_saturation op;
|
|
auto results = op.execute({&input}, {0.5}, {1});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
// result->printIndexedBuffer();
|
|
|
|
ASSERT_TRUE(exp.isSameShape(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, adjustSaturation_5) {
|
|
|
|
NDArray input('c', {3,2,2}, {0,17, 150,255, 100,220, 97,2, 56,5, 230,13}, nd4j::DataType::FLOAT32);
|
|
NDArray exp ('c', {3,2,2}, {50,118.5, 190,255, 100,220, 163.5,128.5, 78,112.5, 230,134}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::adjust_saturation op;
|
|
auto results = op.execute({&input}, {0.5}, {0});
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto result = results->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(result));
|
|
ASSERT_TRUE(exp.equalsTo(result));
|
|
|
|
delete results;
|
|
}
|
|
|
|
|
|
TEST_F(DeclarableOpsTests13, shift_bits_1) {
|
|
auto x = NDArrayFactory::create<int>('c', {5});
|
|
auto y = NDArrayFactory::create<int>(4);
|
|
auto e = x.ulike();
|
|
x.assign(32);
|
|
e.assign(512);
|
|
|
|
nd4j::ops::shift_bits 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(DeclarableOpsTests13, rshift_bits_1) {
|
|
auto x = NDArrayFactory::create<int>('c', {5});
|
|
auto y = NDArrayFactory::create<int>(4);
|
|
auto e = x.ulike();
|
|
x.assign(512);
|
|
e.assign(32);
|
|
|
|
nd4j::ops::rshift_bits 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(DeclarableOpsTests13, cyclic_shift_bits_1) {
|
|
auto x = NDArrayFactory::create<int>('c', {5});
|
|
auto y = NDArrayFactory::create<int>(4);
|
|
auto e = x.ulike();
|
|
x.assign(32);
|
|
e.assign(512);
|
|
|
|
nd4j::ops::cyclic_shift_bits 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(DeclarableOpsTests13, cyclic_rshift_bits_1) {
|
|
auto x = NDArrayFactory::create<int>('c', {5});
|
|
auto y = NDArrayFactory::create<int>(4);
|
|
auto e = x.ulike();
|
|
x.assign(512);
|
|
e.assign(32);
|
|
|
|
nd4j::ops::cyclic_rshift_bits 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(DeclarableOpsTests13, shift_bits_2) {
|
|
auto x = NDArrayFactory::create<int>('c', {5});
|
|
auto y = NDArrayFactory::create<int>('c', {5});
|
|
auto e = x.ulike();
|
|
x.assign(32);
|
|
y.assign(4);
|
|
e.assign(512);
|
|
|
|
nd4j::ops::shift_bits 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(DeclarableOpsTests13, rshift_bits_2) {
|
|
auto x = NDArrayFactory::create<int>('c', {5});
|
|
auto y = NDArrayFactory::create<int>('c', {5});
|
|
auto e = x.ulike();
|
|
x.assign(512);
|
|
y.assign(4);
|
|
e.assign(32);
|
|
|
|
nd4j::ops::rshift_bits 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(DeclarableOpsTests13, cyclic_shift_bits_2) {
|
|
auto x = NDArrayFactory::create<int>('c', {5});
|
|
auto y = NDArrayFactory::create<int>('c', {5});
|
|
auto e = x.ulike();
|
|
x.assign(32);
|
|
y.assign(4);
|
|
e.assign(512);
|
|
|
|
nd4j::ops::cyclic_shift_bits 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(DeclarableOpsTests13, cyclic_rshift_bits_2) {
|
|
auto x = NDArrayFactory::create<int>('c', {5});
|
|
auto y = NDArrayFactory::create<int>('c', {5});
|
|
auto e = x.ulike();
|
|
x.assign(512);
|
|
y.assign(4);
|
|
e.assign(32);
|
|
|
|
nd4j::ops::cyclic_rshift_bits 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(DeclarableOpsTests13, shift_bits_3) {
|
|
auto x = NDArrayFactory::create<int>('c', {5, 5});
|
|
auto y = NDArrayFactory::create<int>('c', {1, 5});
|
|
auto e = x.ulike();
|
|
x.assign(32);
|
|
y.assign(4);
|
|
e.assign(512);
|
|
|
|
nd4j::ops::shift_bits 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(DeclarableOpsTests13, space_to_batch_nd_1) {
|
|
|
|
NDArray x('c', {1, 2, 2, 2, 3}, nd4j::DataType::FLOAT32);
|
|
NDArray blockShape('c', {3}, {2, 2, 2} , nd4j::DataType::INT32); // three spatial dimensions
|
|
NDArray paddings('c', {3, 2}, {0, 0, 0, 0, 0, 0} , nd4j::DataType::INT32);
|
|
|
|
NDArray exp('c', {8, 1, 1, 1, 3}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(1);
|
|
exp.linspace(1);
|
|
|
|
nd4j::ops::space_to_batch_nd op;
|
|
auto result = op.execute({&x, &blockShape, &paddings}, {}, {});
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, space_to_batch_nd_2) {
|
|
|
|
NDArray x('c', {2, 2,4,3, 1}, nd4j::DataType::FLOAT32);
|
|
NDArray blockShape('c', {3}, {2, 2, 3} , nd4j::DataType::INT32); // three spatial dimensions
|
|
NDArray paddings('c', {3, 2}, {0,0, 0,2, 2,1} , nd4j::DataType::INT32);
|
|
|
|
NDArray exp('c', {24, 1,3,2, 1}, { 0, 2, 0, 8, 0, 0, 0, 26, 0, 32, 0, 0, 0, 3, 0, 9, 0, 0, 0, 27, 0, 33, 0, 0, 1,
|
|
0, 7, 0, 0, 0, 25, 0, 31, 0, 0, 0, 0, 5, 0, 11, 0, 0, 0, 29, 0, 35, 0, 0, 0, 6,
|
|
0, 12, 0, 0, 0, 30, 0, 36, 0, 0, 4, 0, 10, 0, 0, 0, 28, 0, 34, 0, 0, 0, 0, 14,
|
|
0, 20, 0, 0, 0, 38, 0, 44, 0, 0, 0, 15, 0, 21, 0, 0, 0, 39, 0, 45, 0, 0, 13, 0,
|
|
19, 0, 0, 0, 37, 0, 43, 0, 0, 0, 0, 17, 0, 23, 0, 0, 0, 41, 0, 47, 0, 0, 0, 18,
|
|
0, 24, 0, 0, 0, 42, 0, 48, 0, 0, 16, 0, 22, 0, 0, 0, 40, 0, 46, 0, 0, 0}, nd4j::DataType::FLOAT32);
|
|
x.linspace(1);
|
|
|
|
nd4j::ops::space_to_batch_nd op;
|
|
auto result = op.execute({&x, &blockShape, &paddings}, {}, {});
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto z = result->at(0);
|
|
// z->printBuffer();
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, space_to_batch_nd_3) {
|
|
|
|
NDArray x('c', {2, 2,4,3, 1}, nd4j::DataType::FLOAT32);
|
|
NDArray blockShape('c', {3}, {2, 2, 3} , nd4j::DataType::INT32); // three spatial dimensions
|
|
NDArray paddings('c', {3, 2}, {1,1, 0,2, 2,1} , nd4j::DataType::INT32);
|
|
|
|
NDArray exp('c', {24, 2,3,2, 1}, { 0, 0, 0, 0, 0, 0, 0, 14, 0, 20, 0, 0, 0, 0, 0, 0, 0, 0, 0, 38, 0, 44, 0, 0, 0, 0, 0, 0, 0, 0, 0, 15,
|
|
0, 21, 0, 0, 0, 0, 0, 0, 0, 0, 0, 39, 0, 45, 0, 0, 0, 0, 0, 0, 0, 0, 13, 0, 19, 0, 0, 0, 0, 0, 0, 0,
|
|
0, 0, 37, 0, 43, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 17, 0, 23, 0, 0, 0, 0, 0, 0, 0, 0, 0, 41, 0, 47, 0, 0,
|
|
0, 0, 0, 0, 0, 0, 0, 18, 0, 24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 42, 0, 48, 0, 0, 0, 0, 0, 0, 0, 0, 16, 0,
|
|
22, 0, 0, 0, 0, 0, 0, 0, 0, 0, 40, 0, 46, 0, 0, 0, 0, 2, 0, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 26, 0, 32,
|
|
0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 0, 9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 27, 0, 33, 0, 0, 0, 0, 0, 0, 0, 0, 1,
|
|
0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 25, 0, 31, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 5, 0, 11, 0, 0, 0, 0, 0, 0,
|
|
0, 0, 0, 29, 0, 35, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6, 0, 12, 0, 0, 0, 0, 0, 0, 0, 0, 0, 30, 0, 36, 0, 0,
|
|
0, 0, 0, 0, 0, 0, 4, 0, 10, 0, 0, 0, 0, 0, 0, 0, 0, 0, 28, 0, 34, 0, 0, 0, 0, 0, 0, 0, 0, 0}, nd4j::DataType::FLOAT32);
|
|
x.linspace(1);
|
|
|
|
nd4j::ops::space_to_batch_nd op;
|
|
auto result = op.execute({&x, &blockShape, &paddings}, {}, {});
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto z = result->at(0);
|
|
// z->printBuffer();
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, batch_to_space_nd_1) {
|
|
|
|
NDArray x('c', {8, 1, 1, 1, 3}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray blockShape('c', {3}, {2, 2, 2} , nd4j::DataType::INT32); // three spatial dimensions
|
|
NDArray crop('c', {3, 2}, {0, 0, 0, 0, 0, 0} , nd4j::DataType::INT32);
|
|
|
|
NDArray exp('c', {1, 2, 2, 2, 3}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(1);
|
|
exp.linspace(1);
|
|
|
|
nd4j::ops::batch_to_space_nd op;
|
|
auto result = op.execute({&x, &blockShape, &crop}, {}, {});
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto z = result->at(0);
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, batch_to_space_nd_2) {
|
|
|
|
NDArray x('c', {24, 1,3,2, 1}, nd4j::DataType::FLOAT32);
|
|
NDArray blockShape('c', {3}, {2, 2, 3} , nd4j::DataType::INT32); // three spatial dimensions
|
|
NDArray crop('c', {3, 2}, {0,0, 0,2, 2,1} , nd4j::DataType::INT32);
|
|
|
|
NDArray exp('c', {2, 2,4,3, 1}, {25, 2, 14, 61, 38, 50, 27, 4, 16, 63, 40, 52, 97, 74, 86, 133, 110, 122, 99, 76, 88, 135, 112, 124,
|
|
31, 8, 20, 67, 44, 56, 33, 10, 22, 69, 46, 58, 103, 80, 92, 139, 116, 128, 105, 82, 94, 141, 118, 130}, nd4j::DataType::FLOAT32);
|
|
x.linspace(1);
|
|
|
|
nd4j::ops::batch_to_space_nd op;
|
|
auto result = op.execute({&x, &blockShape, &crop}, {}, {});
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto z = result->at(0);
|
|
// z->printBuffer();
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, batch_to_space_nd_3) {
|
|
|
|
NDArray x('c', {24, 2,3,2, 1}, nd4j::DataType::FLOAT32);
|
|
NDArray blockShape('c', {3}, {2, 2, 3} , nd4j::DataType::INT32); // three spatial dimensions
|
|
NDArray crop('c', {3, 2}, {1,1, 0,2, 2,1} , nd4j::DataType::INT32);
|
|
|
|
NDArray exp('c', {2, 2,4,3, 1}, {193, 146, 170, 265, 218, 242, 195, 148, 172, 267, 220, 244, 55, 8, 32, 127, 80, 104, 57, 10, 34, 129, 82,
|
|
106, 205, 158, 182, 277, 230, 254, 207, 160, 184, 279, 232, 256, 67, 20, 44, 139, 92, 116, 69, 22, 46, 141, 94, 118}, nd4j::DataType::FLOAT32);
|
|
x.linspace(1);
|
|
|
|
nd4j::ops::batch_to_space_nd op;
|
|
auto result = op.execute({&x, &blockShape, &crop}, {}, {});
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto z = result->at(0);
|
|
// z->printBuffer();
|
|
|
|
ASSERT_TRUE(exp.isSameShape(z));
|
|
ASSERT_TRUE(exp.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, mergemax_1) {
|
|
|
|
NDArray x1('c', {5, 5}, nd4j::DataType::FLOAT32);
|
|
NDArray x2('c', {5, 5}, nd4j::DataType::FLOAT32);
|
|
NDArray x3('c', {5, 5}, nd4j::DataType::FLOAT32);
|
|
NDArray e('c', {5, 5}, nd4j::DataType::FLOAT32);
|
|
x1.assign(3);
|
|
x2.assign(1);
|
|
x3.assign(2);
|
|
e.assign(3);
|
|
|
|
|
|
nd4j::ops::mergemax op;
|
|
auto result = op.execute({&x1, &x2, &x3}, {}, {});
|
|
ASSERT_EQ(Status::OK(), result->status());
|
|
|
|
auto z = result->at(0);
|
|
// z->printBuffer();
|
|
|
|
ASSERT_TRUE(e.isSameShape(z));
|
|
ASSERT_TRUE(e.equalsTo(z));
|
|
|
|
delete result;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, mergemax_2) {
|
|
|
|
NDArray x1('c', {1, 3}, {0., 1, 2}, nd4j::DataType::FLOAT32);
|
|
NDArray x2('c', {1, 1}, {1.}, nd4j::DataType::FLOAT32);
|
|
NDArray out('c', {1, 3}, {-1., -1, -1}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::mergemax op;
|
|
auto status = op.execute({&x1, &x2}, {&out}, {}, {}, {});
|
|
|
|
ASSERT_EQ(20, status);
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_1) {
|
|
|
|
const int sL = 5;
|
|
const int bS = 3;
|
|
const int nIn = 3;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
|
|
const int dataFormat = 0; // [sL,bS,nIn]
|
|
const int directionMode = 0; // forward
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = false; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = false; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 0; // do not apply clipping
|
|
|
|
NDArray x('c', {sL, bS, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx = 0.003;
|
|
Wr = 0.006;
|
|
b = 0.5;
|
|
hI = 1.;
|
|
cI = 2.;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
auto expH = NDArrayFactory::create<float>('c', {sL, bS, nOut}, {0.57574,0.57574,0.57574,0.58006,0.58006,0.58006,0.58434,0.58434,0.58434,
|
|
0.55114,0.55114,0.55114,0.55732,0.55732,0.55732,0.56338,0.56338,0.56338,
|
|
0.53763,0.53763,0.53763,0.54534,0.54534,0.54534,0.55287,0.55287,0.55287,
|
|
0.53626,0.53626,0.53626,0.54487,0.54487,0.54487,0.55327,0.55327,0.55327,
|
|
0.54484,0.54484,0.54484,0.55379,0.55379,0.55379,0.5625 ,0.5625 ,0.5625});
|
|
|
|
auto expClast = NDArrayFactory::create<float>('c', {bS, nOut}, {1.1589154,1.1589154,1.1589154,1.1892855,1.1892855,1.1892855,1.219861 ,1.219861 ,1.219861});
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &hI, &cI}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *h = results->at(0);
|
|
auto *cL = results->at(2);
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expClast.isSameShape(cL));
|
|
ASSERT_TRUE(expClast.equalsTo(cL));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_2) {
|
|
|
|
const int sL = 5;
|
|
const int bS = 3;
|
|
const int nIn = 3;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
|
|
const int dataFormat = 1; // [bS,sL,nIn]
|
|
const int directionMode = 0; // forward
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = false; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = false; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 0; // do not apply clipping
|
|
|
|
NDArray x('c', {bS, sL, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx = 0.003;
|
|
Wr = 0.006;
|
|
b = 0.5;
|
|
hI = 1.;
|
|
cI = 2.;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
auto expH = NDArrayFactory::create<float>('c', {bS, sL, nOut}, {0.575735, 0.575735, 0.575735, 0.541562, 0.541562, 0.541562, 0.514003, 0.514003, 0.514003, 0.495597, 0.495597, 0.495597, 0.485999, 0.485999, 0.485999,
|
|
0.596965, 0.596965, 0.596965, 0.571978, 0.571978, 0.571978, 0.552888, 0.552888, 0.552888, 0.540606, 0.540606, 0.540606, 0.534764, 0.534764, 0.534764,
|
|
0.61725 , 0.61725 , 0.61725 , 0.599828, 0.599828, 0.599828, 0.587627, 0.587627, 0.587627, 0.580408, 0.580408, 0.580408, 0.577735, 0.577735, 0.577735});
|
|
|
|
auto expClast = NDArrayFactory::create<float>('c', {bS, nOut}, {0.996965, 0.996965, 0.996965, 1.146756, 1.146756, 1.146756, 1.301922, 1.301922, 1.301922});
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &hI, &cI}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto *h = results->at(0);
|
|
auto *cL = results->at(2);
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expClast.isSameShape(cL));
|
|
ASSERT_TRUE(expClast.equalsTo(cL));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_3) {
|
|
|
|
const int sL = 5;
|
|
const int bS = 2;
|
|
const int nIn = 4;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
|
|
const int dataFormat = 0; // [sL,bS,nIn]
|
|
const int directionMode = 1; // backward
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = false; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = false; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 0; // do not apply clipping
|
|
|
|
NDArray x('c', {sL,bS, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx = 0.003;
|
|
Wr = 0.006;
|
|
b = 0.5;
|
|
hI = 1.;
|
|
cI = 2.;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
NDArray expH('c', {sL, bS, nOut}, {0.493883, 0.493883, 0.493883, 0.510990, 0.510990, 0.510990, 0.534701, 0.534701, 0.534701, 0.549139,
|
|
0.549139, 0.549139, 0.571900, 0.571900, 0.571900, 0.583561, 0.583561, 0.583561, 0.605106, 0.605106,
|
|
0.605106, 0.614114, 0.614114, 0.614114, 0.635354, 0.635354, 0.635354, 0.642045, 0.642045, 0.642045}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expHL('c', {bS, nOut}, {0.493883, 0.493883, 0.493883, 0.510990, 0.510990, 0.510990}, nd4j::DataType::FLOAT32);
|
|
NDArray expCL('c', {bS, nOut}, {1.061274, 1.061274, 1.061274, 1.115888, 1.115888, 1.115888}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &hI, &cI}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto h = results->at(0);
|
|
auto hL = results->at(1);
|
|
auto cL = results->at(2);
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expHL.isSameShape(hL));
|
|
ASSERT_TRUE(expHL.equalsTo(hL));
|
|
|
|
ASSERT_TRUE(expCL.isSameShape(cL));
|
|
ASSERT_TRUE(expCL.equalsTo(cL));
|
|
|
|
delete results;
|
|
}
|
|
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_4) {
|
|
|
|
const int sL = 5;
|
|
const int bS = 2;
|
|
const int nIn = 4;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
const int dataFormat = 0; // [sL,bS,nIn]
|
|
const int directionMode = 3; // bidirectional concat
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = false; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = false; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 0; // do not apply clipping
|
|
|
|
NDArray x('c', {sL, bS, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {2,nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {2,nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {2,4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {2,bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {2,bS, nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx({0,1, 0,0, 0,0}) = 0.003;
|
|
Wx({1,2, 0,0, 0,0}) = -0.003;
|
|
Wr({0,1, 0,0, 0,0}) = 0.006;
|
|
Wr({1,2, 0,0, 0,0}) = -0.006;
|
|
b({0,1, 0,0}) = 0.5;
|
|
b({1,2, 0,0}) = -0.5;
|
|
hI({0,1, 0,0, 0,0}) = 1;
|
|
hI({1,2, 0,0, 0,0}) = -1;
|
|
cI({0,1, 0,0, 0,0}) = 2;
|
|
cI({1,2, 0,0, 0,0}) = -2;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
NDArray expH('c', {sL, bS, 2*nOut}, {0.577661, 0.577661, 0.577661, -0.107642, -0.107642, -0.107642, 0.585289, 0.585289, 0.585289,
|
|
-0.106937, -0.106937, -0.106937, 0.556517, 0.556517, 0.556517, -0.111647, -0.111647, -0.111647,
|
|
0.567274, 0.567274, 0.567274, -0.110214, -0.110214, -0.110214, 0.547395, 0.547395, 0.547395,
|
|
-0.123305, -0.123305, -0.123305, 0.560640, 0.560640, 0.560640, -0.120862, -0.120862, -0.120862,
|
|
0.550714, 0.550714, 0.550714, -0.156223, -0.156223, -0.156223, 0.565308, 0.565308, 0.565308,
|
|
-0.152313, -0.152313, -0.152313, 0.563741, 0.563741, 0.563741, -0.234128, -0.234128, -0.234128,
|
|
0.578676, 0.578676, 0.578676, -0.228917, -0.228917, -0.228917}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expHL('c', {2,bS, nOut}, {0.563741, 0.563741, 0.563741, 0.578676, 0.578676, 0.578676, -0.107642,
|
|
-0.107642, -0.107642, -0.106937, -0.106937, -0.106937}, nd4j::DataType::FLOAT32);
|
|
NDArray expCL('c', {2,bS, nOut}, {1.217757, 1.217757, 1.217757, 1.272398, 1.272398, 1.272398, -0.295768,
|
|
-0.295768, -0.295768, -0.298453, -0.298453, -0.298453}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &hI, &cI}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto h = results->at(0);
|
|
auto hL = results->at(1);
|
|
auto cL = results->at(2);
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expHL.isSameShape(hL));
|
|
ASSERT_TRUE(expHL.equalsTo(hL));
|
|
|
|
ASSERT_TRUE(expCL.isSameShape(cL));
|
|
ASSERT_TRUE(expCL.equalsTo(cL));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_5) {
|
|
|
|
const int sL = 5;
|
|
const int bS = 2;
|
|
const int nIn = 4;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
const int dataFormat = 1; // [bS,sL,nIn]
|
|
const int directionMode = 3; // bidirectional concat
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = false; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = false; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 0; // do not apply clipping
|
|
|
|
NDArray x('c', {bS, sL, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {2,nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {2,nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {2,4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {2,bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {2,bS, nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx({0,1, 0,0, 0,0}) = 0.003;
|
|
Wx({1,2, 0,0, 0,0}) = -0.003;
|
|
Wr({0,1, 0,0, 0,0}) = 0.006;
|
|
Wr({1,2, 0,0, 0,0}) = -0.006;
|
|
b({0,1, 0,0}) = 0.5;
|
|
b({1,2, 0,0}) = -0.5;
|
|
hI({0,1, 0,0, 0,0}) = 1;
|
|
hI({1,2, 0,0, 0,0}) = -1;
|
|
cI({0,1, 0,0, 0,0}) = 2;
|
|
cI({1,2, 0,0, 0,0}) = -2;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
NDArray expH('c', {bS, sL, 2*nOut}, {0.577661, 0.577661, 0.577661, -0.107659, -0.107659, -0.107659, 0.548099, 0.548099, 0.548099, -0.113406, -0.113406, -0.113406,
|
|
0.526881, 0.526881, 0.526881, -0.12883 , -0.12883 , -0.12883 , 0.515882, 0.515882, 0.515882, -0.16868 , -0.16868 , -0.16868 ,
|
|
0.51409 , 0.51409 , 0.51409 , -0.255185, -0.255185, -0.255185, 0.614599, 0.614599, 0.614599, -0.102739, -0.102739, -0.102739,
|
|
0.599572, 0.599572, 0.599572, -0.105802, -0.105802, -0.105802,0.591089, 0.591089, 0.591089, -0.116681, -0.116681, -0.116681,
|
|
0.588694, 0.588694, 0.588694, -0.149201, -0.149201, -0.149201,0.591492, 0.591492, 0.591492, -0.228917, -0.228917, -0.228917}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expHL('c', {2,bS, nOut}, {0.51409 , 0.51409 , 0.51409 , 0.591492, 0.591492, 0.591492,
|
|
-0.107659, -0.107659, -0.107659, -0.102739, -0.102739, -0.102739}, nd4j::DataType::FLOAT32);
|
|
NDArray expCL('c', {2,bS, nOut}, {1.07293 , 1.07293 , 1.07293,1.346609, 1.346609, 1.346609,
|
|
-0.295811, -0.295811, -0.295811,-0.305394, -0.305394, -0.305394}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &hI, &cI}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto h = results->at(0);
|
|
auto hL = results->at(1);
|
|
auto cL = results->at(2);
|
|
|
|
// h->printBuffer();
|
|
// hL->printBuffer();
|
|
// cL->printBuffer();
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expHL.isSameShape(hL));
|
|
ASSERT_TRUE(expHL.equalsTo(hL));
|
|
|
|
ASSERT_TRUE(expCL.isSameShape(cL));
|
|
ASSERT_TRUE(expCL.equalsTo(cL));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_6) {
|
|
|
|
const int sL = 5;
|
|
const int bS = 2;
|
|
const int nIn = 4;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
const int dataFormat = 0; // [sL,bS,nIn]
|
|
const int directionMode = 2; // bidirectional sum
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = false; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = false; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 0; // do not apply clipping
|
|
|
|
NDArray x('c', {sL, bS, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {2,nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {2,nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {2,4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {2,bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {2,bS, nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx({0,1, 0,0, 0,0}) = 0.003;
|
|
Wx({1,2, 0,0, 0,0}) = -0.003;
|
|
Wr({0,1, 0,0, 0,0}) = 0.006;
|
|
Wr({1,2, 0,0, 0,0}) = -0.006;
|
|
b({0,1, 0,0}) = 0.5;
|
|
b({1,2, 0,0}) = -0.5;
|
|
hI({0,1, 0,0, 0,0}) = 1;
|
|
hI({1,2, 0,0, 0,0}) = -1;
|
|
cI({0,1, 0,0, 0,0}) = 2;
|
|
cI({1,2, 0,0, 0,0}) = -2;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
NDArray expH('c', {sL, bS, nOut}, {0.470019, 0.470019, 0.470019, 0.478352, 0.478352, 0.478352, 0.444871, 0.444871, 0.444871, 0.457060,
|
|
0.457060, 0.457060, 0.424090, 0.424090, 0.424090, 0.439778, 0.439778, 0.439778, 0.394491, 0.394491,
|
|
0.394491, 0.412995, 0.412995, 0.412995, 0.329613, 0.329613, 0.329613, 0.349760, 0.349760, 0.349760}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expHL('c', {2,bS, nOut}, {0.563741, 0.563741, 0.563741, 0.578676, 0.578676, 0.578676, -0.107642,
|
|
-0.107642, -0.107642, -0.106937, -0.106937, -0.106937}, nd4j::DataType::FLOAT32);
|
|
NDArray expCL('c', {2,bS, nOut}, {1.217757, 1.217757, 1.217757, 1.272398, 1.272398, 1.272398, -0.295768,
|
|
-0.295768, -0.295768, -0.298453, -0.298453, -0.298453}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &hI, &cI}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto h = results->at(0);
|
|
auto hL = results->at(1);
|
|
auto cL = results->at(2);
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expHL.isSameShape(hL));
|
|
ASSERT_TRUE(expHL.equalsTo(hL));
|
|
|
|
ASSERT_TRUE(expCL.isSameShape(cL));
|
|
ASSERT_TRUE(expCL.equalsTo(cL));
|
|
|
|
delete results;
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_7) {
|
|
#ifndef HAVE_MKLDNN
|
|
|
|
const int sL = 5;
|
|
const int bS = 2;
|
|
const int nIn = 4;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
|
|
const int dataFormat = 0; // [sL,bS,nIn]
|
|
const int directionMode = 0; // forward
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = false; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = true; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 0; // do not apply clipping
|
|
|
|
NDArray x('c', {sL, bS, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wp('c', {3*nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx = 0.003;
|
|
Wr = 0.006;
|
|
b = 0.5;
|
|
hI = 1.;
|
|
cI = 2.;
|
|
Wp = -0.05;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
NDArray expH('c', {sL, bS, nOut}, {0.55533 , 0.55533 , 0.55533 , 0.562925, 0.562925, 0.562925, 0.531795, 0.531795, 0.531795, 0.542556,
|
|
0.542556, 0.542556, 0.521466, 0.521466, 0.521466, 0.534638, 0.534638, 0.534638, 0.524805, 0.524805,
|
|
0.524805, 0.539187, 0.539187, 0.539187, 0.538309, 0.538309, 0.538309, 0.552923, 0.552923, 0.552923}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expHL('c', {bS, nOut}, {0.538309, 0.538309, 0.538309,0.552923, 0.552923, 0.552923}, nd4j::DataType::FLOAT32);
|
|
NDArray expCL('c', {bS, nOut}, {1.147089, 1.147089, 1.147089,1.197228, 1.197228, 1.197228}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &hI, &cI, &Wp}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto h = results->at(0);
|
|
auto hL = results->at(1);
|
|
auto cL = results->at(2);
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expHL.isSameShape(hL));
|
|
ASSERT_TRUE(expHL.equalsTo(hL));
|
|
|
|
ASSERT_TRUE(expCL.isSameShape(cL));
|
|
ASSERT_TRUE(expCL.equalsTo(cL));
|
|
|
|
delete results;
|
|
#endif
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_8) {
|
|
#ifndef HAVE_MKLDNN
|
|
|
|
const int sL = 5;
|
|
const int bS = 2;
|
|
const int nIn = 4;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
|
|
const int dataFormat = 0; // [sL,bS,nIn]
|
|
const int directionMode = 1; // backward
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = false; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = true; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 1.; // do not apply clipping
|
|
|
|
NDArray x('c', {sL, bS, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wp('c', {3*nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx = 0.003;
|
|
Wr = 0.006;
|
|
b = 0.5;
|
|
hI = 1.;
|
|
cI = 2.;
|
|
Wp = -0.05;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
NDArray expH('c', {sL, bS, nOut}, {0.436221, 0.436221, 0.436221,0.450573, 0.450573, 0.450573,0.463602, 0.463602, 0.463602, 0.474674, 0.474674, 0.474674,
|
|
0.484039, 0.484039, 0.484039,0.490679, 0.490679, 0.490679, 0.494871, 0.494871, 0.494871, 0.499028, 0.499028, 0.499028,
|
|
0.504649, 0.504649, 0.504649, 0.508719, 0.508719, 0.508719}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expHL('c', {bS, nOut}, {0.436221, 0.436221, 0.436221, 0.450573, 0.450573, 0.450573}, nd4j::DataType::FLOAT32);
|
|
NDArray expCL('c', {bS, nOut}, {0.879804, 0.879804, 0.879804,0.914666, 0.914666, 0.914666}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &hI, &cI, &Wp}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto h = results->at(0);
|
|
auto hL = results->at(1);
|
|
auto cL = results->at(2);
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expHL.isSameShape(hL));
|
|
ASSERT_TRUE(expHL.equalsTo(hL));
|
|
|
|
ASSERT_TRUE(expCL.isSameShape(cL));
|
|
ASSERT_TRUE(expCL.equalsTo(cL));
|
|
|
|
delete results;
|
|
#endif
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_9) {
|
|
#ifndef HAVE_MKLDNN
|
|
|
|
const int sL = 5;
|
|
const int bS = 2;
|
|
const int nIn = 4;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
const int dataFormat = 0; // [sL,bS,nIn]
|
|
const int directionMode = 3; // bidirectional concat
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = false; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = true; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 0; // do not apply clipping
|
|
|
|
NDArray x('c', {sL, bS, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {2,nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {2,nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {2,4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {2,bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {2,bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wp('c', {2,3*nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx({0,1, 0,0, 0,0}) = 0.003;
|
|
Wx({1,2, 0,0, 0,0}) = -0.003;
|
|
Wr({0,1, 0,0, 0,0}) = 0.006;
|
|
Wr({1,2, 0,0, 0,0}) = -0.006;
|
|
b({0,1, 0,0}) = 0.5;
|
|
b({1,2, 0,0}) = -0.5;
|
|
hI({0,1, 0,0, 0,0}) = 1;
|
|
hI({1,2, 0,0, 0,0}) = -1;
|
|
cI({0,1, 0,0, 0,0}) = 2;
|
|
cI({1,2, 0,0, 0,0}) = -2;
|
|
Wp({0,1, 0,0}) = -0.05;
|
|
Wp({1,2, 0,0}) = 0.05;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
NDArray expH('c', {sL, bS, 2*nOut}, { 0.55533 , 0.55533 , 0.55533 , -0.104502, -0.104502, -0.104502, 0.562925, 0.562925, 0.562925, -0.103843, -0.103843, -0.103843,
|
|
0.531795, 0.531795, 0.531795, -0.107456, -0.107456, -0.107456,0.542556, 0.542556, 0.542556, -0.106139, -0.106139, -0.106139,
|
|
0.521466, 0.521466, 0.521466, -0.11681 , -0.11681 , -0.11681 , 0.534638, 0.534638, 0.534638, -0.11458 , -0.11458 , -0.11458 ,
|
|
0.524805, 0.524805, 0.524805, -0.145177, -0.145177, -0.145177,0.539187, 0.539187, 0.539187, -0.14157 , -0.14157 , -0.14157 ,
|
|
0.538309, 0.538309, 0.538309, -0.218056, -0.218056, -0.218056,0.552923, 0.552923, 0.552923, -0.213068, -0.213068, -0.213068}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expHL('c', {2,bS, nOut}, {0.538309, 0.538309, 0.538309, 0.552923, 0.552923, 0.552923, -0.104502, -0.104502, -0.104502,
|
|
-0.103843, -0.103843, -0.103843}, nd4j::DataType::FLOAT32);
|
|
NDArray expCL('c', {2,bS, nOut}, {1.147089, 1.147089, 1.147089, 1.197228, 1.197228, 1.197228, -0.289425, -0.289425, -0.289425,
|
|
-0.292174, -0.292174, -0.292174}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &hI, &cI, &Wp}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto h = results->at(0);
|
|
auto hL = results->at(1);
|
|
auto cL = results->at(2);
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expHL.isSameShape(hL));
|
|
ASSERT_TRUE(expHL.equalsTo(hL));
|
|
|
|
ASSERT_TRUE(expCL.isSameShape(cL));
|
|
ASSERT_TRUE(expCL.equalsTo(cL));
|
|
|
|
delete results;
|
|
#endif
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_10) {
|
|
#ifndef HAVE_MKLDNN
|
|
|
|
const int sL = 6;
|
|
const int bS = 5;
|
|
const int nIn = 4;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
const int dataFormat = 0; // [sL,bS,nIn]
|
|
const int directionMode = 0; // forward
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = true; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = true; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 0; // do not apply clipping
|
|
|
|
NDArray x('c', {sL, bS, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray seqLen('c', {bS}, {0,1,2,3,5}, nd4j::DataType::FLOAT32);
|
|
NDArray Wp('c', {3*nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx = 0.003;
|
|
Wr = 0.006;
|
|
b = 0.5;
|
|
hI = 1.;
|
|
cI = 2.;
|
|
Wp = -0.05;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
NDArray expH('c', {sL, bS, nOut}, {0., 0., 0., 0.562925, 0.562925, 0.562925, 0.570404, 0.570404, 0.570404, 0.57777 , 0.57777 , 0.57777 , 0.585023, 0.585023, 0.585023,
|
|
0., 0., 0., 0., 0., 0., 0.576568, 0.576568, 0.576568, 0.586163, 0.586163, 0.586163, 0.595462, 0.595462, 0.595462, 0., 0., 0., 0., 0.,
|
|
0., 0., 0., 0., 0.611224, 0.611224, 0.611224, 0.621298, 0.621298, 0.621298, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
|
|
0.655858, 0.655858, 0.655858, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.692315, 0.692315, 0.692315, 0., 0., 0., 0., 0., 0.,
|
|
0., 0., 0., 0., 0., 0., 0., 0., 0.}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expHL('c', {bS, nOut}, {0., 0., 0., 0.562925, 0.562925, 0.562925, 0.576568, 0.576568, 0.576568, 0.611224, 0.611224, 0.611224, 0.692315, 0.692315, 0.692315}, nd4j::DataType::FLOAT32);
|
|
NDArray expCL('c', {bS, nOut}, {0., 0., 0., 1.534275, 1.534275, 1.534275, 1.40183, 1.40183, 1.40183, 1.449675, 1.449675, 1.449675, 1.767702, 1.767702, 1.767702}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &seqLen, &hI, &cI, &Wp}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto h = results->at(0);
|
|
auto hL = results->at(1);
|
|
auto cL = results->at(2);
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expHL.isSameShape(hL));
|
|
ASSERT_TRUE(expHL.equalsTo(hL));
|
|
|
|
ASSERT_TRUE(expCL.isSameShape(cL));
|
|
ASSERT_TRUE(expCL.equalsTo(cL));
|
|
|
|
delete results;
|
|
#endif
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_11) {
|
|
#ifndef HAVE_MKLDNN
|
|
|
|
const int sL = 6;
|
|
const int bS = 5;
|
|
const int nIn = 4;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
const int dataFormat = 0; // [sL,bS,nIn]
|
|
const int directionMode = 1; // backward
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = true; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = true; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 0; // do not apply clipping
|
|
|
|
NDArray x('c', {sL, bS, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray seqLen('c', {bS}, {0,1,2,3,5}, nd4j::DataType::FLOAT32);
|
|
NDArray Wp('c', {3*nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx = 0.003;
|
|
Wr = 0.006;
|
|
b = 0.5;
|
|
hI = 1.;
|
|
cI = 2.;
|
|
Wp = -0.05;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
NDArray expH('c', {sL, bS, nOut}, {0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.61209,
|
|
0.61209, 0.61209,0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.652042, 0.652042, 0.652042, 0., 0., 0., 0., 0.,
|
|
0., 0., 0., 0., 0.677708, 0.677708, 0.677708, 0.684177, 0.684177, 0.684177, 0., 0., 0.,0., 0., 0.,0.699627, 0.699627,
|
|
0.699627,0.705371, 0.705371, 0.705371,0.710989, 0.710989, 0.710989, 0., 0., 0., 0.719014, 0.719014, 0.719014, 0.724087,
|
|
0.724087, 0.724087, 0.729084, 0.729084, 0.729084, 0.734004, 0.734004, 0.734004 }, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expHL('c', {bS, nOut}, {0., 0., 0., 0.719014, 0.719014, 0.719014, 0.699627, 0.699627, 0.699627, 0.677708, 0.677708, 0.677708, 0.61209, 0.61209, 0.61209}, nd4j::DataType::FLOAT32);
|
|
NDArray expCL('c', {bS, nOut}, {0., 0., 0., 2.092814, 2.092814, 2.092814, 2.08832, 2.08832, 2.08832, 2.009851, 2.009851, 2.009851, 1.646034, 1.646034, 1.646034}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &seqLen, &hI, &cI, &Wp}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto h = results->at(0);
|
|
auto hL = results->at(1);
|
|
auto cL = results->at(2);
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expHL.isSameShape(hL));
|
|
ASSERT_TRUE(expHL.equalsTo(hL));
|
|
|
|
ASSERT_TRUE(expCL.isSameShape(cL));
|
|
ASSERT_TRUE(expCL.equalsTo(cL));
|
|
|
|
delete results;
|
|
#endif
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////
|
|
TEST_F(DeclarableOpsTests13, lstmLayer_12) {
|
|
#ifndef HAVE_MKLDNN
|
|
|
|
const int sL = 6;
|
|
const int bS = 5;
|
|
const int nIn = 4;
|
|
const int nOut = 3;
|
|
|
|
// input arguments
|
|
const int dataFormat = 0; // [sL,bS,nIn]
|
|
const int directionMode = 3; // bidirectional concat
|
|
const int gateAct = 2; // sigmoid activation for input (i), forget (f) and output (o) gates
|
|
const int cellAct = 0; // tanh activation for cell state
|
|
const int outAct = 0; // tanh activation for output
|
|
|
|
const bool hasBiases = true; // biases array is provided
|
|
const bool hasSeqLen = true; // seqLen array is not provided
|
|
const auto hasInitH = true; // initial output is provided
|
|
const auto hasInitC = true; // initial cell state is provided
|
|
const auto hasPH = true; // peephole connections are absent
|
|
const auto retFullSeq = true; // return whole h {h_0, h_1, ... , h_sL-1}, [sL,bS,nOut]
|
|
const auto retLastH = true; // do not return output at last time step
|
|
const auto retLastC = true; // return cells state at last time step
|
|
|
|
const double cellClip = 0; // do not apply clipping
|
|
|
|
NDArray x('c', {sL, bS, nIn}, nd4j::DataType::FLOAT32);
|
|
NDArray Wx('c', {2,nIn, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray Wr('c', {2,nOut, 4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray b('c', {2,4*nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray hI('c', {2,bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray cI('c', {2,bS, nOut}, nd4j::DataType::FLOAT32);
|
|
NDArray seqLen('c', {bS}, {0,1,2,3,5}, nd4j::DataType::FLOAT32);
|
|
NDArray Wp('c', {2,3*nOut}, nd4j::DataType::FLOAT32);
|
|
|
|
x.linspace(0.5, 0.5);
|
|
Wx({0,1, 0,0, 0,0}) = 0.003;
|
|
Wx({1,2, 0,0, 0,0}) = -0.003;
|
|
Wr({0,1, 0,0, 0,0}) = 0.006;
|
|
Wr({1,2, 0,0, 0,0}) = -0.006;
|
|
b({0,1, 0,0}) = 0.5;
|
|
b({1,2, 0,0}) = -0.5;
|
|
hI({0,1, 0,0, 0,0}) = 1;
|
|
hI({1,2, 0,0, 0,0}) = -1;
|
|
cI({0,1, 0,0, 0,0}) = 2;
|
|
cI({1,2, 0,0, 0,0}) = -2;
|
|
Wp({0,1, 0,0}) = -0.05;
|
|
Wp({1,2, 0,0}) = 0.05;
|
|
|
|
std::initializer_list<double> tArgs = {cellClip};
|
|
std::initializer_list<Nd4jLong> iArgs = {dataFormat, directionMode, gateAct, cellAct, outAct};
|
|
std::initializer_list<bool> bArgs = {hasBiases, hasSeqLen, hasInitH, hasInitC, hasPH, retFullSeq, retLastH, retLastC};
|
|
|
|
NDArray expH('c', {sL, bS, 2*nOut}, {0., 0., 0., 0., 0., 0., 0.562925, 0.562925, 0.562925, -0.25361 , -0.25361 , -0.25361 , 0.570404, 0.570404, 0.570404, -0.157103,
|
|
-0.157103, -0.157103, 0.57777 , 0.57777 , 0.57777 , -0.116502, -0.116502, -0.116502,0.585023, 0.585023, 0.585023, -0.100025,
|
|
-0.100025, -0.100025, 0., 0., 0., 0., 0., 0.,0., 0., 0., 0., 0., 0., 0.576568, 0.576568, 0.576568, -0.223072, -0.223072, -0.223072,
|
|
0.586163, 0.586163, 0.586163, -0.135714, -0.135714, -0.135714,0.595462, 0.595462, 0.595462, -0.094438, -0.094438, -0.094438,
|
|
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.611224, 0.611224, 0.611224, -0.193473, -0.193473, -0.193473,
|
|
0.621298, 0.621298, 0.621298, -0.090626, -0.090626, -0.090626, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
|
|
0., 0., 0., 0., 0., 0., 0.655858, 0.655858, 0.655858, -0.098015, -0.098015, -0.098015, 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
|
|
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.692315, 0.692315, 0.692315, -0.143704, -0.143704, -0.143704, 0., 0., 0., 0., 0., 0.,
|
|
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.}, nd4j::DataType::FLOAT32);
|
|
|
|
NDArray expHL('c', {2,bS, nOut}, {0., 0., 0., 0.562925, 0.562925, 0.562925, 0.576568, 0.576568, 0.576568, 0.611224, 0.611224, 0.611224, 0.692315, 0.692315, 0.692315,
|
|
0., 0., 0., -0.25361 , -0.25361 , -0.25361 , -0.157103, -0.157103, -0.157103,-0.116502, -0.116502, -0.116502, -0.100025, -0.100025, -0.100025}, nd4j::DataType::FLOAT32);
|
|
NDArray expCL('c', {2,bS, nOut}, {0., 0., 0.,1.534275, 1.534275, 1.534275,1.40183 , 1.40183 , 1.40183 ,1.449675, 1.449675, 1.449675,1.767702, 1.767702, 1.767702,
|
|
0., 0., 0.,-0.86636 , -0.86636 , -0.86636 ,-0.470245, -0.470245, -0.470245,-0.341856, -0.341856, -0.341856,-0.294986, -0.294986, -0.294986}, nd4j::DataType::FLOAT32);
|
|
|
|
nd4j::ops::lstmLayer op;
|
|
auto results = op.execute({&x, &Wx, &Wr, &b, &seqLen, &hI, &cI, &Wp}, tArgs, iArgs, bArgs);
|
|
|
|
ASSERT_EQ(ND4J_STATUS_OK, results->status());
|
|
|
|
auto h = results->at(0);
|
|
auto hL = results->at(1);
|
|
auto cL = results->at(2);
|
|
|
|
ASSERT_TRUE(expH.isSameShape(h));
|
|
ASSERT_TRUE(expH.equalsTo(h));
|
|
|
|
ASSERT_TRUE(expHL.isSameShape(hL));
|
|
ASSERT_TRUE(expHL.equalsTo(hL));
|
|
|
|
ASSERT_TRUE(expCL.isSameShape(cL));
|
|
ASSERT_TRUE(expCL.equalsTo(cL));
|
|
|
|
delete results;
|
|
#endif
|
|
}
|
|
|
|
|