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cavis/libnd4j/tests_cpu/layers_tests/NlpTests.cpp

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Eclipse Migration Initial Commit
2019-06-06 14:21:15 +02:00
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://www.apache.org/licenses/LICENSE-2.0.
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations
* under the License.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// @author raver119@gmail.com
//
#include "testlayers.h"
#include <ops/declarable/CustomOperations.h>
#include <NDArray.h>
#include <ops/ops.h>
#include <GradCheck.h>
#include <helpers/RandomLauncher.h>
using namespace nd4j;
class NlpTests : public testing::Test {
public:
NlpTests() {
printf("\n");
fflush(stdout);
}
};
TEST_F(NlpTests, basic_sg_hs_test_1) {
auto exp0 = NDArrayFactory::create<float>('c', {1, 10});
auto exp1 = NDArrayFactory::create<float>('c', {1, 10});
exp0.assign(0.01001f);
exp1.assign(0.020005f);
auto target = NDArrayFactory::create<int>(0);
auto ngStarter = NDArrayFactory::empty<int>();
auto indices = NDArrayFactory::create<int>('c', {1}, {1});
auto codes = NDArrayFactory::create<int8_t>('c', {1});
auto syn0 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1Neg = NDArrayFactory::empty<float>();
auto expTable = NDArrayFactory::create<float>('c', {10000});
auto negTable = NDArrayFactory::empty<float>();
auto neu1e = NDArrayFactory::create<float>('c', {10});
syn0.assign(0.01);
syn1.assign(0.02);
expTable.assign(0.5);
auto alpha = NDArrayFactory::create<double>(0.001);
auto randomValue = NDArrayFactory::create<Nd4jLong>(1L);
auto inferenceVector = NDArrayFactory::empty<float>();
nd4j::ops::skipgram op;
auto result = op.execute({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {}, {false}, true);
ASSERT_EQ(Status::OK(), result->status());
auto row0 = syn0({0,1, 0,0}, true);
auto row1 = syn1({1,2, 0,0}, true);
ASSERT_EQ(exp0, row0);
ASSERT_EQ(exp1, row1);
delete result;
}
TEST_F(NlpTests, basic_sg_hs_test_2) {
auto exp0 = NDArrayFactory::create<float>('c', {1, 10});
auto exp1 = NDArrayFactory::create<float>('c', {1, 10});
auto exp2 = NDArrayFactory::create<float>('c', {1, 10});
exp0.assign(0.01f);
exp1.assign(0.020005f);
exp2.assign(0.019995f);
auto target = NDArrayFactory::create<int>(0);
auto ngStarter = NDArrayFactory::empty<int>();
auto indices = NDArrayFactory::create<int>('c', {2}, {1, 2});
auto codes = NDArrayFactory::create<int8_t>('c', {2}, {0, 1});
auto syn0 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1Neg = NDArrayFactory::empty<float>();
auto expTable = NDArrayFactory::create<float>('c', {10000});
auto negTable = NDArrayFactory::empty<float>();
auto neu1e = NDArrayFactory::create<float>('c', {10});
syn0.assign(0.01);
syn1.assign(0.02);
expTable.assign(0.5);
auto alpha = NDArrayFactory::create<double>(0.001);
auto randomValue = NDArrayFactory::create<Nd4jLong>(1L);
auto inferenceVector = NDArrayFactory::empty<float>();
nd4j::ops::skipgram op;
auto result = op.execute({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {}, {false}, true);
ASSERT_EQ(Status::OK(), result->status());
auto row0 = syn0({0,1, 0,0}, true);
auto row1 = syn1({1,2, 0,0}, true);
auto row2 = syn1({2,3, 0,0}, true);
ASSERT_EQ(exp0, row0);
ASSERT_EQ(exp1, row1);
ASSERT_EQ(exp2, row2);
delete result;
}
TEST_F(NlpTests, basic_sg_hs_test_3) {
auto exp0 = NDArrayFactory::create<float>('c', {1, 10});
auto exp1 = NDArrayFactory::create<float>('c', {1, 10});
auto exp2 = NDArrayFactory::create<float>('c', {1, 10});
exp0.assign(0.01f);
exp1.assign(0.020005f);
exp2.assign(0.019995f);
auto target = NDArrayFactory::create<int>(0);
auto ngStarter = NDArrayFactory::empty<int>();
auto indices0 = NDArrayFactory::create<int>('c', {3}, {1, 2, 3});
auto indices1 = NDArrayFactory::create<int>('c', {3}, {3, 1, 2});
auto codes00 = NDArrayFactory::create<int8_t>('c', {3}, {0, 1, 1});
auto codes01 = NDArrayFactory::create<int8_t>('c', {3}, {1, 0, 1});
auto syn00 = NDArrayFactory::create<float>('c', {100, 10});
auto syn01 = NDArrayFactory::create<float>('c', {100, 10});
auto syn10 = NDArrayFactory::create<float>('c', {100, 10});
auto syn11 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1Neg = NDArrayFactory::empty<float>();
auto expTable = NDArrayFactory::create<float>('c', {10000});
auto negTable = NDArrayFactory::empty<float>();
auto neu1e = NDArrayFactory::create<float>('c', {10});
RandomGenerator rng(119L, 198L);
cpp tests fixes Signed-off-by: raver119 <raver119@gmail.com>
2019-07-17 06:47:53 +02:00
RandomLauncher::fillUniform(LaunchContext::defaultContext(), rng, &syn00, 0.0, 1.0);
RandomLauncher::fillUniform(LaunchContext::defaultContext(), rng, &syn10, 0.0, 1.0);
Eclipse Migration Initial Commit
2019-06-06 14:21:15 +02:00
syn01.assign(syn00);
syn11.assign(syn10);
expTable.assign(0.5);
auto alpha = NDArrayFactory::create<double>(0.001);
auto randomValue = NDArrayFactory::create<Nd4jLong>(1L);
auto inferenceVector = NDArrayFactory::empty<float>();
nd4j::ops::skipgram op;
auto result0 = op.execute({&target, &ngStarter, &indices0, &codes00, &syn00, &syn10, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {}, {false}, true);
auto result1 = op.execute({&target, &ngStarter, &indices1, &codes01, &syn01, &syn11, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {}, {false}, true);
ASSERT_EQ(Status::OK(), result0->status());
auto row00 = syn00({0,1, 0,0}, true);
auto row01 = syn01({0,1, 0,0}, true);
auto row1 = syn10({1,2, 0,0}, true);
auto row2 = syn11({1,2, 0,0}, true);
ASSERT_EQ(row2, row1);
ASSERT_EQ(row00, row01);
delete result0;
delete result1;
}
TEST_F(NlpTests, basic_sg_hs_ns_test_1) {
auto target = NDArrayFactory::create<int>(0);
auto ngStarter = NDArrayFactory::create<int>(1);
auto indices = NDArrayFactory::create<int>('c', {5}, {1, 2, 3, 4, 5});
auto codes = NDArrayFactory::create<int8_t>('c', {5}, {1, 1, 0, 1, 1});
auto syn0 = NDArrayFactory::create<float>('c', {100, 150});
auto syn1 = NDArrayFactory::create<float>('c', {100, 150});
auto syn1Neg = NDArrayFactory::create<float>('c', {100, 150});
auto expTable = NDArrayFactory::create<float>('c', {1000});
auto negTable = NDArrayFactory::create<float>('c', {1000});
auto neu1e = NDArrayFactory::create<float>('c', {10});
negTable.linspace(1.0);
auto alpha = NDArrayFactory::create<double>(1.25);
auto randomValue = NDArrayFactory::create<Nd4jLong>(119L);
auto inferenceVector = NDArrayFactory::empty<float>();
nd4j::ops::skipgram op;
auto result = op.execute({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {3}, {false}, true);
ASSERT_EQ(Status::OK(), result->status());
delete result;
}
TEST_F(NlpTests, basic_sg_ns_test_1) {
auto exp0 = NDArrayFactory::create<float>('c', {1, 10});
exp0.assign(0.01);
auto target = NDArrayFactory::create<int>(1);
auto ngStarter = NDArrayFactory::create<int>(3);
auto indices = NDArrayFactory::empty<int>();
auto codes = NDArrayFactory::empty<int8_t>();
auto syn0 = NDArrayFactory::create<float>('c', {10, 10});
auto syn1 = NDArrayFactory::empty<float>();
auto syn1Neg = NDArrayFactory::create<float>('c', {10, 10});
auto expTable = NDArrayFactory::create<float>('c', {1000});
auto negTable = NDArrayFactory::create<float>('c', {1000});
auto neu1e = NDArrayFactory::create<float>('c', {10});
auto syn1Neg2 = NDArrayFactory::create<float>('c', {10, 10});
syn0.assign(0.01);
syn1.assign(0.02);
syn1Neg.assign(0.03);
syn1Neg2.assign(0.03);
expTable.assign(0.5);
auto alpha = NDArrayFactory::create<double>(0.001);
auto randomValue = NDArrayFactory::create<Nd4jLong>(2L);
auto inferenceVector = NDArrayFactory::empty<float>();
nd4j::ops::skipgram op;
auto result = op.execute({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {1, 1}, {false}, true);
ASSERT_EQ(Status::OK(), result->status());
auto row0 = syn0({1,2, 0,0}, true);
ASSERT_EQ(exp0, row0);
ASSERT_FALSE(syn1Neg2.equalsTo(syn1Neg, 1e-6));
delete result;
}
TEST_F(NlpTests, basic_cb_hs_test_1) {
auto exp0 = NDArrayFactory::create<float>('c', {1, 10});
auto exp1 = NDArrayFactory::create<float>('c', {1, 10});
auto exp2 = NDArrayFactory::create<float>('c', {1, 10});
exp0.assign(0.0095f);
exp1.assign(0.019875f);
exp2.assign(0.02f);
auto target = NDArrayFactory::create<int>(0);
auto ngStarter = NDArrayFactory::empty<int>();
auto context = NDArrayFactory::create<int>('c', {3}, {0, 1, 2});
auto locked = NDArrayFactory::create<int>('c', {3});
auto indices = NDArrayFactory::create<int>('c', {2}, {4, 5});
auto codes = NDArrayFactory::create<int8_t>('c', {2}, {1, 1});
auto syn0 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1Neg = NDArrayFactory::empty<float>();
auto expTable = NDArrayFactory::create<float>('c', {10000});
auto negTable = NDArrayFactory::empty<float>();
auto numWords = NDArrayFactory::create<int>('c', {1}, {1});
syn0.assign(0.01);
syn1.assign(0.02);
expTable.assign(0.5);
auto alpha = NDArrayFactory::create<double>(0.025);
auto randomValue = NDArrayFactory::create<Nd4jLong>(2L);
auto inferenceVector = NDArrayFactory::empty<float>();
nd4j::ops::cbow op;
auto result = op.execute({&target, &ngStarter, &context, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &numWords, &locked, &inferenceVector}, {}, {}, {true}, true);
ASSERT_EQ(Status::OK(), result->status());
auto row_s0_0 = syn0({0,1, 0,0}, true);
auto row_s0_1 = syn0({1,2, 0,0}, true);
auto row_s0_2 = syn0({2,3, 0,0}, true);
auto row_s1_4 = syn1({4,5, 0,0}, true);
auto row_s1_5 = syn1({5,6, 0,0}, true);
auto row_s1_6 = syn1({6,7, 0,0}, true);
ASSERT_EQ(exp0, row_s0_0);
ASSERT_EQ(exp0, row_s0_1);
ASSERT_EQ(exp0, row_s0_2);
ASSERT_EQ(exp1, row_s1_4);
ASSERT_EQ(exp1, row_s1_5);
ASSERT_EQ(exp2, row_s1_6);
delete result;
}
TEST_F(NlpTests, basic_cb_ns_test_1) {
auto exp0 = NDArrayFactory::create<float>('c', {1, 10});
auto exp1 = NDArrayFactory::create<float>('c', {1, 10});
auto exp2 = NDArrayFactory::create<float>('c', {1, 10});
exp0.assign(0.0096265625);
exp1.assign(0.01);
exp2.assign(0.030125f);
auto target = NDArrayFactory::create<int>(0);
auto ngStarter = NDArrayFactory::create<int>(6);
auto context = NDArrayFactory::create<int>('c', {3}, {0, 1, 2});
auto locked = NDArrayFactory::create<int>('c', {3});
auto indices = NDArrayFactory::empty<int>();
auto codes = NDArrayFactory::empty<int8_t>();
auto syn0 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1Neg = NDArrayFactory::create<float>('c', {100, 10});
auto expTable = NDArrayFactory::create<float>('c', {10000});
auto negTable = NDArrayFactory::create<float>('c', {100000});
auto numWords = NDArrayFactory::create<int>('c', {2}, {1, 2});
syn0.assign(0.01);
syn1.assign(0.02);
syn1Neg.assign(0.03);
expTable.assign(0.5);
auto alpha = NDArrayFactory::create<double>(0.025);
auto randomValue = NDArrayFactory::create<Nd4jLong>(2L);
auto inferenceVector = NDArrayFactory::empty<float>();
nd4j::ops::cbow op;
auto result = op.execute({&target, &ngStarter, &context, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &numWords, &locked, &inferenceVector}, {}, {1, 2, 0}, {true}, true);
ASSERT_EQ(Status::OK(), result->status());
auto row_s0_0 = syn0({0,1, 0,0}, true);
auto row_s0_1 = syn0({1,2, 0,0}, true);
auto row_s0_2 = syn0({2,3, 0,0}, true);
auto row_s1_4 = syn1({4,5, 0,0}, true);
auto row_s1_5 = syn1({5,6, 0,0}, true);
auto row_s1_6 = syn1Neg({6,7, 0,0}, true);
ASSERT_EQ(exp0, row_s0_0);
ASSERT_EQ(exp0, row_s0_1);
ASSERT_EQ(exp0, row_s0_2);
ASSERT_EQ(exp2, row_s1_6);
delete result;
}
TEST_F(NlpTests, test_sg_hs_batch_1) {
auto exp0 = NDArrayFactory::create<float>('c', {1, 10});
auto exp1 = NDArrayFactory::create<float>('c', {1, 10});
auto exp2 = NDArrayFactory::create<float>('c', {1, 10});
exp0.assign(0.01f);
exp1.assign(0.020005f);
exp2.assign(0.019995f);
auto target = NDArrayFactory::create<int>('c', {2}, {0, 5});
auto ngStarter = NDArrayFactory::empty<int>();
auto indices = NDArrayFactory::create<int>('c', {2, 2}, {1, 2, 3, 4});
auto codes = NDArrayFactory::create<int8_t>('c', {2, 2}, {0, 1, 1, 1});
auto syn0 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1Neg = NDArrayFactory::empty<float>();
auto expTable = NDArrayFactory::create<float>('c', {10000});
auto negTable = NDArrayFactory::empty<float>();
auto alpha = NDArrayFactory::create<double>('c', {2}, {0.001, 0.024});
auto randomValue = NDArrayFactory::create<Nd4jLong>('c', {2}, {1L, 3L});
auto inferenceVector = NDArrayFactory::empty<float>();
auto neu1e = NDArrayFactory::create<float>('c', {2, 10});
syn0.assign(0.01);
syn1.assign(0.02);
expTable.assign(0.5);
nd4j::ops::skipgram op;
auto result = op.execute({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {}, {false, true}, true);
ASSERT_EQ(Status::OK(), result->status());
auto row0 = syn0({0,1, 0,0}, true);
auto row1 = syn1({1,2, 0,0}, true);
auto row2 = syn1({2,3, 0,0}, true);
ASSERT_TRUE(exp0.equalsTo(row0, 1e-6));
ASSERT_TRUE(exp1.equalsTo(row1, 1e-6));
ASSERT_TRUE(exp2.equalsTo(row2, 1e-6));
delete result;
}
TEST_F(NlpTests, test_sg_ns_batch_1) {
auto exp0 = NDArrayFactory::create<float>('c', {1, 10});
auto exp1 = NDArrayFactory::create<float>('c', {1, 10});
auto exp2 = NDArrayFactory::create<float>('c', {1, 10});
exp0.assign(0.01f);
exp1.assign(0.020005f);
exp2.assign(0.019995f);
auto target = NDArrayFactory::create<int>('c', {2}, {0, 5});
auto ngStarter = NDArrayFactory::create<int>('c', {2}, {3, 8});
auto indices = NDArrayFactory::empty<int>();
auto codes = NDArrayFactory::empty<int8_t>();
auto syn0 = NDArrayFactory::create<float>('c', {100, 10});
auto syn1Neg = NDArrayFactory::create<float>('c', {100, 10});
auto syn1 = NDArrayFactory::empty<float>();
auto expTable = NDArrayFactory::create<float>('c', {10000});
auto negTable = NDArrayFactory::create<float>('c', {100000});
auto alpha = NDArrayFactory::create<double>('c', {2}, {0.001, 0.024});
auto randomValue = NDArrayFactory::create<Nd4jLong>('c', {2}, {1L, 3L});
auto inferenceVector = NDArrayFactory::empty<float>();
auto neu1e = NDArrayFactory::create<float>('c', {2, 10});
syn0.assign(0.01);
syn1.assign(0.02);
expTable.assign(0.5);
negTable.linspace(0.0);
nd4j::ops::skipgram op;
auto result = op.execute({&target, &ngStarter, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &inferenceVector, &neu1e}, {}, {4, 5}, {false, true}, true);
ASSERT_EQ(Status::OK(), result->status());
auto row0 = syn0({0,0, 0,0}, true);
auto row1 = syn0({5,0, 0,0}, true);
auto row2 = syn0({2,0, 0,0}, true);
delete result;
}
TEST_F(NlpTests, test_cbow_hs_batch_1) {
Shugeo release fix2 (#70) * Corrected input checking and tests for bitcast op. * Fixed an issue with non_max_suppression form generation and processing with score threshold given. * Fixed bilinear resize kernel and tests. * push for Serhii Signed-off-by: raver119 <raver119@gmail.com> * Added test for nearest_neighbor resize with int input. * Added data type check for input/output match. * Eliminate error in macros. * Improved output message for type checking. * Fixed input/output types for op. * Eliminated waste logging. * Refactored resize_bilinear helper for multithreading for cpu platform. * Cosmetic changes only. * Fixed error for string substitution. * Skip test for cbow_batch with cuda. * fix for resizeNearestNeighbor output dtype Signed-off-by: raver119 <raver119@gmail.com> * Refactored non_max_suppression helper. * Refactored shape generation and input handling. * Added additional test.
2019-11-22 20:42:44 +01:00
#ifdef __CUDABLAS__
return ;
#endif
Eclipse Migration Initial Commit
2019-06-06 14:21:15 +02:00
auto target = NDArrayFactory::create<int>(0);
auto ngStarter = NDArrayFactory::empty<int>();
auto context = NDArrayFactory::create<int>('c', {2, 3}, {0, 1, 2, 100, 101, 102});
auto locked = NDArrayFactory::create<int>('c', {2, 3});
auto indices = NDArrayFactory::create<int>('c', {2, 2}, {4, 5, 40, 50});
auto codes = NDArrayFactory::create<int8_t>('c', {2, 2}, {1, 1, 1, 1});
auto syn0 = NDArrayFactory::create<float>('c', {244, 10});
auto syn1 = NDArrayFactory::create<float>('c', {244, 10});
auto syn1Neg = NDArrayFactory::empty<float>();
auto expTable = NDArrayFactory::create<float>('c', {10000});
auto negTable = NDArrayFactory::empty<float>();
auto numWords = NDArrayFactory::create<int>('c', {2}, {1, 2});
syn0.assign(0.01);
syn1.assign(0.02);
expTable.assign(0.5);
auto alpha = NDArrayFactory::create<double>('c', {2}, {0.025, 0.025});
auto randomValue = NDArrayFactory::create<Nd4jLong>('c', {2}, {2L, 2L});
auto inferenceVector = NDArrayFactory::empty<float>();
nd4j::ops::cbow op;
auto result = op.execute({&target, &ngStarter, &context, &indices, &codes, &syn0, &syn1, &syn1Neg, &expTable, &negTable, &alpha, &randomValue, &numWords, &locked, &inferenceVector}, {}, {}, {true}, true);
ASSERT_EQ(Status::OK(), result->status());
auto exp0 = NDArrayFactory::create<float>('c', {1, 10});
auto exp1 = NDArrayFactory::create<float>('c', {1, 10});
auto exp2 = NDArrayFactory::create<float>('c', {1, 10});
exp0.assign(0.0095f);
exp1.assign(0.019875f);
exp2.assign(0.02f);
auto row_s0_0 = syn0({0,1, 0,0}, true);
auto row_s0_1 = syn0({1,2, 0,0}, true);
auto row_s0_2 = syn0({2,3, 0,0}, true);
auto row_s1_4 = syn1({4,5, 0,0}, true);
auto row_s1_5 = syn1({5,6, 0,0}, true);
auto row_s1_6 = syn1({6,7, 0,0}, true);
ASSERT_EQ(exp0, row_s0_0);
ASSERT_EQ(exp0, row_s0_1);
ASSERT_EQ(exp0, row_s0_2);
ASSERT_EQ(exp1, row_s1_4);
ASSERT_EQ(exp1, row_s1_5);
ASSERT_EQ(exp2, row_s1_6);
delete result;
}