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/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://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.
*/
#include "GenModelTest.h"
#include <memory>
CircleGen genSimpleQuantizeModel(circle::TensorType from_t, float input_scale, int input_zeropoint,
circle::TensorType to_t, float output_scale, int output_zeropoint)
{
CircleGen cgen;
int in = cgen.addTensor({{1, 4, 4, 1}, from_t}, input_scale, input_zeropoint);
int out = cgen.addTensor({{1, 4, 4, 1}, to_t}, output_scale, output_zeropoint);
cgen.addOperatorQuantize({{in}, {out}});
cgen.setInputsAndOutputs({in}, {out});
return cgen;
}
TEST_F(GenModelTest, OneOp_Quantize_Uint8toInt8)
{
CircleGen cgen =
genSimpleQuantizeModel(circle::TensorType_UINT8, 1., 128, circle::TensorType_INT8, 2., -10);
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->addTestCase(
TestCaseData{}
.addInput<uint8_t>({127, 48, 151, 232, 56, 176, 47, 37, 51, 52, 39, 94, 15, 108, 142, 243})
.addOutput<int8_t>(
{-10, -50, 2, 42, -46, 14, -50, -55, -48, -48, -54, -27, -66, -20, -3, 48}));
_context->setBackends({"cpu"});
SUCCEED();
}
TEST_F(GenModelTest, OneOp_Quantize_Int8toUint8)
{
CircleGen cgen =
genSimpleQuantizeModel(circle::TensorType_INT8, 2., -10, circle::TensorType_UINT8, 1., 128);
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->addTestCase(
TestCaseData{}
.addInput<int8_t>({-10, -50, 2, 42, -46, 14, -50, -55, -48, -48, -54, -27, -66, -20, -3, 48})
.addOutput<uint8_t>({128, 48, 152, 232, 56, 176, 48, 38, 52, 52, 40, 94, 16, 108, 142, 244}));
_context->setBackends({"cpu"});
SUCCEED();
}
TEST_F(GenModelTest, neg_OneOp_Quantize_Uint8toInt16)
{
CircleGen cgen =
genSimpleQuantizeModel(circle::TensorType_UINT8, 1., 128, circle::TensorType_INT16, 2., -10);
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->setBackends({"acl_cl", "acl_neon", "cpu"});
_context->expectFailModelLoad();
SUCCEED();
}
TEST_F(GenModelTest, neg_OneOp_Quantize_Int8toInt16)
{
CircleGen cgen =
genSimpleQuantizeModel(circle::TensorType_INT8, 2., -10, circle::TensorType_INT16, 1., 128);
_context = std::make_unique<GenModelTestContext>(cgen.finish());
_context->setBackends({"acl_cl", "acl_neon", "cpu"});
_context->expectFailModelLoad();
SUCCEED();
}
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