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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 "fixtures.h"
#include "NNPackages.h"
#include <nnfw_internal.h>
#include "CircleGen.h"
TEST_F(RegressionTest, github_1535)
{
auto package_path = NNPackages::get().getModelAbsolutePath(NNPackages::ADD);
nnfw_session *session1 = nullptr;
NNFW_ENSURE_SUCCESS(nnfw_create_session(&session1));
NNFW_ENSURE_SUCCESS(nnfw_load_model_from_file(session1, package_path.c_str()));
NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(session1, "cpu;acl_cl;acl_neon"));
NNFW_ENSURE_SUCCESS(nnfw_prepare(session1));
nnfw_session *session2 = nullptr;
NNFW_ENSURE_SUCCESS(nnfw_create_session(&session2));
NNFW_ENSURE_SUCCESS(nnfw_load_model_from_file(session2, package_path.c_str()));
NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(session2, "cpu"));
NNFW_ENSURE_SUCCESS(nnfw_prepare(session2));
NNFW_ENSURE_SUCCESS(nnfw_close_session(session1));
NNFW_ENSURE_SUCCESS(nnfw_close_session(session2));
SUCCEED();
}
TEST_F(RegressionTest, neg_github_3826)
{
// Model is not important
CircleGen cgen;
int in = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
int out = cgen.addTensor({{1, 1, 1, 1}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorAveragePool2D({{in}, {out}}, circle::Padding_SAME, 2, 2, 2, 2,
circle::ActivationFunctionType_NONE);
cgen.setInputsAndOutputs({in}, {out});
auto cbuf = cgen.finish();
nnfw_session *session = nullptr;
NNFW_ENSURE_SUCCESS(nnfw_create_session(&session));
NNFW_ENSURE_SUCCESS(nnfw_load_circle_from_buffer(session, cbuf.buffer(), cbuf.size()));
// To test when there is no backends loaded for the session
NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(session, "unavailable_backend"));
ASSERT_EQ(nnfw_prepare(session), NNFW_STATUS_ERROR);
NNFW_ENSURE_SUCCESS(nnfw_close_session(session));
}
TEST_F(RegressionTest, github_11748)
{
// At the 1st call, input tensor is static. From the 2nd call, input tensor becomes dynamic.
// the following model and calling sequence were what nnstreamer people used for their test case.
CircleGen cgen;
int lhs = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32});
std::vector<float> rhs_data{2};
uint32_t rhs_buf = cgen.addBuffer(rhs_data);
int rhs = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32, rhs_buf});
int out = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32});
cgen.addOperatorAdd({{lhs, rhs}, {out}}, circle::ActivationFunctionType_NONE);
cgen.setInputsAndOutputs({lhs}, {out});
auto cbuf = cgen.finish();
nnfw_session *session = nullptr;
NNFW_ENSURE_SUCCESS(nnfw_create_session(&session));
NNFW_ENSURE_SUCCESS(nnfw_load_circle_from_buffer(session, cbuf.buffer(), cbuf.size()));
// To test when there is no backends loaded for the session
NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(session, "cpu"));
NNFW_ENSURE_SUCCESS(nnfw_prepare(session));
uint32_t input_num = -1;
NNFW_ENSURE_SUCCESS(nnfw_input_size(session, &input_num));
nnfw_tensorinfo t_input;
NNFW_ENSURE_SUCCESS(nnfw_input_tensorinfo(session, 0, &t_input));
uint32_t output_num = -1;
NNFW_ENSURE_SUCCESS(nnfw_output_size(session, &output_num));
nnfw_tensorinfo t_output;
NNFW_ENSURE_SUCCESS(nnfw_output_tensorinfo(session, 0, &t_output));
// when new_dim == 1, input tensor is static. From 2, input tensor becomes dynamic.
for (int32_t new_dim = 1; new_dim <= 4; new_dim++)
{
nnfw_tensorinfo t_new_input;
t_new_input.dtype = t_input.dtype;
t_new_input.rank = 1;
t_new_input.dims[0] = new_dim;
NNFW_ENSURE_SUCCESS(nnfw_set_input_tensorinfo(session, 0, &t_new_input));
NNFW_ENSURE_SUCCESS(nnfw_input_size(session, &input_num));
NNFW_ENSURE_SUCCESS(nnfw_input_tensorinfo(session, 0, &t_input));
ASSERT_EQ(input_num, 1);
ASSERT_EQ(t_input.rank, t_new_input.rank);
ASSERT_EQ(t_input.dims[0], new_dim);
uint8_t input_buf[new_dim * sizeof(float)];
NNFW_ENSURE_SUCCESS(
nnfw_set_input(session, 0, t_input.dtype, &input_buf, new_dim * sizeof(float)));
uint8_t output_buf[new_dim * sizeof(float)];
NNFW_ENSURE_SUCCESS(
nnfw_set_output(session, 0, t_output.dtype, &output_buf, new_dim * sizeof(float)));
NNFW_ENSURE_SUCCESS(nnfw_run(session));
NNFW_ENSURE_SUCCESS(nnfw_output_size(session, &output_num));
NNFW_ENSURE_SUCCESS(nnfw_output_tensorinfo(session, 0, &t_output));
ASSERT_EQ(output_num, 1);
ASSERT_EQ(t_output.rank, t_new_input.rank);
ASSERT_EQ(t_output.dims[0], new_dim);
// seems weird calling but anyway nnstreamer people case calls this again.
// Anyways, runtime should work
NNFW_ENSURE_SUCCESS(
nnfw_set_input(session, 0, t_input.dtype, &input_buf, new_dim * sizeof(float)));
NNFW_ENSURE_SUCCESS(
nnfw_set_output(session, 0, t_output.dtype, &output_buf, new_dim * sizeof(float)));
NNFW_ENSURE_SUCCESS(nnfw_run(session));
}
NNFW_ENSURE_SUCCESS(nnfw_close_session(session));
}
TEST_F(RegressionTest, github_4585)
{
// A single tensor which is an input and an output at the same time
CircleGen cgen;
int t = cgen.addTensor({{1, 1}, circle::TensorType::TensorType_FLOAT32});
cgen.setInputsAndOutputs({t}, {t});
auto cbuf = cgen.finish();
nnfw_session *session = nullptr;
NNFW_ENSURE_SUCCESS(nnfw_create_session(&session));
NNFW_ENSURE_SUCCESS(nnfw_load_circle_from_buffer(session, cbuf.buffer(), cbuf.size()));
// To test when there is no backends loaded for the session
NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(session, "cpu"));
NNFW_ENSURE_SUCCESS(nnfw_prepare(session));
// Change input tensorinfo (Make dynamic shape inference happen)
nnfw_tensorinfo ti_new = {NNFW_TYPE_TENSOR_FLOAT32, 2, {1, 2}};
NNFW_ENSURE_SUCCESS(nnfw_set_input_tensorinfo(session, 0, &ti_new));
std::vector<float> in_buf{1, 1};
std::vector<float> out_buf{-1, -1};
NNFW_ENSURE_SUCCESS(
nnfw_set_input(session, 0, ti_new.dtype, in_buf.data(), in_buf.size() * sizeof(float)));
NNFW_ENSURE_SUCCESS(
nnfw_set_output(session, 0, ti_new.dtype, out_buf.data(), out_buf.size() * sizeof(float)));
NNFW_ENSURE_SUCCESS(nnfw_run(session));
ASSERT_EQ(in_buf, out_buf);
NNFW_ENSURE_SUCCESS(nnfw_close_session(session));
}
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