tests/nnfw_api/src/RegressionTests.cc

   1 /*
   2  * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
   3  *
   4  * Licensed under the Apache License, Version 2.0 (the "License");
   5  * you may not use this file except in compliance with the License.
   6  * You may obtain a copy of the License at
   7  *
   8  *    http://www.apache.org/licenses/LICENSE-2.0
   9  *
  10  * Unless required by applicable law or agreed to in writing, software
  11  * distributed under the License is distributed on an "AS IS" BASIS,
  12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13  * See the License for the specific language governing permissions and
  14  * limitations under the License.
  15  */
  16
  17 #include "fixtures.h"
  18 #include "NNPackages.h"
  19
  20 #include <nnfw_internal.h>
  21
  22 #include "CircleGen.h"
  23
  24 TEST_F(RegressionTest, github_1535)
  25 {
  26   auto package_path = NNPackages::get().getModelAbsolutePath(NNPackages::ADD);
  27
  28   nnfw_session *session1 = nullptr;
  29   NNFW_ENSURE_SUCCESS(nnfw_create_session(&session1));
  30   NNFW_ENSURE_SUCCESS(nnfw_load_model_from_file(session1, package_path.c_str()));
  31   NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(session1, "cpu;acl_cl;acl_neon"));
  32   NNFW_ENSURE_SUCCESS(nnfw_prepare(session1));
  33
  34   nnfw_session *session2 = nullptr;
  35   NNFW_ENSURE_SUCCESS(nnfw_create_session(&session2));
  36   NNFW_ENSURE_SUCCESS(nnfw_load_model_from_file(session2, package_path.c_str()));
  37   NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(session2, "cpu"));
  38   NNFW_ENSURE_SUCCESS(nnfw_prepare(session2));
  39
  40   NNFW_ENSURE_SUCCESS(nnfw_close_session(session1));
  41   NNFW_ENSURE_SUCCESS(nnfw_close_session(session2));
  42
  43   SUCCEED();
  44 }
  45
  46 TEST_F(RegressionTest, neg_github_3826)
  47 {
  48   // Model is not important
  49   CircleGen cgen;
  50   int in = cgen.addTensor({{1, 2, 2, 1}, circle::TensorType::TensorType_FLOAT32});
  51   int out = cgen.addTensor({{1, 1, 1, 1}, circle::TensorType::TensorType_FLOAT32});
  52   cgen.addOperatorAveragePool2D({{in}, {out}}, circle::Padding_SAME, 2, 2, 2, 2,
  53                                 circle::ActivationFunctionType_NONE);
  54   cgen.setInputsAndOutputs({in}, {out});
  55   auto cbuf = cgen.finish();
  56
  57   nnfw_session *session = nullptr;
  58   NNFW_ENSURE_SUCCESS(nnfw_create_session(&session));
  59   NNFW_ENSURE_SUCCESS(nnfw_load_circle_from_buffer(session, cbuf.buffer(), cbuf.size()));
  60   // To test when there is no backends loaded for the session
  61   NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(session, "unavailable_backend"));
  62   ASSERT_EQ(nnfw_prepare(session), NNFW_STATUS_ERROR);
  63   NNFW_ENSURE_SUCCESS(nnfw_close_session(session));
  64 }
  65
  66 TEST_F(RegressionTest, github_11748)
  67 {
  68   // At the 1st call, input tensor is static. From the 2nd call, input tensor becomes dynamic.
  69   // the following model and calling sequence were what nnstreamer people used for their test case.
  70   CircleGen cgen;
  71   int lhs = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32});
  72
  73   std::vector<float> rhs_data{2};
  74   uint32_t rhs_buf = cgen.addBuffer(rhs_data);
  75   int rhs = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32, rhs_buf});
  76
  77   int out = cgen.addTensor({{1}, circle::TensorType::TensorType_FLOAT32});
  78   cgen.addOperatorAdd({{lhs, rhs}, {out}}, circle::ActivationFunctionType_NONE);
  79   cgen.setInputsAndOutputs({lhs}, {out});
  80   auto cbuf = cgen.finish();
  81
  82   nnfw_session *session = nullptr;
  83   NNFW_ENSURE_SUCCESS(nnfw_create_session(&session));
  84   NNFW_ENSURE_SUCCESS(nnfw_load_circle_from_buffer(session, cbuf.buffer(), cbuf.size()));
  85   // To test when there is no backends loaded for the session
  86   NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(session, "cpu"));
  87   NNFW_ENSURE_SUCCESS(nnfw_prepare(session));
  88
  89   uint32_t input_num = -1;
  90   NNFW_ENSURE_SUCCESS(nnfw_input_size(session, &input_num));
  91
  92   nnfw_tensorinfo t_input;
  93   NNFW_ENSURE_SUCCESS(nnfw_input_tensorinfo(session, 0, &t_input));
  94
  95   uint32_t output_num = -1;
  96   NNFW_ENSURE_SUCCESS(nnfw_output_size(session, &output_num));
  97
  98   nnfw_tensorinfo t_output;
  99   NNFW_ENSURE_SUCCESS(nnfw_output_tensorinfo(session, 0, &t_output));
 100
 101   // when new_dim == 1, input tensor is static. From 2, input tensor becomes dynamic.
 102   for (int32_t new_dim = 1; new_dim <= 4; new_dim++)
 103   {
 104     nnfw_tensorinfo t_new_input;
 105     t_new_input.dtype = t_input.dtype;
 106     t_new_input.rank = 1;
 107     t_new_input.dims[0] = new_dim;
 108     NNFW_ENSURE_SUCCESS(nnfw_set_input_tensorinfo(session, 0, &t_new_input));
 109
 110     NNFW_ENSURE_SUCCESS(nnfw_input_size(session, &input_num));
 111     NNFW_ENSURE_SUCCESS(nnfw_input_tensorinfo(session, 0, &t_input));
 112
 113     ASSERT_EQ(input_num, 1);
 114     ASSERT_EQ(t_input.rank, t_new_input.rank);
 115     ASSERT_EQ(t_input.dims[0], new_dim);
 116
 117     uint8_t input_buf[new_dim * sizeof(float)];
 118     NNFW_ENSURE_SUCCESS(
 119         nnfw_set_input(session, 0, t_input.dtype, &input_buf, new_dim * sizeof(float)));
 120
 121     uint8_t output_buf[new_dim * sizeof(float)];
 122     NNFW_ENSURE_SUCCESS(
 123         nnfw_set_output(session, 0, t_output.dtype, &output_buf, new_dim * sizeof(float)));
 124
 125     NNFW_ENSURE_SUCCESS(nnfw_run(session));
 126
 127     NNFW_ENSURE_SUCCESS(nnfw_output_size(session, &output_num));
 128     NNFW_ENSURE_SUCCESS(nnfw_output_tensorinfo(session, 0, &t_output));
 129
 130     ASSERT_EQ(output_num, 1);
 131     ASSERT_EQ(t_output.rank, t_new_input.rank);
 132     ASSERT_EQ(t_output.dims[0], new_dim);
 133
 134     // seems weird calling but anyway nnstreamer people case calls this again.
 135     // Anyways, runtime should work
 136     NNFW_ENSURE_SUCCESS(
 137         nnfw_set_input(session, 0, t_input.dtype, &input_buf, new_dim * sizeof(float)));
 138     NNFW_ENSURE_SUCCESS(
 139         nnfw_set_output(session, 0, t_output.dtype, &output_buf, new_dim * sizeof(float)));
 140     NNFW_ENSURE_SUCCESS(nnfw_run(session));
 141   }
 142
 143   NNFW_ENSURE_SUCCESS(nnfw_close_session(session));
 144 }
 145
 146 TEST_F(RegressionTest, github_4585)
 147 {
 148   // A single tensor which is an input and an output at the same time
 149   CircleGen cgen;
 150   int t = cgen.addTensor({{1, 1}, circle::TensorType::TensorType_FLOAT32});
 151   cgen.setInputsAndOutputs({t}, {t});
 152   auto cbuf = cgen.finish();
 153
 154   nnfw_session *session = nullptr;
 155   NNFW_ENSURE_SUCCESS(nnfw_create_session(&session));
 156   NNFW_ENSURE_SUCCESS(nnfw_load_circle_from_buffer(session, cbuf.buffer(), cbuf.size()));
 157   // To test when there is no backends loaded for the session
 158   NNFW_ENSURE_SUCCESS(nnfw_set_available_backends(session, "cpu"));
 159   NNFW_ENSURE_SUCCESS(nnfw_prepare(session));
 160
 161   // Change input tensorinfo (Make dynamic shape inference happen)
 162   nnfw_tensorinfo ti_new = {NNFW_TYPE_TENSOR_FLOAT32, 2, {1, 2}};
 163   NNFW_ENSURE_SUCCESS(nnfw_set_input_tensorinfo(session, 0, &ti_new));
 164
 165   std::vector<float> in_buf{1, 1};
 166   std::vector<float> out_buf{-1, -1};
 167
 168   NNFW_ENSURE_SUCCESS(
 169       nnfw_set_input(session, 0, ti_new.dtype, in_buf.data(), in_buf.size() * sizeof(float)));
 170   NNFW_ENSURE_SUCCESS(
 171       nnfw_set_output(session, 0, ti_new.dtype, out_buf.data(), out_buf.size() * sizeof(float)));
 172
 173   NNFW_ENSURE_SUCCESS(nnfw_run(session));
 174
 175   ASSERT_EQ(in_buf, out_buf);
 176
 177   NNFW_ENSURE_SUCCESS(nnfw_close_session(session));
 178 }