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| // Copyright 2026 The ODML Authors. | |
| // | |
| // 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. | |
| namespace litert::lm { | |
| namespace { | |
| TEST(LogTensorBufferTest, LogTensor_Float) { | |
| struct alignas(kHostMemoryBufferAlignment) { | |
| float d[5] = {1.1, 2.2, -3.3, 4.4, 5.5}; | |
| } data; | |
| auto tensor_buffer = TensorBuffer::CreateFromHostMemory( | |
| RankedTensorType(ElementType::Float32, Layout(Dimensions({5}))), data.d, | |
| 5 * sizeof(float)); | |
| ASSERT_TRUE(tensor_buffer.HasValue()); | |
| EXPECT_OK(LogTensor(*tensor_buffer, 2, "Float Prefix: ")); | |
| } | |
| TEST(LogTensorBufferTest, LogTensor_Int8) { | |
| struct alignas(kHostMemoryBufferAlignment) { | |
| int8_t d[5] = {1, 2, -3, 4, 5}; | |
| } data; | |
| auto tensor_buffer = TensorBuffer::CreateFromHostMemory( | |
| RankedTensorType(ElementType::Int8, Layout(Dimensions({5}))), data.d, | |
| 5 * sizeof(int8_t)); | |
| ASSERT_TRUE(tensor_buffer.HasValue()); | |
| EXPECT_OK(LogTensor(*tensor_buffer, 5, "Int8 Prefix: ")); | |
| } | |
| TEST(LogTensorBufferTest, LogTensor_Bool) { | |
| struct alignas(kHostMemoryBufferAlignment) { | |
| bool d[3] = {true, false, true}; | |
| } data; | |
| auto tensor_buffer = TensorBuffer::CreateFromHostMemory( | |
| RankedTensorType(ElementType::Bool, Layout(Dimensions({3}))), data.d, | |
| 3 * sizeof(bool)); | |
| ASSERT_TRUE(tensor_buffer.HasValue()); | |
| EXPECT_OK(LogTensor(*tensor_buffer, 3, "Bool Prefix: ")); | |
| } | |
| TEST(LogTensorBufferTest, DumpTensorToCsv_Float) { | |
| struct alignas(kHostMemoryBufferAlignment) { | |
| float d[5] = {1.1, 2.2, -3.3, 4.4, 5.5}; | |
| } data; | |
| auto tensor_buffer = TensorBuffer::CreateFromHostMemory( | |
| RankedTensorType(ElementType::Float32, Layout(Dimensions({5}))), data.d, | |
| 5 * sizeof(float)); | |
| ASSERT_TRUE(tensor_buffer.HasValue()); | |
| std::string filename = testing::TempDir() + "/test_float.csv"; | |
| EXPECT_OK(DumpTensorToCsv(*tensor_buffer, filename)); | |
| std::ifstream f(filename); | |
| std::string line; | |
| ASSERT_TRUE(std::getline(f, line)); | |
| EXPECT_EQ(line, "1.1,2.2,-3.3,4.4,5.5"); | |
| } | |
| TEST(LogTensorBufferTest, DumpTensorToCsv_Int8) { | |
| struct alignas(kHostMemoryBufferAlignment) { | |
| int8_t d[5] = {1, 2, -3, 4, 5}; | |
| } data; | |
| auto tensor_buffer = TensorBuffer::CreateFromHostMemory( | |
| RankedTensorType(ElementType::Int8, Layout(Dimensions({5}))), data.d, | |
| 5 * sizeof(int8_t)); | |
| ASSERT_TRUE(tensor_buffer.HasValue()); | |
| std::string filename = testing::TempDir() + "/test_int8.csv"; | |
| EXPECT_OK(DumpTensorToCsv(*tensor_buffer, filename)); | |
| std::ifstream f(filename); | |
| std::string line; | |
| ASSERT_TRUE(std::getline(f, line)); | |
| EXPECT_EQ(line, "1,2,-3,4,5"); | |
| } | |
| TEST(LogTensorBufferTest, DumpTensorToCsv_Bool) { | |
| struct alignas(kHostMemoryBufferAlignment) { | |
| bool d[3] = {true, false, true}; | |
| } data; | |
| auto tensor_buffer = TensorBuffer::CreateFromHostMemory( | |
| RankedTensorType(ElementType::Bool, Layout(Dimensions({3}))), data.d, | |
| 3 * sizeof(bool)); | |
| ASSERT_TRUE(tensor_buffer.HasValue()); | |
| std::string filename = testing::TempDir() + "/test_bool.csv"; | |
| EXPECT_OK(DumpTensorToCsv(*tensor_buffer, filename)); | |
| std::ifstream f(filename); | |
| std::string line; | |
| ASSERT_TRUE(std::getline(f, line)); | |
| EXPECT_EQ(line, "1,0,1"); | |
| } | |
| } // namespace | |
| } // namespace litert::lm | |