TensorRT-LLMs/cpp/tests/unit_tests/layers/topPSamplingLayerTest.cpp
Dan Blanaru 16d2467ea8 Update TensorRT-LLM (#2755)
* Update TensorRT-LLM

---------

Co-authored-by: Denis Kayshev <topenkoff@gmail.com>
Co-authored-by: akhoroshev <arthoroshev@gmail.com>
Co-authored-by: Patrick Reiter Horn <patrick.horn@gmail.com>

Update
2025-02-11 03:01:00 +00:00

194 lines
6.3 KiB
C++

/*
* Copyright (c) 2022-2024, NVIDIA CORPORATION. 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 "tests/unit_tests/layers/baseSamplingLayerTest.h"
namespace
{
using namespace tensorrt_llm::tests::layers::sampling;
using namespace tensorrt_llm::runtime;
template <typename T>
class TopPSamplingLayerTest : public BaseSamplingLayerTest<T>
{
void SetUp() override
{
this->mStream = std::make_shared<tensorrt_llm::runtime::CudaStream>();
this->mBufferManager = std::make_shared<tensorrt_llm::runtime::BufferManager>(this->mStream);
int device;
cudaGetDevice(&device);
cudaGetDeviceProperties(&mDeviceProp, device);
this->mComputeProbs = true;
}
void initLayer(TestSamplingParams const& params) override
{
auto const decodingDomain
= tensorrt_llm::layers::DecoderDomain(this->maxBatchSize(), 1, this->mVocabSize, this->mVocabSizePadded);
this->mSamplingLayer = std::make_shared<tensorrt_llm::layers::TopPSamplingLayer<T>>(
decodingDomain, this->mBufferManager, &mDeviceProp);
}
protected:
cudaDeviceProp mDeviceProp{};
};
TYPED_TEST_SUITE(TopPSamplingLayerTest, FloatAndHalfTypes);
TYPED_TEST(TopPSamplingLayerTest, TopKSkipDecode)
{
SizeType32 topK = 2;
float topP = 0.0f;
TestSamplingParams params;
params.topKs = {topK};
params.topPs = {topP};
std::vector<std::set<int32_t>> expectedOutputIds{
// batch
{0}, {0}, {0}, {0}, {0}, {0}, // step 0
{0}, {0}, {0}, {0}, {0}, {0}, // step 1
{0}, {0}, {0}, {0}, {0}, {0}, // step 2
{0}, {0}, {0}, {0}, {0}, {0} // step 3
};
this->runTest(expectedOutputIds, params);
}
TYPED_TEST(TopPSamplingLayerTest, TopKTopPSkipDecode)
{
SizeType32 topK = 2;
float topP = 1.0f;
TestSamplingParams params;
params.topKs = {topK};
params.topPs = {topP};
std::vector<std::set<int32_t>> expectedOutputIds{
// batch
{0}, {0}, {0}, {0}, {0}, {0}, // step 0
{0}, {0}, {0}, {0}, {0}, {0}, // step 1
{0}, {0}, {0}, {0}, {0}, {0}, // step 2
{0}, {0}, {0}, {0}, {0}, {0} // step 3
};
this->runTest(expectedOutputIds, params);
}
TYPED_TEST(TopPSamplingLayerTest, BatchTopKTopP)
{
std::vector<SizeType32> topKs = {0, 1, 1, 0, 1, 0};
std::vector<float> topPs = {0.3f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f};
TestSamplingParams params;
params.topKs = topKs;
params.topPs = topPs;
std::vector<std::set<int32_t>> expectedOutputIds{
// batch
{4}, {0}, {0}, {4, 5}, {0}, {4, 5}, // step 0
{0}, {0}, {0}, {0, 1}, {0}, {0, 1}, // step 1
{2}, {0}, {0}, {2, 3}, {0}, {2, 3}, // step 2
{0}, {0}, {0}, {0, 1}, {0}, {0, 1} // step 3
};
this->runTest(expectedOutputIds, params);
}
TYPED_TEST(TopPSamplingLayerTest, TopP)
{
SizeType32 topK = 0;
float topP = 0.3f;
TestSamplingParams params;
params.topKs = {topK};
params.topPs = {topP};
std::vector<std::set<int32_t>> expectedOutputIds{
// batch
{4}, {4}, {4}, {4}, {4}, {4}, // step 0
{0}, {0}, {0}, {0}, {0}, {0}, // step 1
{2}, {2}, {2}, {2}, {2}, {2}, // step 2
{0}, {0}, {0}, {0}, {0}, {0} // step 3
};
this->runTest(expectedOutputIds, params);
}
TYPED_TEST(TopPSamplingLayerTest, BatchTopP)
{
std::vector<float> topPs = {0.3f, 0.3f, 0.5f, 0.8f, 0.5f, 0.8f};
TestSamplingParams params;
params.topPs = topPs;
std::vector<std::set<int32_t>> expectedOutputIds{
// batch
{4}, {4}, {4, 5}, {4, 5, 6}, {4, 5}, {4, 5, 6}, // step 0
{0}, {0}, {0, 1}, {0, 1, 2}, {0, 1}, {0, 1, 2}, // step 1
{2}, {2}, {2, 3}, {2, 3, 4}, {2, 3}, {2, 3, 4}, // step 2
{0}, {0}, {0, 1}, {0, 1, 2}, {0, 1}, {0, 1, 2} // step 3
};
this->runTest(expectedOutputIds, params);
}
TYPED_TEST(TopPSamplingLayerTest, TopKBatchTopP)
{
std::vector<float> topPs = {0.5f, 0.3f, 0.5f, 0.5f, 0.3f, 0.5f};
TestSamplingParams params;
params.topPs = topPs;
std::vector<std::set<int32_t>> expectedOutputIds{
// batch
{4, 5}, {4}, {4, 5}, {4, 5}, {4}, {4, 5}, // step 0
{0, 1}, {0}, {0, 1}, {0, 1}, {0}, {0, 1}, // step 1
{2, 3}, {2}, {2, 3}, {2, 3}, {2}, {2, 3}, // step 2
{0, 1}, {0}, {0, 1}, {0, 1}, {0}, {0, 1} // step 3
};
this->runTest(expectedOutputIds, params);
}
TYPED_TEST(TopPSamplingLayerTest, TopPDecay)
{
TestSamplingParams params;
params.topPs = {0.8f, 0.5f, 0.3f, 0.2f, 0.5f, 1.0f};
params.decay = {0.3f, 0.3f, 0.3f, 0.9f, 0.3f, 0.8f};
params.topPResetIds = {2, -1, 2, -1, 2, -1};
params.minTopP = {0.5f, 0.1f, 0.3f, 0.1f, 0.1f, 0.1f};
std::vector<std::set<int32_t>> expectedOutputIds{
// batch
{4, 5, 6}, {4, 5}, {4}, {4}, {4, 5}, {4, 5, 6, 7}, // step 0
{0, 1}, {0}, {0}, {0}, {0}, {0, 1, 2}, // step 1
{2, 3}, {2}, {2}, {2}, {2}, {2, 3}, // step 2
{0, 1, 2}, {0}, {0}, {0}, {0, 1}, {0, 1} // step 3
};
this->runTest(expectedOutputIds, params);
}
TYPED_TEST(TopPSamplingLayerTest, LargeBatch)
{
SizeType32 topK = 0;
float topP = 0.3f;
TestSamplingParams params;
params.topKs = {topK};
params.topPs = {topP};
// Force to use more than 1 block
params.batchSize = this->mDeviceProp.maxThreadsPerBlock + 1;
std::vector<std::set<int32_t>> expectedOutputId{{4}, {0}, {2}, {0}};
std::vector<std::set<int32_t>> expectedOutputIds;
expectedOutputIds.reserve(expectedOutputId.size() * params.batchSize);
for (auto const& id : expectedOutputId)
{
for (int32_t i = 0; i < params.batchSize; ++i)
{
expectedOutputIds.emplace_back(id);
}
}
this->runTest(expectedOutputIds, params);
}
} // namespace