/*
 * SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 * SPDX-License-Identifier: Apache-2.0
 *
 * 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 "envUtils.h"
#include "tensorrt_llm/common/logger.h"
#include <cstdlib>

namespace tensorrt_llm::common
{

static std::optional<int32_t> getIntEnv(char const* name)
{
    char const* const env = std::getenv(name);
    if (env == nullptr)
    {
        return std::nullopt;
    }
    int32_t const val = std::stoi(env);
    if (val <= 0)
    {
        return std::nullopt;
    }
    return {val};
};

// XQA kernels (optimized kernels for generation phase).
bool forceXQAKernels()
{
    static bool const forceXQA = (getIntEnv("TRTLLM_FORCE_XQA").value_or(0) != 0);
    return forceXQA;
}

int32_t xqaMaxNbCtaPerKVHeadFactor()
{
    return envXqaNbCtaPerKVHead().value_or(8);
}

std::optional<int32_t> envXqaNbCtaPerKVHead()
{
    static std::optional<int32_t> const ret = getIntEnv("TRTLLM_XQA_BLOCKS_PER_SEQUENCE");
    return ret;
}

bool getEnvDisableXQAJIT()
{
    static bool init = false;
    static bool disableXQAJIT = false;
    if (!init)
    {
        init = true;
        char const* disable_xqa_jit_var = std::getenv("TRTLLM_DISABLE_XQA_JIT");
        if (disable_xqa_jit_var)
        {
            if (disable_xqa_jit_var[0] == '1' && disable_xqa_jit_var[1] == '\0')
            {
                disableXQAJIT = true;
            }
        }
    }
    return disableXQAJIT;
}

// Tune the number of blocks per sequence for accuracy/performance purpose.
bool getEnvMmhaMultiblockDebug()
{
    static bool init = false;
    static bool forceMmhaMaxSeqLenTile = false;
    if (!init)
    {
        init = true;
        char const* enable_mmha_debug_var = std::getenv("TRTLLM_ENABLE_MMHA_MULTI_BLOCK_DEBUG");
        if (enable_mmha_debug_var)
        {
            if (enable_mmha_debug_var[0] == '1' && enable_mmha_debug_var[1] == '\0')
            {
                forceMmhaMaxSeqLenTile = true;
            }
        }
    }
    return forceMmhaMaxSeqLenTile;
}

int getEnvMmhaBlocksPerSequence()
{
    static bool init = false;
    static int mmhaBlocksPerSequence = 0;
    if (!init)
    {
        init = true;
        char const* mmhaBlocksPerSequenceEnv = std::getenv("TRTLLM_MMHA_BLOCKS_PER_SEQUENCE");
        if (mmhaBlocksPerSequenceEnv)
        {
            mmhaBlocksPerSequence = std::atoi(mmhaBlocksPerSequenceEnv);
            if (mmhaBlocksPerSequence <= 0)
            {
                TLLM_LOG_WARNING("Invalid value for TRTLLM_MMHA_BLOCKS_PER_SEQUENCE. Will use default values instead!");
            }
        }
    }
    return mmhaBlocksPerSequence;
}

int getEnvMmhaKernelBlockSize()
{
    static bool init = false;
    static int mmhaKernelBlockSize = 0;
    if (!init)
    {
        init = true;
        char const* mmhaKernelBlockSizeEnv = std::getenv("TRTLLM_MMHA_KERNEL_BLOCK_SIZE");
        if (mmhaKernelBlockSizeEnv)
        {
            mmhaKernelBlockSize = std::atoi(mmhaKernelBlockSizeEnv);
            if (mmhaKernelBlockSize <= 0)
            {
                TLLM_LOG_WARNING("Invalid value for TRTLLM_MMHA_KERNEL_BLOCK_SIZE. Will use default values instead!");
            }
        }
    }
    return mmhaKernelBlockSize;
}

} // namespace tensorrt_llm::common