Merge pull request #472 from Indraveen-Technologies/week-4-contributions
Week 4 Contribution: Code conversion using Gemini and Codestral
This commit is contained in:
Ed Donner
GitHub
643
week4/community-contributions/Week4_day3_Gemini_Codestral.ipynb
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643
week4/community-contributions/Week4_day3_Gemini_Codestral.ipynb
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"cells": [
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{
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"cell_type": "markdown",
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"id": "ac833f26-d429-4fd2-8f83-92174f1c951a",
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"metadata": {},
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"source": [
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"# Code conversion using Gemini and Codestral in Windows 11"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c230178c-6f31-4c5a-a888-16b7037ffbf9",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"import io\n",
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"import sys\n",
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"import gradio as gr\n",
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"import subprocess\n",
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"from google import genai\n",
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"from google.genai import types\n",
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"from mistralai import Mistral\n",
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"from dotenv import load_dotenv\n",
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"from IPython.display import Markdown, display, update_display"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "6d824484-eaaa-456a-b7dc-7e3277fec34a",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load Gemini and Mistral API Keys\n",
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"\n",
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"load_dotenv(override=True)\n",
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"gemini_api_key = os.getenv(\"GOOGLE_API_KEY\")\n",
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"mistral_api_key = os.getenv(\"MISTRAL_API_KEY\")\n",
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"\n",
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"if not mistral_api_key or not gemini_api_key:\n",
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" print(\"API Key not found!\")\n",
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"else:\n",
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" print(\"API Key loaded in memory\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "86f3633e-81f9-4c13-b7b5-793ddc4f886f",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Models to be used\n",
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"\n",
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"MODEL_GEMINI = 'gemini-2.5-flash'\n",
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"MODEL_CODESTRAL = 'codestral-latest'"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3f3a6d53-70f9-46b8-a490-a50f3a1adf9e",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load Gemini client\n",
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"try:\n",
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" gemini_client = genai.Client(api_key=gemini_api_key)\n",
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" print(\"Google GenAI Client initialized successfully!\")\n",
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"\n",
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" codestral_client = Mistral(api_key=mistral_api_key)\n",
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" print(\"Mistral Client initialized successfully!\")\n",
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"except Exception as e:\n",
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" print(f\"Error initializing Client: {e}\")\n",
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" exit() "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f816fbe8-e094-499f-98a5-588ebecf8c72",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Gemini System prompt\n",
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"\n",
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"system_message = \"You are an assistant that reimplements Python code in high-performance C++ optimized for a Windows PC. \"\n",
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"system_message += \"Use Windows-specific optimizations where applicable (e.g., multithreading with std::thread, SIMD, or WinAPI if necessary). \"\n",
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"system_message += \"Respond only with the equivalent C++ code; include comments only where absolutely necessary. \"\n",
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"system_message += \"Avoid any explanation or text outside the code. \"\n",
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"system_message += \"The C++ output must produce identical functionality with the fastest possible execution time on Windows.\"\n",
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"\n",
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"generate_content_config = types.GenerateContentConfig(system_instruction=system_message)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "01227835-15d2-40bd-a9dd-2ef35ad371dc",
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"metadata": {},
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"outputs": [],
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"source": [
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"def user_prompt_for(python):\n",
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" user_prompt = (\n",
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" \"Convert the following Python code into high-performance C++ optimized for Windows. \"\n",
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" \"Use standard C++20 or newer with Windows-compatible libraries and best practices. \"\n",
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" \"Ensure the implementation runs as fast as possible and produces identical output. \"\n",
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" \"Use appropriate numeric types to avoid overflow or precision loss. \"\n",
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" \"Avoid unnecessary abstraction; prefer direct computation and memory-efficient structures. \"\n",
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" \"Respond only with C++ code, include all required headers (like <iomanip>, <vector>, etc.), and limit comments to only what's essential.\\n\\n\"\n",
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" )\n",
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" user_prompt += python\n",
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" return user_prompt"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8d9fc8e2-acf0-4122-a8a9-5aadadf982ab",
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"metadata": {},
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"outputs": [],
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"source": [
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"def user_message_gemini(python): \n",
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" return types.Content(role=\"user\", parts=[types.Part.from_text(text=user_prompt_for(python))]) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "334c8b84-6e37-40fc-97ac-40a1b3aa29fa",
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"metadata": {},
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"outputs": [],
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"source": [
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"def messages_for(python):\n",
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" return [\n",
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" {\"role\": \"system\", \"content\": system_message},\n",
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" {\"role\": \"user\", \"content\": user_prompt_for(python)}\n",
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" ]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4aca87ac-6330-4ed4-a36f-1726fd0ada1a",
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"metadata": {},
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"outputs": [],
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"source": [
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"def write_output(cpp):\n",
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" code = cpp.replace(\"```cpp\", \"\").replace(\"```c++\", \"\").replace(\"```\", \"\").strip()\n",
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" \n",
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" if not \"#include\" in code:\n",
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" raise ValueError(\"C++ code appears invalid: missing #include directives.\")\n",
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"\n",
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" with open(\"optimized.cpp\", \"w\", encoding=\"utf-8\", newline=\"\\n\") as f:\n",
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" f.write(code) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "fcf42642-1a55-4556-8738-0c8c02effa9c",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Generate CPP code using Gemini\n",
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"\n",
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"def optimize_gemini(python):\n",
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" stream = gemini_client.models.generate_content_stream(\n",
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" model = MODEL_GEMINI,\n",
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" config=generate_content_config,\n",
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" contents=user_message_gemini(python)\n",
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" )\n",
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" cpp_code = \"\"\n",
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" for chunk in stream:\n",
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" chunk_text = chunk.text\n",
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" cpp_code += chunk_text\n",
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" print(chunk_text, end=\"\", flush=True) \n",
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" write_output(cpp_code)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3f06a301-4397-4d63-9226-657bb2ddb792",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Generate CPP code using Codestral\n",
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"\n",
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"def optimize_codestral(python):\n",
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" stream = codestral_client.chat.stream(\n",
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" model = MODEL_CODESTRAL,\n",
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" messages = messages_for(python), \n",
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" )\n",
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" \n",
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" cpp_code = \"\"\n",
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" for chunk in stream:\n",
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" chunk_text = chunk.data.choices[0].delta.content\n",
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" cpp_code += chunk_text\n",
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" print(chunk_text, end=\"\", flush=True) \n",
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" write_output(cpp_code)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8bd51601-7c1d-478d-b043-6f92739e5c4b",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Actual code to convert\n",
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"\n",
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"pi = \"\"\"\n",
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"import time\n",
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"\n",
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"def calculate(iterations, param1, param2):\n",
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" result = 1.0\n",
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" for i in range(1, iterations+1):\n",
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" j = i * param1 - param2\n",
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" result -= (1/j)\n",
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" j = i * param1 + param2\n",
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" result += (1/j)\n",
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" return result\n",
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"\n",
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"start_time = time.time()\n",
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"result = calculate(100_000_000, 4, 1) * 4\n",
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"end_time = time.time()\n",
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"\n",
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"print(f\"Result: {result:.12f}\")\n",
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"print(f\"Execution Time: {(end_time - start_time):.6f} seconds\")\n",
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"\"\"\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "db9ea24e-d381-48ac-9196-853d2527dcca",
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"metadata": {},
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"outputs": [],
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"source": [
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"exec(pi)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f3e26708-8475-474d-8e96-e602c3d5ef9f",
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"metadata": {},
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"outputs": [],
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"source": [
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"optimize_gemini(pi)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2cc23ea7-6062-4354-92bc-730baa52a50b",
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"metadata": {},
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"outputs": [],
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"source": [
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"# CPP Compilation\n",
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"\n",
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"!g++ -O3 -std=c++20 -o optimized.exe optimized.cpp"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9b14704d-95fe-4ed2-861f-af591bf3090e",
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"metadata": {},
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"outputs": [],
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"source": [
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"!.\\optimized.exe"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "5d756d1a-1d49-4cfb-bed7-8748d848b083",
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"metadata": {},
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"outputs": [],
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"source": [
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"optimize_codestral(pi)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "6e286dc8-9532-48b1-b748-a7950972e7df",
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"metadata": {},
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"outputs": [],
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"source": [
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"!g++ -O3 -std=c++20 -o optimized.exe optimized.cpp"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "61fe0044-7679-4245-9e59-50642f3d80c6",
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"metadata": {},
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"outputs": [],
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"source": [
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"!.\\optimized.exe"
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]
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},
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{
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"cell_type": "markdown",
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"id": "f0c0392c-d2a7-4619-82a2-f7b9fa7c43f9",
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"metadata": {},
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"source": [
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"## Hard Code"
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]
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},
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{
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"cell_type": "code",
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|
"execution_count": null,
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||||||
|
"id": "9ca53eb4-46cd-435b-a950-0e2a8f845535",
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"metadata": {},
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"outputs": [],
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"source": [
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"python_hard = \"\"\"# Be careful to support large number sizes\n",
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"\n",
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"def lcg(seed, a=1664525, c=1013904223, m=2**32):\n",
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" value = seed\n",
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" while True:\n",
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" value = (a * value + c) % m\n",
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" yield value\n",
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" \n",
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"def max_subarray_sum(n, seed, min_val, max_val):\n",
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" lcg_gen = lcg(seed)\n",
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" random_numbers = [next(lcg_gen) % (max_val - min_val + 1) + min_val for _ in range(n)]\n",
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" max_sum = float('-inf')\n",
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" for i in range(n):\n",
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" current_sum = 0\n",
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" for j in range(i, n):\n",
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" current_sum += random_numbers[j]\n",
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||||||
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" if current_sum > max_sum:\n",
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||||||
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" max_sum = current_sum\n",
|
||||||
|
" return max_sum\n",
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"\n",
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"def total_max_subarray_sum(n, initial_seed, min_val, max_val):\n",
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" total_sum = 0\n",
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" lcg_gen = lcg(initial_seed)\n",
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" for _ in range(20):\n",
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" seed = next(lcg_gen)\n",
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" total_sum += max_subarray_sum(n, seed, min_val, max_val)\n",
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||||||
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" return total_sum\n",
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"\n",
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||||||
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"# Parameters\n",
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"n = 10000 # Number of random numbers\n",
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"initial_seed = 42 # Initial seed for the LCG\n",
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"min_val = -10 # Minimum value of random numbers\n",
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"max_val = 10 # Maximum value of random numbers\n",
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"\n",
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"# Timing the function\n",
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"import time\n",
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||||||
|
"start_time = time.time()\n",
|
||||||
|
"result = total_max_subarray_sum(n, initial_seed, min_val, max_val)\n",
|
||||||
|
"end_time = time.time()\n",
|
||||||
|
"\n",
|
||||||
|
"print(\"Total Maximum Subarray Sum (20 runs):\", result)\n",
|
||||||
|
"print(\"Execution Time: {:.6f} seconds\".format(end_time - start_time))\n",
|
||||||
|
"\"\"\""
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "697cc9fe-efdb-40b7-8e43-871bd2df940e",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"exec(python_hard)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "17ed6329-6c5f-45af-91ff-06d73830dd0d",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"optimize_gemini(python_hard)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "0b57f0e7-46c9-4235-86eb-389faf37b7bb",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# CPP Compilation\n",
|
||||||
|
"\n",
|
||||||
|
"!g++ -O3 -std=c++20 -o optimized.exe optimized.cpp"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "b8ce8d01-fda8-400d-b3d4-6f1ad3008d28",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"!.\\optimized.exe"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "adbcdac7-8656-41c9-8707-d8a71998d393",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"optimize_codestral(python_hard)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "9f9fc9b1-29cf-4510-83f8-1484d26e871e",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# CPP Compilation\n",
|
||||||
|
"\n",
|
||||||
|
"!g++ -O3 -std=c++20 -o optimized.exe optimized.cpp"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "52170458-c4a1-4920-8d83-8c5ba7250759",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"!.\\optimized.exe"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "da6aee85-2792-487b-bef3-fec5dcf12623",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Accommodating the entire code in Gradio"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "f2a90c4f-c289-4658-a6ce-51b80e20f91f",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def stream_gemini(python):\n",
|
||||||
|
" stream = gemini_client.models.generate_content_stream(\n",
|
||||||
|
" model = MODEL_GEMINI,\n",
|
||||||
|
" config=generate_content_config,\n",
|
||||||
|
" contents=user_message_gemini(python)\n",
|
||||||
|
" )\n",
|
||||||
|
"\n",
|
||||||
|
" cpp_code = \"\"\n",
|
||||||
|
" for chunk in stream:\n",
|
||||||
|
" chunk_text = chunk.text or \"\"\n",
|
||||||
|
" cpp_code += chunk_text\n",
|
||||||
|
" yield cpp_code.replace('```cpp\\n','').replace('```','')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "6e872171-96d8-4041-8cb0-0c632c5e957f",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def stream_codestral(python):\n",
|
||||||
|
" stream = codestral_client.chat.stream(\n",
|
||||||
|
" model = MODEL_CODESTRAL,\n",
|
||||||
|
" messages = messages_for(python), \n",
|
||||||
|
" )\n",
|
||||||
|
"\n",
|
||||||
|
" cpp_code = \"\"\n",
|
||||||
|
" for chunk in stream:\n",
|
||||||
|
" chunk_text = chunk.data.choices[0].delta.content or \"\"\n",
|
||||||
|
" cpp_code += chunk_text\n",
|
||||||
|
" yield cpp_code.replace('```cpp\\n','').replace('```','') "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "3340b36b-1241-4b0f-9e69-d4e5cc215a27",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def optimize(python, model):\n",
|
||||||
|
" if model.lower() == 'gemini':\n",
|
||||||
|
" result = stream_gemini(python)\n",
|
||||||
|
" elif model.lower() == 'codestral':\n",
|
||||||
|
" result = stream_codestral(python)\n",
|
||||||
|
" else:\n",
|
||||||
|
" raise ValueError(\"Unknown model\")\n",
|
||||||
|
" \n",
|
||||||
|
" for stream_so_far in result:\n",
|
||||||
|
" yield stream_so_far "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "277ddd6c-e71e-4512-965a-57fca341487a",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"### Gradio Implementation"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "222a9eae-236e-4ba3-8f23-3d9b879ec2d0",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"custom_css = \"\"\"\n",
|
||||||
|
".scrollable-box textarea {\n",
|
||||||
|
" overflow: auto !important;\n",
|
||||||
|
" height: 400px;\n",
|
||||||
|
"}\n",
|
||||||
|
"\n",
|
||||||
|
".python {background-color: #306998;}\n",
|
||||||
|
".cpp {background-color: #050;}\n",
|
||||||
|
"\n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"\n",
|
||||||
|
"theme = gr.themes.Soft()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "b4bd6ed1-ff8c-42d4-8da6-24b9cfd134db",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def execute_python(code):\n",
|
||||||
|
" try:\n",
|
||||||
|
" result = subprocess.run(\n",
|
||||||
|
" [\"python\", \"-c\", code],\n",
|
||||||
|
" capture_output=True,\n",
|
||||||
|
" text=True,\n",
|
||||||
|
" timeout=60\n",
|
||||||
|
" )\n",
|
||||||
|
" if result.returncode == 0:\n",
|
||||||
|
" return result.stdout or \"[No output]\"\n",
|
||||||
|
" else:\n",
|
||||||
|
" return f\"[Error]\\n{result.stderr}\"\n",
|
||||||
|
" except subprocess.TimeoutExpired:\n",
|
||||||
|
" return \"[Error] Execution timed out.\"\n",
|
||||||
|
" except Exception as e:\n",
|
||||||
|
" return f\"[Exception] {str(e)}\" "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "1507c973-8699-48b2-80cd-45900c97a867",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def execute_cpp(code):\n",
|
||||||
|
" write_output(code)\n",
|
||||||
|
" \n",
|
||||||
|
" try:\n",
|
||||||
|
" compile_cmd = [\"g++\", \"-O3\", \"-std=c++20\", \"-o\", \"optimized.exe\", \"optimized.cpp\"]\n",
|
||||||
|
" compile_result = subprocess.run(compile_cmd, capture_output=True, text=True, check=True)\n",
|
||||||
|
" \n",
|
||||||
|
" run_cmd = [\"optimized.exe\"]\n",
|
||||||
|
" run_result = subprocess.run(run_cmd, check=True, text=True, capture_output=True, timeout=60)\n",
|
||||||
|
" \n",
|
||||||
|
" return run_result.stdout or \"[No output]\"\n",
|
||||||
|
" \n",
|
||||||
|
" except subprocess.CalledProcessError as e:\n",
|
||||||
|
" return f\"[Compile/Runtime Error]\\n{e.stderr}\"\n",
|
||||||
|
" except subprocess.TimeoutExpired:\n",
|
||||||
|
" return \"[Error] Execution timed out.\"\n",
|
||||||
|
" except Exception as e:\n",
|
||||||
|
" return f\"[Exception] {str(e)}\" "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "374f00f3-8fcf-4ae9-bf54-c5a44dd74844",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"with gr.Blocks(css=custom_css, theme=theme) as ui:\n",
|
||||||
|
" gr.Markdown(\"## Convert code from Python to C++\")\n",
|
||||||
|
" with gr.Row():\n",
|
||||||
|
" python = gr.Textbox(label=\"Python code:\", lines=10, value=python_hard, elem_classes=[\"scrollable-box\"])\n",
|
||||||
|
" cpp = gr.Textbox(label=\"C++ code:\", lines=10, elem_classes=[\"scrollable-box\"])\n",
|
||||||
|
" with gr.Row():\n",
|
||||||
|
" model = gr.Dropdown([\"Gemini\", \"Codestral\"], label=\"Select model\", value=\"Gemini\")\n",
|
||||||
|
" convert = gr.Button(\"Convert code\")\n",
|
||||||
|
" with gr.Row():\n",
|
||||||
|
" python_run = gr.Button(\"Run Python\")\n",
|
||||||
|
" cpp_run = gr.Button(\"Run C++\")\n",
|
||||||
|
" with gr.Row():\n",
|
||||||
|
" python_out = gr.TextArea(label=\"Python result:\", elem_classes=[\"python\"])\n",
|
||||||
|
" cpp_out = gr.TextArea(label=\"C++ result:\", elem_classes=[\"cpp\"])\n",
|
||||||
|
"\n",
|
||||||
|
" convert.click(optimize, inputs=[python,model], outputs=[cpp])\n",
|
||||||
|
" python_run.click(execute_python,inputs=[python], outputs=[python_out])\n",
|
||||||
|
" cpp_run.click(execute_cpp, inputs=[cpp], outputs=[cpp_out])\n",
|
||||||
|
"\n",
|
||||||
|
"ui.launch(inbrowser=True) "
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 3 (ipykernel)",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python3"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 3
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython3",
|
||||||
|
"version": "3.12.10"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 5
|
||||||
|
}
|
||||||
@@ -0,0 +1,476 @@
|
|||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "4c07cdc9-bce0-49ad-85c7-14f1872b8519",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# Python to CPP using Qwen2.5-Coder-32B-Instruct with Hyperbolic Inference Endpoint in Windows"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "f051c517-c4fd-4248-98aa-b808fae76cf6",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import os\n",
|
||||||
|
"import io\n",
|
||||||
|
"import sys\n",
|
||||||
|
"import gradio as gr\n",
|
||||||
|
"import subprocess\n",
|
||||||
|
"from dotenv import load_dotenv\n",
|
||||||
|
"from huggingface_hub import InferenceClient\n",
|
||||||
|
"from google import genai\n",
|
||||||
|
"from google.genai import types\n",
|
||||||
|
"from mistralai import Mistral"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "c6c8777b-57bc-436a-978f-21a37ea310ae",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Load Api Keys from env\n",
|
||||||
|
"\n",
|
||||||
|
"load_dotenv(override=True)\n",
|
||||||
|
"\n",
|
||||||
|
"hf_api_key = os.getenv(\"HF_TOKEN\")\n",
|
||||||
|
"gemini_api_key = os.getenv(\"GOOGLE_API_KEY\")\n",
|
||||||
|
"mistral_api_key = os.getenv(\"MISTRAL_API_KEY\")\n",
|
||||||
|
"\n",
|
||||||
|
"if not mistral_api_key or not gemini_api_key or not hf_api_key:\n",
|
||||||
|
" print(\"API Key not found!\")\n",
|
||||||
|
"else:\n",
|
||||||
|
" print(\"API Key loaded in memory\")"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "e5cf6f93-7e07-40e0-98b8-d4e74ea18402",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# MODELs \n",
|
||||||
|
"\n",
|
||||||
|
"MODEL_QWEN = \"Qwen/Qwen2.5-Coder-32B-Instruct\"\n",
|
||||||
|
"MODEL_GEMINI = 'gemini-2.5-flash'\n",
|
||||||
|
"MODEL_CODESTRAL = 'codestral-latest'"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "689547c3-aaa5-4800-86a2-da52765997d8",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"# Load Clients\n",
|
||||||
|
"\n",
|
||||||
|
"try:\n",
|
||||||
|
" gemini_client = genai.Client(api_key=gemini_api_key)\n",
|
||||||
|
" print(\"Google GenAI Client initialized successfully!\")\n",
|
||||||
|
"\n",
|
||||||
|
" codestral_client = Mistral(api_key=mistral_api_key)\n",
|
||||||
|
" print(\"Mistral Client initialized successfully!\")\n",
|
||||||
|
" \n",
|
||||||
|
" hf_client = InferenceClient(provider=\"hyperbolic\",api_key=hf_api_key)\n",
|
||||||
|
" print(\"Hyperbolic Inference Client initialized successfully!\")\n",
|
||||||
|
"except Exception as e:\n",
|
||||||
|
" print(f\"Error initializing Client: {e}\")\n",
|
||||||
|
" exit() "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "1c3a81f4-99c3-463a-ae30-4656a7a246d2",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"system_message = \"You are an assistant that reimplements Python code in high-performance C++ optimized for a Windows PC. \"\n",
|
||||||
|
"system_message += \"Use Windows-specific optimizations where applicable (e.g., multithreading with std::thread, SIMD, or WinAPI if necessary). \"\n",
|
||||||
|
"system_message += \"Respond only with the equivalent C++ code; include comments only where absolutely necessary. \"\n",
|
||||||
|
"system_message += \"Avoid any explanation or text outside the code. \"\n",
|
||||||
|
"system_message += \"The C++ output must produce identical functionality with the fastest possible execution time on Windows.\"\n",
|
||||||
|
"\n",
|
||||||
|
"generate_content_config = types.GenerateContentConfig(system_instruction=system_message)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "0fde9514-1005-4539-b01b-0372730ce67b",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def user_prompt_for(python):\n",
|
||||||
|
" user_prompt = (\n",
|
||||||
|
" \"Convert the following Python code into high-performance C++ optimized for Windows. \"\n",
|
||||||
|
" \"Use standard C++20 or newer with Windows-compatible libraries and best practices. \"\n",
|
||||||
|
" \"Ensure the implementation runs as fast as possible and produces identical output. \"\n",
|
||||||
|
" \"Use appropriate numeric types to avoid overflow or precision loss. \"\n",
|
||||||
|
" \"Avoid unnecessary abstraction; prefer direct computation and memory-efficient structures. \"\n",
|
||||||
|
" \"Respond only with C++ code, include all required headers (like <iomanip>, <vector>, etc.), and limit comments to only what's essential.\\n\\n\"\n",
|
||||||
|
" )\n",
|
||||||
|
" user_prompt += python\n",
|
||||||
|
" return user_prompt"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "89c8b010-08dd-4695-a784-65162d82a24b",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def user_message_gemini(python): \n",
|
||||||
|
" return types.Content(role=\"user\", parts=[types.Part.from_text(text=user_prompt_for(python))]) "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "66923158-983d-46f7-ab19-f216fb1f6a87",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def messages_for(python):\n",
|
||||||
|
" return [\n",
|
||||||
|
" {\"role\": \"system\", \"content\": system_message},\n",
|
||||||
|
" {\"role\": \"user\", \"content\": user_prompt_for(python)}\n",
|
||||||
|
" ]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "9ab59a54-b28a-4d07-b04f-b568e6e25dfb",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def write_output(cpp):\n",
|
||||||
|
" code = cpp.replace(\"```cpp\", \"\").replace(\"```c++\", \"\").replace(\"```\", \"\").strip()\n",
|
||||||
|
" \n",
|
||||||
|
" if not \"#include\" in code:\n",
|
||||||
|
" raise ValueError(\"C++ code appears invalid: missing #include directives.\")\n",
|
||||||
|
"\n",
|
||||||
|
" with open(\"qwenOptimized.cpp\", \"w\", encoding=\"utf-8\", newline=\"\\n\") as f:\n",
|
||||||
|
" f.write(code) "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "e05ea9f0-6ade-4699-b5fa-fb8ef9f16bcb",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"### Python Codes"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "c515ce2c-1f8d-4484-8d34-9ffe1372dad4",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"python_easy = \"\"\"\n",
|
||||||
|
"import time\n",
|
||||||
|
"\n",
|
||||||
|
"def calculate(iterations, param1, param2):\n",
|
||||||
|
" result = 1.0\n",
|
||||||
|
" for i in range(1, iterations+1):\n",
|
||||||
|
" j = i * param1 - param2\n",
|
||||||
|
" result -= (1/j)\n",
|
||||||
|
" j = i * param1 + param2\n",
|
||||||
|
" result += (1/j)\n",
|
||||||
|
" return result\n",
|
||||||
|
"\n",
|
||||||
|
"start_time = time.time()\n",
|
||||||
|
"result = calculate(100_000_000, 4, 1) * 4\n",
|
||||||
|
"end_time = time.time()\n",
|
||||||
|
"\n",
|
||||||
|
"print(f\"Result: {result:.12f}\")\n",
|
||||||
|
"print(f\"Execution Time: {(end_time - start_time):.6f} seconds\")\n",
|
||||||
|
"\"\"\""
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "83ab4080-71ae-45e6-970b-030dc462f571",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"python_hard = \"\"\"# Be careful to support large number sizes\n",
|
||||||
|
"\n",
|
||||||
|
"def lcg(seed, a=1664525, c=1013904223, m=2**32):\n",
|
||||||
|
" value = seed\n",
|
||||||
|
" while True:\n",
|
||||||
|
" value = (a * value + c) % m\n",
|
||||||
|
" yield value\n",
|
||||||
|
" \n",
|
||||||
|
"def max_subarray_sum(n, seed, min_val, max_val):\n",
|
||||||
|
" lcg_gen = lcg(seed)\n",
|
||||||
|
" random_numbers = [next(lcg_gen) % (max_val - min_val + 1) + min_val for _ in range(n)]\n",
|
||||||
|
" max_sum = float('-inf')\n",
|
||||||
|
" for i in range(n):\n",
|
||||||
|
" current_sum = 0\n",
|
||||||
|
" for j in range(i, n):\n",
|
||||||
|
" current_sum += random_numbers[j]\n",
|
||||||
|
" if current_sum > max_sum:\n",
|
||||||
|
" max_sum = current_sum\n",
|
||||||
|
" return max_sum\n",
|
||||||
|
"\n",
|
||||||
|
"def total_max_subarray_sum(n, initial_seed, min_val, max_val):\n",
|
||||||
|
" total_sum = 0\n",
|
||||||
|
" lcg_gen = lcg(initial_seed)\n",
|
||||||
|
" for _ in range(20):\n",
|
||||||
|
" seed = next(lcg_gen)\n",
|
||||||
|
" total_sum += max_subarray_sum(n, seed, min_val, max_val)\n",
|
||||||
|
" return total_sum\n",
|
||||||
|
"\n",
|
||||||
|
"# Parameters\n",
|
||||||
|
"n = 10000 # Number of random numbers\n",
|
||||||
|
"initial_seed = 42 # Initial seed for the LCG\n",
|
||||||
|
"min_val = -10 # Minimum value of random numbers\n",
|
||||||
|
"max_val = 10 # Maximum value of random numbers\n",
|
||||||
|
"\n",
|
||||||
|
"# Timing the function\n",
|
||||||
|
"import time\n",
|
||||||
|
"start_time = time.time()\n",
|
||||||
|
"result = total_max_subarray_sum(n, initial_seed, min_val, max_val)\n",
|
||||||
|
"end_time = time.time()\n",
|
||||||
|
"\n",
|
||||||
|
"print(\"Total Maximum Subarray Sum (20 runs):\", result)\n",
|
||||||
|
"print(\"Execution Time: {:.6f} seconds\".format(end_time - start_time))\n",
|
||||||
|
"\"\"\""
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "31498c5c-ecdd-4ed7-9607-4d09af893b98",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Code Implementation"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "ea4a4968-e04f-4939-8c42-32c960699354",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def stream_gemini(python):\n",
|
||||||
|
" stream = gemini_client.models.generate_content_stream(\n",
|
||||||
|
" model = MODEL_GEMINI,\n",
|
||||||
|
" config=generate_content_config,\n",
|
||||||
|
" contents=user_message_gemini(python)\n",
|
||||||
|
" )\n",
|
||||||
|
"\n",
|
||||||
|
" cpp_code = \"\"\n",
|
||||||
|
" for chunk in stream:\n",
|
||||||
|
" chunk_text = chunk.text or \"\"\n",
|
||||||
|
" cpp_code += chunk_text\n",
|
||||||
|
" yield cpp_code.replace('```cpp\\n','').replace('```','')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "69601eee-520f-4813-b796-aee9118e8a72",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def stream_codestral(python):\n",
|
||||||
|
" stream = codestral_client.chat.stream(\n",
|
||||||
|
" model = MODEL_CODESTRAL,\n",
|
||||||
|
" messages = messages_for(python), \n",
|
||||||
|
" )\n",
|
||||||
|
"\n",
|
||||||
|
" cpp_code = \"\"\n",
|
||||||
|
" for chunk in stream:\n",
|
||||||
|
" chunk_text = chunk.data.choices[0].delta.content or \"\"\n",
|
||||||
|
" cpp_code += chunk_text\n",
|
||||||
|
" yield cpp_code.replace('```cpp\\n','').replace('```','') "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "cb8899cf-54c0-4d2d-8772-42925c2e1d13",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def stream_qwen(python):\n",
|
||||||
|
" stream = hf_client.chat.completions.create(\n",
|
||||||
|
" model = MODEL_QWEN,\n",
|
||||||
|
" messages = messages_for(python),\n",
|
||||||
|
" stream=True\n",
|
||||||
|
" )\n",
|
||||||
|
" cpp_code = \"\"\n",
|
||||||
|
" for chunk in stream:\n",
|
||||||
|
" chunk_text = chunk.choices[0].delta.content\n",
|
||||||
|
" cpp_code += chunk_text\n",
|
||||||
|
" yield cpp_code.replace('```cpp\\n','').replace('```','')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "98862fef-905c-4b50-bc7a-4c0462495b5c",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def optimize(python, model):\n",
|
||||||
|
" if model.lower() == 'gemini':\n",
|
||||||
|
" result = stream_gemini(python)\n",
|
||||||
|
" elif model.lower() == 'codestral':\n",
|
||||||
|
" result = stream_codestral(python)\n",
|
||||||
|
" elif model.lower() == 'qwen_coder':\n",
|
||||||
|
" result = stream_qwen(python)\n",
|
||||||
|
" else:\n",
|
||||||
|
" raise ValueError(\"Unknown model\")\n",
|
||||||
|
" \n",
|
||||||
|
" for stream_so_far in result:\n",
|
||||||
|
" yield stream_so_far "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "aa9372df-db01-41d0-842c-4857b20f93f0",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"custom_css = \"\"\"\n",
|
||||||
|
".scrollable-box textarea {\n",
|
||||||
|
" overflow: auto !important;\n",
|
||||||
|
" height: 400px;\n",
|
||||||
|
"}\n",
|
||||||
|
"\n",
|
||||||
|
".python {background-color: #306998;}\n",
|
||||||
|
".cpp {background-color: #050;}\n",
|
||||||
|
"\n",
|
||||||
|
"\"\"\"\n",
|
||||||
|
"\n",
|
||||||
|
"theme = gr.themes.Soft()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "dbcf9fe9-c3da-466b-8478-83dcdbe7d48e",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def execute_python(code):\n",
|
||||||
|
" try:\n",
|
||||||
|
" result = subprocess.run(\n",
|
||||||
|
" [\"python\", \"-c\", code],\n",
|
||||||
|
" capture_output=True,\n",
|
||||||
|
" text=True,\n",
|
||||||
|
" timeout=60\n",
|
||||||
|
" )\n",
|
||||||
|
" if result.returncode == 0:\n",
|
||||||
|
" return result.stdout or \"[No output]\"\n",
|
||||||
|
" else:\n",
|
||||||
|
" return f\"[Error]\\n{result.stderr}\"\n",
|
||||||
|
" except subprocess.TimeoutExpired:\n",
|
||||||
|
" return \"[Error] Execution timed out.\"\n",
|
||||||
|
" except Exception as e:\n",
|
||||||
|
" return f\"[Exception] {str(e)}\" "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "8029e00d-1ee8-43d1-8c87-2aa0544cf94c",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"def execute_cpp(code):\n",
|
||||||
|
" write_output(code)\n",
|
||||||
|
" \n",
|
||||||
|
" try:\n",
|
||||||
|
" compile_cmd = [\"g++\", \"-O3\", \"-std=c++20\", \"-o\", \"optimized.exe\", \"optimized.cpp\"]\n",
|
||||||
|
" compile_result = subprocess.run(compile_cmd, capture_output=True, text=True, check=True)\n",
|
||||||
|
" \n",
|
||||||
|
" run_cmd = [\"optimized.exe\"]\n",
|
||||||
|
" run_result = subprocess.run(run_cmd, check=True, text=True, capture_output=True, timeout=60)\n",
|
||||||
|
" \n",
|
||||||
|
" return run_result.stdout or \"[No output]\"\n",
|
||||||
|
" \n",
|
||||||
|
" except subprocess.CalledProcessError as e:\n",
|
||||||
|
" return f\"[Compile/Runtime Error]\\n{e.stderr}\"\n",
|
||||||
|
" except subprocess.TimeoutExpired:\n",
|
||||||
|
" return \"[Error] Execution timed out.\"\n",
|
||||||
|
" except Exception as e:\n",
|
||||||
|
" return f\"[Exception] {str(e)}\" "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "d5f4e88c-be15-4870-9f99-82b6273ee739",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"with gr.Blocks(css=custom_css, theme=theme) as ui:\n",
|
||||||
|
" gr.Markdown(\"## Convert code from Python to C++\")\n",
|
||||||
|
" with gr.Row():\n",
|
||||||
|
" python = gr.Textbox(label=\"Python code:\", lines=10, value=python_hard, elem_classes=[\"scrollable-box\"])\n",
|
||||||
|
" cpp = gr.Textbox(label=\"C++ code:\", lines=10, elem_classes=[\"scrollable-box\"])\n",
|
||||||
|
" with gr.Row():\n",
|
||||||
|
" model = gr.Dropdown([\"Gemini\", \"Codestral\", \"QWEN_Coder\"], label=\"Select model\", value=\"Gemini\")\n",
|
||||||
|
" convert = gr.Button(\"Convert code\")\n",
|
||||||
|
" with gr.Row():\n",
|
||||||
|
" python_run = gr.Button(\"Run Python\")\n",
|
||||||
|
" cpp_run = gr.Button(\"Run C++\")\n",
|
||||||
|
" with gr.Row():\n",
|
||||||
|
" python_out = gr.TextArea(label=\"Python result:\", elem_classes=[\"python\"])\n",
|
||||||
|
" cpp_out = gr.TextArea(label=\"C++ result:\", elem_classes=[\"cpp\"])\n",
|
||||||
|
"\n",
|
||||||
|
" convert.click(optimize, inputs=[python,model], outputs=[cpp])\n",
|
||||||
|
" python_run.click(execute_python,inputs=[python], outputs=[python_out])\n",
|
||||||
|
" cpp_run.click(execute_cpp, inputs=[cpp], outputs=[cpp_out])\n",
|
||||||
|
"\n",
|
||||||
|
"ui.launch(inbrowser=True) "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "aa1a231e-2743-4cee-afe2-783d2b9513e5",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": []
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 3 (ipykernel)",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python3"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 3
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython3",
|
||||||
|
"version": "3.12.10"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 5
|
||||||
|
}
|
||||||
Reference in New Issue
Block a user