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Merge pull request #726 from max-solo23/main

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add my version of python to c++ converter
This commit is contained in:
Ed Donner
2025-10-18 14:36:23 -04:00
committed by GitHub
parent 4e9a76b83a 859d5eb2b6
commit 395dae7402
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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "a389285f-5e8e-46ec-bcae-9b159ef7aa80",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import io\n",
"\n",
"import sys\n",
"from dotenv import load_dotenv\n",
"from openai import OpenAI\n",
"import google.generativeai\n",
"import anthropic\n",
"from IPython.display import Markdown, display, update_display\n",
"import gradio as gr\n",
"import subprocess"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "850164b8-5bab-402f-9e80-d251930d9017",
"metadata": {},
"outputs": [],
"source": [
"load_dotenv()\n",
"os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', 'your-key-if-not-using-env')\n",
"os.environ['ANTHROPIC_API_KEY'] = os.getenv('ANTHROPIC_API_KEY', 'your-key-if-not-using-env')"
]
},
{
"cell_type": "code",
"execution_count": 56,
"id": "87650c13-e987-42a2-9089-23827bc81ffb",
"metadata": {},
"outputs": [],
"source": [
"openai = OpenAI()\n",
"claude = anthropic.Anthropic()\n",
"OPENAI_MODEL = \"gpt-5-nano\"\n",
"CLAUDE_MODEL = \"claude-3-5-sonnet-20240620\" # CLAUDE_MODEL = \"claude-3-haiku-20240307\""
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "9d359c39-4eab-478c-a208-08a38b799093",
"metadata": {},
"outputs": [],
"source": [
"system_message = \"You are an assistant that reimplements Python code in high performance C++ for an windows 10. \"\n",
"system_message += \"Respond only with C++ code; use comments sparingly and do not provide any explanation other than occasional comments. \"\n",
"system_message += \"The C++ response needs to produce an identical output in the fastest possible time.\""
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "1d8da092-6c5c-4c42-aed9-dc219fdd97bb",
"metadata": {},
"outputs": [],
"source": [
"def user_prompt_for(python):\n",
" user_prompt = \"Rewrite this Python code in C++ with the fastest possible implementation that produces identical output in the least time. Add a pause in the end of the code so it waits button press after execution. \"\n",
" user_prompt += \"Respond only with C++ code; do not explain your work other than a few comments. \"\n",
" user_prompt += \"Pay attention to number types to ensure no int overflows. Remember to #include all necessary C++ packages such as iomanip.\\n\\n\"\n",
" user_prompt += python\n",
" return user_prompt"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "be49c7dc-5c82-468e-b41e-7fca27fbb2e0",
"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": 7,
"id": "afeded80-a4a0-4349-89c3-2e9370730e92",
"metadata": {},
"outputs": [],
"source": [
"def write_output(cpp):\n",
" code = cpp.replace(\"```cpp\",\"\").replace(\"```\",\"\")\n",
" with open(\"optimized.cpp\", \"w\") as f:\n",
" f.write(code)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "6a53a889-9146-4049-850d-9b44d7245b8b",
"metadata": {},
"outputs": [],
"source": [
"def optimize_gpt(python): \n",
" stream = openai.chat.completions.create(model=OPENAI_MODEL, messages=messages_for(python), stream=True)\n",
" reply = \"\"\n",
" for chunk in stream:\n",
" fragment = chunk.choices[0].delta.content or \"\"\n",
" reply += fragment\n",
" print(fragment, end='', flush=True)\n",
" write_output(reply)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "3d31f2e4-2bcb-4d9a-bb73-6979784c9234",
"metadata": {},
"outputs": [],
"source": [
"def optimize_claude(python):\n",
" result = claude.messages.stream(\n",
" model=CLAUDE_MODEL,\n",
" max_tokens=2000,\n",
" system=system_message,\n",
" messages=[{\"role\": \"user\", \"content\": user_prompt_for(python)}],\n",
" )\n",
" reply = \"\"\n",
" with result as stream:\n",
" for text in stream.text_stream:\n",
" reply += text\n",
" print(text, end=\"\", flush=True)\n",
" write_output(reply)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "bff0c7f1-6402-46a7-940d-5233e93d1089",
"metadata": {},
"outputs": [],
"source": [
"pi = \"\"\"\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": 11,
"id": "b878f33e-9008-496d-b8f6-f844c22e6a04",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Result: 3.141592658589\n",
"Execution Time: 9.382045 seconds\n"
]
}
],
"source": [
"exec(pi)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "af8bc910-9136-4305-a1a8-a47fa0566505",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"#include <iostream>\n",
"#include <iomanip>\n",
"#include <chrono>\n",
"\n",
"int main() {\n",
" const long long iterations = 100000000LL;\n",
" const double param1 = 4.0;\n",
" const double param2 = 1.0;\n",
"\n",
" double result = 1.0;\n",
"\n",
" auto start = std::chrono::high_resolution_clock::now();\n",
" for (long long i = 1; i <= iterations; ++i) {\n",
" double j = i * param1 - param2;\n",
" result -= 1.0 / j;\n",
" j = i * param1 + param2;\n",
" result += 1.0 / j;\n",
" }\n",
" auto end = std::chrono::high_resolution_clock::now();\n",
"\n",
" double final_result = result * 4.0;\n",
"\n",
" std::cout.setf(std::ios::fixed);\n",
" std::cout << std::setprecision(12);\n",
" std::cout << \"Result: \" << final_result << \"\\n\";\n",
"\n",
" std::chrono::duration<double> elapsed = end - start;\n",
" std::cout << std::setprecision(6);\n",
" std::cout << \"Execution Time: \" << elapsed.count() << \" seconds\" << std::endl;\n",
"\n",
" return 0;\n",
"}"
]
}
],
"source": [
"optimize_gpt(pi)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "8d37469c-ab26-452f-8efb-e1b65f842f90",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Result: 3.141592658589\n",
"Execution Time: 9.346793 seconds\n"
]
}
],
"source": [
"exec(pi)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "1164d9cc-7ad8-4e5c-98bb-a186ad23f4d7",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\".\" non e riconosciuto come comando interno o esterno,\n",
" un programma eseguibile o un file batch.\n"
]
}
],
"source": [
"!g++ -O2 -std=c++17 optimized.cpp -o optimized\n",
"!./optimized"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "d4b501d0-3707-4c07-95c7-7f6fe389859c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"```cpp\n",
" <iostream>\n",
"omanip>e <i\n",
"ono>lude <chr\n",
"include <conio.h>\n",
"\n",
" calculate(long long int iterations, double param1, double param2) {\n",
" result = 1.0;\n",
" long int i = 1; i <= iterations; i++) {\n",
"double j = i * param1 - param2;\n",
" (1.0 / j);ult -=\n",
" * param1 + param2;\n",
" (1.0 / j);ult +=\n",
" }\n",
" return result;\n",
"}\n",
"\n",
" main() {\n",
" start_time = std::chrono::high_resolution_clock::now();\n",
" result = calculate(100000000, 4, 1) * 4;\n",
"d_time = std::chrono::high_resolution_clock::now();\n",
"\n",
" << std::fixed << std::setprecision(12) << \"Result: \" << result << std::endl;\n",
"cout << \"Execution Time: \" << std::chrono::duration_cast<std::chrono::duration<double>>(end_time - start_time).count() << \" seconds\" << std::endl;\n",
"\n",
"d::cout << \"Press any key to exit...\" << std::endl;\n",
"_getch();\n",
"; return 0\n",
"}\n",
"```"
]
}
],
"source": [
"optimize_claude(pi)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "c81bf6fc-27b7-4f42-a2c9-42eff17b6e41",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\".\" non e riconosciuto come comando interno o esterno,\n",
" un programma eseguibile o un file batch.\n"
]
}
],
"source": [
"!g++ -O2 -std=c++17 optimized.cpp -o optimized\n",
"!./optimized\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "a5e8e6f5-50d4-4c37-8a10-dd07fbd24089",
"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": "code",
"execution_count": 33,
"id": "cd8a29a9-94fa-43f5-ae4d-517182cfd218",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Total Maximum Subarray Sum (20 runs): 10980\n",
"Execution Time: 34.608083 seconds\n"
]
}
],
"source": [
"exec(python_hard)"
]
},
{
"cell_type": "code",
"execution_count": 57,
"id": "39c64322-ef0f-4d58-a54e-c31077ceadb9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"#include <iostream>\n",
"#include <iomanip>\n",
"#include <cstdint>\n",
"#include <limits>\n",
"#include <chrono>\n",
"\n",
"static inline uint32_t lcg_next(uint32_t value) {\n",
" const uint64_t a = 1664525ULL;\n",
" const uint64_t c = 1013904223ULL;\n",
" const uint64_t m = 0x100000000ULL; // 2^32\n",
" uint64_t t = a * value + c;\n",
" t %= m;\n",
" return static_cast<uint32_t>(t);\n",
"}\n",
"\n",
"static inline int64_t max_subarray_sum_with_seed(uint32_t seed, int n, int min_val, int max_val) {\n",
" int range = max_val - min_val + 1;\n",
" int64_t max_ending_here = 0;\n",
" int64_t max_so_far = std::numeric_limits<int64_t>::min();\n",
" uint32_t v = seed;\n",
" bool started = false;\n",
" for (int i = 0; i < n; ++i) {\n",
" v = lcg_next(v);\n",
" int x = static_cast<int>(v % range) + min_val;\n",
" if (!started) {\n",
" max_ending_here = x;\n",
" max_so_far = x;\n",
" started = true;\n",
" } else {\n",
" max_ending_here = (max_ending_here > 0) ? max_ending_here + x : x;\n",
" if (max_ending_here > max_so_far) max_so_far = max_ending_here;\n",
" }\n",
" }\n",
" return max_so_far;\n",
"}\n",
"\n",
"int main() {\n",
" const int n = 10000;\n",
" const uint32_t initial_seed = 42;\n",
" const int min_val = -10;\n",
" const int max_val = 10;\n",
"\n",
" auto start = std::chrono::high_resolution_clock::now();\n",
"\n",
" uint32_t seed = initial_seed;\n",
" long long total = 0;\n",
" for (int t = 0; t < 20; ++t) {\n",
" seed = lcg_next(seed);\n",
" total += max_subarray_sum_with_seed(seed, n, min_val, max_val);\n",
" }\n",
"\n",
" auto end = std::chrono::high_resolution_clock::now();\n",
" std::chrono::duration<double> diff = end - start;\n",
"\n",
" std::cout << \"Total Maximum Subarray Sum (20 runs): \" << total << \"\\n\";\n",
" std::cout << std::fixed << std::setprecision(6);\n",
" std::cout << \"Execution Time: \" << diff.count() << \" seconds\" << std::endl;\n",
"\n",
" std::cout << \"Press Enter to exit...\";\n",
" std::cin.ignore(std::numeric_limits<std::streamsize>::max(), '\\n');\n",
" std::cin.get();\n",
"\n",
" return 0;\n",
"}"
]
}
],
"source": [
"optimize_gpt(python_hard)"
]
},
{
"cell_type": "code",
"execution_count": 58,
"id": "922f484e-4e16-4ca6-b80d-0736972e18f5",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\".\" non e riconosciuto come comando interno o esterno,\n",
" un programma eseguibile o un file batch.\n"
]
}
],
"source": [
"!g++ -O2 -std=c++17 optimized.cpp -o optimized\n",
"!./optimized"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "38009c18-7496-4d55-bb0a-bfcc7c6a430e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"#include <iostream>\n",
"#include <vector>\n",
"ono>lude <chr\n",
" <limits>\n",
">include <algorithm\n",
"stdint>e <c\n",
"ip>clude <ioman\n",
"onio.h>e <c\n",
"\n",
" LCG {\n",
"private:\n",
"64_t value;\n",
"64_t a = 1664525;\n",
"_t c = 1013904223;\n",
"_t m = 1ULL << 32;\n",
"\n",
"public:\n",
"uint64_t seed) : value(seed) {}\n",
"\n",
"64_t next() {\n",
" (a * value + c) % m;\n",
" return value;\n",
" }\n",
"};\n",
"\n",
"_t max_subarray_sum(int n, uint64_t seed, int min_val, int max_val) {\n",
"g(seed);lc\n",
"<int64_t> random_numbers(n);\n",
" (int i = 0; i < n; ++i) {\n",
"[i] = lcg.next() % (max_val - min_val + 1) + min_val;\n",
" }\n",
"\n",
"t max_sum = std::numeric_limits<int64_t>::min();\n",
"int64_t current_sum = 0;\n",
" = 0; i < n; ++i) {\n",
"_sum = std::max(current_sum + random_numbers[i], random_numbers[i]);\n",
" = std::max(max_sum, current_sum);\n",
"} \n",
"; return max_sum\n",
"}\n",
"\n",
"64_t total_max_subarray_sum(int n, uint64_t initial_seed, int min_val, int max_val) {\n",
" total_sum = 0;\n",
"CG lcg(initial_seed);\n",
" = 0; i < 20; ++i) {\n",
"uint64_t seed = lcg.next();\n",
"sum += max_subarray_sum(n, seed, min_val, max_val);\n",
" }\n",
"; return total_sum\n",
"}\n",
"\n",
" main() {\n",
"const int n = 10000;\n",
" uint64_t initial_seed = 42;\n",
" min_val = -10;\n",
" int max_val = 10;\n",
"\n",
"auto start_time = std::chrono::high_resolution_clock::now();\n",
"int64_t result = total_max_subarray_sum(n, initial_seed, min_val, max_val);\n",
" = std::chrono::high_resolution_clock::now();\n",
"\n",
" duration = std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time);\n",
"\n",
"< \"Total Maximum Subarray Sum (20 runs): \" << result << std::endl;\n",
" << \"Execution Time: \" << std::fixed << std::setprecision(6) << duration.count() / 1e6 << \" seconds\" << std::endl;\n",
"\n",
"d::cout << \"Press any key to continue...\";\n",
"etch();\n",
"\n",
" 0; return\n",
"}"
]
}
],
"source": [
"optimize_claude(python_hard)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "9012f543-ab06-4d7c-bf5f-250f4a6c43bd",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\".\" non e riconosciuto come comando interno o esterno,\n",
" un programma eseguibile o un file batch.\n"
]
}
],
"source": [
"!g++ -O2 -std=c++17 optimized.cpp -o optimized\n",
"!./optimized"
]
},
{
"cell_type": "code",
"execution_count": 59,
"id": "3a1e4027-3309-48d5-9387-a8b309a325bf",
"metadata": {},
"outputs": [],
"source": [
"def stream_gpt(python): \n",
" stream = openai.chat.completions.create(model=OPENAI_MODEL, messages=messages_for(python), stream=True)\n",
" reply = \"\"\n",
" for chunk in stream:\n",
" fragment = chunk.choices[0].delta.content or \"\"\n",
" reply += fragment\n",
" yield reply.replace('```cpp\\n','').replace('```','')"
]
},
{
"cell_type": "code",
"execution_count": 60,
"id": "bcfa7016-ce17-4a8d-aa43-9acdd884159e",
"metadata": {},
"outputs": [],
"source": [
"def stream_claude(python):\n",
" result = claude.messages.stream(\n",
" model=CLAUDE_MODEL,\n",
" max_tokens=2000,\n",
" system=system_message,\n",
" messages=[{\"role\": \"user\", \"content\": user_prompt_for(python)}],\n",
" )\n",
" reply = \"\"\n",
" with result as stream:\n",
" for text in stream.text_stream:\n",
" reply += text\n",
" yield reply.replace('```cpp\\n','').replace('```','')"
]
},
{
"cell_type": "code",
"execution_count": 61,
"id": "56790d11-d24d-40ab-8f1a-5283726b5764",
"metadata": {},
"outputs": [],
"source": [
"def optimize(python, model):\n",
" if model==\"GPT\":\n",
" result = stream_gpt(python)\n",
" elif model==\"Claude\":\n",
" result = stream_claude(python)\n",
" else:\n",
" raise ValueError(\"Unknown model\")\n",
" for stream_so_far in result:\n",
" yield stream_so_far "
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "6d7c83c0-e239-44df-b977-3fb6a2398b6a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"* Running on local URL: http://127.0.0.1:7860\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
"<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 63,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"with gr.Blocks() as ui:\n",
" with gr.Row():\n",
" python = gr.Textbox(label=\"Python code: \", lines=10, value=python_hard)\n",
" cpp = gr.Textbox(label=\"C++ code: \", lines=10)\n",
" with gr.Row():\n",
" model = gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\", value=\"GPT\")\n",
" convert = gr.Button(\"Convert code\")\n",
"\n",
" convert.click(optimize, inputs=[python, model], outputs=[cpp])\n",
"ui.launch(inbrowser=True)"
]
},
{
"cell_type": "code",
"execution_count": 65,
"id": "d9156094-3e06-4c3a-9ede-3e6f9bf94de7",
"metadata": {},
"outputs": [],
"source": [
"def execute_python(code):\n",
" try:\n",
" output = io.StringIO()\n",
" sys.stdout = output\n",
" exec(code)\n",
" finally:\n",
" sys.stdout = sys.__stdout__\n",
" return output.getvalue()"
]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "4da83af8-c8e1-474d-b954-d07957f55c37",
"metadata": {},
"outputs": [],
"source": [
"def execute_cpp(code):\n",
" write_output(code)\n",
" try:\n",
" compile_cmd = [\"g++\", \"-O2\", \"-std=c++17\", \"optimized.cpp\", \"-o\", \"optimized\"]\n",
" compile_result = subprocess.run(compile_cmd, check=True, text=True, capture_output=True)\n",
" run_cmd = [\"./optimized\"]\n",
" run_result = subprocess.run(run_cmd, check=True, text=True, capture_output=True)\n",
" return run_result.stdout\n",
" except subprocess.CalledProcessError as e:\n",
" return f\"An error occurred:\\n{e.stderr}\""
]
},
{
"cell_type": "code",
"execution_count": 66,
"id": "55f3f532-aa10-4c91-9d22-e7463f9a646b",
"metadata": {},
"outputs": [],
"source": [
"# !g++ -O2 -std=c++17 optimized.cpp -o optimized\n",
"# !./optimized"
]
},
{
"cell_type": "code",
"execution_count": 67,
"id": "56f3ba77-a339-48f2-bd81-44cdd90c9458",
"metadata": {},
"outputs": [],
"source": [
"css = \"\"\"\n",
".python {background-color: #306998;}\n",
".cpp {background-color: #050;}\n",
"\"\"\""
]
},
{
"cell_type": "code",
"execution_count": 68,
"id": "38c17a7a-45c5-4656-99ef-556f7d1a909b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"* Running on local URL: http://127.0.0.1:7861\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
"<div><iframe src=\"http://127.0.0.1:7861/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"with gr.Blocks(css=css) as ui:\n",
" gr.Markdown(\"## Convert code from Python to C++\")\n",
" with gr.Row():\n",
" python = gr.Textbox(label=\"Python code:\", value=python_hard, lines=10)\n",
" cpp = gr.Textbox(label=\"C++ code:\", lines=10)\n",
" with gr.Row():\n",
" model = gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\", value=\"GPT\")\n",
" with gr.Row():\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": "3.11.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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week4/community-contributions/max.solo23/optimized.cpp Normal file
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#include <iostream>
#include <vector>
#include <limits>
#include <chrono>
#include <iomanip>
#include <cstdint>
class LCG {
private:
uint64_t value;
const uint64_t a = 1664525;
const uint64_t c = 1013904223;
const uint64_t m = 1ULL << 32;
public:
LCG(uint64_t seed) : value(seed) {}
uint64_t next() {
value = (a * value + c) % m;
return value;
}
};
int64_t max_subarray_sum(int n, uint64_t seed, int min_val, int max_val) {
LCG lcg(seed);
std::vector<int64_t> random_numbers(n);
for (int i = 0; i < n; ++i) {
random_numbers[i] = lcg.next() % (max_val - min_val + 1) + min_val;
}
int64_t max_sum = std::numeric_limits<int64_t>::min();
int64_t current_sum = 0;
int64_t min_sum = 0;
for (int i = 0; i < n; ++i) {
current_sum += random_numbers[i];
max_sum = std::max(max_sum, current_sum - min_sum);
min_sum = std::min(min_sum, current_sum);
}
return max_sum;
}
int64_t total_max_subarray_sum(int n, uint64_t initial_seed, int min_val, int max_val) {
int64_t total_sum = 0;
LCG lcg(initial_seed);
for (int i = 0; i < 20; ++i) {
uint64_t seed = lcg.next();
total_sum += max_subarray_sum(n, seed, min_val, max_val);
}
return total_sum;
}
int main() {
const int n = 10000;
const uint64_t initial_seed = 42;
const int min_val = -10;
const int max_val = 10;
auto start_time = std::chrono::high_resolution_clock::now();
int64_t result = total_max_subarray_sum(n, initial_seed, min_val, max_val);
auto end_time = std::chrono::high_resolution_clock::now();
auto duration = std::chrono::duration_cast<std::chrono::microseconds>(end_time - start_time);
std::cout << "Total Maximum Subarray Sum (20 runs): " << result << std::endl;
std::cout << "Execution Time: " << std::fixed << std::setprecision(6) << duration.count() / 1e6 << " seconds" << std::endl;
std::cout << "Press Enter to exit...";
std::cin.get();
return 0;
}

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