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Running on Zero
Running on Zero
| import numpy as np | |
| from numba import jit | |
| import time | |
| # Numba-optimized function without reshape | |
| def from_buffer_fast(buf): | |
| return np.frombuffer(buf, dtype=np.uint8) | |
| # Benchmarking function | |
| def benchmark(func, buf): | |
| start_time = time.time() | |
| func(buf) | |
| end_time = time.time() | |
| return end_time - start_time | |
| # Generate random buffer and dtype | |
| buf = np.random.randint(0, 255, size=10**6, dtype=np.uint8).tobytes() | |
| # Benchmark np.frombuffer | |
| original_time = benchmark(np.frombuffer, buf) | |
| print("np.frombuffer time:", original_time) | |
| # Benchmark Numba-optimized function without reshape | |
| numba_time = benchmark(from_buffer_fast, buf) | |
| print("Numba-optimized function time:", numba_time) | |