v0.9.10

v0.0.10 - Improved Memory Management

Highlights

This release improves the buffer sizing system to provide more flexibility and better memory utilization on the GPU.

New Features

Dynamic Buffer Capacity System

• Buffers now track total pixel capacity instead of fixed width×height dimensions
• Reuse the same buffer for different aspect ratios within capacity

buffer = Image(4096, 4096)  # 16M pixel capacity

buffer.resize(8192, 2048)   # Landscape (16M pixels)
buffer.resize(2048, 8192)   # Portrait (16M pixels)
buffer.resize(4096, 4096)   # Square (16M pixels)

New resize() Method

• Atomic dimension updates - change width and height together safely
• Prevents validation order issues

img = Image(1920, 1080)
img.resize(3840, 540)  # Works smoothly

Changes

API Changes

• Image.get_max_capacity() now returns int (total pixels) instead of tuple[int, int]

# Before
max_w, max_h = img.get_max_capacity()  # (1920, 1080)

# After
max_pixels = img.get_max_capacity()     # 2,073,600

Internal Improvements

• Removed internal ensure_capacity() utility function
• All operations now use buffer.resize() directly
• Cleaner buffer reuse patterns across all modules

Documentation

• Updated buffer sizing examples
• Clarified capacity concepts in Image & Memory guide
• All examples updated to reflect new API

Migration Guide

If you used get_max_capacity():

# Before
max_w, max_h = img.get_max_capacity()
if width * height > max_w * max_h:
    raise ValueError("Too large")

# After
max_pixels = img.get_max_capacity()
if width * height > max_pixels:
    raise ValueError("Too large")

If you set dimensions individually:

# Before (could fail depending on order)
img.width = 3840
img.height = 540

# After (recommended)
img.resize(3840, 540)

# Individual setters still work for simple cases
img.width = 1920
img.height = 1080

Breaking Changes

• Image.get_max_capacity() return type changed from tuple[int, int] to int
  • Impact: Low - This method is rarely used directly in user code
  • Fix: Use total pixel capacity instead of individual dimensions (see migration guide)

Technical Details

• All C/CUDA kernels remain unchanged and 100% compatible
• Buffer indexing works identically
• Zero performance impact - same GPU operations, cleaner Python API