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Chainer v2 α
Seiya Tokui @ Preferred Networks
Chainer Meetup #04 | Feb. 23, 2017
(MinPy)
Era of dynamic graph frameworks
Chainer as a pioneer in this field
• 2015/06: v1.0
• 2015/09: v1.3 (CuPy)
• 2015/11: v1.5 (Link/Chain, CuPy in Cython)
• 2016/06: [MinPy]
• 2016/07: v1.11 (Trainer)
• 2017/01: [PyTorch, TensorFlow Fold]
• 2017/02: v2.0a
Libraries on top of Chainer
• ChainerRL (beta): https://github.com/pfnet/chainerrl
Reinforcement learning
• ChainerMN (to appear)
Multi-node distributed learning
Release plan
• Feb. 23: v2.0.0a1
• Mar. xx: v2.0.0b1
• Apr. xx: v2.0.0
How to use Chainer v2.0.0a1
pip install chainer –-pre
pip install cupy
Documentation: http://docs.chainer.org/en/v2.0.0a1/
CuPy Documentation: http://cupy.docs.chainer.org/
Features of v2.0.0a1
• CuPy is separated into an independent package
• Unified configuration / training mode
• Removed deprecated/obsolete APIs
• Interface improvements
CuPy is separated
• CuPy is now a separate project!
• https://github.com/cupy/cupy
• At the moment, the development of CuPy is still taking place
at Chainer v1
• Changes are merged to cupy/cupy after each minor release
• In the future, any changes that break compatibilities will be made in
the cupy repository
Unified configuration
Thread-local-like object to configure Chainer
• chainer.config: thread-local configuration
• chainer.global_config: process-wide configuration
• Users usually only have to touch chainer.config.
Built-in configuration entries
• debug
• enable_backprop
• train
• type_check
• (use_cudnn, deterministic: to be added)
Training mode
• All functions/classes that have training/test mode
distinctions now use chainer.config.train flag
• Evaluator automatically switches the flag
→ No need to pass train/test flags manually anymore!
Switching configuration
with chainer.using_config(‘train’, False):
... # code runs in test mode
with chainer.using_config(‘debug’, True):
... # code runs in debug mode
Removed/modified APIs
• Array-creation functions in chainer.cuda module
• FunctionSet
• wscale option of links and scale option of init_weight
(specify weight initializers instead)
• force_tuple option of F.split_axis is now set to True by
default
• Some minor updates
Major features planned for beta and final releases
• Optimizer with UpdateRule
Can specify hyperparameters for each parameter (e.g. learning rate,
hook functions)
• Uninitialized variable
Used to implement the parameter-shape placeholder
• Remove volatile flag
Use chainer.config.enable_backprop flag instead
• PyCharm-friendly Link/Chain APIs
Chainer v2 alpha

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Chainer v2 alpha

  • 1. Chainer v2 α Seiya Tokui @ Preferred Networks Chainer Meetup #04 | Feb. 23, 2017
  • 2. (MinPy) Era of dynamic graph frameworks
  • 3. Chainer as a pioneer in this field • 2015/06: v1.0 • 2015/09: v1.3 (CuPy) • 2015/11: v1.5 (Link/Chain, CuPy in Cython) • 2016/06: [MinPy] • 2016/07: v1.11 (Trainer) • 2017/01: [PyTorch, TensorFlow Fold] • 2017/02: v2.0a
  • 4. Libraries on top of Chainer • ChainerRL (beta): https://github.com/pfnet/chainerrl Reinforcement learning • ChainerMN (to appear) Multi-node distributed learning
  • 5. Release plan • Feb. 23: v2.0.0a1 • Mar. xx: v2.0.0b1 • Apr. xx: v2.0.0
  • 6. How to use Chainer v2.0.0a1 pip install chainer –-pre pip install cupy Documentation: http://docs.chainer.org/en/v2.0.0a1/ CuPy Documentation: http://cupy.docs.chainer.org/
  • 7. Features of v2.0.0a1 • CuPy is separated into an independent package • Unified configuration / training mode • Removed deprecated/obsolete APIs • Interface improvements
  • 8. CuPy is separated • CuPy is now a separate project! • https://github.com/cupy/cupy • At the moment, the development of CuPy is still taking place at Chainer v1 • Changes are merged to cupy/cupy after each minor release • In the future, any changes that break compatibilities will be made in the cupy repository
  • 9. Unified configuration Thread-local-like object to configure Chainer • chainer.config: thread-local configuration • chainer.global_config: process-wide configuration • Users usually only have to touch chainer.config.
  • 10. Built-in configuration entries • debug • enable_backprop • train • type_check • (use_cudnn, deterministic: to be added)
  • 11. Training mode • All functions/classes that have training/test mode distinctions now use chainer.config.train flag • Evaluator automatically switches the flag → No need to pass train/test flags manually anymore!
  • 12. Switching configuration with chainer.using_config(‘train’, False): ... # code runs in test mode with chainer.using_config(‘debug’, True): ... # code runs in debug mode
  • 13. Removed/modified APIs • Array-creation functions in chainer.cuda module • FunctionSet • wscale option of links and scale option of init_weight (specify weight initializers instead) • force_tuple option of F.split_axis is now set to True by default • Some minor updates
  • 14. Major features planned for beta and final releases • Optimizer with UpdateRule Can specify hyperparameters for each parameter (e.g. learning rate, hook functions) • Uninitialized variable Used to implement the parameter-shape placeholder • Remove volatile flag Use chainer.config.enable_backprop flag instead • PyCharm-friendly Link/Chain APIs