Paddle

Commit Graph

Author	SHA1	Message	Date
Yu Yang	2f82d72ede	Fix bug in yield dictionary in DataProvider. (#197 ) * Fix bug in yield dictionary in DataProvider. * Also make virtualenv work in Paddle.	8 years ago
Yu Yang	90b9cba7fe	Add min_pool_size, Add default value of should_shuffle (#70 ) * min_pool_size would be infinite by default. * add unittest for min_pool_size * Fix bug in can_over_batch_size * add unittest for can_over_batch_size * Add DEFINE_PROVIDER_EX * Add default value of should_shuffle * When training, the default value of should_shuffle is True. * When testing, the default value of should_shuffle is False. * User a set a provider should_shuffle or not by pass it to `@provider` * should_shuffle can handle a list of value, not just boolean * Add input order mapping by using name * Add unittest * Add check to check input format. * Default is close for speed reason. * User could stop train when check error, or continue train without this train sample. * use deque instead of vector in generators pool, make erase generator faster. * Add chinese/english documentation * Make should shuffle = false in unittest * Add python files to depends.	9 years ago

Author

SHA1

Message

Date

Yu Yang

2f82d72ede

Fix bug in yield dictionary in DataProvider. (#197 )

* Fix bug in yield dictionary in DataProvider.
* Also make virtualenv work in Paddle.

Yu Yang

90b9cba7fe

Add min_pool_size, Add default value of should_shuffle (#70 )

* min_pool_size would be infinite by default.
  * add unittest for min_pool_size
* Fix bug in can_over_batch_size
  * add unittest for can_over_batch_size
* Add DEFINE_PROVIDER_EX
* Add default value of should_shuffle
  * When training, the default value of should_shuffle is True.
  * When testing, the default value of should_shuffle is False.
  * User a set a provider should_shuffle or not by pass it to `@provider`
  * should_shuffle can handle a list of value, not just boolean
* Add input order mapping by using name
  * Add unittest
* Add check to check input format.
  * Default is close for speed reason.
  * User could stop train when check error, or continue train without
    this train sample.
* use deque instead of vector in generators pool, make erase
  generator faster.
* Add chinese/english documentation
* Make should shuffle = false in unittest
* Add python files to depends.

2 Commits (fc9ca53ae421ec2eac5648ec8de6a1e7a993bfd0)