5 Commits (da7c0f1326677ec7c22b6cdbd6595e2f4a1d59a2)

Author	SHA1	Message	Date
qijun	319742c641	format python code in demo, doc, doc_cn and paddle directories	9 years ago
luotao1	3dd8c9bea4	add maxout layer, including interface and unittest (#229) ... * add maxout layer, including interface and unittest * follow maxout comments * auto setting channels * fix unittest bug in test_RecurrentGradientMachine	9 years ago
Zrachel	1c2ebe467b	add interface and test of RecurrentGradientMachine (#156) ... * add interface and unittest of RecurrentGradientMachine for the function of multiple Subsequence inlinks with unequal token length	9 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
xuwei06	9a9de9240d	Correctly handle memory in RecurrentGradientMachine for hirarchical RNN ... Change-Id: I8e0a8ea6fc2760652d9c76440a539c90860062d3	9 years ago