- 01 7月, 2018 1 次提交
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由 Xin Pan 提交于
This is part of big move of v2 codes to legacy sub dir.
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- 12 2月, 2018 1 次提交
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由 qingqing01 提交于
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- 17 1月, 2018 1 次提交
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由 ying 提交于
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- 16 6月, 2017 1 次提交
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由 xuwei06 提交于
No longer need to use SubsequenceInput. The framework will detect.
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- 09 12月, 2016 1 次提交
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由 Yi Wang 提交于
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- 12 11月, 2016 1 次提交
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由 qijun 提交于
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- 24 10月, 2016 1 次提交
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由 luotao1 提交于
* add maxout layer, including interface and unittest * follow maxout comments * auto setting channels * fix unittest bug in test_RecurrentGradientMachine
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- 08 10月, 2016 1 次提交
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由 Zrachel 提交于
* add interface and unittest of RecurrentGradientMachine for the function of multiple Subsequence inlinks with unequal token length
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- 20 9月, 2016 1 次提交
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由 Yu Yang 提交于
* 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.
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- 14 9月, 2016 1 次提交
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由 xuwei06 提交于
Change-Id: I8e0a8ea6fc2760652d9c76440a539c90860062d3
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- 29 8月, 2016 1 次提交
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由 zhangjinchao01 提交于
ISSUE=4586495 git-svn-id: https://svn.baidu.com/idl/trunk/paddle@1408 1ad973e4-5ce8-4261-8a94-b56d1f490c56
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