- 27 11月, 2017 2 次提交
- 24 11月, 2017 2 次提交
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由 QI JUN 提交于
* is_training to is_test in dropout op * handle dropout and batch_norm operator when prune pdesc in testing mode * handle dropout and batch_norm operator when prune pdesc in testing mode * add get_inference_program method * fix dropout op * fix ci * test data after each batch training * refine code * refine test_book3 * fix ci * follow comments
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由 fengjiayi 提交于
* Change all `data_type` in Python to `dtype` * Change `date_type` in C++ to `dtype` * Refine
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- 20 11月, 2017 1 次提交
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由 fengjiayi 提交于
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- 17 11月, 2017 1 次提交
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由 Qiao Longfei 提交于
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- 15 11月, 2017 2 次提交
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由 dzhwinter 提交于
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由 Helin Wang 提交于
- Removed all main_program and startup_program in the demo. - Using paddle.default_main_program() hides the implementation detail (e.g., using g_main_program) from the user, we can change the implementation in the future much easier.
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- 14 11月, 2017 2 次提交
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由 Qiao Longfei 提交于
* init commit * change some dir name
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由 Helin Wang 提交于
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- 05 11月, 2017 1 次提交
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由 Yu Yang 提交于
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- 04 11月, 2017 1 次提交
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由 Qiao Longfei 提交于
* add acc layer * memory log level change from 3 to 10 * use gaussian random to init conv parameters * use initializer * fix import * batch_norm use helper to create persistable var * refine code * train only 2 batches for test * use g_program and g_init_program * use XavierInitializer to init fc parameter
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- 02 11月, 2017 1 次提交
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由 Qiao Longfei 提交于
* optimizer use init_program * create persistable variable * add create_persistable_var to block * optimizer use create_persistable_var * fix prefix * move create_global_persistable_var from Block to LayerHelper * Polish Optimizer initialization code. * Using the LayerHelper to create initialize operator and variables * add_accumulator should use an independent data type * default use param data type for accumulator
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- 31 10月, 2017 1 次提交
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由 Qiao Longfei 提交于
* add resnet * optimize code
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- 30 10月, 2017 1 次提交
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由 Qiao Longfei 提交于
* add batch_norm_layer * add img_conv_group layer and test * add check to Tensor.type() * forward can run * with backward * change label data time from int32 to int64 * refine code * follow comment
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