- 24 10月, 2017 1 次提交
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由 chengduoZH 提交于
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- 18 10月, 2017 1 次提交
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由 chengduoZH 提交于
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- 14 10月, 2017 2 次提交
- 13 10月, 2017 4 次提交
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由 Abhinav Arora 提交于
* Adding Hard Sigmoid Activation * Adding a comment for slope to be only positive * Fixing grammatical mistake in comment
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由 Yan Chunwei 提交于
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由 Abhinav Arora 提交于
* add adam op moment1_out = beta1 * moment1 + (1 − beta1) * grad moment2_out = beta2 * moment2 + (1 − beta2) * grad * grad moment1_hat = moment1_out / (1 - beta1^t) moment2_hat = moment2_out / (1 - beta2^t) param_out = param - learning_rate * moment1_hat / (sqrt(moment2_hat) + epsilon) * fix moment 2 * Adding the Adam optimization operator * Adding more tests for Adam op
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由 fengjiayi 提交于
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- 12 10月, 2017 14 次提交
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由 chengduoZH 提交于
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由 guosheng 提交于
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由 chengduoZH 提交于
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由 guosheng 提交于
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由 chengduoZH 提交于
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由 kexinzhao 提交于
* Implementing the DecayedAdagrad optimizer step operator * implementing DecayedAdagrad operator * remove file * small fix
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由 武毅 提交于
* add cudnn_conv_op * WIP * update * update * fix grad check * use platform::memory * add support group for cudnn * update * follow comments * fix onlycpu build * update cuda define * follow comments * follow comments * merge with updates * fix compile error * follow comments * follow comments
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由 chengduoZH 提交于
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由 Yu Yang 提交于
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由 chengduoZH 提交于
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由 chengduoZH 提交于
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由 fengjiayi 提交于
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由 Abhinav Arora 提交于
* Adding thresholded_relu op * Adding test for thresholded relu op
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由 fengjiayi 提交于
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- 11 10月, 2017 18 次提交
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由 guosheng 提交于
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由 ranqiu 提交于
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由 xzl 提交于
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由 qiaolongfei 提交于
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由 kexinzhao 提交于
* implementing softplus * small fix * small fix * small fix * small fix
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由 fengjiayi 提交于
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由 qiaolongfei 提交于
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由 kavyasrinet 提交于
* Implemented the hardShrink activation * Fixing the unit test
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由 fengjiayi 提交于
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由 Siddharth Goyal 提交于
* Add numerically-stable logsigmoid activation * Add softshrink operator * Adjust relative tolerance for grad-check * Address review comments
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由 fengjiayi 提交于
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由 fengjiayi 提交于
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由 fengjiayi 提交于
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由 Yu Yang 提交于
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由 Yu Yang 提交于
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由 fengjiayi 提交于
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由 fengjiayi 提交于
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由 Markus Kliegl 提交于
* conv_shift_op: initial implementation using Eigen Limitations: - both gradient outputs must be specified and are always computed - explicit for loops => could be optimized in various ways (e.g., different memory layout) * conv shift - gradient fixes fix case when not all output gradients desired * conv shift: minor cleanup * conv shift - more minor cleanup * conv shift: clean up & initial GPU implementation * fix rebase issue
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