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We need to polish documentations of our operators. An example is
Paddle/paddle/operators/auc_op.cc
Lines 77 to 91 in 1363ddb
| AddComment( | |
| R"DOC(Computes the AUC according forward output and label. | |
| Best to use for binary classification evaluations. | |
| If input label contains values other than 0 and 1, it will be cast | |
| to bool. | |
| You can find the definations here: | |
| https://en.wikipedia.org/wiki/Receiver_operating_characteristic#Area_under_the_curve | |
| Possible curves are: | |
| - ROC: Receiver operating characteristic | |
| - PR: Precision Recall | |
| )DOC"); | |
| } |
We can take ONNX's documentation as a reference. This also helps us preparing joining ONNX.
The following operators' documentation needs polishment.
If you are going to file a PR to polish one or more of them, please check them so to avoid conflict of interests with others.
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- accuracy_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- activation_op.cc
- adadelta_op.cc
- adagrad_op.cc
- adam_op.cc
- adamax_op.cc
- auc_op.cc
- batch_norm_op.cc
- cast_op.cc
- clip_op.cc
- concat_op.cc
- cond_op.cc
- conv2d_op.cc
- conv2dtranspose_op.cc
- conv_shift_op.cc
- cos_sim_op.cc
- crop_op.cc
- cross_entropy_op.cc
- decayed_adagrad_op.cc
- dropout_op.cc
- dynamic_recurrent_op.cc
- elementwise_add_op.cc
- elementwise_div_op.cc
- elementwise_mul_op.cc
- elementwise_op.h
- elementwise_sub_op.cc
- feed_op.cc
- fetch_op.cc
- fill_constant_batch_size_like_op.cc
- fill_constant_op.cc
- fill_zeros_like_op.cc
- gather_op.cc
- gaussian_random_op.cc
- gru_unit_op.cc
- huber_loss_op.cc
- increment_op.cc
- l1_norm_op.cc
- load_op.cc
- lookup_table_op.cc
- lrn_op.cc
- lstm_op.cc
- lstm_unit_op.cc
- margin_rank_loss_op.cc
- matmul_op.cc
- mean_op.cc
- minus_op.cc
- modified_huber_loss_op.cc
- momentum_op.cc
- mul_op.cc
- multiplex_op.cc
- nccl_op.cc
- nccl_op.cc
- nccl_op.cc
- nccl_op.cc
- pad_op.cc
- pool_op.cc
- pool_op.cc
- pool_with_index_op.cc
- pool_with_index_op.cc
- prelu_op.cc
- proximal_adagrad_op.cc
- proximal_gd_op.cc
- rank_loss_op.cc
- recurrent_op.cc
- reduce_op.cc
- reduce_op.cc
- reduce_op.cc
- reduce_op.cc
- reduce_op.cc
- reshape_op.cc
- rmsprop_op.cc
- save_op.cc
- scale_op.cc
- scatter_op.cc
- seq_expand_op.cc
- sequence_concat_op.cc
- sequence_conv_op.cc
- sequence_pool_op.cc
- sequence_softmax_op.cc
- sgd_op.cc
- sigmoid_cross_entropy_with_logits_op.cc
- sign_op.cc
- smooth_l1_loss_op.cc
- softmax_op.cc
- softmax_with_cross_entropy_op.cc
- split_op.cc
- squared_l2_distance_op.cc
- squared_l2_norm_op.cc
- sum_op.cc
- top_k_op.cc
- transpose_op.cc
- uniform_random_op.cc
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