| // Copyright 2021 The Deeplab2 Authors. | |
| // | |
| // Licensed under the Apache License, Version 2.0 (the "License"); | |
| // you may not use this file except in compliance with the License. | |
| // You may obtain a copy of the License at | |
| // | |
| // http://www.apache.org/licenses/LICENSE-2.0 | |
| // | |
| // Unless required by applicable law or agreed to in writing, software | |
| // distributed under the License is distributed on an "AS IS" BASIS, | |
| // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| // See the License for the specific language governing permissions and | |
| // limitations under the License. | |
| syntax = "proto2"; | |
| package deeplab2; | |
| option java_multiple_files = true; | |
| // Configure the solver options. | |
| // Next ID: 17 | |
| message SolverOptions { | |
| optional bool use_sync_batchnorm = 1 [default = true]; | |
| optional float batchnorm_momentum = 14 [default = 0.99]; | |
| optional float batchnorm_epsilon = 15 [default = 0.001]; | |
| // Set the learning rate policy for training. Available policies: 'poly', | |
| // 'cosine'. | |
| optional string learning_policy = 2 [default = 'poly']; | |
| // Set the base learning rate for model training. | |
| optional float base_learning_rate = 3 [default = 1e-3]; | |
| // Set the power value used in the poly learning policy. | |
| optional float poly_learning_power = 4 [default = 0.9]; | |
| // End learning rate for polynomial learning rate schedule. | |
| optional float poly_end_learning_rate = 5 [default = 0.0]; | |
| // Set the number of steps for the warmup phase. We currently only | |
| // support linear warmup, i.e., if global_step < warmup_steps, the | |
| // learning rate will be `global_step / warmup_steps * base_learning_rate`. | |
| optional int32 warmup_steps = 6 [default = 0]; | |
| // Set the optimizer method. Supported types: 'adam', 'sgd'. | |
| optional string optimizer = 7 [default = 'adam']; | |
| // Set the value of the weight decay for training. | |
| optional float weight_decay = 8 [default = 0]; | |
| // Set whether to use gradient clipping or not. | |
| optional bool use_gradient_clipping = 9 [default = false]; | |
| // Set the norm used in gradient clipping. | |
| optional float clip_gradient_norm = 10 [default = 10.0]; | |
| // Set the number of steps for training. | |
| optional int32 training_number_of_steps = 11 [default = 60000]; | |
| // Set the backbone learning rate multiplier when different learning rates | |
| // are desired for the backbone and for the other layers. For example, | |
| // MaX-DeepLab uses this field to set a 0.1x learning rate for the pretrained | |
| // backbone parameters. | |
| optional float backbone_learning_rate_multiplier = 16 [default = 1.0]; | |
| } | |
| /********** Submessages used to config loss options **********/ | |
| // Configure the loss options. | |
| message LossOptions { | |
| message SingleLossOptions { | |
| // Set the name of the loss. | |
| optional string name = 1; | |
| // Set the global weight of the loss used to weight the contribution of this | |
| // loss with respect to all other losses. | |
| optional float weight = 2 [default = 1.0]; | |
| // Set the percentage of top-k pixels to be used for backpropagation. | |
| optional float top_k_percent = 3 [default = 1.0]; | |
| } | |
| // Set the loss options for the semantic segmentation output. | |
| optional SingleLossOptions semantic_loss = 1; | |
| // Set the loss options for the center head. | |
| optional SingleLossOptions center_loss = 2; | |
| // Set the loss options for the regression head. | |
| optional SingleLossOptions regression_loss = 3; | |
| // Set the loss options for the motion head. | |
| optional SingleLossOptions motion_loss = 4; | |
| // Set the loss options for the next regression head. | |
| optional SingleLossOptions next_regression_loss = 5; | |
| // Set the loss options for the PQ-style loss. | |
| optional SingleLossOptions pq_style_loss = 6; | |
| // Set the loss options for the mask id cross entropy loss. | |
| optional SingleLossOptions mask_id_cross_entropy_loss = 7; | |
| // Set the loss options for the instance discrimination loss. | |
| optional SingleLossOptions instance_discrimination_loss = 8; | |
| } | |
| // Configure the trainer options. | |
| message TrainerOptions { | |
| // Set the maximum number of checkpoints to keep. | |
| optional int32 num_checkpoints_to_keep = 1 [default = 5]; | |
| // Set the number of steps after which a checkpoint should be made. | |
| optional int32 save_checkpoints_steps = 2 [default = 1000]; | |
| // Set after how many steps the summary should be written. Must be a multiple | |
| // of steps_per_loop. | |
| optional int32 save_summaries_steps = 3 [default = 1000]; | |
| // Set how many steps one `inner` train loop should have. This relates to the | |
| // orbit framework: | |
| // https://github.com/tensorflow/models/blob/master/orbit/controller.py#L33 | |
| optional int32 steps_per_loop = 4 [default = 1000]; | |
| // Set the loss options. | |
| optional LossOptions loss_options = 5; | |
| // Set the solver options. | |
| optional SolverOptions solver_options = 6; | |
| } | |