| ## @package layer_model_instantiator |
| # Module caffe2.python.layer_model_instantiator |
| from __future__ import absolute_import |
| from __future__ import division |
| from __future__ import print_function |
| from __future__ import unicode_literals |
| |
| from caffe2.python import core |
| from caffe2.python.layers.layers import InstantiationContext |
| from caffe2.python.layers.tags import Tags |
| |
| |
| def generate_predict_net(model): |
| predict_net = core.Net('predict_net') |
| |
| for layer in model.layers: |
| if Tags.TRAIN_ONLY not in layer.tags: |
| layer.add_operators( |
| predict_net, context=InstantiationContext.PREDICTION) |
| return predict_net |
| |
| |
| def generate_eval_net(model): |
| eval_net = core.Net('eval_net') |
| |
| for layer in model.layers: |
| layer.add_operators( |
| eval_net, context=InstantiationContext.EVAL) |
| |
| input_schema = model.input_feature_schema + model.trainer_extra_schema |
| output_schema = model.output_schema + model.metrics_schema |
| eval_net.set_input_record(input_schema) |
| eval_net.set_output_record(output_schema) |
| return eval_net |
| |
| |
| def _generate_training_net_only(model): |
| train_net = core.Net('train_net') |
| train_init_net = model.create_init_net('train_init_net') |
| |
| for layer in model.layers: |
| layer.add_operators(train_net, train_init_net) |
| |
| input_schema = model.input_feature_schema + model.trainer_extra_schema |
| output_schema = model.output_schema + model.metrics_schema |
| train_net.set_input_record(input_schema) |
| train_net.set_output_record(output_schema) |
| return train_init_net, train_net |
| |
| |
| def generate_training_nets_forward_only(model): |
| train_init_net, train_net = _generate_training_net_only(model) |
| return train_init_net, train_net |
| |
| |
| def generate_training_nets(model): |
| train_init_net, train_net = _generate_training_net_only(model) |
| |
| loss = model.loss |
| grad_map = train_net.AddGradientOperators(loss.field_blobs()) |
| model.apply_optimizers(train_net, train_init_net, grad_map) |
| return train_init_net, train_net |