blob: 4680e1d051db55ee8956e635fa4d923999aed82f [file] [log] [blame]
## @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