def save_model_bundle(self):
"""Save a model bundle.
This is a zip file with the model weights in .pth format and a serialized
copy of the LearningConfig, which allows for making predictions in the future.
"""
from rastervision.pytorch_learner.learner_pipeline_config import (
LearnerPipelineConfig)
log.info('Creating bundle.')
model_bundle_dir = join(self.tmp_dir, 'model-bundle')
make_dir(model_bundle_dir)
shutil.copyfile(self.last_model_path,
join(model_bundle_dir, 'model.pth'))
# copy modules into bundle
if isdir(self.modules_dir):
log.info('Copying modules into bundle.')
bundle_modules_dir = join(model_bundle_dir, MODULES_DIRNAME)
if isdir(bundle_modules_dir):
shutil.rmtree(bundle_modules_dir)
shutil.copytree(self.modules_dir, bundle_modules_dir)
pipeline_cfg = LearnerPipelineConfig(learner=self.cfg)
save_pipeline_config(pipeline_cfg,
join(model_bundle_dir, 'pipeline-config.json'))
zipdir(model_bundle_dir, self.model_bundle_path)
def __exit__(self, type, value, traceback):
"""
This writes a zip file for a group of scenes at {output_uri}/{uuid}.zip.
This method is called once per instance of the chip command.
A number of instances of the chip command can run simultaneously to
process chips in parallel. The uuid in the zip path above is what allows
separate instances to avoid overwriting each others' output.
"""
output_path = join(self.tmp_dir_obj.name, 'output.zip')
zipdir(self.sample_dir, output_path)
upload_or_copy(output_path, self.output_uri)
self.tmp_dir_obj.cleanup()
def save_model_bundle(self):
"""Save a model bundle.
This is a zip file with the model weights in .pth format and a serialized
copy of the LearningConfig, which allows for making predictions in the future.
"""
from rastervision.pytorch_learner.learner_pipeline_config import (
LearnerPipelineConfig)
model_bundle_dir = join(self.tmp_dir, 'model-bundle')
make_dir(model_bundle_dir)
shutil.copyfile(self.last_model_path,
join(model_bundle_dir, 'model.pth'))
pipeline_cfg = LearnerPipelineConfig(learner=self.cfg)
save_pipeline_config(pipeline_cfg,
join(model_bundle_dir, 'pipeline-config.json'))
zipdir(model_bundle_dir, self.model_bundle_path)
