def run(experiment_id, restore_path, output_template_dir=None):
"""Convert from trained model."""
# Export model
run_export(experiment_id,
restore_path,
image_size=(None, None),
images=[],
config_file=None)
export_dir = get_export_directory(experiment_id, restore_path)
# Set arguments
input_pb_path = os.path.join(export_dir, "minimal_graph_with_shape.pb")
dest_dir_path = export_dir
project_name = "project"
activate_hard_quantization = True
threshold_skipping = True
cache_dma = True
# Generate project
run_generate_project(input_path=input_pb_path,
dest_dir_path=dest_dir_path,
project_name=project_name,
activate_hard_quantization=activate_hard_quantization,
threshold_skipping=threshold_skipping,
cache_dma=cache_dma)
# Create output dir from template
output_root_dir = os.path.join(export_dir, "output")
output_directories = create_output_directory(output_root_dir,
output_template_dir)
# Save meta.yaml to model output dir
shutil.copy(os.path.join(export_dir, "meta.yaml"),
output_directories.get("model_dir"))
# Save minimal_graph_with_shape.pb to model output dir for TensforflowGraphRunner
shutil.copy(os.path.join(export_dir, "minimal_graph_with_shape.pb"),
output_directories.get("model_dir"))
# Make
project_dir_name = "{}.prj".format(project_name)
project_dir = os.path.join(dest_dir_path, project_dir_name)
make_all(project_dir, output_directories.get("library_dir"))
def run(experiment_id,
restore_path,
output_template_dir=None,
image_size=(None, None),
project_name=None):
"""Convert from trained model.
Returns:
output_root_dir (str): Path of exported dir.
(i.e. `(path to saved)/saved/det_20190326181434/export/save.ckpt-161/128x128/output/`)
"""
# Export model
export_dir = run_export(experiment_id,
restore_path=restore_path,
image_size=image_size)
# Set arguments
input_pb_path = os.path.join(export_dir, "minimal_graph_with_shape.pb")
if not project_name:
project_name = "project"
activate_hard_quantization = True
threshold_skipping = True
cache_dma = True
# Generate project
run_generate_project(input_path=input_pb_path,
dest_dir_path=export_dir,
project_name=project_name,
activate_hard_quantization=activate_hard_quantization,
threshold_skipping=threshold_skipping,
cache_dma=cache_dma)
# Create output dir from template
output_root_dir = os.path.join(export_dir, "output")
output_directories = create_output_directory(output_root_dir,
output_template_dir)
# Save meta.yaml to model output dir
shutil.copy(os.path.join(export_dir, "meta.yaml"),
output_directories.get("model_dir"))
# Save minimal_graph_with_shape.pb to model output dir for TensforflowGraphRunner
shutil.copy(os.path.join(export_dir, "minimal_graph_with_shape.pb"),
output_directories.get("model_dir"))
# Make
project_dir_name = "{}.prj".format(project_name)
project_dir = os.path.join(export_dir, project_dir_name)
make_all(project_dir, output_directories.get("library_dir"))
return output_root_dir