openvino/model-optimizer/extensions/load/caffe/loader.py

55 lines
2.4 KiB
Python

# Copyright (C) 2018-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
from extensions.load.loader import Loader
from mo.front.caffe import custom_layers_mapping, loader
from mo.front.caffe.extractor import caffe_type_extractors, caffe_extractor
from mo.front.common.register_custom_ops import update_extractors_with_extensions, check_for_duplicates
from mo.front.extractor import extract_node_attrs
from mo.graph.graph import Graph
from mo.utils.error import Error
from mo.utils.telemetry_utils import send_op_names_info, send_shapes_info
from mo.utils.utils import refer_to_faq_msg
class CaffeLoader(Loader):
enabled = True
def load(self, graph: Graph):
argv = graph.graph['cmd_params']
caffe_pb2 = loader.import_caffe_pb2(argv.caffe_parser_path)
proto, model = loader.load_caffe_proto_model(caffe_pb2, argv.input_proto, argv.input_model)
update_extractors_with_extensions(
caffe_type_extractors,
argv.disable_omitting_optional if hasattr(argv, 'disable_omitting_optional') else False,
argv.disable_flattening_optional_params if hasattr(argv, 'disable_flattening_optional_params') else False
)
try:
original_shapes = loader.caffe_pb_to_nx(graph, proto, model)
except ValueError as e:
raise Error('Invalid prototxt file: value error {}. ' +
refer_to_faq_msg(11), str(e)) from e
graph.check_empty_graph('load_caffe_proto_model')
graph.__setattr__('proto_path', argv.input_proto)
graph.__setattr__('caffemodel_path', argv.input_model)
graph.__setattr__('name', getattr(proto, 'name', None) or argv.model_name)
graph.graph['layout'] = 'NCHW'
graph.graph['fw'] = 'caffe'
graph.graph['original_shapes'] = original_shapes
graph.graph['caffe_pb2'] = caffe_pb2
custom_layers_map = custom_layers_mapping.load_layers_xml(argv.k)
custom_layers_mapping.update_extractors(
caffe_type_extractors,
custom_layers_map,
argv.disable_omitting_optional if hasattr(argv, 'disable_omitting_optional') else False,
argv.enable_flattening_nested_params if hasattr(argv, 'enable_flattening_nested_params') else False
)
extract_node_attrs(graph, lambda node: caffe_extractor(node, check_for_duplicates(caffe_type_extractors)))
send_op_names_info('caffe', graph)
send_shapes_info('caffe', graph)