def dump_xmodel(self):
if self.quant_mode < 2:
return
compiler = CompilerFactory.get_compiler("xmodel")
xmodel_dir = os.path.join(self._output_dir, "xmodel")
generic_utils.mkdir_if_not_exist(xmodel_dir)
compile_args = []
if self.lstm:
for direction, graph in self._cell_graphs:
compile_args.append((graph, {'direction': direction}))
else:
compile_args.append((graph, {}))
for graph, attr_kwargs in compile_args:
for node in graph.nodes:
# TODO(yuwang): Set out tensor shape in parser.
# Maybe specify shape for all tensors?
# Input shape must be specified for xgraph shape inference.
if node.op.type == OpTypes.INPUT:
node.out_tensors[0].shape = node.op.attr['shape']
try:
compiler.do_compile(
graph,
os.path.join(xmodel_dir, graph.name),
quant_config_info=self.quant_config,
graph_attr_kwargs=attr_kwargs)
except Exception as e:
print('[ERROR] Failed to dump xmodel: {}'.format(e))
return
print('[INFO] Successfully convert nndct graph to xmodel!')
def write_proto(path, message, as_text=False):
dir_name = os.path.dirname(path)
generic_utils.mkdir_if_not_exist(dir_name)
if dir_name:
os.makedirs(dir_name, exist_ok=True)
if as_text:
with open(path, "w") as f:
f.write(text_format.MessageToString(message))
else:
with open(path, "wb") as f:
f.write(message.SerializeToString())
def maybe_export_graph(path, graph):
if not os.environ.get('EXPORT_NNDCT_TF_PARSER_INTERNAL', ''):
return
dir_name = os.path.dirname(path)
generic_utils.mkdir_if_not_exist(dir_name)
if isinstance(graph, tf.Graph):
graph = graph.as_graph_def()
write_binary_proto(path, graph)
elif isinstance(graph, graph_pb2.GraphDef):
write_binary_proto(path, graph)
elif isinstance(graph, ops.Graph):
viz.export_to_netron(path, graph)
else:
pass
def write(self, filepath):
self._printer.print('# Generated by NNDCT. Do not edit!')
self._printer.newline()
self.write_imports()
self.write_class_def()
generic_utils.mkdir_if_not_exist(os.path.dirname(filepath))
with open(filepath, 'w') as f:
f.write(self._printer.get())
f.flush()
os.fsync(f.fileno())
layer_to_node = {}
for node in self._graph.nodes:
entity = self._translator.get_entity(node.name)
if entity.need_init:
layer_to_node[entity.name] = node
return layer_to_node
