Lines Matching refs:name
34 def __init__(self, name, dtype, dims):
35 self.name = name
51 return "{}: (name: {}, iotype: {}, dtype: {}, dims: {}, used_count: {})".format(self.index,
52 self.name, self.iotype2str[self.iotype], self.dtype2str[self.dtype],
87 def add_operand(self, name, type):
88 node = self.name_node_dict[name]
89 if name not in self.name_operand_dict:
99 operand = Operand(name, dtype, dims)
100 self.name_operand_dict[name] = operand;
101 self.name_operand_dict[name].add_iotype(type)
102 return self.name_operand_dict[name].index
107 tf.import_graph_def(self.graph_def, name="")
121 # the BiasAdd name is possible be changed into the output name,
135 # the BiasAdd name is possible be changed into the output name,
151 self.converted_nodes.add(node.name)
153 scope_name = TFConverter.get_scope_name(node.name)
198 output_operand_index = self.add_operand(anode.name, Operand.IOTYPE_OUTPUT)
200 output_operand_index = self.add_operand(self.edges[bnode.name][0].name, Operand.IOTYPE_OUTPUT)
206 self.converted_nodes.add(node.name)
208 scope_name = TFConverter.get_scope_name(node.name)
246 output_operand_index = self.add_operand(anode.name, Operand.IOTYPE_OUTPUT)
249 output_operand_index = self.add_operand(self.edges[bnode.name][0].name, Operand.IOTYPE_OUTPUT)
251 output_operand_index = self.add_operand(self.edges[scope_name+'/concat_1'][0].name, Operand.IOTYPE_OUTPUT)
258 self.converted_nodes.add(node.name)
289 output_operand_index = self.add_operand(node.name, Operand.IOTYPE_OUTPUT)
298 self.converted_nodes.add(node.name)
300 output_operand_index = self.add_operand(node.name, Operand.IOTYPE_OUTPUT)
311 self.converted_nodes.add(pnode.name)
314 self.converted_nodes.add(node.name)
316 output_operand_index = self.add_operand(node.name, Operand.IOTYPE_OUTPUT)
327 self.converted_nodes.add(node.name)
329 output_operand_index = self.add_operand(node.name, Operand.IOTYPE_OUTPUT)
335 self.converted_nodes.add(node.name)
344 input_operand_index = self.add_operand(i1_node.name, Operand.IOTYPE_INPUT)
349 input_operand_index = self.add_operand(i0_node.name, Operand.IOTYPE_INPUT)
355 input_operand_index = self.add_operand(i0_node.name, Operand.IOTYPE_INPUT)
358 input_operand_index = self.add_operand(i1_node.name, Operand.IOTYPE_INPUT)
360 output_operand_index = self.add_operand(node.name, Operand.IOTYPE_OUTPUT)
366 self.converted_nodes.add(node.name)
369 input_operand_index = self.add_operand(i0_node.name, Operand.IOTYPE_INPUT)
371 output_operand_index = self.add_operand(node.name, Operand.IOTYPE_OUTPUT)
378 self.converted_nodes.add(node.name)
402 output_operand_index = self.add_operand(node.name, Operand.IOTYPE_OUTPUT)
408 if node.name in self.converted_nodes:
412 if self.in_conv2d_scope(node.name):
416 if self.in_dense_scope(node.name):
425 if node.name in self.output_names:
426 input_name = self.id_different_scope_dict[node.name]
427 if TFConverter.get_scope_name(input_name)!=TFConverter.get_scope_name(node.name):
447 np.array([operand.index, len(operand.name)], dtype=np.uint32).tofile(f)
448 f.write(operand.name.encode('utf-8'))
464 self.name_node_dict[node.name] = node
474 if node.name not in used_names:
475 self.output_names.append(node.name)
484 name = node.name
487 # do not change the output name
488 if name in self.output_names:
489 self.name_node_dict[input].name = name
490 self.name_node_dict[name] = self.name_node_dict[input]
492 self.id_different_scope_dict[name] = input
494 id_dict[name] = input
516 def get_scope_name(name):
517 index = name.rfind('/')
520 return name[0:index]
523 def in_conv2d_scope(self, name):
524 inner_scope = TFConverter.get_scope_name(name)
534 def in_dense_scope(self, name):
535 inner_scope = TFConverter.get_scope_name(name)
545 # mostly, conv2d/dense is a sub block in graph, get the scope name
548 scope = TFConverter.get_scope_name(node.name)
557 scope = TFConverter.get_scope_name(node.name)
566 # get the input name to the conv2d/dense sub block
568 scope = TFConverter.get_scope_name(node.name)