def get_input(self, node):
input_nodes = []
for name in node.input:
name = get_real_name(name)
if name in self.node_dict:
input_nodes.append(self.get_node(name))
return input_nodes
def get_input(self, node):
input_nodes = []
for name in node.input:
name = get_real_name(name)
if name in self.node_dict:
input_nodes.append(self.get_node(name))
return input_nodes
def emit(self):
# Decompose DAG into chains
chains = []
for node in self.graph.topologically_sorted():
attach_to_chain = None
if len(node.input) == 1:
parent = get_real_name(node.input[0])
for chain in chains:
if chain[
-1].name == parent: # Node is part of an existing chain.
attach_to_chain = chain
break
if attach_to_chain is None: # Start a new chain for this node.
attach_to_chain = []
chains.append(attach_to_chain)
attach_to_chain.append(node)
# Generate Python code line by line
source = self.emit_imports()
source += self.emit_class_def(self.graph.name)
self.indent()
source += self.emit_setup_def()
self.indent()
blocks = []
for chain in chains:
b = ''
for node in chain:
b += self.emit_node(node)
blocks.append(b[:-1])
source += '\n\n'.join(blocks)
return source
def emit(self):
# Decompose DAG into chains
chains = []
for node in self.graph.topologically_sorted():
attach_to_chain = None
if len(node.input) == 1:
parent = get_real_name(node.input[0])
for chain in chains:
if chain[-1].name == parent: # Node is part of an existing chain.
attach_to_chain = chain
break
if attach_to_chain is None: # Start a new chain for this node.
attach_to_chain = []
chains.append(attach_to_chain)
attach_to_chain.append(node)
# Generate Python code line by line
source = self.emit_imports()
source += self.emit_class_def(self.graph.name)
self.indent()
source += self.emit_setup_def()
self.indent()
blocks = []
for chain in chains:
b = ''
for node in chain:
b += self.emit_node(node)
blocks.append(b[:-1])
source += '\n\n'.join(blocks)
return source