from collections import defaultdict import framework from framework import Program, default_main_program, Parameter, Variable import backward from backward import _rename_arg_ from . import core dtype_to_size = { core.DataType.FP16: 2, core.DataType.FP32: 4, core.DataType.FP64: 8, core.DataType.INT16: 2, core.DataType.INT32: 4, core.DataType.INT64: 8, core.DataType.BOOL: 1 } class ControlFlowGraph(object): def __init__(self, Program): self._program = Program self._succesors = defaultdict(set) self._presucessors = defaultdict(set) self._uses = defaultdict(set) self._defs = defaultdict(set) self._live_in = defaultdict(set) self._live_out = defaultdict(set) def _add_connections(self, connections): for node1, node2 in connections: self._add(node1, node2) def _add(self, node1, node2): self._succesors[node1].add(node2) self._presucessors[node2].add(node1) def _build_graph(self): program_desc = self._program.get_desc() block_size = program_desc.num_blocks() # TODO(qijun) handle Program with if/while operators self.global_block_desc = program_desc.block(0) self.op_size = self.global_block_desc.op_size() op_node_connections = [(i, i + 1) for i in range(self.op_size - 1)] self._add_connections(op_node_connections) self.ops = [self.global_block_desc.op(i) for i in range(self.op_size)] for i in range(self.op_size): self._uses[i].update(self.ops[i].input_arg_names()) self._defs[i].update(self.ops[i].output_arg_names()) def _update_graph(self, old_name, new_name, begin_idx=0): for i in range(begin_idx, self.op_size): if old_name in self._uses[i]: self._uses[i].remove(old_name) self._uses[i].add(new_name) if old_name in self._defs[i]: self._defs[i].remove(old_name) self._defs[i].add(new_name) if old_name in self._live_in[i]: self._live_in[i].remove(old_name) self._live_out[i].add(new_name) if old_name in self._live_out[i]: self._live_out[i].remove(old_name) self._live_out[i].add(new_name) def _reach_fixed_point(self, live_in, live_out): if len(live_in) != len(self._live_in): return False if len(live_out) != len(self._live_out): return False for i in range(self.op_size): if live_in[i] != self._live_in[i]: return False for i in range(self.op_size): if live_out[i] != self._live_out[i]: return False return True def _dataflow_analyze(self): self._build_graph() live_in = defaultdict(set) live_out = defaultdict(set) while True: for i in range(self.op_size): live_in[i] = set(self._live_in[i]) live_out[i] = set(self._live_out[i]) self._live_in[i] = self._uses[i] | ( self._live_out[i] - self._defs[i]) for s in self._succesors[i]: self._live_out[i] |= self._live_in[s] if self._reach_fixed_point(live_in, live_out): break def _get_diff(self, a, b): u = a & b return a - u, b - u def memory_optimize(self): self._build_graph() self._dataflow_analyze() self.pool = [] for i in range(self.op_size): if self.pool: out_pair = [(x, self.global_block_desc.var(str(x)).shape()) for x in self._defs[i]] for x, x_shape in out_pair: if not self.global_block_desc.var(str(x)).persistable(): for index, cache_pair in enumerate(self.pool): cache_var = cache_pair[0] cache_shape = cache_pair[1] if x_shape == cache_shape: x_dtype = self.global_block_desc.var(str( x)).dtype() cache_dtype = self.global_block_desc.var( str(cache_var)).dtype() # TODO(qijun): actually, we should compare dtype_to_size[x_dtype] # and dtype_to_size[cache_dtype] if x_dtype == cache_dtype: print( "Hit Cache !!!! cache pool index is %d, var name is %s, cached var name is %s, var shape is %s " % (index, x, cache_var, str(cache_shape))) self.pool.pop(index) _rename_arg_( self.ops, x, cache_var, begin_idx=i) self._program.current_block().var(str( x)).desc = self.global_block_desc.var( str(cache_var)) self._update_graph( x, cache_var, begin_idx=i) break in_diff, out_diff = self._get_diff(self._live_in[i], self._live_out[i]) can_optimize = filter( lambda x: not self.global_block_desc.var(str(x)).persistable(), in_diff) if can_optimize: for var_name in can_optimize: self.pool.append( (var_name, self.global_block_desc.var(str(var_name)).shape())) def get_program(self): return self._program def memory_optimize(input_program): graph = ControlFlowGraph(input_program) graph.memory_optimize() result_program = graph.get_program() return result_program