# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License from functools import reduce import paddle from paddle.fluid.framework import Variable from paddle.distributed.auto_parallel.dist_tensor import DistributedTensor from .base_cost import Cost class TensorCost: def __init__(self, tensor=None, dist_tensor=None, shape=None, dtype=None): self._check_args(tensor, dist_tensor, shape, dtype) self._tensor = tensor self._dist_tensor = dist_tensor self._shape = shape self._dtype = dtype self._cost = self.calc_cost() @property def tensor(self): return self._tensor @property def dist_tensor(self): return self._dist_tensor @property def shape(self): return self._shape @property def dtype(self): return self._dtype def _check_args(self, tensor, dist_tensor, shape, dtype): if tensor is not None: assert (shape is None and dist_tensor is None and dtype is None) if not isinstance(tensor, Variable): raise TypeError( "Please check tensor type is Variable, but got {}".format( type(tensor))) elif dist_tensor is not None: assert (tensor is None and shape is None) if not isinstance(dist_tensor, DistributedTensor): raise TypeError( "Please check dist_tensor type is DistributedTensor, but got {}" .format(type(dist_tensor))) elif shape is not None: assert (tensor is None and dist_tensor is None and dtype is not None) if not isinstance(shape, (list, set)): raise TypeError( "Please check shape type is list or set, but got {}".format( type(shape))) elif dtype is not None: assert (tensor is None and dist_tensor is None and shape is not None) @property def cost(self): return self._cost def calc_cost(self): dtype = None shape = None if self.dist_tensor: shape = self.dist_tensor.local_sizes() dtype = self.dist_tensor.serial_tensor.dtype elif self.tensor: shape = self.tensor.shape dtype = self.tensor.dtype elif self.shape and self.dtype: shape = self.shape dtype = self.dtype total_count = reduce(lambda x, y: x * y, shape) if dtype == paddle.float32 or dtype == paddle.int32: dtype_factor = 4 elif node.dtype == paddle.int64: dtype_factor = 8 elif node.dtype == paddle.uint8: dtype_factor = 1 else: dtype_factor = 2 memory = total_count * dtype_factor assert memory >= 0 cost = Cost(memory=memory) return cost