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增加paddle单卡的accuracy测试用例

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This commit is contained in:
MorningForest 2022-04-15 20:03:44 +08:00
parent 3ea74b52d2
commit 665d79a3ed
3 changed files with 62 additions and 3 deletions
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3
fastNLP/core/metrics/backend/paddle_backend/backend.py
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@ -14,11 +14,13 @@ if _NEED_IMPORT_PADDLE:
import paddle.distributed as dist
from paddle.fluid.dygraph import parallel_helper
def _simple_gather_all_tensors(result, group: Any, world_size: int) -> List:
gathered_result = [paddle.zeros_like(result) for _ in range(world_size)]
dist.all_gather(gathered_result, result, group)
return gathered_result
class PaddleBackend(Backend):
def __init__(self):
super().__init__()
@ -124,4 +126,3 @@ class PaddleBackend(Backend):
# TODO 如果在这里处理的话，会不会在别的地方引起bug？
device = get_device_from_visible(device)
return paddle_to(tensor, device)

3
fastNLP/core/metrics/backend/torch_backend/backend.py
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@ -11,7 +11,6 @@ from fastNLP.core.drivers.torch_driver.dist_utils import fastnlp_torch_all_gathe
if _NEED_IMPORT_TORCH:
import torch
import torch.distributed as dist
import torch.nn.functional as F
def _simple_gather_all_tensors(result, group: Any, world_size: int) -> List:
@ -33,7 +32,7 @@ class TorchBackend(Backend):
if dist.is_initialized():
if method is None:
raise AggregateMethodError(should_have_aggregate_method=True)
tensor = fastnlp_torch_all_gather(tensor)
tensor = self.all_gather_object(tensor)
if isinstance(tensor[0], torch.Tensor):
tensor = torch.stack(tensor)
# 第一步, aggregate结果

59
tests/core/metrics/test_accutacy_paddle.py Normal file
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@ -0,0 +1,59 @@
import os
import pytest
import paddle
import paddle.distributed
import paddle.distributed.fleet.base.role_maker as role_maker
import paddle.distributed.fleet as fleet
from fastNLP.core.metrics import Accuracy
from fastNLP.core.drivers.paddle_driver.fleet_launcher import FleetLauncher
############################################################################
#
# 测试 单机单卡情况下的Accuracy
#
############################################################################
def test_accuracy_single():
pred = paddle.to_tensor([[1.19812393, -0.82041764, -0.53517765, -0.73061031, -1.45006669,
0.46514302],
[-0.85775983, -2.18273783, -1.07505429, -1.45561373, 0.40011844,
1.02202022],
[-0.39487389, 0.65682763, -0.62424040, 0.53692561, -0.28390560,
-0.02559055],
[-0.22586937, -0.07676325, -0.95977223, 0.36395910, -0.91758579,
-0.83857095],
[0.25136873, 2.49652624, 1.06251311, 1.60194016, 1.01451588,
0.08403367],
[0.10844281, 1.19017303, -0.11378096, 1.12686944, -0.08654942,
0.48605862],
[1.27320433, -1.13902378, 1.47072780, -0.98665696, -0.42589864,
0.64618838],
[0.83809763, -0.05356205, 0.03042423, -0.28371972, 0.81611472,
-0.45802942],
[0.38535264, 0.09721313, 2.27187467, 0.32045507, -0.20711982,
-0.13550705],
[-0.75228405, -1.34161997, 1.08697927, 0.33218071, -1.19470012,
2.58735061]])
tg = paddle.to_tensor([1, 2, 1, 3, 5, 4, 4, 2, 1, 5])
acc_metric = Accuracy()
acc_metric.update(pred, tg)
result = acc_metric.get_metric()
true_result = {'acc': 0.3}
assert true_result == result
############################################################################
#
# 测试 单机多卡情况下的Accuracy
#
############################################################################
def test_accuracy_ddp():
launcher = FleetLauncher(devices=[0, 1])
launcher.launch()
role = role_maker.PaddleCloudRoleMaker(is_collective=True)
fleet.init(role)
if fleet.is_server():
pass
elif fleet.is_worker():
print(os.getenv("PADDLE_TRAINER_ID"))