diff --git a/fastNLP/core/metrics/backend/paddle_backend/backend.py b/fastNLP/core/metrics/backend/paddle_backend/backend.py index 4028fcf4..cf7feb79 100644 --- a/fastNLP/core/metrics/backend/paddle_backend/backend.py +++ b/fastNLP/core/metrics/backend/paddle_backend/backend.py @@ -11,11 +11,12 @@ from fastNLP.envs.imports import _NEED_IMPORT_PADDLE if _NEED_IMPORT_PADDLE: 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)] - paddle.distributed.all_gather(gathered_result, result, group) + dist.all_gather(gathered_result, result, group) return gathered_result class PaddleBackend(Backend): @@ -36,13 +37,13 @@ class PaddleBackend(Backend): tensor = paddle.stack(tensor) # 第一步, aggregate结果 if method == 'sum': - tensor = paddle.sum(tensor, dim=0) + tensor = paddle.sum(tensor, axis=0) elif method == 'mean': - tensor = paddle.mean(tensor, dim=0) + tensor = paddle.mean(tensor, axis=0) elif method == 'max': - tensor, _ = paddle.max(tensor, dim=0) + tensor, _ = paddle.max(tensor, axis=0) elif method == 'min': - tensor, _ = paddle.min(tensor, dim=0) + tensor, _ = paddle.min(tensor, axis=0) else: raise AggregateMethodError(should_have_aggregate_method=False) @@ -80,11 +81,12 @@ class PaddleBackend(Backend): 聚合 group 中所有的 result；由于不同 group 中 result 大小不同，因此在适当的时候需要进行 padding """ # TODO check 正确性 - if group is None: - group = paddle.distributed.get_group(0) + # 有 paddle 那边的 bug，2.3 版本的时候修复了，到时候改一下 + # if group is None: + # group = dist.get_group(0) - world_size = group.nranks - paddle.distributed.barrier(group=group) + world_size = group.nranks if group is not None else dist.get_world_size() + dist.barrier(group=group) # 张量为 标量的情况，简单地gather就好 if result.ndim == 0: @@ -93,10 +95,10 @@ class PaddleBackend(Backend): # 获得 result 的 shape local_size = paddle.to_tensor(result.shape) # 将 group 中所有 result 的大小聚合在一起 - local_sizes = [paddle.zeros_like(local_size) for _ in range(world_size)] - paddle.distributed.all_gather(local_sizes, local_size, group=group) + local_sizes = [] + dist.all_gather(local_sizes, local_size, group=group) # 堆叠后，计算出 shape 每一维度的最大值 - max_size = paddle.stack(local_sizes).max(axis=0).values + max_size = paddle.stack(local_sizes).max(axis=0) all_sizes_equal = all(all(ls == max_size) for ls in local_sizes) # 如果所有的结果大小相同，那么可以直接聚合 @@ -111,10 +113,10 @@ class PaddleBackend(Backend): pad_dims.append(val.item()) result_padded = paddle.nn.functional.pad(result, pad_dims) # 重新进行聚合 - gathered_result = [paddle.zeros_like(result_padded) for _ in range(world_size)] - paddle.distributed.all_gather(gathered_result, result_padded, group) + gathered_result = [] + dist.all_gather(gathered_result, result_padded, group) for idx, item_size in enumerate(local_sizes): - slice_param = [slice(dim_size) for dim_size in item_size] + slice_param = [slice(dim_size) for dim_size in item_size.tolist()] gathered_result[idx] = gathered_result[idx][slice_param] return gathered_result diff --git a/tests/core/controllers/test_trainer_paddle.py b/tests/core/controllers/test_trainer_paddle.py new file mode 100644 index 00000000..ed102c99 --- /dev/null +++ b/tests/core/controllers/test_trainer_paddle.py @@ -0,0 +1,151 @@ +import pytest +import os +from typing import Any +from dataclasses import dataclass + +from paddle.optimizer import Adam +from paddle.io import DataLoader + +from fastNLP.core.controllers.trainer import Trainer +from fastNLP.core.metrics.accuracy import Accuracy +from fastNLP.core.callbacks.progress_callback import RichCallback +from fastNLP.envs import FASTNLP_DISTRIBUTED_CHECK + + +from tests.helpers.models.paddle_model import PaddleNormalModel_Classification +from tests.helpers.datasets.paddle_data import PaddleDataset_MNIST +from tests.helpers.callbacks.helper_callbacks import RecordLossCallback, RecordMetricCallback +from tests.helpers.utils import magic_argv_env_context + +@dataclass +class MNISTTrainPaddleConfig: + num_labels: int = 10 + feature_dimension: int = 784 + + batch_size: int = 32 + shuffle: bool = True + validate_every = -5 + + driver: str = "paddle" + device = "gpu" + +@dataclass +class MNISTTrainFleetConfig: + num_labels: int = 10 + feature_dimension: int = 784 + + batch_size: int = 32 + shuffle: bool = True + validate_every = -5 + +@dataclass +class TrainerParameters: + model: Any = None + optimizers: Any = None + train_dataloader: Any = None + validate_dataloaders: Any = None + input_mapping: Any = None + output_mapping: Any = None + metrics: Any = None + +# @pytest.fixture(params=[0], autouse=True) +# def model_and_optimizers(request): +# """ +# 初始化单卡模式的模型和优化器 +# """ +# trainer_params = TrainerParameters() +# print(paddle.device.get_device()) + +# if request.param == 0: +# trainer_params.model = PaddleNormalModel_Classification( +# num_labels=MNISTTrainPaddleConfig.num_labels, +# feature_dimension=MNISTTrainPaddleConfig.feature_dimension +# ) +# trainer_params.optimizers = Adam(parameters=trainer_params.model.parameters(), learning_rate=0.0001) +# train_dataloader = DataLoader( +# dataset=PaddleDataset_MNIST("train"), +# batch_size=MNISTTrainPaddleConfig.batch_size, +# shuffle=True +# ) +# val_dataloader = DataLoader( +# dataset=PaddleDataset_MNIST(mode="test"), +# batch_size=MNISTTrainPaddleConfig.batch_size, +# shuffle=True +# ) +# trainer_params.train_dataloader = train_dataloader +# trainer_params.validate_dataloaders = val_dataloader +# trainer_params.validate_every = MNISTTrainPaddleConfig.validate_every +# trainer_params.metrics = {"acc": Accuracy()} + +# return trainer_params + + +@pytest.mark.parametrize("driver,device", [("paddle", "cpu"), ("paddle", 1)]) +# @pytest.mark.parametrize("driver,device", [("fleet", [0, 1])]) +@pytest.mark.parametrize("callbacks", [[RecordMetricCallback(monitor="acc#acc", metric_threshold=0.7, larger_better=True), + RichCallback(5), RecordLossCallback(loss_threshold=0.3)]]) +@magic_argv_env_context +def test_trainer_paddle( + # model_and_optimizers: TrainerParameters, + driver, + device, + callbacks, + n_epochs=15, +): + trainer_params = TrainerParameters() + + trainer_params.model = PaddleNormalModel_Classification( + num_labels=MNISTTrainPaddleConfig.num_labels, + feature_dimension=MNISTTrainPaddleConfig.feature_dimension + ) + trainer_params.optimizers = Adam(parameters=trainer_params.model.parameters(), learning_rate=0.0001) + train_dataloader = DataLoader( + dataset=PaddleDataset_MNIST("train"), + batch_size=MNISTTrainPaddleConfig.batch_size, + shuffle=True + ) + val_dataloader = DataLoader( + dataset=PaddleDataset_MNIST(mode="test"), + batch_size=MNISTTrainPaddleConfig.batch_size, + shuffle=True + ) + trainer_params.train_dataloader = train_dataloader + trainer_params.validate_dataloaders = val_dataloader + trainer_params.validate_every = MNISTTrainPaddleConfig.validate_every + trainer_params.metrics = {"acc": Accuracy(backend="paddle")} + if not isinstance(device, (int, str)) and len(device) > 1 and FASTNLP_DISTRIBUTED_CHECK not in os.environ: + with pytest.raises(SystemExit) as exc: + trainer = Trainer( + model=trainer_params.model, + driver=driver, + device=device, + optimizers=trainer_params.optimizers, + train_dataloader=trainer_params.train_dataloader, + validate_dataloaders=trainer_params.validate_dataloaders, + validate_every=trainer_params.validate_every, + input_mapping=trainer_params.input_mapping, + output_mapping=trainer_params.output_mapping, + metrics=trainer_params.metrics, + + n_epochs=n_epochs, + callbacks=callbacks, + ) + assert exc.value.code == 0 + return + else: + trainer = Trainer( + model=trainer_params.model, + driver=driver, + device=device, + optimizers=trainer_params.optimizers, + train_dataloader=trainer_params.train_dataloader, + validate_dataloaders=trainer_params.validate_dataloaders, + validate_every=trainer_params.validate_every, + input_mapping=trainer_params.input_mapping, + output_mapping=trainer_params.output_mapping, + metrics=trainer_params.metrics, + + n_epochs=n_epochs, + callbacks=callbacks, + ) + trainer.run() \ No newline at end of file diff --git a/tests/core/drivers/paddle_driver/test_paddle_driver.py b/tests/core/drivers/paddle_driver/test_paddle_driver.py index d992fdb7..9febc27d 100644 --- a/tests/core/drivers/paddle_driver/test_paddle_driver.py +++ b/tests/core/drivers/paddle_driver/test_paddle_driver.py @@ -1,17 +1,11 @@ import unittest import torch -from fastNLP.envs.set_env import set_env -from fastNLP.envs.set_env_on_import import set_env_on_import_paddle -set_env_on_import_paddle() -set_env("paddle") +from fastNLP.core.drivers.paddle_driver.paddle_driver import PaddleDriver import paddle from paddle.io import Dataset, DataLoader -from fastNLP.core.drivers.paddle_driver.paddle_driver import PaddleDriver - - class Net(paddle.nn.Layer): def __init__(self): super(Net, self).__init__()