PaddleDriver的测试例调整

tests/core/drivers/paddle_driver/test_paddle_driver.py

@@ -1,75 +1,28 @@
-import unittest
-
-import torch
+import os
+import pytest
+os.environ["FASTNLP_BACKEND"] = "paddle"
 
 from fastNLP.core.drivers.paddle_driver.paddle_driver import PaddleDriver
-import paddle
-from paddle.io import Dataset, DataLoader
-
-class Net(paddle.nn.Layer):
-    def __init__(self):
-        super(Net, self).__init__()
-
-        self.fc1 = paddle.nn.Linear(784, 64)
-        self.fc2 = paddle.nn.Linear(64, 32)
-        self.fc3 = paddle.nn.Linear(32, 10)
-        self.fc4 = paddle.nn.Linear(10, 10)
-
-    def forward(self, x):
-        
-        x = self.fc1(x)
-        x = self.fc2(x)
-        x = self.fc3(x)
-        x = self.fc4(x)
-
-        return x
-
-
-class PaddleDataset(Dataset):
-    def __init__(self):
-        super(PaddleDataset, self).__init__()
-        self.items = [paddle.rand((3, 4)) for i in range(320)]
-
-    def __len__(self):
-        return len(self.items)
-
-    def __getitem__(self, idx):
-        return self.items[idx]
-
-
-class TorchNet(torch.nn.Module):
-    def __init__(self):
-        super(TorchNet, self).__init__()
-
-        self.torch_fc1 = torch.nn.Linear(10, 10)
-        self.torch_softmax = torch.nn.Softmax(0)
-        self.torch_conv2d1 = torch.nn.Conv2d(10, 10, 3)
-        self.torch_tensor = torch.ones(3, 3)
-        self.torch_param = torch.nn.Parameter(torch.ones(4, 4))
-
-
-class TorchDataset(torch.utils.data.Dataset):
-    def __init__(self):
-        super(TorchDataset, self).__init__()
-        self.items = [torch.ones(3, 4) for i in range(320)]
-
-    def __len__(self):
-        return len(self.items)
-
-    def __getitem__(self, idx):
-        return self.items[idx]
+from tests.helpers.models.paddle_model import PaddleNormalModel_Classification_1
+from tests.helpers.datasets.paddle_data import PaddleNormalDataset
+from tests.helpers.datasets.torch_data import TorchNormalDataset
+from tests.helpers.models.torch_model import TorchNormalModel_Classification_1
 
+import torch
+import paddle
+from paddle.io import DataLoader
 
-class PaddleDriverTestCase(unittest.TestCase):
+class TestPaddleDriverFunctions:
     """
-    PaddleDriver的测试类，由于类的特殊性仅测试部分函数，其它的由PaddleSingleDriver和PaddleFleetDriver完成测试
+    PaddleDriver的测试类，使用仅测试部分函数，其它的由PaddleSingleDriver和PaddleFleetDriver完成测试
     """
 
-    def setUp(self):
-        model = Net()
+    @classmethod
+    def setup_class(self):
+        model = PaddleNormalModel_Classification_1(10, 32)
         self.driver = PaddleDriver(model)
 
-    def test_check_single_optimizer_legacy(self):
+    def test_check_single_optimizer_legality(self):
         """
         测试传入单个optimizer时的表现
         """
@@ -80,12 +33,12 @@ class PaddleDriverTestCase(unittest.TestCase):
 
         self.driver.set_optimizers(optimizer)
 
-        optimizer = torch.optim.Adam(TorchNet().parameters(), 0.01)
+        optimizer = torch.optim.Adam(TorchNormalModel_Classification_1(10, 32).parameters(), 0.01)
         # 传入torch的optimizer时，应该报错ValueError
         with self.assertRaises(ValueError) as cm:
             self.driver.set_optimizers(optimizer)
 
-    def test_check_optimizers_legacy(self):
+    def test_check_optimizers_legality(self):
         """
         测试传入optimizer list的表现
         """
@@ -99,22 +52,27 @@ class PaddleDriverTestCase(unittest.TestCase):
         self.driver.set_optimizers(optimizers)
 
         optimizers += [
-            torch.optim.Adam(TorchNet().parameters(), 0.01)
+            torch.optim.Adam(TorchNormalModel_Classification_1(10, 32).parameters(), 0.01)
         ]
 
         with self.assertRaises(ValueError) as cm:
             self.driver.set_optimizers(optimizers)
 
-    def test_check_dataloader_legacy_in_train(self):
+    def test_check_dataloader_legality_in_train(self):
         """
         测试is_train参数为True时，_check_dataloader_legality函数的表现
         """
-        dataloader = paddle.io.DataLoader(PaddleDataset())
+        dataloader = paddle.io.DataLoader(PaddleNormalDataset())
         PaddleDriver._check_dataloader_legality(dataloader, "dataloader", True)
 
+        # batch_size 和 batch_sampler 均为 None 的情形
+        dataloader = paddle.io.DataLoader(PaddleNormalDataset(), batch_size=None)
+        with self.assertRaises(ValueError) as cm:
+            PaddleDriver._check_dataloader_legality(dataloader, "dataloader", True)
+
         # 创建torch的dataloader
         dataloader = torch.utils.data.DataLoader(
-            TorchDataset(),
+            TorchNormalDataset(),
             batch_size=32, shuffle=True
         )
         with self.assertRaises(ValueError) as cm:
@@ -125,21 +83,31 @@ class PaddleDriverTestCase(unittest.TestCase):
         测试is_train参数为False时，_check_dataloader_legality函数的表现
         """
         # 此时传入的应该是dict
-        dataloader = {"train": paddle.io.DataLoader(PaddleDataset()), "test":paddle.io.DataLoader(PaddleDataset())}
+        dataloader = {
+            "train": paddle.io.DataLoader(PaddleNormalDataset()),
+            "test":paddle.io.DataLoader(PaddleNormalDataset())
+        }
+        PaddleDriver._check_dataloader_legality(dataloader, "dataloader", False)
+
+        # batch_size 和 batch_sampler 均为 None 的情形
+        dataloader = {
+            "train": paddle.io.DataLoader(PaddleNormalDataset()),
+            "test":paddle.io.DataLoader(PaddleNormalDataset(), batch_size=None)
+        }
         PaddleDriver._check_dataloader_legality(dataloader, "dataloader", False)
 
         # 传入的不是dict，应该报错
-        dataloader = paddle.io.DataLoader(PaddleDataset())
+        dataloader = paddle.io.DataLoader(PaddleNormalDataset())
         with self.assertRaises(ValueError) as cm:
             PaddleDriver._check_dataloader_legality(dataloader, "dataloader", False)
 
         # 创建torch的dataloader
         train_loader = torch.utils.data.DataLoader(
-            TorchDataset(),
+            TorchNormalDataset(),
             batch_size=32, shuffle=True
         )
         test_loader = torch.utils.data.DataLoader(
-            TorchDataset(),
+            TorchNormalDataset(),
             batch_size=32, shuffle=True
         )
         dataloader = {"train": train_loader, "test": test_loader}
@@ -240,7 +208,7 @@ class PaddleDriverTestCase(unittest.TestCase):
         """
         # 先确保不影响运行
         # TODO：正确性
-        dataloader = DataLoader(PaddleDataset())
+        dataloader = DataLoader(PaddleNormalDataset())
         self.driver.set_deterministic_dataloader(dataloader)
 
     def test_set_sampler_epoch(self):
@@ -249,7 +217,7 @@ class PaddleDriverTestCase(unittest.TestCase):
         """
         # 先确保不影响运行
         # TODO：正确性
-        dataloader = DataLoader(PaddleDataset())
+        dataloader = DataLoader(PaddleNormalDataset())
         self.driver.set_sampler_epoch(dataloader, 0)
 
     def test_get_dataloader_args(self):
@@ -258,5 +226,5 @@ class PaddleDriverTestCase(unittest.TestCase):
         """
         # 先确保不影响运行
         # TODO：正确性
-        dataloader = DataLoader(PaddleDataset())
+        dataloader = DataLoader(PaddleNormalDataset())
         res = PaddleDriver.get_dataloader_args(dataloader)