[test] ignore 8 gpu test (#1080)

* [test] ignore 8 gpu test

* polish code

* polish workflow

* polish workflow

.github/workflows/build.yml

@@ -15,7 +15,7 @@ jobs:
     runs-on: [self-hosted, gpu]
     container:
       image: hpcaitech/pytorch-cuda:1.10.1-11.3.0
-      options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10
+      options: --shm-size=2gb --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10
     timeout-minutes: 40
     steps:
       - uses: actions/checkout@v2
@@ -25,10 +25,10 @@ jobs:
         run: |
           [ ! -z "$(ls -A /github/home/cuda_ext_cache/)" ] && cp -r /github/home/cuda_ext_cache/* /__w/ColossalAI/ColossalAI/
           pip install -r requirements/requirements.txt
-          pip install -r requirements/requirements-test.txt
           pip install -v -e .
           cp -r /__w/ColossalAI/ColossalAI/build /github/home/cuda_ext_cache/
           cp /__w/ColossalAI/ColossalAI/*.so /github/home/cuda_ext_cache/
+          pip install -r requirements/requirements-test.txt
       - name: Unit Testing
         run: |
           PYTHONPATH=$PWD pytest tests

tests/components_to_test/gpt.py

@@ -7,9 +7,9 @@ from colossalai.utils.cuda import get_current_device
 
 
 class DummyDataLoader(DummyDataGenerator):
-    vocab_size = 50304
+    vocab_size = 128
     batch_size = 4
-    seq_len = 1024
+    seq_len = 64
 
     def generate(self):
         input_ids = torch.randint(0,
@@ -47,6 +47,8 @@ class GPTLMModel(nn.Module):
         # Only return lm_logits
         return self.model(input_ids=input_ids, attention_mask=attention_mask, use_cache=not self.checkpoint)[0]
 
+def gpt2_micro(checkpoint=True):
+    return GPTLMModel(checkpoint=checkpoint, hidden_size=32, num_layers=2, num_attention_heads=4, max_seq_len=64, vocab_size=128)
 
 def gpt2_s(checkpoint=True):
     return GPTLMModel(checkpoint=checkpoint)
@@ -76,4 +78,4 @@ def get_training_components():
     testloader = DummyDataLoader()
 
     criterion = GPTLMLoss()
-    return gpt2_s, trainloader, testloader, torch.optim.Adam, criterion
+    return gpt2_micro, trainloader, testloader, torch.optim.Adam, criterion

tests/test_data_pipeline_tensor_parallel/test_cifar_with_data_pipeline_tensor.py

@@ -83,6 +83,7 @@ def run_trainer(rank, world_size, port):
 
 
 @pytest.mark.dist
+@pytest.mark.skip("This test requires 8 GPUs to execute")
 @rerun_if_address_is_in_use()
 def test_hybrid_parallel():
     world_size = 8

tests/test_layers/test_3d/test_3d.py

@@ -51,6 +51,7 @@ def check_layer_and_operation(rank, world_size, port):
 
 
 @pytest.mark.dist
+@pytest.mark.skip("This test requires 8 GPUs to execute")
 @rerun_if_address_is_in_use()
 def test_3d():
     world_size = 8

tests/test_tensor/test_model.py

@@ -328,7 +328,6 @@ def run_model_dist(rank, world_size, port):
 
 @pytest.mark.dist
 @pytest.mark.parametrize('world_size', [1, 4])
-# @parameterize('world_size', [1, 4])
 @rerun_if_address_is_in_use()
 def test_model(world_size):
     run_func = partial(run_model_dist, world_size=world_size, port=free_port())

tests/test_utils/test_checkpoint/test_checkpoint_1d.py

@@ -67,6 +67,7 @@ def check_checkpoint_1d(rank, world_size, port):
 
 
 @pytest.mark.dist
+@pytest.mark.skip("This test should be invoked with 8 GPUs")
 @rerun_on_exception(exception_type=mp.ProcessRaisedException, pattern=".*Address already in use.*")
 def test_checkpoint_1d():
     world_size = 8

tests/test_utils/test_checkpoint/test_checkpoint_2d.py

@@ -67,6 +67,7 @@ def check_checkpoint_2d(rank, world_size, port):
 
 
 @pytest.mark.dist
+@pytest.mark.skip("This test should be invoked with 8 GPUs")
 @rerun_on_exception(exception_type=mp.ProcessRaisedException, pattern=".*Address already in use.*")
 def test_checkpoint_2d():
     world_size = 8

tests/test_utils/test_checkpoint/test_checkpoint_2p5d.py

@@ -67,6 +67,7 @@ def check_checkpoint_2p5d(rank, world_size, port):
 
 
 @pytest.mark.dist
+@pytest.mark.skip("This test should be invoked with 8 GPUs")
 @rerun_on_exception(exception_type=mp.ProcessRaisedException, pattern=".*Address already in use.*")
 def test_checkpoint_2p5d():
     world_size = 8

tests/test_utils/test_checkpoint/test_checkpoint_3d.py

@@ -67,6 +67,7 @@ def check_checkpoint_3d(rank, world_size, port):
 
 
 @pytest.mark.dist
+@pytest.mark.skip("This test requires 8 GPUs to execute")
 @rerun_on_exception(exception_type=mp.ProcessRaisedException, pattern=".*Address already in use.*")
 def test_checkpoint_3d():
     world_size = 8

tests/test_utils/test_memory.py

@@ -22,7 +22,7 @@ def run_dist(rank, world_size, port):
 
 
 @pytest.mark.dist
-@pytest.mark.parametrize("world_size", [4, 5])
+@pytest.mark.parametrize("world_size", [3, 4])
 def test_memory_utils(world_size):
     run_func = partial(run_dist, world_size=world_size, port=free_port())
     mp.spawn(run_func, nprocs=world_size)

tests/test_zero/test_tensor_utils.py

@@ -85,7 +85,7 @@ def run_dist(rank, world_size, port):
 
 
 @pytest.mark.dist
-@pytest.mark.parametrize("world_size", [4, 5])
+@pytest.mark.parametrize("world_size", [2, 4])
 @rerun_if_address_is_in_use()
 def test_zero_tensor_utils(world_size):
     run_func = partial(run_dist, world_size=world_size, port=free_port())