diff --git a/tests/test_utils/test_materialize_arbitary_lazy_module.py b/tests/test_utils/test_materialize_arbitary_lazy_module.py
deleted file mode 100644
index b84293490..000000000
--- a/tests/test_utils/test_materialize_arbitary_lazy_module.py
+++ /dev/null
@@ -1,55 +0,0 @@
-import torch
-from colossalai.utils.model.lazy_init_context import LazyInitContext
-from torchvision.models import resnet34
-import random
-import numpy as np
-
-MANUAL_SEED = 0
-random.seed(MANUAL_SEED)
-np.random.seed(MANUAL_SEED)
-torch.manual_seed(MANUAL_SEED)
-
-
-class MLP(torch.nn.Module):
-
-    def __init__(self, dim: int = 4):
-        super().__init__()
-        intermediate_dim = dim * 4
-        self.dense_1 = torch.nn.Linear(dim, intermediate_dim)
-        self.activation = torch.nn.GELU()
-        self.dense_2 = torch.nn.Linear(intermediate_dim, dim)
-        self.dropout = torch.nn.Dropout(0.1)
-
-    def forward(self, x):
-        x = self.dense_1(x)
-        x = self.activation(x)
-        x = self.dense_2(x)
-        x = self.dropout(x)
-        return x
-
-
-def test_lazy_init():
-    cpu_rng_state = torch.get_rng_state()
-    origin_model = MLP()
-    origin_param_dict = dict(origin_model.named_parameters())
-    torch.set_rng_state(cpu_rng_state)
-    ctx = LazyInitContext()
-    with ctx:
-        model = MLP()
-    for param in model.parameters():
-        assert param.is_meta
-    for buffer in model.buffers():
-        assert buffer.is_meta
-    for module in model.children():
-        ctx.lazy_init_parameters(module)
-        for param in module.parameters():
-            assert not param.is_meta
-        for buffer in module.buffers():
-            assert not buffer.is_meta
-    param_dict = dict(model.named_parameters())
-    for key in origin_param_dict.keys():
-        assert origin_param_dict[key].data.equal(param_dict[key].data)
-
-
-if __name__ == '__main__':
-    test_lazy_init()