[Platform] Deprecate seed_everything (#31659)

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

tests/kernels/core/test_activation.py

@@ -18,7 +18,7 @@ from vllm.model_executor.layers.activation import (
     SiluAndMul,
     SwigluOAIAndMul,
 )
-from vllm.platforms import current_platform
+from vllm.utils.torch_utils import set_random_seed
 
 DTYPES = [torch.half, torch.bfloat16, torch.float]
 NUM_TOKENS = [7, 83, 2048]  # Arbitrary values for testing
@@ -52,7 +52,7 @@ def test_act_and_mul(
     seed: int,
     device: str,
 ) -> None:
-    current_platform.seed_everything(seed)
+    set_random_seed(seed)
     torch.set_default_device(device)
     x = torch.randn(num_tokens, 2 * d, dtype=dtype)
     if activation == "silu_and_mul":
@@ -129,7 +129,7 @@ def test_activation(
     seed: int,
     device: str,
 ) -> None:
-    current_platform.seed_everything(seed)
+    set_random_seed(seed)
     torch.set_default_device(device)
     x = torch.randn(num_tokens, d, dtype=dtype)
     layer = activation[0]()

tests/kernels/core/test_fused_qk_norm_rope.py

@@ -8,6 +8,7 @@ from tests.kernels.utils import opcheck
 from vllm.model_executor.layers.layernorm import RMSNorm
 from vllm.model_executor.layers.rotary_embedding import RotaryEmbedding
 from vllm.platforms import current_platform
+from vllm.utils.torch_utils import set_random_seed
 
 DTYPES = [torch.bfloat16, torch.float16]
 IS_NEOX = [True, False]
@@ -64,7 +65,7 @@ def test_fused_qk_norm_rope_matches_reference(
     rotary_ratio: float,
 ):
     torch.set_default_device(device)
-    current_platform.seed_everything(seed)
+    set_random_seed(seed)
     num_heads, num_kv_heads, head_dim = 16, 4, 128
     num_tokens = 4
 

tests/kernels/core/test_layernorm.py

@@ -7,7 +7,7 @@ import torch
 from tests.kernels.quant_utils import FP8_DTYPE
 from tests.kernels.utils import opcheck
 from vllm.model_executor.layers.layernorm import RMSNorm
-from vllm.platforms import current_platform
+from vllm.utils.torch_utils import set_random_seed
 
 DTYPES = [torch.half, torch.bfloat16, torch.float]
 NUM_TOKENS = [7, 83, 4096]  # Arbitrary values for testing
@@ -34,7 +34,7 @@ def test_rms_norm(
     device: str,
     strided_input: bool,
 ) -> None:
-    current_platform.seed_everything(seed)
+    set_random_seed(seed)
     torch.set_default_device(device)
     layer = RMSNorm(hidden_size).to(dtype=dtype)
     layer.weight.data.normal_(mean=1.0, std=0.1)
@@ -88,7 +88,7 @@ def test_fused_rms_norm_quant(
     device: str,
     strided_input: bool,
 ) -> None:
-    current_platform.seed_everything(seed)
+    set_random_seed(seed)
     torch.set_default_device(device)
 
     weight = torch.empty(hidden_size, dtype=dtype).normal_(mean=1.0, std=0.1)

tests/kernels/core/test_mrope.py

@@ -10,6 +10,7 @@ from transformers import __version__ as TRANSFORMERS_VERSION
 from vllm.model_executor.layers.rotary_embedding import get_rope
 from vllm.platforms import current_platform
 from vllm.transformers_utils.config import get_config
+from vllm.utils.torch_utils import set_random_seed
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
@@ -24,7 +25,7 @@ def generate_test_data(
     device: torch.device,
 ):
     """Generate test data for given configuration."""
-    current_platform.seed_everything(42)
+    set_random_seed(42)
     # Create 2D positions (3, num_tokens) for multimodal case
     positions = torch.randint(
         0, max_position_embeddings // 4, (3, num_tokens), device=device

tests/kernels/core/test_pos_encoding.py

@@ -9,7 +9,7 @@ import torch
 
 from tests.kernels.allclose_default import get_default_atol, get_default_rtol
 from vllm.model_executor.layers.rotary_embedding import get_rope
-from vllm.platforms import current_platform
+from vllm.utils.torch_utils import set_random_seed
 
 IS_NEOX_STYLE = [True, False]
 DTYPES = [torch.bfloat16, torch.float]
@@ -79,7 +79,7 @@ def test_rotary_embedding(
     if rotary_dim is None:
         rotary_dim = head_size
 
-    current_platform.seed_everything(seed)
+    set_random_seed(seed)
     torch.set_default_device(device)
     if rotary_dim is None:
         rotary_dim = head_size