From 4359630b1755294a35fb90a585b44111522f053e Mon Sep 17 00:00:00 2001 From: Dongfeng Yu Date: Fri, 7 Nov 2025 23:35:18 +0000 Subject: [PATCH] Clean up unused code Signed-off-by: Dongfeng Yu --- .../unittest/_torch/thop/parallel/test_moe.py | 27 ++++++------------- 1 file changed, 8 insertions(+), 19 deletions(-) diff --git a/tests/unittest/_torch/thop/parallel/test_moe.py b/tests/unittest/_torch/thop/parallel/test_moe.py index ddfa2eca65f..3daa157ecdf 100644 --- a/tests/unittest/_torch/thop/parallel/test_moe.py +++ b/tests/unittest/_torch/thop/parallel/test_moe.py @@ -263,7 +263,7 @@ def routing_reference_no_aux(expert_logits, # TopK -> Softmax -def routing_reference_renormalize(expert_logits, top_k, num_experts, padding): +def routing_reference_renormalize(expert_logits, top_k, padding): topk_values, topk_idx = torch.topk(expert_logits, k=top_k, dim=-1) topk_values = torch.nn.functional.softmax(topk_values.float(), dim=-1) @@ -279,8 +279,7 @@ def routing_reference_renormalize(expert_logits, top_k, num_experts, padding): # Softmax->TopK -> Normalize -def routing_reference_renormalize_naive(expert_logits, top_k, num_experts, - padding): +def routing_reference_renormalize_naive(expert_logits, top_k, padding): norm_topk_prob = True scores = torch.nn.functional.softmax(expert_logits.float(), dim=-1) topk_values, topk_idx = torch.topk(scores, k=top_k, dim=-1) @@ -1002,7 +1001,6 @@ class TestMoeFp4: { "num_experts": 256, "top_k": 8, - "padding": 8, "n_groups": 8, "top_k_groups": 4, "routed_scaling": 2.5, @@ -1014,7 +1012,6 @@ class TestMoeFp4: { "num_experts": 72, "top_k": 6, - "padding": 8, "n_groups": 1, "top_k_groups": 1, "routed_scaling": 2.5, @@ -1026,7 +1023,6 @@ class TestMoeFp4: { "num_experts": 128, "top_k": 8, - "padding": 8, "n_groups": None, "top_k_groups": None, "routed_scaling": None, @@ -1038,7 +1034,6 @@ class TestMoeFp4: { "num_experts": 128, "top_k": 4, - "padding": 8, "n_groups": None, "top_k_groups": None, "routed_scaling": None, @@ -1050,7 +1045,6 @@ class TestMoeFp4: { "num_experts": 512, "top_k": 10, - "padding": 8, "n_groups": None, "top_k_groups": None, "routed_scaling": None, @@ -1080,7 +1074,6 @@ def test_autotune(self, num_tokens, hidden_size, intermediate_size, { "num_experts": 72, "top_k": 6, - "padding": 8, "n_groups": 1, "top_k_groups": 1, "routed_scaling": 2.5, @@ -1110,7 +1103,6 @@ def test_autotune_fp8_fp4(self, num_tokens, hidden_size, intermediate_size, { "num_experts": 256, "top_k": 8, - "padding": 8, "n_groups": 8, "top_k_groups": 4, "routed_scaling": 2.5, @@ -1122,7 +1114,6 @@ def test_autotune_fp8_fp4(self, num_tokens, hidden_size, intermediate_size, { "num_experts": 128, "top_k": 4, - "padding": 8, "n_groups": None, "top_k_groups": None, "routed_scaling": None, @@ -1134,7 +1125,6 @@ def test_autotune_fp8_fp4(self, num_tokens, hidden_size, intermediate_size, { "num_experts": 512, "top_k": 10, - "padding": 8, "n_groups": None, "top_k_groups": None, "routed_scaling": None, @@ -1166,7 +1156,6 @@ def test_no_autotune(self, num_tokens, hidden_size, intermediate_size, { "num_experts": 128, "top_k": 4, - "padding": 8, "n_groups": None, "top_k_groups": None, "routed_scaling": None, @@ -1305,10 +1294,10 @@ def run_moe_fp4_test(self, num_tokens: int, hidden_size: int, routed_scaling, padding) elif routing_method_type == RoutingMethodType.Renormalize: permute_info, scores = routing_reference_renormalize( - expert_logits, top_k, num_experts, padding) + expert_logits, top_k, padding) elif routing_method_type == RoutingMethodType.RenormalizeNaive: permute_info, scores = routing_reference_renormalize_naive( - expert_logits, top_k, num_experts, padding) + expert_logits, top_k, padding) args = moe_args(num_tokens, num_experts, hidden_size, intermediate_size, top_k, padding, hidden_states_fp4_bytes, @@ -1552,10 +1541,10 @@ def run_moe_fp8_fp4_test(self, num_tokens: int, hidden_size: int, routed_scaling, padding) elif routing_method_type == RoutingMethodType.Renormalize: permute_info, scores = routing_reference_renormalize( - expert_logits, top_k, num_experts, padding) + expert_logits, top_k, padding) elif routing_method_type == RoutingMethodType.RenormalizeNaive: permute_info, scores = routing_reference_renormalize_naive( - expert_logits, top_k, num_experts, padding) + expert_logits, top_k, padding) args = moe_args(num_tokens, num_experts, hidden_size, intermediate_size, top_k, padding, hidden_states_fp8, None, @@ -2028,10 +2017,10 @@ def test_moe_mxe2m1_weights(num_tokens, hidden_size, intermediate_size, sf_block_size) # ue8m0 scaling factors if routing_method_type == RoutingMethodType.Renormalize: permute_info, scores = routing_reference_renormalize( - expert_logits, top_k, num_experts, padding) + expert_logits, top_k, padding) elif routing_method_type == RoutingMethodType.RenormalizeNaive: permute_info, scores = routing_reference_renormalize_naive( - expert_logits, top_k, num_experts, padding) + expert_logits, top_k, padding) else: raise ValueError("Invalid routing method type")