chore: Cleanup disable_fp4_allgather. (#6006)

Signed-off-by: Bo Li <[email protected]>

Author: bobboli

tensorrt_llm/_torch/models/modeling_deepseekv3.py

@@ -511,8 +511,6 @@ def compute_routed_output(self, hidden_states, hidden_states_fp4,
         # max-throughput
         use_dp_padding = False
         if self.use_dp and self.mapping.tp_size > 1:
-            # FP4 all_gather moves this bf16 allgather in to after topk and fp4 quantization
-            # to reduce allreduce BW
             if isinstance(self.experts, TRTLLMGenFusedMoE):
                 hidden_states = allgather(hidden_states,
                                           self.mapping,

tensorrt_llm/_torch/models/modeling_qwen3_moe.py

@@ -20,7 +20,6 @@
 from ..modules.linear import TensorParallelMode
 from ..modules.rms_norm import RMSNorm
 from ..speculative import SpecMetadata
-from ..utils import disable_fp4_allgather
 from .modeling_qwen3 import Qwen3Attention
 from .modeling_speculative import SpecDecOneEngineForCausalLM
 from .modeling_utils import (DecoderModel, EagerFusionConfig,
@@ -133,11 +132,7 @@ def forward(
             assert not self.enable_attention_dp
 
         if self.enable_attention_dp and self.mapping.tp_size > 1:
-            # FP4 all_gather moves this bf16 allgather in to after topk and fp4 quantization
-            # to reduce allreduce BW
-            if (disable_fp4_allgather()
-                    and not self.experts.enable_alltoall) or isinstance(
-                        self.experts, TRTLLMGenFusedMoE):
+            if isinstance(self.experts, TRTLLMGenFusedMoE):
                 hidden_states = allgather(hidden_states,
                                           self.mapping,
                                           dim=0,

tensorrt_llm/_torch/modules/fused_moe/fused_moe_cutlass.py

@@ -4,8 +4,7 @@
 
 from ...distributed import allgather, reducescatter
 from ...model_config import ModelConfig
-from ...utils import (EventType, Fp4QuantizedTensor, ceil_div,
-                      disable_fp4_allgather, swizzle_sf)
+from ...utils import EventType, Fp4QuantizedTensor, ceil_div, swizzle_sf
 from .interface import MoE
 from .quantization import (DeepSeekFP8BlockScalesFusedMoEMethod,
                            FP8QDQFusedMoEMethod, MoEWeightLoadingMode,
@@ -220,8 +219,7 @@ def forward_chunk(
             # TODO: remove this once we have correct fusedmoe kernel ready
             token_final_scales = None
 
-        use_allgather = self.use_dp and self.parallel_size > 1 and not disable_fp4_allgather(
-        )
+        use_allgather = self.use_dp and self.parallel_size > 1
 
         # quantize inputs
         use_deepseek_fp8_block_scale = False

tensorrt_llm/_torch/utils.py

@@ -1,5 +1,4 @@
 import contextlib
-import os
 import threading
 from dataclasses import dataclass
 from enum import Enum
@@ -100,13 +99,6 @@ def shape(self):
         return self.fp4_tensor.shape
 
 
-_disable_fp4_allgather = os.getenv("TLLM_DISABLE_FP4_ALLGATHER", "0") == "1"
-
-
-def disable_fp4_allgather():
-    return _disable_fp4_allgather
-
-
 def compute_swizzled_sf_shape(row: int, col: int):
     padded_row = pad_up(row, 128)
     padded_col = pad_up(col, 4)