[bridge] Fix off-by-one in sliding window size for Gemma2, Gemma3, Mistral, and GPT-OSS

src/megatron/bridge/models/gemma/gemma2_bridge.py

@@ -51,7 +51,7 @@ def provider_bridge(self, hf_pretrained: PreTrainedCausalLM) -> Gemma2ModelProvi
         provider.query_pre_attn_scalar = hf_config.query_pre_attn_scalar
         provider.attn_logit_softcapping = hf_config.attn_logit_softcapping
         provider.final_logit_softcapping = hf_config.final_logit_softcapping
-        provider.window_size = (hf_config.sliding_window, 0)
+        provider.window_size = (hf_config.sliding_window - 1, 0)
 
         provider.normalization = "RMSNorm"
         provider.activation_func = fast_gelu

src/megatron/bridge/models/gemma/gemma3_provider.py

@@ -302,7 +302,7 @@ def __init__(
         config = copy.deepcopy(config)
         if _is_local_attn_layer(layer_number, config.interleaved_attn_pattern):
             # local attention, (q, k)
-            config.window_size = (config.window_size, 0)
+            config.window_size = (config.window_size - 1, 0)
         else:
             # global attention
             config.window_size = None

src/megatron/bridge/models/gpt_oss/gpt_oss_bridge.py

@@ -93,7 +93,7 @@ def provider_bridge(self, hf_pretrained: PreTrainedCausalLM) -> GPTModelProvider
         provider.glu_linear_offset = 1.0
 
         provider.softmax_type = "learnable"
-        provider.window_size = (128, 0)
+        provider.window_size = (hf_pretrained.config.sliding_window - 1, 0)
         provider.window_attn_skip_freq = 2
 
         # GPT-OSS uses intermediate_size for MoE FFN hidden size

src/megatron/bridge/models/gpt_oss/gpt_oss_provider.py

@@ -74,7 +74,7 @@ class GPTOSSProvider(GPTModelProvider):
     moe_ffn_hidden_size: int = 2880
     moe_router_load_balancing_type: str = "none"
     seq_length: int = 131072
-    window_size: Optional[Tuple[int, int]] = (128, 0)
+    window_size: Optional[Tuple[int, int]] = (127, 0)
     softmax_type: Literal["vanilla", "off-by-one", "learnable"] = "learnable"
     activation_func: Callable = quick_gelu
     glu_linear_offset: float = 1.0

src/megatron/bridge/models/mistral/mistral_bridge.py

@@ -54,7 +54,7 @@ def provider_bridge(self, hf_pretrained: PreTrainedCausalLM) -> MistralModelProv
 
         window_size, cp_comm_type = (None, None)
         if getattr(hf_config, "sliding_window", None) is not None:
-            window_size = [hf_config.sliding_window, 0]
+            window_size = [hf_config.sliding_window - 1, 0]
             cp_comm_type = "a2a"
 
         provider = cls(

tests/unit_tests/models/gemma/test_gemma2_bridge.py

@@ -320,7 +320,7 @@ def test_provider_bridge_gemma2_specific_features(self, mock_pretrained_gemma2_2
         assert result.query_pre_attn_scalar == gemma2_2b_config.query_pre_attn_scalar
         assert result.attn_logit_softcapping == gemma2_2b_config.attn_logit_softcapping
         assert result.final_logit_softcapping == gemma2_2b_config.final_logit_softcapping
-        assert result.window_size == (gemma2_2b_config.sliding_window, 0)
+        assert result.window_size == (gemma2_2b_config.sliding_window - 1, 0)
         assert result.add_bias_linear == False  # Gemma2 doesn't use bias in linear layers
         assert result.layernorm_zero_centered_gamma == True  # Gemma2-specific RMSNorm behavior
 
@@ -406,8 +406,8 @@ def test_provider_bridge_sliding_window_config(self, mock_pretrained_gemma2_2b,
         result = bridge.provider_bridge(mock_pretrained_gemma2_2b)
 
         # Check sliding window configuration specific to Gemma2
-        assert result.window_size == (gemma2_2b_config.sliding_window, 0)
-        assert result.window_size == (4096, 0)
+        assert result.window_size == (gemma2_2b_config.sliding_window - 1, 0)
+        assert result.window_size == (4095, 0)
 
     def test_provider_bridge_query_pre_attn_scalar_variants(self, mock_pretrained_gemma2_27b, gemma2_27b_config):
         """Test query_pre_attn_scalar for 27B model which has different value."""

tests/unit_tests/models/gpt_oss/test_gpt_oss_bridges.py

@@ -39,6 +39,7 @@ def gpt_oss_cfg(self):
             "torch_dtype": "bfloat16",
             "vocab_size": 201088,
             "hidden_act": "silu",
+            "sliding_window": 4096,
         }
 
     @pytest.fixture