fix(recipe): declare DSv3 GB300 deterministic recipe environment inline

Flat perf recipes must assign one inline cfg.env_vars literal
(docs/recipe-usage.md, enforced by test_perf_recipe_environment.py).
Replace the pop/update on the parent mapping with the full literal,
grouped into determinism and other settings. The resulting environment
is unchanged.

Allow *_deterministic_config recipes to pin
NVTE_ALLOW_NONDETERMINISTIC_ALGO=0 in the environment invariant test.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Signed-off-by: Zhiyu Li <zhiyul@nvidia.com>

Author: ZhiyuLi-Nvidia

src/megatron/bridge/perf_recipes/deepseek/gb300/deepseek_v3.py

@@ -208,17 +208,39 @@ def deepseek_v3_pretrain_256gpu_gb300_fp8mx_deterministic_config() -> ConfigCont
     # TODO: revert back to NCCL EP once the NCCL EP issue is fixed.
     cfg.model.moe_flex_dispatcher_backend = "hybridep"
     cfg.model.moe_use_grouped_tensor = False
-    cfg.env_vars.pop("NCCL_EP_HT_EM_PULL_PUSH")
-    cfg.env_vars.update(
-        {
-            # HybridEP topology for the target system.
-            "NUM_OF_HYBRID_EP_RANKS_PER_NVLINK_DOMAIN": 32,
-            "NUM_OF_TOKENS_PER_CHUNK_COMBINE_API": 128,
-            "NVLINK_DOMAIN_SIZE": 72,
-            "USE_MNNVL": 1,
-        }
-    )
     apply_determinism_overrides(cfg)
+    # Keep process settings next to the recipe so users can see the exact benchmark environment.
+    cfg.env_vars = {
+        **COMMON_PERF_ENV_VARS,
+        # ---- Determinism (same values as apply_determinism_overrides) ----
+        "CUBLAS_WORKSPACE_CONFIG": ":4096:8",
+        "NCCL_ALGO": "Ring",
+        "NVTE_ALLOW_NONDETERMINISTIC_ALGO": "0",
+        "MAMBA_DETERMINISTIC": "1",
+        "CAUSAL_CONV1D_DETERMINISTIC": "1",
+        # ---- Others ----
+        # CUDA stream scheduling for this model and parallel layout.
+        "CUDA_DEVICE_MAX_CONNECTIONS": 32,
+        # CUDA graph and allocator behavior for this recipe.
+        "NCCL_GRAPH_REGISTER": 0,
+        "PYTORCH_CUDA_ALLOC_CONF": "expandable_segments:True,graph_capture_record_stream_reuse:True",
+        "TORCH_NCCL_AVOID_RECORD_STREAMS": 0,
+        # NCCL user-buffer and launch settings.
+        "NCCL_NVLS_ENABLE": 0,
+        # HybridEP topology for the target system.
+        "NUM_OF_HYBRID_EP_RANKS_PER_NVLINK_DOMAIN": 32,
+        "NUM_OF_TOKENS_PER_CHUNK_COMBINE_API": 128,
+        "NVLINK_DOMAIN_SIZE": 72,
+        "USE_MNNVL": 1,
+        # Transformer Engine overlap settings for this model.
+        "CUDNNFE_CLUSTER_OVERLAP_MARGIN": 8,
+        "NVTE_BWD_LAYERNORM_SM_MARGIN": 20,
+        "NVTE_CUTEDSL_FUSED_GROUPED_MLP": 1,
+        "NVTE_FWD_LAYERNORM_SM_MARGIN": 20,
+        # Use cuDNN LayerNorm for this measured baseline.
+        "NVTE_NORM_BWD_USE_CUDNN": 1,
+        "NVTE_NORM_FWD_USE_CUDNN": 1,
+    }
     return cfg
 
 

tests/unit_tests/recipes/test_perf_recipe_environment.py

@@ -217,7 +217,10 @@ def test_explicit_environment_invariants_across_all_flat_recipes():
             assert environment.keys().isdisjoint(_DEEPSEEK_NON_BASELINE_ENV_NAMES)
             assert environment["NVTE_FWD_LAYERNORM_SM_MARGIN"] == 20
             assert environment["NVTE_BWD_LAYERNORM_SM_MARGIN"] == 20
-            if path.parent.name == "gb300" and path.stem == "deepseek_v3":
+            if function_name.endswith("_deterministic_config"):
+                # Bit-exact recipes pin deterministic TE kernels.
+                assert environment["NVTE_ALLOW_NONDETERMINISTIC_ALGO"] == "0"
+            elif path.parent.name == "gb300" and path.stem == "deepseek_v3":
                 # The DeepSeek V3 GB300 recipes run the TE op-fuser grouped MLP, whose quantized scale
                 # gradient is accumulated with atomics; TE raises when bit-exact execution is requested,
                 # so these recipes must not pin NVTE_ALLOW_NONDETERMINISTIC_ALGO=0.