minor fix for megatron compatibility (#1149)

Author: zhuzilin

slime/backends/megatron_utils/loss.py

@@ -771,7 +771,7 @@ def loss_function(
 
     return (
         loss,
-        num_tokens if args.calculate_per_token_loss else 1,
+        torch.tensor(num_tokens if args.calculate_per_token_loss else 1, device=logits.device),
         {
             "keys": list(log.keys()),
             "values": torch.tensor(

slime/backends/megatron_utils/model.py

@@ -84,9 +84,6 @@ def get_optimizer_param_scheduler(args: Namespace, optimizer: MegatronOptimizer)
 def setup_model_and_optimizer(
     args: Namespace,
     role: str = "actor",
-    no_wd_decay_cond: Callable[..., bool] | None = None,
-    scale_lr_cond: Callable[..., bool] | None = None,
-    lr_mult: float = 1.0,
 ) -> tuple[list[DDP], MegatronOptimizer, OptimizerParamScheduler]:
     """Build model(s), wrap with DDP, and construct optimizer and scheduler.
 
@@ -119,11 +116,8 @@ def setup_model_and_optimizer(
     config.timers = None
 
     optimizer = get_megatron_optimizer(
-        config,
-        model,
-        no_wd_decay_cond,
-        scale_lr_cond,
-        lr_mult,
+        config=config,
+        model_chunks=model,
         use_gloo_process_groups=args.enable_gloo_process_groups,
     )
     opt_param_scheduler = get_optimizer_param_scheduler(args, optimizer)

slime/backends/megatron_utils/model_provider.py

@@ -94,19 +94,19 @@ def model_provider(pre_process: bool = True, post_process: bool = True, vp_stage
                 # Define the decoder layer spec
                 if use_te:
                     transformer_layer_spec = get_gpt_layer_with_transformer_engine_spec(
-                        args.num_experts,
-                        args.moe_grouped_gemm,
-                        args.qk_layernorm,
-                        args.multi_latent_attention,
-                        args.moe_use_legacy_grouped_gemm,
+                        num_experts=args.num_experts,
+                        moe_grouped_gemm=args.moe_grouped_gemm,
+                        qk_layernorm=args.qk_layernorm,
+                        multi_latent_attention=args.multi_latent_attention,
+                        moe_use_legacy_grouped_gemm=args.moe_use_legacy_grouped_gemm,
                     )
                 else:
                     transformer_layer_spec = get_gpt_layer_local_spec(
-                        args.num_experts,
-                        args.moe_grouped_gemm,
-                        args.qk_layernorm,
-                        args.multi_latent_attention,
-                        args.moe_use_legacy_grouped_gemm,
+                        num_experts=args.num_experts,
+                        moe_grouped_gemm=args.moe_grouped_gemm,
+                        qk_layernorm=args.qk_layernorm,
+                        multi_latent_attention=args.multi_latent_attention,
+                        moe_use_legacy_grouped_gemm=args.moe_use_legacy_grouped_gemm,
                     )
 
         build_model_context = nullcontext

slime_plugins/models/glm4.py

@@ -3,11 +3,11 @@
 
 def get_glm_spec(args, config, vp_stage):
     transformer_layer_spec = get_gpt_layer_with_transformer_engine_spec(
-        args.num_experts,
-        args.moe_grouped_gemm,
-        args.qk_layernorm,
-        args.multi_latent_attention,
-        args.moe_use_legacy_grouped_gemm,
+        num_experts=args.num_experts,
+        moe_grouped_gemm=args.moe_grouped_gemm,
+        qk_layernorm=args.qk_layernorm,
+        multi_latent_attention=args.multi_latent_attention,
+        moe_use_legacy_grouped_gemm=args.moe_use_legacy_grouped_gemm,
         post_self_attn_layernorm=args.post_self_attn_layernorm,
         post_mlp_layernorm=args.post_mlp_layernorm,
     )