Fix the loss unassigned bug

fix: remove useless params

examples/pretrain_gpt_moe_demo.sh

@@ -0,0 +1,97 @@
+#!/bin/bash
+
+
+export CUDA_DEVICE_MAX_CONNECTIONS=1
+
+GPUS_PER_NODE=8
+# Change for multinode config
+MASTER_ADDR=localhost
+MASTER_PORT=6001
+NNODES=1
+NODE_RANK=0
+WORLD_SIZE=$(($GPUS_PER_NODE*$NNODES))
+
+CHECKPOINT_PATH=checkpoint
+VOCAB_FILE=/data/gpt2-vocab.json
+MERGE_FILE=/data/gpt2-merges.txt
+DATA_PATH=./train_data/my-gpt2_text_document
+
+
+DISTRIBUTED_ARGS="
+    --nproc_per_node $GPUS_PER_NODE \
+    --nnodes $NNODES \
+    --node_rank $NODE_RANK \
+    --master_addr $MASTER_ADDR \
+    --master_port $MASTER_PORT \
+"
+
+GPT_ARGS="
+    --tensor-model-parallel-size 2 \
+    --pipeline-model-parallel-size 2 \
+    --sequence-parallel \
+    --ffn-hidden-size 6784 \
+    --norm-epsilon 1e-5 \
+    --num-layers 18 \
+    --hidden-size 2560 \
+    --num-attention-heads 20 \
+    --seq-length 4096 \
+    --max-position-embeddings 4096 \
+    --bf16
+    --micro-batch-size 2 \
+    --global-batch-size 32 \
+    --lr 3.4e-4 \
+    --train-iters 10000 \
+    --lr-decay-iters 8000 \
+    --lr-decay-style cosine \
+    --min-lr 3.4e-5 \
+    --weight-decay 0.1 \
+    --lr-warmup-iters 2000 \
+    --clip-grad 1.0 \
+    --use-mcore-models \
+    --use-flash-attn \
+    --untie-embeddings-and-output-weights \
+    --use-rotary-position-embeddings \
+    --disable-bias-linear \
+    --normalization RMSNorm \
+    --no-position-embedding \
+    --no-masked-softmax-fusion \
+    --swiglu \
+    --attention-dropout 0 \
+    --hidden-dropout 0 \
+"
+
+DATA_ARGS="
+    --data-path $DATA_PATH \
+    --vocab-file $VOCAB_FILE \
+    --merge-file $MERGE_FILE \
+    --dataloader-type cyclic \
+    --split 949,50,1
+"
+
+#     --expert-model-parallel-size 2 \
+MOE_ARGS="
+    --num-experts 4 \
+    --moe-grouped-gemm \
+    --moe-router-topk 1 \
+    --moe-router-load-balancing-type aux_loss \
+    --moe-aux-loss-coeff 1e-2 \
+"
+
+
+OUTPUT_ARGS="
+    --log-interval 1 \
+    --save-interval 10000 \
+    --eval-interval 1000 \
+    --eval-iters 10 \
+    --tensorboard-dir ./tensorboard/test_mcore_moe \
+    --tensorboard-log-interval 1 \
+"
+
+torchrun $DISTRIBUTED_ARGS pretrain_gpt.py \
+    $GPT_ARGS \
+    $MOE_ARGS \
+    $DATA_ARGS \
+    $OUTPUT_ARGS \
+    --distributed-backend nccl \
+    --save $CHECKPOINT_PATH \
+    --load $CHECKPOINT_PATH

megatron/core/pipeline_parallel/schedules.py

@@ -213,7 +213,7 @@ def forward_step(
     if hasattr(config, 'num_moe_experts') and config.num_moe_experts is not None:
         # Calculate the loss scale based on the grad_scale_func if available, else default to 1.
         loss_scale = (
-            config.grad_scale_func(torch.tensor(1.0, device=loss.device))
+            config.grad_scale_func(torch.tensor(1.0, device=output_tensor.device))
             if config.grad_scale_func is not None
             else torch.tensor(1.0)
         )