fix dataloader bug and add ci for static

paddlenlp/trainer/auto_trainer.py

@@ -92,9 +92,12 @@ def _get_meshes_for_loader(self):
         def _get_mesh(pp_idx=0):
             return self.global_mesh.get_mesh_with_dim("pp")[pp_idx]
 
+        # Note(lizhiyu): If the values returned by `DataLoader` have the format `[images, labels]`,
+        # error may occurs here.
         meshes = []
-        for pp_idx in range(self.args.pipeline_parallel_degree):
-            meshes.append(_get_mesh(pp_idx))
+        meshes.append(_get_mesh(0))
+        if self.args.pipeline_parallel_degree > 1:
+            meshes.append(_get_mesh(self.args.pipeline_parallel_degree - 1))
         return meshes
 
     def _wrap_for_dist_loader(self, train_dataloader):

scripts/distribute/ci_case_auto.sh

@@ -50,6 +50,8 @@ function llama_case_list_auto() {
     llama_dygraph_auto_bs8_fp32_DP2-MP2-PP2
     llama_dygraph_auto_bs8_fp16_DP2-MP2-PP2
 
+    llama_dygraph2static_auto_bs8_fp16_DP2-MP2-PP2
+
     llama_static_auto_recompute_bs8_fp32_DP1-MP1-PP1
     llama_static_auto_recompute_bs16_fp32_DP2-MP1-PP1
     llama_static_auto_recompute_bs16_fp32_DP2-MP2-PP1
@@ -1509,6 +1511,74 @@ function llama_dygraph_auto_bs8_fp16_DP2-MP2-PP2() {
     check_result $FUNCNAME ${loss_base} ${loss} ${ips_base} ${ips} ${mem_base} ${mem}
     echo "=========== $FUNCNAME run  end ==========="
 }
+
+function llama_dygraph2static_auto_bs8_fp16_DP2-MP2-PP2() {
+    echo "=========== $FUNCNAME run begin ==========="
+    export PYTHONPATH=$root_path/:$PYTHONPATH
+    export FLAGS_call_stack_level=3
+    export NVIDIA_TF32_OVERRIDE=0
+
+    task_name="llama_auto_bs8_fp16_dp2mp2pp2"
+    case_out_dir="output/$task_name"
+    case_log_dir="output/$task_name""_log"
+    rm -rf $case_out_dir
+    rm -rf $case_log_dir
+
+    python -u -m paddle.distributed.launch --gpus "0,1,2,3,4,5,6,7" --log_dir $case_log_dir run_pretrain_auto.py \
+        --model_type "llama" \
+        --model_name_or_path "facebook/llama-7b" \
+        --tokenizer_name_or_path "facebook/llama-7b" \
+        --input_dir "./data" \
+        --output_dir $case_out_dir \
+        --split 949,50,1 \
+        --max_seq_length 2048 \
+        --hidden_size 1024 \
+        --intermediate_size 3072 \
+        --num_hidden_layers 8 \
+        --num_attention_heads 32 \
+        --per_device_train_batch_size 1 \
+        --per_device_eval_batch_size 4 \
+        --gradient_accumulation_steps 4 \
+        --use_flash_attention 0 \
+        --use_fused_rms_norm 0 \
+        --fp16 1 \
+        --fp16_opt_level "O2" \
+        --amp_master_grad 1 \
+        --scale_loss 1024 \
+        --pipeline_parallel_degree 2 \
+        --tensor_parallel_degree 2 \
+        --sharding_parallel_degree 1 \
+        --learning_rate 0.0001 \
+        --min_learning_rate 0.00001 \
+        --max_steps 10 \
+        --save_steps 5000 \
+        --weight_decay 0.01 \
+        --warmup_ratio 0.01 \
+        --logging_steps 1 \
+        --dataloader_num_workers 1 \
+        --sharding "" \
+        --eval_steps 1000000 \
+        --disable_tqdm true \
+        --continue_training 0 \
+        --recompute 0 \
+        --do_train \
+        --do_eval \
+        --device "gpu" \
+        --data_impl "mmap" \
+        --enable_auto_parallel 1 \
+        --to_static 1 \
+        --max_grad_norm 1.0 \
+        >>${log_path}/$FUNCNAME 2>&1
+    loss=`cat $case_log_dir/workerlog.0 | grep 'global_step: 10' | awk -F 'loss: ' '{print $2}' | awk -F ',' '{print $1}'`
+    ips=-1
+    mem=-1
+    echo "result: loss=$loss ips=$ips mem=$mem"
+    loss_base=9.38341904
+    ips_base=-1
+    mem_base=-1
+    check_result $FUNCNAME ${loss_base} ${loss} ${ips_base} ${ips} ${mem_base} ${mem}
+    echo "=========== $FUNCNAME run  end ==========="
+}
 ############ case end ############
 
 function check_result() {