fix pylint

internlm/core/parallel/shard.py

@@ -11,7 +11,7 @@
 from internlm.core.context import global_context as gpc
 from internlm.core.parallel.comm.utils import _split
 from internlm.utils.logger import get_logger
-from internlm.utils.utils import ModelType, TensorParallelMode
+from internlm.utils.utils import TensorParallelMode
 
 logger = get_logger(__file__)
 

internlm/core/trainer_builder.py

@@ -20,6 +20,7 @@
 from internlm.model.losses.ce_loss import FlashGPTLMLoss
 from internlm.model.metrics import AccPerplex
 from internlm.monitor.monitor import send_alert_message
+from internlm.train import initialize_model
 from internlm.train.pipeline import (
     get_scheduler_hooks,
     initialize_llm_profile,
@@ -41,7 +42,6 @@
 from internlm.utils.parallel import get_parallel_log_file_name, is_using_isp
 from internlm.utils.simple_memory_profiler import SimpleMemoryProfiler
 from internlm.utils.writer import Writer
-from internlm.train import initialize_model
 
 # global llm logger
 logger = logging.getLogger(__file__)
@@ -95,7 +95,7 @@ def __init__(
         self.current_time = self._setup_time_and_logging()
         # load config_lines
         config_lines = self._read_config(kwargs["config"])
-        
+
         # set amp and parallel attribute for model
         model = initialize_model(model)
 
@@ -371,4 +371,4 @@ def _update_profilers(self, batch_count: int, prof):
         if self.memory_profiler is not None:
             self.memory_profiler.step()
         if batch_count % 2 == 0:
-            prof.step()
+            prof.step()

internlm/data/build_dataloader.py

@@ -30,7 +30,6 @@
     PackedDatasetWithPadForMultimodal,
     get_packed_dataset_without_short_length,
 )
-from internlm.data.utils import get_dataset_type_ids_map
 from internlm.utils.logger import get_logger
 from internlm.utils.utils import DataType
 
@@ -149,14 +148,14 @@ def build_train_loader_with_data_type():
     Returns: train_dl
     """
     data_cfg = gpc.config.data
-    
+
     if data_cfg.type == DataType.tokenized.name:
         train_ds, train_sampler, train_collate_fn = get_tokenized_train_loader_items(data_cfg)
     elif data_cfg.type == DataType.streaming.name:
         train_ds, train_sampler, train_collate_fn = get_hf_train_loader_items(data_cfg)
     else:
         raise ValueError(f"dataset type {data_cfg.type} is not supported")
-    
+
     # Create the training data loader
     train_dl = DataLoader(
         dataset=train_ds,

internlm/data/utils.py

@@ -6,8 +6,6 @@
 import torch
 
 from internlm.core.context import global_context as gpc
-from internlm.core.context.process_group_initializer import ParallelMode
-from internlm.utils.utils import ModelType
 
 
 def get_dataset_type_ids_map(path):
@@ -69,5 +67,5 @@ def packed_data_normalizer(data, label):
     data["indexes"] = data["indexes"][0]
     data["cu_seqlens"] = data["cu_seqlens"][0].squeeze(0)
     data["max_seqlen"] = (data["cu_seqlens"][1:] - data["cu_seqlens"][:-1]).max().item()
-    
+
     return data, label

internlm/model/registry.py

@@ -75,6 +75,7 @@ def has(self, module_name: str):
 
 model_initializer = Registry("model_initializer")
 
+
 def register_model_initializer() -> None:
     model_initializer.register_module(ModelType.INTERNLM.name, InternLM1)
     model_initializer.register_module(ModelType.INTERNLM2_PUBLIC.name, InternLM2)

internlm/model/utils.py

@@ -1,6 +1,5 @@
 from typing import Any, Dict, List
 
-from internlm.core.context import global_context as gpc
 from internlm.model.modules.mha import MHA
 
 

internlm/train/pipeline.py

@@ -3,7 +3,7 @@
 
 import math
 import time
-from typing import Callable, Iterable, List, Optional, Tuple, TypeVar, Union
+from typing import Iterable, List, Tuple, TypeVar, Union
 
 import torch
 from torch import nn
@@ -44,7 +44,6 @@
 from internlm.core.parallel.comm.zero import ParamAsyncBcastHandler
 from internlm.core.trainer import TrainState
 from internlm.data.utils import unpack_type_ids
-from internlm.model.builder import create_model
 from internlm.model.metrics import SchedulerMetricHook
 from internlm.model.modules.embedding import Embedding1D
 from internlm.model.modules.linear import (
@@ -61,7 +60,6 @@
 )
 from internlm.model.moe.moe import MoE
 from internlm.model.ops.norm import RMSNorm
-from internlm.model.registry import register_model_initializer
 from internlm.monitor import set_env_var
 from internlm.monitor.monitor import monitor_manager as mm
 from internlm.solver.optimizer import (