change 'xxx if xxx else None' to 'xxx or None'

colossalai/shardformer/modeling/command.py

@@ -3,13 +3,18 @@ import warnings
 from typing import List, Optional, Tuple, Union
 
 import torch
-import torch.nn.functional as F
 import torch.utils.checkpoint
 from torch import nn
 from torch.nn import CrossEntropyLoss
 from transformers.cache_utils import Cache, DynamicCache
 from transformers.modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast
-from transformers.models.cohere.modeling_cohere import CohereForCausalLM, CohereModel, StaticCache, apply_rotary_pos_emb, repeat_kv
+from transformers.models.cohere.modeling_cohere import (
+    CohereForCausalLM,
+    CohereModel,
+    StaticCache,
+    apply_rotary_pos_emb,
+    repeat_kv,
+)
 from transformers.utils import logging
 
 from colossalai.pipeline.stage_manager import PipelineStageManager
@@ -584,6 +589,7 @@ def get_command_flash_attention_model_forward(shard_config, sp_mode=None, sp_siz
 
     return forward
 
+
 def get_lm_forward_with_dist_cross_entropy(shard_config: ShardConfig):
     from transformers import CohereForCausalLM
 
@@ -683,4 +689,4 @@ def get_lm_forward_with_dist_cross_entropy(shard_config: ShardConfig):
             attentions=outputs.attentions,
         )
 
-    return forward
+    return forward

colossalai/shardformer/policies/bert.py

@@ -67,7 +67,7 @@ class BertPolicy(Policy):
         else:
             norm_cls = col_nn.LayerNorm
 
-        sp_mode = self.shard_config.sequence_parallelism_mode if self.shard_config.enable_sequence_parallelism else None
+        sp_mode = self.shard_config.sequence_parallelism_mode or None
         assert sp_mode != "all_to_all", "all_to_all sequence parallelism is not supported for Bert"
         if sp_mode == "ring":
             warnings.warn(

colossalai/shardformer/policies/bloom.py

@@ -50,7 +50,7 @@ class BloomPolicy(Policy):
         else:
             norm_cls = col_nn.LayerNorm
 
-        sp_mode = self.shard_config.sequence_parallelism_mode if self.shard_config.enable_sequence_parallelism else None
+        sp_mode = self.shard_config.sequence_parallelism_mode or None
         assert sp_mode != "all_to_all", "all_to_all sequence parallelism is not supported for BLOOM"
         if sp_mode == "ring":
             warnings.warn(

colossalai/shardformer/policies/chatglm2.py

@@ -57,7 +57,7 @@ class ChatGLMPolicy(Policy):
             else:
                 norm_cls = col_nn.LayerNorm
 
-        sp_mode = self.shard_config.sequence_parallelism_mode if self.shard_config.enable_sequence_parallelism else None
+        sp_mode = self.shard_config.sequence_parallelism_mode or None
         assert sp_mode != "all_to_all", "all_to_all sequence parallelism is not supported for ChatGLM2"
         if sp_mode == "ring":
             warnings.warn(

colossalai/shardformer/policies/command.py

@@ -73,11 +73,9 @@ class CommandPolicy(Policy):
             warnings.warn(
                 f"For Command, sequence parallelism is currently not compatible with pipeline parallelism, set to be False"
             )
-        sp_mode = self.shard_config.sequence_parallelism_mode if self.shard_config.enable_sequence_parallelism else None
-        sp_size = self.shard_config.sequence_parallel_size if self.shard_config.enable_sequence_parallelism else None
-        sp_group = (
-            self.shard_config.sequence_parallel_process_group if self.shard_config.enable_sequence_parallelism else None
-        )
+        sp_mode = self.shard_config.sequence_parallelism_mode or None
+        sp_size = self.shard_config.sequence_parallel_size or None
+        sp_group = self.shard_config.sequence_parallel_process_group or None
         sp_partial_derived = sp_mode in ["split_gather", "ring"]
 
         if sp_mode == "all_to_all":
@@ -112,7 +110,6 @@ class CommandPolicy(Policy):
                     target_key=CohereModel,
                 )
 
-
         if self.shard_config.enable_tensor_parallelism:
             assert (
                 self.model.config.num_attention_heads % self.shard_config.tensor_parallel_size == 0

colossalai/shardformer/policies/gpt2.py

@@ -65,7 +65,7 @@ class GPT2Policy(Policy):
         else:
             norm_cls = col_nn.LayerNorm
 
-        sp_mode = self.shard_config.sequence_parallelism_mode if self.shard_config.enable_sequence_parallelism else None
+        sp_mode = self.shard_config.sequence_parallelism_mode or None
         assert sp_mode != "all_to_all", "all_to_all sequence parallelism is not supported for GPT2"
         if sp_mode == "ring":
             warnings.warn(

colossalai/shardformer/policies/llama.py

@@ -73,11 +73,9 @@ class LlamaPolicy(Policy):
             warnings.warn(
                 f"For llama, sequence parallelism is currently not compatible with pipeline parallelism, set to be False"
             )
-        sp_mode = self.shard_config.sequence_parallelism_mode if self.shard_config.enable_sequence_parallelism else None
-        sp_size = self.shard_config.sequence_parallel_size if self.shard_config.enable_sequence_parallelism else None
-        sp_group = (
-            self.shard_config.sequence_parallel_process_group if self.shard_config.enable_sequence_parallelism else None
-        )
+        sp_mode = self.shard_config.sequence_parallelism_mode or None
+        sp_size = self.shard_config.sequence_parallel_size or None
+        sp_group = self.shard_config.sequence_parallel_process_group or None
         sp_partial_derived = sp_mode in ["split_gather", "ring"]
 
         if sp_mode == "all_to_all":