fix typo examples and docs (#3932)

docs/source/en/advanced_tutorials/parallelize_your_training_like_Megatron.md

@@ -141,16 +141,16 @@ for mn, module in model.named_modules():
 
         if 'mlp.c_fc' in mn:
             if 'weight' in pn or 'bias' in pn:
-                split_param_col_tp1d(param, pg)  # colmn slice
+                split_param_col_tp1d(param, pg)  # column slice
                 # keep the shape of the output from c_fc
                 param.compute_spec.set_output_replicate(False)
         elif 'mlp.c_proj' in mn:
             if 'weight' in pn:
                 split_param_row_tp1d(param, pg)  # row slice
         elif 'wte' in mn or 'wpe' in mn:
-            split_param_col_tp1d(param, pg)  # colmn slice
+            split_param_col_tp1d(param, pg)  # column slice
         elif 'c_attn' in mn or 'c_proj' in mn:
-            split_param_col_tp1d(param, pg)  # colmn slice
+            split_param_col_tp1d(param, pg)  # column slice
 ```
 
 The modified model is illustrated below.

docs/source/zh-Hans/advanced_tutorials/parallelize_your_training_like_Megatron.md

@@ -126,16 +126,16 @@ for mn, module in model.named_modules():
 
         if 'mlp.c_fc' in mn:
             if 'weight' in pn or 'bias' in pn:
-                split_param_col_tp1d(param, pg)  # colmn slice
+                split_param_col_tp1d(param, pg)  # column slice
                 # keep the shape of the output from c_fc
                 param.compute_spec.set_output_replicate(False)
         elif 'mlp.c_proj' in mn:
             if 'weight' in pn:
                 split_param_row_tp1d(param, pg)  # row slice
         elif 'wte' in mn or 'wpe' in mn:
-            split_param_col_tp1d(param, pg)  # colmn slice
+            split_param_col_tp1d(param, pg)  # column slice
         elif 'c_attn' in mn or 'c_proj' in mn:
-            split_param_col_tp1d(param, pg)  # colmn slice
+            split_param_col_tp1d(param, pg)  # column slice
 ```
 
 修改后的模型如下图所示。

examples/images/dreambooth/README.md

@@ -37,7 +37,7 @@ The `text` include the tag `Teyvat`, `Name`,`Element`, `Weapon`, `Region`, `Mode
 
 ## Training
 
-We provide the script `colossalai.sh` to run the training task with colossalai. Meanwhile, we also provided traditional training process of dreambooth, `dreambooth.sh`, for possible comparation. For instance, the script of training process for [stable-diffusion-v1-4] model can be modified into:
+We provide the script `colossalai.sh` to run the training task with colossalai. Meanwhile, we also provided traditional training process of dreambooth, `dreambooth.sh`, for possible comparison. For instance, the script of training process for [stable-diffusion-v1-4] model can be modified into:
 
 ```bash
 export MODEL_NAME="CompVis/stable-diffusion-v1-4"

examples/language/bert/README.md

 ## Overview
 
-This directory includes two parts: Using the Booster API fintune Huggingface Bert and AlBert models and benchmarking Bert and AlBert models with different Booster Plugin.
+This directory includes two parts: Using the Booster API finetune Huggingface Bert and AlBert models and benchmarking Bert and AlBert models with different Booster Plugin.
 
 ## Finetune
 ```

examples/language/gpt/gemini/train_gpt_demo.py

@@ -162,7 +162,7 @@ def tensor_parallelize(model: torch.nn.Module, pg: ProcessGroup):
             # shard it w.r.t tp pattern
             if 'mlp.c_fc' in mn:
                 if 'weight' in pn or 'bias' in pn:
-                    split_param_col_tp1d(param, pg)    # colmn slice
+                    split_param_col_tp1d(param, pg)    # column slice
                     # keep the shape of the output from c_fc
                     param.compute_spec.set_output_replicate(False)
                 else:
@@ -173,9 +173,9 @@ def tensor_parallelize(model: torch.nn.Module, pg: ProcessGroup):
                 else:
                     param.set_dist_spec(ReplicaSpec())
             elif 'wte' in mn or 'wpe' in mn:
-                split_param_col_tp1d(param, pg)    # colmn slice
+                split_param_col_tp1d(param, pg)    # column slice
             elif 'c_attn' in mn or 'c_proj' in mn:
-                split_param_col_tp1d(param, pg)    # colmn slice
+                split_param_col_tp1d(param, pg)    # column slice
             else:
                 param.set_dist_spec(ReplicaSpec())
             param.visited = True
@@ -237,7 +237,7 @@ def main():
         if args.tp_degree > 1:
             tensor_parallelize(model, tp_pg)
 
-        # asign running configurations
+        # assign running configurations
         if args.distplan == "CAI_ZeRO1":
             zero_stage = 1
         elif args.distplan == "CAI_ZeRO2":

examples/language/gpt/titans/model/embed.py

@@ -305,7 +305,7 @@ class _VocabParallelCrossEntropy(torch.autograd.Function):
     @staticmethod
     def backward(ctx, grad_output):
 
-        # Retreive tensors from the forward path.
+        # Retrieve tensors from the forward path.
         softmax, target_mask, masked_target_1d = ctx.saved_tensors
 
         # All the inputs have softmax as their gradient.

examples/language/opt/opt_train_demo.py

@@ -38,7 +38,7 @@ def train_epoch(epoch, model, optimizer, lr_scheduler, dataloader, booster, coor
         
         for batch in pbar:
 
-            # Foward
+            # Forward
             optimizer.zero_grad()
             batch = move_to_cuda(batch, torch.cuda.current_device())
             

examples/language/palm/train.py

@@ -140,15 +140,15 @@ def tensor_parallelize(model: torch.nn.Module, pg: ProcessGroup):
                 continue
             param.set_dist_spec(ReplicaSpec())
             if 'net.0' in mn:
-                split_param_col_tp1d(param, pg)    # colmn slice
+                split_param_col_tp1d(param, pg)    # column slice
             elif 'to_q' in mn:
-                split_param_col_tp1d(param, pg)    # colmn slice
+                split_param_col_tp1d(param, pg)    # column slice
             elif 'to_kv' in mn:
                 split_param_row_tp1d(param, pg)    # row slice
             elif 'to_out' in mn:
                 split_param_row_tp1d(param, pg)    # row slice
             elif '1.1' in mn:
-                split_param_col_tp1d(param, pg)    # colmn slice
+                split_param_col_tp1d(param, pg)    # column slice
             elif '1.2' in mn:
                 split_param_row_tp1d(param, pg)    # row slice
             else: