[doc] Fix typo under colossalai and doc(#3618)

* Fixed several spelling errors under colossalai

* Fix the spelling error in colossalai and docs directory

* Cautious Changed the spelling error under the example folder

* Update runtime_preparation_pass.py

revert autograft to autograd

* Update search_chunk.py

utile to until

* Update check_installation.py

change misteach to mismatch in line 91

* Update 1D_tensor_parallel.md

revert to perceptron

* Update 2D_tensor_parallel.md

revert to perceptron in line 73

* Update 2p5D_tensor_parallel.md

revert to perceptron in line 71

* Update 3D_tensor_parallel.md

revert to perceptron in line 80

* Update README.md

revert to resnet in line 42

* Update reorder_graph.py

revert to indice in line 7

* Update p2p.py

revert to megatron in line 94

* Update initialize.py

revert to torchrun in line 198

* Update routers.py

change to detailed in line 63

* Update routers.py

change to detailed in line 146

* Update README.md

revert  random number in line 402

examples/language/gpt/README.md

@@ -40,7 +40,7 @@ We provide two stable solutions.
 One utilizes the Gemini to implement hybrid parallel strategies of Gemini, DDP/ZeRO, and Tensor Parallelism for a huggingface GPT model.
 The other one use [Titans](https://github.com/hpcaitech/Titans), a distributed executed model zoo maintained by ColossalAI,to implement the hybrid parallel strategies of TP + ZeRO + PP.
 
-We recommend using Gemini to qucikly run your model in a distributed manner.
+We recommend using Gemini to quickly run your model in a distributed manner.
 It doesn't require significant changes to the model structures, therefore you can apply it on a new model easily.
 And use Titans as an advanced weapon to pursue a more extreme performance.
 Titans has included the some typical models, such as Vit and GPT.

examples/language/gpt/experiments/auto_offload/README.md

@@ -27,7 +27,7 @@ pip install transformers
 
 ## Dataset
 
-For simplicity, the input data is randonly generated here.
+For simplicity, the input data is randomly generated here.
 
 ## Training
 

examples/language/gpt/experiments/auto_parallel/README.md

@@ -34,7 +34,7 @@ conda install -c conda-forge coin-or-cbc
 
 ## Dataset
 
-For simplicity, the input data is randonly generated here.
+For simplicity, the input data is randomly generated here.
 
 ## Training
 

examples/language/gpt/experiments/pipeline_parallel/README.md

@@ -27,7 +27,7 @@ pip install transformers
 
 ## Dataset
 
-For simplicity, the input data is randonly generated here.
+For simplicity, the input data is randomly generated here.
 
 ## Training
 

examples/language/opt/train_gemini_opt.py

@@ -163,7 +163,7 @@ def main():
     else:
         init_dev = get_current_device()
 
-    # shard init prameters
+    # shard init parameters
     if args.shardinit:
         logger.info("Sharding initialization !", ranks=[0])
     else:
@@ -192,7 +192,7 @@ def main():
                                                    config=config,
                                                    local_files_only=False)
 
-    # enable graident checkpointing
+    # enable gradient checkpointing
     model.gradient_checkpointing_enable()
 
     numel = sum([p.numel() for p in model.parameters()])