Fix spelling errors in DeepSpeed codebase
diff --git a/deepspeed/autotuning/autotuner.py b/deepspeed/autotuning/autotuner.py
index 76cecd5dc5dd..5ff873c582fe 100755
--- a/deepspeed/autotuning/autotuner.py
+++ b/deepspeed/autotuning/autotuner.py
@@ -101,7 +101,7 @@ def __init__(self, args, active_resources):
 
         self.records = {}
         self.optimal_cmd = None
-        self.optmal_ds_config = None
+        self.optimal_ds_config = None
 
         self.mlflow_parent_id = None
 
@@ -1093,7 +1093,7 @@ def write_optimal_config(self):
                 fd.write("\n")
                 fd.flush()
             self.optimal_cmd = cmd
-            self.optmal_ds_config = ds_config
+            self.optimal_ds_config = ds_config
             logger.info(
                 f"Wrote the optimal DeepSpeed configuration found by autotuning to {ds_config_path}, and the corresponding DeepSpeed command to {cmd_path}"
             )
diff --git a/deepspeed/checkpoint/deepspeed_checkpoint.py b/deepspeed/checkpoint/deepspeed_checkpoint.py
index ef36b0c5ef3f..77634222d292 100644
--- a/deepspeed/checkpoint/deepspeed_checkpoint.py
+++ b/deepspeed/checkpoint/deepspeed_checkpoint.py
@@ -98,11 +98,11 @@ def show_tp_embedding_map(self):
     def show_tp_final_norm_map(self):
         self._dump_mapping(self.tp_to_final_norm_map, 'tp_to_final_norm_layers')
 
-    def show_pp_tranformer_map(self):
-        self._dump_mapping(self.pp_to_transformer_map, 'pp_to_tranformer_layers')
+    def show_pp_transformer_map(self):
+        self._dump_mapping(self.pp_to_transformer_map, 'pp_to_transformer_layers')
 
     def show_transformer_file_map(self):
-        self._dump_mapping(self.transformer_file_map, 'rank_to_tranformer_files')
+        self._dump_mapping(self.transformer_file_map, 'rank_to_transformer_files')
 
     def _build_global_state(self):
         sd = torch.load(self.mp_rank_files[0], map_location=torch.device('cpu'))
diff --git a/deepspeed/comm/comm.py b/deepspeed/comm/comm.py
index 913dcf84d681..2ae6b581a272 100644
--- a/deepspeed/comm/comm.py
+++ b/deepspeed/comm/comm.py
@@ -5,7 +5,7 @@
 """
     DeepSpeed Communication Package: deepspeed.comm
     deepspeed.comm
-        -- import and use deepspeeed.ops.comm
+        -- import and use deepspeed.ops.comm
         -- use torch.distributed directly if both this package and torch.distributed use the same NCCL version
         -- use custom collectives
             -- can either use torch.dist or ds.ops.comm?
diff --git a/deepspeed/compression/compress.py b/deepspeed/compression/compress.py
index 9c4632f8aef3..a047b5127eb1 100644
--- a/deepspeed/compression/compress.py
+++ b/deepspeed/compression/compress.py
@@ -191,7 +191,7 @@ def student_initialization(student_model, teacher_model, deepspeed_config):
             The layer of teacher will be used for student's reinitializedion
             Example 1: [1,3,5,7,9], means we want to matches the 2nd/4th/6th/8th/10th layer of teacher to the first 5 layers of student
         student_layer (`list` or None)
-            The layer of student need to be re-intiialized
+            The layer of student need to be re-initialized
             Example 1: None, means we want to reinitialize all the layers
             Example 1: [0,1,2,3,4], means  we want to reinitialize the first 5 layers
         other_module_name (`list of string`)
diff --git a/deepspeed/compression/helper.py b/deepspeed/compression/helper.py
index fdca916e9f15..b06f085b8e1c 100644
--- a/deepspeed/compression/helper.py
+++ b/deepspeed/compression/helper.py
@@ -176,13 +176,13 @@ def is_module_compressible(module, mpu=None):
     return ret
 
 
-def compression_preparation(model, compression_techinique_list, mpu):
+def compression_preparation(model, compression_technique_list, mpu):
     """
     Prepare the compression techniques of a model.
     Args:
         model (`torch.nn.Module`)
             The model to prepare the compression techniques of.
-        compression_techinique_list (`list`)
+        compression_technique_list (`list`)
             The list of compression techniques to prepare the model to.
             list[]
     """
@@ -190,7 +190,7 @@ def compression_preparation(model, compression_techinique_list, mpu):
     for module_name, module in model.named_modules():
         if is_module_compressible(module, mpu):
             module_replacement(model, module_name, mpu=mpu)
-    for module_name_lists, _, compression_technique in compression_techinique_list:
+    for module_name_lists, _, compression_technique in compression_technique_list:
         for mnl in module_name_lists:
             for module_name in mnl:
                 module_replacement(model, module_name, compression_technique)
diff --git a/deepspeed/compression/utils.py b/deepspeed/compression/utils.py
index 3534f994cd78..481e833bdf8c 100644
--- a/deepspeed/compression/utils.py
+++ b/deepspeed/compression/utils.py
@@ -72,7 +72,7 @@ def forward(ctx, input, num_bits, min_value=None, max_value=None, num_groups=1):
                 The input which needs to be quantized
             num_bits (int, >=4)
                 Number of bits to use for quantization
-            min_value/max_vlue (torch.FloatTensor)
+            min_value/max_value (torch.FloatTensor)
                 Used for static activation quantization
             num_groups (int)
                 How many groups to partition the quantization into
@@ -114,7 +114,7 @@ def forward(ctx, input, num_bits, min_value=None, max_value=None, num_groups=1):
                 The input which needs to be quantized
             num_bits (int, >=4)
                 Number of bits to use for quantization
-            min_value/max_vlue (torch.FloatTensor)
+            min_value/max_value (torch.FloatTensor)
                 Used for static activation quantization
             num_groups (int)
                 How many groups to partition the quantization into
@@ -158,7 +158,7 @@ def forward(ctx, input, num_bits, min_value=None, max_value=None, num_groups=1):
                 The input which needs to be quantized
             num_bits (int)
                 Dummy variable
-            min_value/max_vlue (torch.FloatTensor)
+            min_value/max_value (torch.FloatTensor)
                 Used for static activation quantization; for now they are dummy variable
             num_groups (int)
                 How many groups to partition the quantization into
@@ -199,7 +199,7 @@ def forward(ctx, input, num_bits, min_value=None, max_value=None, num_groups=1):
                 The input which needs to be quantized
             num_bits (int)
                 Dummy variable
-            min_value/max_vlue (torch.FloatTensor)
+            min_value/max_value (torch.FloatTensor)
                 Used for static activation quantization; for now they are dummy variable
             num_groups (int)
                 How many groups to partition the quantization into
diff --git a/deepspeed/elasticity/config.py b/deepspeed/elasticity/config.py
index 9c574d3537c8..7c6bd42cdfd9 100644
--- a/deepspeed/elasticity/config.py
+++ b/deepspeed/elasticity/config.py
@@ -84,7 +84,7 @@ def __init__(self, param_dict):
             raise ElasticityConfigError("Elasticity min_gpus cannot be greater than max_gpus, "
                                         f"given min_gpus: {self.min_gpus}, max_gpus: {self.max_gpus}")
 
-        self.model_parallel_size = param_dict.get(MODEL_PARLLEL_SIZE, MODEL_PARLLEL_SIZE_DEFAULT)
+        self.model_parallel_size = param_dict.get(MODEL_PARALLEL_SIZE, MODEL_PARALLEL_SIZE_DEFAULT)
         if self.model_parallel_size < 1:
             raise ElasticityConfigError("Model-Parallel size cannot be less than 1, "
                                         f"given model-parallel size: {self.model_parallel_size}")
diff --git a/deepspeed/elasticity/constants.py b/deepspeed/elasticity/constants.py
index 85a38c749b2a..b3134c54b4d6 100644
--- a/deepspeed/elasticity/constants.py
+++ b/deepspeed/elasticity/constants.py
@@ -50,8 +50,8 @@
 NUM_GPUS_PER_NODE = 'num_gpus_per_node'
 NUM_GPUS_PER_NODE_DEFAULT = 1
 
-MODEL_PARLLEL_SIZE = "model_parallel_size"
-MODEL_PARLLEL_SIZE_DEFAULT = 1
+MODEL_PARALLEL_SIZE = "model_parallel_size"
+MODEL_PARALLEL_SIZE_DEFAULT = 1
 
 # Minimum running time (minutes) before the scheduler will scale us, 0 implies it's unknown
 MIN_TIME = "min_time"
diff --git a/deepspeed/runtime/config.py b/deepspeed/runtime/config.py
index dd9d77b6a158..bc5511226565 100755
--- a/deepspeed/runtime/config.py
+++ b/deepspeed/runtime/config.py
@@ -46,8 +46,8 @@
     ELASTICITY,
     IGNORE_NON_ELASTIC_BATCH_INFO,
     IGNORE_NON_ELASTIC_BATCH_INFO_DEFAULT,
-    MODEL_PARLLEL_SIZE,
-    MODEL_PARLLEL_SIZE_DEFAULT,
+    MODEL_PARALLEL_SIZE,
+    MODEL_PARALLEL_SIZE_DEFAULT,
     NUM_GPUS_PER_NODE,
     NUM_GPUS_PER_NODE_DEFAULT,
 )
@@ -712,7 +712,7 @@ def __init__(self, config: Union[str, dict], mpu=None):
             # Ensure the resource scheduler saw the same elastic config we are using at runtime
             ensure_immutable_elastic_config(runtime_elastic_config_dict=elastic_dict)
 
-            self.elastic_model_parallel_size = elastic_dict.get(MODEL_PARLLEL_SIZE, MODEL_PARLLEL_SIZE_DEFAULT)
+            self.elastic_model_parallel_size = elastic_dict.get(MODEL_PARALLEL_SIZE, MODEL_PARALLEL_SIZE_DEFAULT)
             if self.elastic_model_parallel_size < 1:
                 raise ElasticityConfigError("Model-Parallel size cannot be less than 1, "
                                             f"given model-parallel size: {self.elastic_model_parallel_size}")

fix spelling error with deepspeed/
detail info: 
        modified:   deepspeed/autotuning/autotuner.py
        modified:   deepspeed/checkpoint/deepspeed_checkpoint.py
        modified:   deepspeed/comm/comm.py
        modified:   deepspeed/compression/compress.py
        modified:   deepspeed/compression/helper.py
        modified:   deepspeed/compression/utils.py
        modified:   deepspeed/elasticity/config.py
        modified:   deepspeed/elasticity/constants.py
        modified:   deepspeed/runtime/config.py

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