Fix

Author: co63oc

python/paddle/decomposition/decomp.py

@@ -228,11 +228,11 @@ def decompose(
 
     if not isinstance(blacklist, (set, frozenset)):
         raise TypeError(
-            f'Expected type of blacklisst is set|frozenset, but got {type(blacklist)}.'
+            f'Expected type of blacklist is set|frozenset, but got {type(blacklist)}.'
         )
     if not isinstance(whitelist, (set, frozenset)):
         raise TypeError(
-            f'Expected type of whiltelist is set|frozenset, but got {type(whitelist)}.'
+            f'Expected type of whitelist is set|frozenset, but got {type(whitelist)}.'
         )
 
     blacklist = core.prim_config["forward_blacklist"] | blacklist
@@ -288,7 +288,7 @@ def decompose(
 
 def _decompose_subgraph(block, orig_vars, dst_vars, op_filter):
     """
-    The operators in block wich satisfy the filter conditon will be decomposed into primitives.
+    The operators in block which satisfy the filter condition will be decomposed into primitives.
 
     Args:
         block (Block|Sequence[Block]): The blocks of program to be processed.
@@ -689,7 +689,7 @@ def _decomp_bwd_with_vjp(
             grad_var_to_var, orig_grads=bwd_op.results(), new_grads=res
         )
 
-        # step5: replace original backward op with new primiive ops
+        # step5: replace original backward op with new primitive ops
         insert_idx = bwd_op_idx
         for i in range(before_num_ops, after_num_ops):
             block.move_op(block.ops[i], insert_idx)
@@ -759,7 +759,7 @@ def _decomp_bwd_without_vjp(
         grad_var_to_var, orig_grads=grad_inputs, new_grads=res
     )
 
-    # step5: replace original backward op with new primiive ops
+    # step5: replace original backward op with new primitive ops
     insert_idx = bwd_op_idx
     for i in range(before_num_ops, after_num_ops):
         block.move_op(block.ops[i], insert_idx)
@@ -957,7 +957,7 @@ def _decomp_fwd_program(pir_program, pir_grad_var_to_var):
     with paddle.pir.core.program_guard(pir_program):
         ops = pir_program.global_block().ops
         bwd_ops = _get_all_bwd_ops(pir_program)
-        # ops including compile-time infermeta, causing mismatched input shape and output shape, which is unsupported when decompoing.
+        # ops including compile-time infermeta, causing mismatched input shape and output shape, which is unsupported when decomposing.
         black_fwd_ops = ["pd_op.stack", "pd_op.squeeze"]
         undecomposed_fwd_ops = []
 

python/paddle/distributed/auto_parallel/static/tuner/optimization_tuner.py

@@ -88,20 +88,20 @@ def get_metric(results):
     assert isinstance(
         results, dict
     ), f"results should be type of dictionary, but got {type(results)}."
-    if 'Throughtput' in results and isinstance(results['Throughtput'], float):
-        return float(results['Throughtput'])
+    if 'Throughput' in results and isinstance(results['Throughput'], float):
+        return float(results['Throughput'])
     else:
         return -1.0
 
 
 def parse_results(results):
-    if results['Throughtput'] > 0:
-        return "Throughtput: {} step / s.".format(results['Throughtput'])
+    if results['Throughput'] > 0:
+        return "Throughput: {} step / s.".format(results['Throughput'])
     et = results.get("ErrorType", None)
     if et == "ResourceExhaustedError":
         return "Fail with OOM"
     else:
-        return "Fail with UNKWON ERROR"
+        return "Fail with UNKNOWN ERROR"
 
 
 # TODO only dependent on dist context
@@ -241,7 +241,7 @@ def rank(self):
     def device_id(self):
         return paddle.distributed.ParallelEnv().device_id
 
-    # TODO Generate compelet program with all parts like forward, backward, update
+    # TODO Generate complete program with all parts like forward, backward, update
     # as well as parallelism transformation.
     def _build_programs_without_optimization(self):
         serial_main_program = self._baseline_dist_context.serial_main_program
@@ -512,7 +512,7 @@ def _profile_trial(self, trial):
                 results = json.load(fp)
             return results
         except FileNotFoundError:
-            Error_results = {"Throughtput": -1, "ErrorType": 'FatalError'}
+            Error_results = {"Throughput": -1, "ErrorType": 'FatalError'}
             return Error_results
 
     def _evaluate_trial(self, trial):
@@ -539,9 +539,9 @@ def _evaluate_trial(self, trial):
     def _update(self, i, trial, results):
         self._finished_trials.append(trial)
 
-        cur_mertic = get_metric(results)
-        if self._best_metric is None or cur_mertic > self._best_metric:
-            self._best_metric = cur_mertic
+        cur_metric = get_metric(results)
+        if self._best_metric is None or cur_metric > self._best_metric:
+            self._best_metric = cur_metric
             self._best_iter = i
 
     def _get_trial_dir(self, trial):

python/paddle/distributed/auto_parallel/static/tuner/profiler.py

@@ -258,7 +258,7 @@ def profiler(args):
         )
 
         result_dict = {
-            "Throughtput": avg_tput,
+            "Throughput": avg_tput,
             "ErrorType": None,
         }
 
@@ -274,7 +274,7 @@ def profiler(args):
     except Exception as e:
         error_type = get_cpp_error_type(e)
         result_dict = {
-            "Throughtput": -1,
+            "Throughput": -1,
             "ErrorType": error_type,
         }
         if not os.path.isfile(result_path):