Fix defition definition (#60679)

co63oc · web-flow · commit 0ac9c29c2217 · 2024-01-11T14:32:52.000+08:00
diff --git a/python/paddle/device/cuda/cuda_graphed_layer.py b/python/paddle/device/cuda/cuda_graphed_layer.py
@@ -66,9 +66,9 @@ def forward(ctx, context, *args):
             ctx.save_for_backward(context, context.args_static, y)
             return y.detach()
         else:
-            for x_staic, x in zip(context.args_static, args):
-                if isinstance(x_staic, paddle.Tensor):
-                    x_staic.copy_(x, True)
+            for x_static, x in zip(context.args_static, args):
+                if isinstance(x_static, paddle.Tensor):
+                    x_static.copy_(x, True)
 
             context.forward_graph.replay()
             y = context.y_static
diff --git a/python/paddle/distributed/auto_parallel/interface.py b/python/paddle/distributed/auto_parallel/interface.py
@@ -237,9 +237,9 @@ def __call__(self, *args, **kwargs):
 
 def exclude_ops_in_recompute(run_function):
     """
-    Exclude some operators in recompute segements.
+    Exclude some operators in recompute segments.
         Args:
-        run_function (callabe): The callabe function to be excluded.
+        run_function (callable): The callable function to be excluded.
 
     Returns:
         ExcludeOperator: The callable object.
diff --git a/python/paddle/distributed/auto_parallel/random.py b/python/paddle/distributed/auto_parallel/random.py
@@ -29,7 +29,7 @@
 _basic_seed = 42
 _basic_name = ""
 
-# use Prime number as offset to avoid confict
+# use Prime number as offset to avoid conflict
 _mesh_offset = 173
 _dim_offsets = [11, 23, 37, 73]
 
@@ -57,7 +57,7 @@ def parallel_manual_seed(seed, name=""):
 
     This function should be called only once before auto parallel compiles the computation graph (e.g. auto_parallel.engine.prepare() or fit()).
 
-    This seed only affects how randomness-relative **operators** (dropout, fuse op with dropout inside, etc) are execute amonge mesh, and would NOT affect other processe like Parameter initialization.
+    This seed only affects how randomness-relative **operators** (dropout, fuse op with dropout inside, etc) are execute amonge mesh, and would NOT affect other process like Parameter initialization.
 
     Examples:
         # seed relative to training step
@@ -85,7 +85,7 @@ def determinate_rng(
     ), "Cannot provide dims mapping and placements at same time."
     # TODO(JZ-LIANG) Support Mesh with any high rank
     # use a string to unique integer hashing algorithm for seed computation.
-    # instead of using offsets to coodinate seed across devices.
+    # instead of using offsets to coordinate seed across devices.
     if len(process_mesh.shape) > 4:
         raise NotImplementedError(
             "Auto Parallel Random Control for Mesh's rank > 4 is NOT supported! Got {}".format(
@@ -131,7 +131,7 @@ def determinate_rng(
     else:
         assert (
             seed_ not in _rng_name_to_seed.values()
-        ), "Seed Confilt! current seed: {}, current sharding expr: {}, generated seed: {}".format(
+        ), "Seed Conflict! current seed: {}, current sharding expr: {}, generated seed: {}".format(
             seed_, sharding_expr, _rng_name_to_seed
         )
         _rng_name_to_seed[sharding_expr] = seed_
diff --git a/python/paddle/distributed/auto_parallel/static/cost/estimate_cost.py b/python/paddle/distributed/auto_parallel/static/cost/estimate_cost.py
@@ -24,7 +24,7 @@
 
 
 class CostEstimator:
-    _sepical_op_type = ["fused_attention", "fused_feedforward"]
+    _special_op_type = ["fused_attention", "fused_feedforward"]
 
     def __init__(
         self, program, cluster, mode="modeling", rank=None, loop_count=10
@@ -207,7 +207,7 @@ def _estimate_core(self, dist_context, resharder, block):
 
                 if dist_op_cost is None:
                     assert (
-                        dist_op.serial_op.type in CostEstimator._sepical_op_type
+                        dist_op.serial_op.type in CostEstimator._special_op_type
                     )
                     continue
                 for item in dist_op_cost:
diff --git a/python/paddle/distributed/auto_parallel/static/cost/op_runtime_cost.py b/python/paddle/distributed/auto_parallel/static/cost/op_runtime_cost.py
@@ -88,7 +88,7 @@ def _filter_vars_with_zero_in_degree_and_ignore_feed_fetch_vars():
         for op in cloned_main_block.ops:
             op: Operator
             if is_comm_op(op):
-                # ignore communication op from graph, bacause sometimes we want to profile a sub-graph
+                # ignore communication op from graph, because sometimes we want to profile a sub-graph
                 # and these dangling operators will not work (no graph to communicate to/from)
                 continue
             input_var_names, output_var_names = _collect_op_input_var_names(
@@ -262,7 +262,7 @@ def measure_program_real_op_cost(
     >>> from paddle.distributed.auto_parallel.static.utils import measure_program_real_op_cost
     >>> place: str = paddle.device.get_device() # here we assume place = "cuda:x"
     >>> place = paddle.CUDAPlace(int(place.split(':')[1]))
-    >>> # here "program" is an inner object that has alredy been built before
+    >>> # here "program" is an inner object that has already been built before
     >>> measure_program_real_op_cost(program, verbose_level=1)
     '''
 
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_assign.py b/python/paddle/distributed/auto_parallel/static/operators/dist_assign.py
@@ -22,7 +22,7 @@ def __init__(self, op_type):
         super().__init__(op_type)
 
 
-# TODO reomve assign dist op
+# TODO remove assign dist op
 # register_distributed_operator_impl_container(DistributedAssign("assign"))
 
 
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_concat.py b/python/paddle/distributed/auto_parallel/static/operators/dist_concat.py
@@ -43,16 +43,16 @@ def update_dims_mapping(dist_op):
         input_specs = []
         for name in input_arg_names:
             input_specs.append(get_dist_tensor_spec(dist_op, name))
-        output_sepc = get_dist_tensor_spec(dist_op, output_arg_names[0], False)
+        output_spec = get_dist_tensor_spec(dist_op, output_arg_names[0], False)
 
         # step2: infer spmd
         rule = get_phi_spmd_rule("concat")
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         fw_results = rule.infer_forward(input_specs, axis)
-        bw_results = rule.infer_backward(input_specs, output_sepc, axis)
+        bw_results = rule.infer_backward(input_specs, output_spec, axis)
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op,
             input_arg_names,
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_cross_entropy.py b/python/paddle/distributed/auto_parallel/static/operators/dist_cross_entropy.py
@@ -64,7 +64,7 @@ def update_dims_mapping(dist_op):
 
         # step2: infer spmd
         rule = get_phi_spmd_rule("softmax_with_cross_entropy")
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         fw_results = rule.infer_forward(
             logits_spec,
             label_spec,
@@ -87,7 +87,7 @@ def update_dims_mapping(dist_op):
         )
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op,
             [logits_name, label_name],
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_default.py b/python/paddle/distributed/auto_parallel/static/operators/dist_default.py
@@ -141,12 +141,12 @@ def update_dims_mapping(dist_op):
 
         # step2: infer spmd
         rule = get_phi_spmd_rule("default_")
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         fw_results = rule.infer_forward(input_specs, output_specs)
         bw_results = rule.infer_backward(input_specs, output_specs)
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op, input_arg_names, output_arg_names, fw_results, bw_results
         )
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_dropout.py b/python/paddle/distributed/auto_parallel/static/operators/dist_dropout.py
@@ -58,12 +58,12 @@ def update_dims_mapping(dist_op):
 
         # step2: infer spmd
         rule = get_phi_spmd_rule("dropout")
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         fw_results = rule.infer_forward(x_spec)
         bw_results = rule.infer_backward(x_spec, output_spec)
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op, [x_name], [out_name], fw_results, bw_results
         )
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_eltwise.py b/python/paddle/distributed/auto_parallel/static/operators/dist_eltwise.py
@@ -77,7 +77,7 @@ def update_dims_mapping(dist_op):
         bw_results = rule.infer_backward(*input_specs, output_spec)
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op, input_arg_names, [output_arg_name], fw_results, bw_results
         )
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_embedding.py b/python/paddle/distributed/auto_parallel/static/operators/dist_embedding.py
@@ -81,14 +81,14 @@ def update_dims_mapping(dist_op):
 
         # step2: infer spmd
         rule = get_phi_spmd_rule("embedding")
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         fw_results = rule.infer_forward(x_spec, w_spec, padding_idx, is_sparse)
         bw_results = rule.infer_backward(
             x_spec, w_spec, output_spec, padding_idx, is_sparse
         )
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op, [x_name, w_name], [out_name], fw_results, bw_results
         )
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_fused_rope.py b/python/paddle/distributed/auto_parallel/static/operators/dist_fused_rope.py
@@ -103,7 +103,7 @@ def update_dims_mapping(dist_op):
 
         # step2: infer spmd
         rule = get_phi_spmd_rule("fused_rotary_position_embedding")
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         fw_results = rule.infer_forward(
             q_spec,
             k_spec,
@@ -153,7 +153,7 @@ def update_dims_mapping(dist_op):
             )
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op,
             input_arg_names=[
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_layer_norm.py b/python/paddle/distributed/auto_parallel/static/operators/dist_layer_norm.py
@@ -57,7 +57,7 @@ def update_dims_mapping(dist_op):
 
         # step2: infer spmd
         rule = get_phi_spmd_rule("layer_norm")
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         fw_results = rule.infer_forward(
             x_spec, scale_spec, bias_spec, 1.0, begin_norm_axis
         )
@@ -73,7 +73,7 @@ def update_dims_mapping(dist_op):
         )
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op,
             [x_name, scale_name, bias_name],
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_matmul.py b/python/paddle/distributed/auto_parallel/static/operators/dist_matmul.py
@@ -522,12 +522,12 @@ def update_dims_mapping_matmul(dist_op):
 
     # step2: infer spmd
     rule = get_phi_spmd_rule("matmul")
-    # tensor order following order in PHI defition
+    # tensor order following order in PHI definition
     fw_results = rule.infer_forward(x_spec, y_spec, trans_x, trans_y)
     bw_results = rule.infer_backward(x_spec, y_spec, out_spec, trans_x, trans_y)
 
     # step3: update dist_attr
-    # tensor order following order in PHI defition
+    # tensor order following order in PHI definition
     input_arg_names = [x_name, y_name]
     output_arg_names = [out_name]
     changed = update_op_dims_mapping(
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_reduce_sum_p.py b/python/paddle/distributed/auto_parallel/static/operators/dist_reduce_sum_p.py
@@ -73,7 +73,7 @@ def update_dims_mapping(dist_op):
         )
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op, [input_arg_name], [output_arg_name], fw_results, bw_results
         )
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_reshape.py b/python/paddle/distributed/auto_parallel/static/operators/dist_reshape.py
@@ -62,12 +62,12 @@ def update_dims_mapping(dist_op):
 
         # step2: infer spmd
         rule = get_phi_spmd_rule("reshape")
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         fw_results = rule.infer_forward(x_spec, shape)
         bw_results = rule.infer_backward(x_spec, output_spec, shape)
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op, [x_name], [out_name], fw_results, bw_results
         )
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_split.py b/python/paddle/distributed/auto_parallel/static/operators/dist_split.py
@@ -73,12 +73,12 @@ def update_dims_mapping(dist_op):
 
         # step2: infer spmd
         rule = get_phi_spmd_rule(rule_type)
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         fw_results = rule.infer_forward(x_spec, first_attr, axis)
         bw_results = rule.infer_backward(x_spec, output_specs, first_attr, axis)
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op, [x_name], output_arg_names, fw_results, bw_results
         )
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_transpose.py b/python/paddle/distributed/auto_parallel/static/operators/dist_transpose.py
@@ -61,12 +61,12 @@ def update_dims_mapping(dist_op):
 
         # step2: infer spmd
         rule = get_phi_spmd_rule("transpose")
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         fw_results = rule.infer_forward(x_spec, axes)
         bw_results = rule.infer_backward(x_spec, output_spec, axes)
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op, [x_name], [out_name], fw_results, bw_results
         )
diff --git a/python/paddle/distributed/auto_parallel/static/operators/dist_unsqueeze2.py b/python/paddle/distributed/auto_parallel/static/operators/dist_unsqueeze2.py
@@ -45,12 +45,12 @@ def update_dims_mapping(dist_op):
 
         # step2: infer spmd
         rule = get_phi_spmd_rule("unsqueeze2")
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         fw_results = rule.infer_forward(input_spec, axes)
         bw_results = rule.infer_backward(input_spec, output_spec, axes)
 
         # step3: update dist_attr
-        # tensor order following order in PHI defition
+        # tensor order following order in PHI definition
         changed = update_op_dims_mapping(
             dist_op,
             [x_name],
