Fix typos does't doesn't (#70682)

co63oc · web-flow · commit bec58b8bf2dd · 2025-01-24T15:26:44.000+08:00
diff --git a/paddle/cinn/hlir/pe/schedule.cc b/paddle/cinn/hlir/pe/schedule.cc
@@ -1368,7 +1368,7 @@ void CudaScheduleInjectiveWithVectorize(poly::Stage *stage,
   // the first bind position from tail
   int bind_idx = stage->n_out_dims() - 1;
   // it will add a new dim by split before vectorize, but the new dim will
-  // be eliminated when vectorizing, so the bind_idx does't need to increase
+  // be eliminated when vectorizing, so the bind_idx doesn't need to increase
   if (vector_width > 1) {
     stage->Split(bind_idx, vector_width);
   }
diff --git a/paddle/phi/infermeta/spmd_rules/embedding.cc b/paddle/phi/infermeta/spmd_rules/embedding.cc
@@ -239,7 +239,7 @@ SpmdInfo EmbeddingGradInferSpmd(const DistMetaTensor& x,
 
   if (sparse) {
     PADDLE_THROW(common::errors::InvalidArgument(
-        "EmbeddingGradInferSpmd does't support sparse currently."));
+        "EmbeddingGradInferSpmd doesn't support sparse currently."));
   }
 
   // Propagate sharding info using composite operators.
diff --git a/paddle/phi/kernels/gpu/dgc_kernel.cu b/paddle/phi/kernels/gpu/dgc_kernel.cu
@@ -117,7 +117,7 @@ void DGCKernel(const Context& dev_ctx,
   if (static_cast<int>(*current_step) < static_cast<int>(rampup_begin_step)) {
     VLOG(10) << "current_step:" << *current_step
              << " < rampup_begin_step:" << rampup_begin_step
-             << " so does't use dgc";
+             << " so doesn't use dgc";
     return;
   }
 
diff --git a/paddle/phi/kernels/impl/dgc_clip_by_norm_kernel_impl.h b/paddle/phi/kernels/impl/dgc_clip_by_norm_kernel_impl.h
@@ -38,7 +38,7 @@ void DGCClipByNormKernel(const Context& dev_ctx,
   if (static_cast<int>(*current_step) < static_cast<int>(rampup_begin_step)) {
     VLOG(10) << "current_step:" << *current_step
              << " < rampup_begin_step:" << rampup_begin_step
-             << " so does't use dgc_clip_by_norm";
+             << " so doesn't use dgc_clip_by_norm";
     return;
   }
 
diff --git a/python/paddle/distributed/auto_parallel/static/pir_pass.py b/python/paddle/distributed/auto_parallel/static/pir_pass.py
@@ -1042,7 +1042,7 @@ def set_process_mesh(vars, attrs, process_mesh):
     op_input_vars = op.operands_source()
     op_output_vars = op.results()
 
-    # NOTE(zhangwl):dist_skip_op donnot have op_mesh
+    # NOTE(zhangwl):dist_skip_op do not have op_mesh
     op_mesh = None
     if op.name() in dist_skip_op_list:
         input_var_process_mesh = None
diff --git a/python/paddle/jit/dy2static/program_translator.py b/python/paddle/jit/dy2static/program_translator.py
@@ -1883,7 +1883,7 @@ def _to_prim(
     start_idx=-1,
     backward_length=-1,
 ):
-    """Swith to static graph and call to_prim."""
+    """Switch to static graph and call to_prim."""
     # TODO(Aurelius84): Fix this cycle import problem
     from paddle.incubate.autograd import primapi
 
diff --git a/python/paddle/jit/sot/opcode_translator/executor/opcode_executor.py b/python/paddle/jit/sot/opcode_translator/executor/opcode_executor.py
@@ -2171,7 +2171,7 @@ def create_if_branch_fn(
             update_var_names, self.stack, cur_index, []
         )
 
-        # 5. create if sturcture and call true_fn and false_fn
+        # 5. create if structure and call true_fn and false_fn
         var_loader.load(result)
 
         # in 3.13, we have to copy the original 'TO_BOOL' to make the generated bytecode valid.
diff --git a/python/paddle/tensor/creation.py b/python/paddle/tensor/creation.py
@@ -731,7 +731,7 @@ def _handle_np_dtype(
             data.stop_gradient = stop_gradient
             return data
         elif isinstance(data, core.DenseTensor):
-            # should't expose it to users, just for internal use.
+            # shouldn't expose it to users, just for internal use.
             # convert core.DenseTensor to Tensor first
             # Currently, there is no copy when places are same
             data = paddle.Tensor(data, place=place)
diff --git a/python/paddle/vision/ops.py b/python/paddle/vision/ops.py
@@ -1888,9 +1888,9 @@ class ConvNormActivation(Sequential):
             in which case it will calculated as ``padding = (kernel_size - 1) // 2 * dilation``
         groups (int, optional): Number of blocked connections from input channels to output channels. Default: 1
         norm_layer (Callable[..., paddle.nn.Layer], optional): Norm layer that will be stacked on top of the convolution layer.
-            If ``None`` this layer wont be used. Default: ``paddle.nn.BatchNorm2D``
+            If ``None`` this layer won't be used. Default: ``paddle.nn.BatchNorm2D``
         activation_layer (Callable[..., paddle.nn.Layer], optional): Activation function which will be stacked on top of the normalization
-            layer (if not ``None``), otherwise on top of the conv layer. If ``None`` this layer wont be used. Default: ``paddle.nn.ReLU``
+            layer (if not ``None``), otherwise on top of the conv layer. If ``None`` this layer won't be used. Default: ``paddle.nn.ReLU``
         dilation (int): Spacing between kernel elements. Default: 1
         bias (bool|None, optional): Whether to use bias in the convolution layer. By default, biases are included if ``norm_layer is None``.
     """
diff --git a/test/dygraph_to_static/test_declarative.py b/test/dygraph_to_static/test_declarative.py
@@ -115,7 +115,7 @@ def test_instance_same_class(self):
         self.assertTrue(isinstance(net_2.forward, StaticFunction))
         self.assertNotEqual(net_1.forward, net_2.forward)
 
-        # convert layer into static progam of net_1
+        # convert layer into static program of net_1
         net_1.forward.concrete_program  # noqa: B018
         self.assertTrue(len(net_1.forward.program_cache) == 1)
         # check no conversion applid with net_2
@@ -174,7 +174,7 @@ def test_with_error(self):
 
         net = SimpleNet()
 
-        # 1. kwargs and input_spec should not be specificed in same time
+        # 1. kwargs and input_spec should not be specified in same time
         with self.assertRaises(ValueError):
             net(x, a=1, other_kwarg=2)
 
diff --git a/test/dygraph_to_static/test_loop.py b/test/dygraph_to_static/test_loop.py
@@ -41,7 +41,7 @@ def while_loop_dyfunc(x):
 def while_loop_dyfunc_without_tensor(x):
     a = 1
     # There are no tensors in the while condition, which means it's a plain while in python,
-    # so it wont't be transformed to `while_loop` op.
+    # so it won't be transformed to `while_loop` op.
     while not a > 4 and a > 0:
         x = x + 1
         a = a + 1
diff --git a/test/ipu/test_ipu_strategy_ipu.py b/test/ipu/test_ipu_strategy_ipu.py
@@ -88,7 +88,7 @@ def test_set_other_options(self):
 
         # The custom logger need 2 int as inputs
         logger = lambda progress, total: print(
-            f"compile progrss: {progress}/{total}"
+            f"compile progress: {progress}/{total}"
         )
         ipu_strategy.set_options({'compilation_progress_logger': logger})
 
diff --git a/test/ps/test_fl_ps.py b/test/ps/test_fl_ps.py
@@ -45,8 +45,8 @@ def test_launch_fl_ps(self):
     if not os.path.exists('./train_data'):
         os.system('sh download_data.sh')
         os.system('rm -rf ctr_data.tar.gz')
-        os.sysyem('rm -rf train_data_full')
-        os.sysyem('rm -rf test_data_full')
+        os.system('rm -rf train_data_full')
+        os.system('rm -rf test_data_full')
     unittest.main()
     if os.path.exists('./train_data'):
         os.system('rm -rf train_data')

Original file line number	Diff line number	Diff line change
`@@ -1368,7 +1368,7 @@ void CudaScheduleInjectiveWithVectorize(poly::Stage *stage,`
`1368`	`1368`	`// the first bind position from tail`
`1369`	`1369`	`int bind_idx = stage->n_out_dims() - 1;`
`1370`	`1370`	`// it will add a new dim by split before vectorize, but the new dim will`
`1371`		`- // be eliminated when vectorizing, so the bind_idx does't need to increase`
	`1371`	`+ // be eliminated when vectorizing, so the bind_idx doesn't need to increase`
`1372`	`1372`	`if (vector_width > 1) {`
`1373`	`1373`	`stage->Split(bind_idx, vector_width);`
`1374`	`1374`	`}`
Original file line number	Diff line number	Diff line change
`@@ -239,7 +239,7 @@ SpmdInfo EmbeddingGradInferSpmd(const DistMetaTensor& x,`
`239`	`239`
`240`	`240`	`if (sparse) {`
`241`	`241`	`PADDLE_THROW(common::errors::InvalidArgument(`
`242`		`- "EmbeddingGradInferSpmd does't support sparse currently."));`
	`242`	`+ "EmbeddingGradInferSpmd doesn't support sparse currently."));`
`243`	`243`	`}`
`244`	`244`
`245`	`245`	`// Propagate sharding info using composite operators.`
Original file line number	Diff line number	Diff line change
`@@ -117,7 +117,7 @@ void DGCKernel(const Context& dev_ctx,`
`117`	`117`	`if (static_cast<int>(*current_step) < static_cast<int>(rampup_begin_step)) {`
`118`	`118`	`VLOG(10) << "current_step:" << *current_step`
`119`	`119`	`<< " < rampup_begin_step:" << rampup_begin_step`
`120`		`- << " so does't use dgc";`
	`120`	`+ << " so doesn't use dgc";`
`121`	`121`	`return;`
`122`	`122`	`}`
`123`	`123`
Original file line number	Diff line number	Diff line change
`@@ -38,7 +38,7 @@ void DGCClipByNormKernel(const Context& dev_ctx,`
`38`	`38`	`if (static_cast<int>(*current_step) < static_cast<int>(rampup_begin_step)) {`
`39`	`39`	`VLOG(10) << "current_step:" << *current_step`
`40`	`40`	`<< " < rampup_begin_step:" << rampup_begin_step`
`41`		`- << " so does't use dgc_clip_by_norm";`
	`41`	`+ << " so doesn't use dgc_clip_by_norm";`
`42`	`42`	`return;`
`43`	`43`	`}`
`44`	`44`
Original file line number	Diff line number	Diff line change
`@@ -2171,7 +2171,7 @@ def create_if_branch_fn(`
`2171`	`2171`	`update_var_names, self.stack, cur_index, []`
`2172`	`2172`	`)`
`2173`	`2173`
`2174`		`- # 5. create if sturcture and call true_fn and false_fn`
	`2174`	`+ # 5. create if structure and call true_fn and false_fn`
`2175`	`2175`	`var_loader.load(result)`
`2176`	`2176`
`2177`	`2177`	`# in 3.13, we have to copy the original 'TO_BOOL' to make the generated bytecode valid.`