Fix some typos (basline_arr, acturally, etc.) (#61787)

co63oc · web-flow · commit 94d6fe39bbf4 · 2024-02-20T12:05:01.000+08:00
diff --git a/test/ir/inference/test_trt_convert_multiclass_nms.py b/test/ir/inference/test_trt_convert_multiclass_nms.py
@@ -188,7 +188,7 @@ def assert_tensors_near(
         # the order of tensorrt outputs are not consistent with paddle
         for key, arr in tensor.items():
             if key == "nms_output_boxes":
-                basline_arr = np.array(
+                baseline_arr = np.array(
                     sorted(
                         baseline[key].reshape((-1, 6)),
                         key=lambda i: [i[0], i[1]],
@@ -198,19 +198,19 @@ def assert_tensors_near(
                     sorted(arr.reshape((-1, 6)), key=lambda i: [i[0], i[1]])
                 )
             else:
-                basline_arr = np.array(baseline[key].reshape((-1, 1)))
+                baseline_arr = np.array(baseline[key].reshape((-1, 1)))
                 arr = np.array(arr.reshape((-1, 1)))
 
             self.assertTrue(
-                basline_arr.shape == arr.shape,
+                baseline_arr.shape == arr.shape,
                 "The output shapes are not equal, the baseline shape is "
-                + str(basline_arr.shape)
+                + str(baseline_arr.shape)
                 + ', but got '
                 + str(arr.shape),
             )
-            diff = abs(basline_arr - arr)
+            diff = abs(baseline_arr - arr)
             np.testing.assert_allclose(
-                basline_arr,
+                baseline_arr,
                 arr,
                 rtol=rtol,
                 atol=atol,
diff --git a/test/ir/inference/test_trt_convert_multiclass_nms3.py b/test/ir/inference/test_trt_convert_multiclass_nms3.py
@@ -197,7 +197,7 @@ def assert_tensors_near(
             if key == "nms_output_index":
                 continue
             if key == "nms_output_boxes":
-                basline_arr = np.array(
+                baseline_arr = np.array(
                     sorted(
                         baseline[key].reshape((-1, 6)),
                         key=lambda i: [i[0], i[1]],
@@ -207,19 +207,19 @@ def assert_tensors_near(
                     sorted(arr.reshape((-1, 6)), key=lambda i: [i[0], i[1]])
                 )
             else:
-                basline_arr = np.array(baseline[key].reshape((-1, 1)))
+                baseline_arr = np.array(baseline[key].reshape((-1, 1)))
                 arr = np.array(arr.reshape((-1, 1)))
 
             self.assertTrue(
-                basline_arr.shape == arr.shape,
+                baseline_arr.shape == arr.shape,
                 "The output shapes are not equal, the baseline shape is "
-                + str(basline_arr.shape)
+                + str(baseline_arr.shape)
                 + ', but got '
                 + str(arr.shape),
             )
-            diff = abs(basline_arr - arr)
+            diff = abs(baseline_arr - arr)
             np.testing.assert_allclose(
-                basline_arr,
+                baseline_arr,
                 arr,
                 rtol=rtol,
                 atol=atol,
diff --git a/test/legacy_test/test_device_guard.py b/test/legacy_test/test_device_guard.py
@@ -32,7 +32,7 @@ def execute(main_program, startup_program):
     exe.run(main_program)
 
 
-def get_vaild_warning_num(warning, w):
+def get_valid_warning_num(warning, w):
     num = 0
     for i in range(len(w)):
         if warning in str(w[i].message):
@@ -162,7 +162,7 @@ def test_without_kernel_op(self):
                         paddle.assign(paddle.less_than(x=i, y=loop_len), cond)
         if not in_pir_mode():
             warning = "The Op(while) is not support to set device."
-            warning_num = get_vaild_warning_num(warning, w)
+            warning_num = get_valid_warning_num(warning, w)
             assert warning_num == 1
 
         all_ops = main_program.global_block().ops
diff --git a/test/quantization/README.md b/test/quantization/README.md
@@ -51,7 +51,7 @@ Notes:
    ```... → input1 → conv2d → output1 → batch_norm → output2 → relu → output3 → ...```
    and we want to quantize the `conv2d` op, then after applying FP32 optimizations the sequence will become
    ```... → input1 → conv2d → output3 → ...```
-   and the quantization scales have to be collected for the `input1` and `outpu3` tensors in the Quant model.
+   and the quantization scales have to be collected for the `input1` and `output3` tensors in the Quant model.
 2. Quantization of the following operators is supported: `conv2d`, `depthwise_conv2d`, `mul`, `fc`, `matmul`, `pool2d`, `reshape2`, `transpose2`, `concat`.
 3. The longest sequence of consecutive quantizable operators in the model, the biggest performance boost can be achieved through quantization:
    ```... → conv2d → conv2d → pool2d → conv2d → conv2d → ...```
diff --git a/test/quantization/test_imperative_out_scale.py b/test/quantization/test_imperative_out_scale.py
@@ -40,7 +40,7 @@
     set_flags({"FLAGS_cudnn_deterministic": True})
 
 
-def get_vaild_warning_num(warning, w):
+def get_valid_warning_num(warning, w):
     num = 0
     for i in range(len(w)):
         if warning in str(w[i].message):
@@ -119,7 +119,7 @@ def forward(self, inputs):
         return x
 
 
-class TestImperativeOutSclae(unittest.TestCase):
+class TestImperativeOutScale(unittest.TestCase):
     def setUp(self):
         self.root_path = tempfile.TemporaryDirectory()
         self.param_save_path = os.path.join(
diff --git a/test/quantization/test_post_training_quantization_lstm_model.py b/test/quantization/test_post_training_quantization_lstm_model.py
@@ -76,9 +76,9 @@ def reader():
                     if plen is None or len(plen) != 4:
                         break
 
-                    alllen = struct.unpack('i', plen)[0]
-                    label_len = alllen & 0xFFFF
-                    seq_len = (alllen >> 16) & 0xFFFF
+                    all_len = struct.unpack('i', plen)[0]
+                    label_len = all_len & 0xFFFF
+                    seq_len = (all_len >> 16) & 0xFFFF
 
                     label = in_file.read(4 * label_len)
                     label = np.frombuffer(label, dtype=np.int32).reshape(
@@ -106,9 +106,9 @@ def reader():
                     if plen is None or len(plen) != 4:
                         break
 
-                    alllen = struct.unpack('i', plen)[0]
-                    label_len = alllen & 0xFFFF
-                    seq_len = (alllen >> 16) & 0xFFFF
+                    all_len = struct.unpack('i', plen)[0]
+                    label_len = all_len & 0xFFFF
+                    seq_len = (all_len >> 16) & 0xFFFF
 
                     label = in_file.read(4 * label_len)
                     label = np.frombuffer(label, dtype=np.int32).reshape(
diff --git a/test/standalone_executor/test_standalone_controlflow.py b/test/standalone_executor/test_standalone_controlflow.py
@@ -25,7 +25,7 @@
 
 #  test the compatibility of new executor: run old
 #  and new executor twice and check the result.
-#  please override the _get_feeds() and build_prgram(), run_dygraph_once()
+#  please override the _get_feeds() and build_program(), run_dygraph_once()
 class TestCompatibility(unittest.TestCase):
     def setUp(self):
         self.place = (
diff --git a/test/standalone_executor/test_standalone_custom_event.py b/test/standalone_executor/test_standalone_custom_event.py
@@ -94,12 +94,12 @@ def set_custom_stream(self, prog):
             ops[op_index].dist_attr.execution_stream = "s2"
             ops[op_index].dist_attr.stream_priority = -1
 
-    def split_program(self, prog, apply_mannual_event=False):
+    def split_program(self, prog, apply_manual_event=False):
         # split two subprograms
         waiter_recorder_events_map = {11: [8, 10]}
         prog_block = prog.global_block()
         ops = prog_block.ops
-        if apply_mannual_event:
+        if apply_manual_event:
             for waiter, recorders in waiter_recorder_events_map.items():
                 for recorder in recorders:
                     _add_event_dependency(ops[recorder], ops[waiter])
@@ -159,7 +159,7 @@ def run_program(
         self,
         apply_custom_stream=False,
         split_prog=False,
-        apply_mannual_event=False,
+        apply_manual_event=False,
     ):
         paddle.seed(2022)
         main_program, startup_program, fetch_list = build_program()
@@ -170,7 +170,7 @@ def run_program(
         main_progs = [main_program]
         startup_progs = [startup_program]
         if apply_custom_stream and split_prog:
-            main_progs = self.split_program(main_program, apply_mannual_event)
+            main_progs = self.split_program(main_program, apply_manual_event)
         outs = []
         exe = self.create_standalone_exe(main_progs, startup_progs, fetch_list)
         for i in range(self.steps):
@@ -184,11 +184,11 @@ def test_result(self):
         baselines = self.run_program()
         stream_outs = self.run_program(apply_custom_stream=True)
         split_outs = self.run_program(apply_custom_stream=True, split_prog=True)
-        mannual_outs = self.run_program(
-            apply_custom_stream=True, split_prog=True, apply_mannual_event=True
+        manual_outs = self.run_program(
+            apply_custom_stream=True, split_prog=True, apply_manual_event=True
         )
         for bl, out0, out1, out2 in zip(
-            baselines, stream_outs, split_outs, mannual_outs
+            baselines, stream_outs, split_outs, manual_outs
         ):
             self.assertEqual(bl[0], out0[0])
             self.assertEqual(bl[0], out2[0])
diff --git a/test/standalone_executor/test_standalone_executor_multi_micro_batch.py b/test/standalone_executor/test_standalone_executor_multi_micro_batch.py
@@ -28,7 +28,7 @@
 paddle.enable_static()
 
 
-class TestEncorderMulitMicroBatchRun(unittest.TestCase):
+class TestEncoderMultiMicroBatchRun(unittest.TestCase):
     def setUp(self):
         self.place_desc = (
             paddle.CUDAPlace(0)
@@ -213,7 +213,7 @@ def run_train(self, split=False, micro_batch_num=1):
         return res
 
     def check_result(self, expected_result, actual_result):
-        # FIXME(Ruibiao): The output result of Encorder layers is unstable in some case.
+        # FIXME(Ruibiao): The output result of Encoder layers is unstable in some case.
         if self.place.is_cpu_place() or platform.system().lower() == "windows":
             np.testing.assert_allclose(
                 expected_result, actual_result, atol=1e-6, rtol=1e-6
diff --git a/test/tokenizer/tokenizer_utils.py b/test/tokenizer/tokenizer_utils.py
@@ -43,7 +43,7 @@ def convert_to_unicode(text):
 
 def whitespace_tokenize(text):
     """
-    Runs basic whitespace cleaning and splitting on a peice of text.
+    Runs basic whitespace cleaning and splitting on a piece of text.
     Args:
         text (str): Text to be tokened.
     Returns:
@@ -60,7 +60,7 @@ def _is_whitespace(char):
     """
     Checks whether `chars` is a whitespace character.
     """
-    # \t, \n, and \r are technically contorl characters but we treat them
+    # \t, \n, and \r are technically control characters but we treat them
     # as whitespace since they are generally considered as such.
     if char == " " or char == "\t" or char == "\n" or char == "\r":
         return True
diff --git a/test/xpu/test_reduce_max_op_xpu.py b/test/xpu/test_reduce_max_op_xpu.py
@@ -48,7 +48,7 @@ def set_case(self):
             }
             self.temp_x = np.random.random(self.shape)
             self.dtype = self.in_type
-            if self.dtype == np.uint16:  # bfloat16 acturally
+            if self.dtype == np.uint16:  # bfloat16 actually
                 self.x = convert_float_to_uint16(self.temp_x)
             else:
                 self.x = self.temp_x.astype(self.dtype)
