[CodeStyle][F632] Replace 'is' and 'is not' with == and != respectively (#46708)

* Update README.md

* Update README.md

* Fix F632: replace 'is', 'is not' with ==, != respectively

python/paddle/distributed/parallel.py

@@ -76,7 +76,7 @@ def _is_cpuonly(backend):
     if (backend in ['auto', 'nccl', 'bkcl', 'hccl', 'heter', 'cncl'] and
         (core.is_compiled_with_cuda() or core.is_compiled_with_xpu()
          or core.is_compiled_with_npu()
-         or core.is_compiled_with_mlu())) or backend is 'xccl':
+         or core.is_compiled_with_mlu())) or backend == 'xccl':
 
         # passes 'auto' and can use cuda or xpu, use the default logics. so return False
         return False

python/paddle/fluid/tests/custom_op/test_custom_relu_model.py

@@ -293,7 +293,7 @@ class TestStaticModel(unittest.TestCase):
                 # For PE
                 if use_pe:
                     places = paddle.static.cpu_places(
-                    ) if device is 'cpu' else paddle.static.cuda_places()
+                    ) if device == 'cpu' else paddle.static.cuda_places()
                     main_program = paddle.static.CompiledProgram(
                         paddle.static.default_main_program(
                         )).with_data_parallel(loss_name=loss.name,

python/paddle/fluid/tests/custom_op/test_custom_relu_op_setup.py

@@ -72,7 +72,7 @@ def custom_relu_static_pe(func, device, dtype, np_x, use_func=True):
     paddle.enable_static()
     paddle.set_device(device)
 
-    places = static.cpu_places() if device is 'cpu' else static.cuda_places()
+    places = static.cpu_places() if device == 'cpu' else static.cuda_places()
     with static.scope_guard(static.Scope()):
         with static.program_guard(static.Program()):
             x = static.data(name='X', shape=[None, 8], dtype=dtype)

python/paddle/fluid/tests/unittests/auto_parallel_gpt_model.py

@@ -278,7 +278,7 @@ class TransformerDecoder(nn.Layer):
         self.num_layers = num_layers
         self.layers = decoder_layers
         self.norm = norm
-        if norm is "LayerNorm":
+        if norm == "LayerNorm":
             self.norm = nn.LayerNorm(hidden_size)
         elif norm is not None:
             raise ValueError("Only support LayerNorm")

python/paddle/fluid/tests/unittests/test_auto_parallel_completion_gpt.py

@@ -266,7 +266,7 @@ class TransformerDecoder(nn.Layer):
         self.num_layers = num_layers
         self.layers = decoder_layers
         self.norm = norm
-        if norm is "LayerNorm":
+        if norm == "LayerNorm":
             self.norm = nn.LayerNorm(hidden_size)
         elif norm is not None:
             raise ValueError("Only support LayerNorm")

python/paddle/fluid/tests/unittests/test_auto_parallel_partitioner_gpt.py

@@ -313,7 +313,7 @@ class TransformerDecoder(nn.Layer):
         self.num_layers = num_layers
         self.layers = decoder_layers
         self.norm = norm
-        if norm is "LayerNorm":
+        if norm == "LayerNorm":
             self.norm = nn.LayerNorm(hidden_size)
         elif norm is not None:
             raise ValueError("Only support LayerNorm")

python/paddle/fluid/tests/unittests/test_lookup_table_bf16_op.py

@@ -26,7 +26,7 @@ from paddle import enable_static
 
 def _lookup(weights, ids, flat_ids, op_version="lookup_table"):
     w_shape = weights.shape
-    out_shape = list(ids.shape[:-1]) if op_version is "lookup_table" else list(
+    out_shape = list(ids.shape[:-1]) if op_version == "lookup_table" else list(
         ids.shape)
     out_shape.append(w_shape[-1])
     out = weights[flat_ids].reshape(out_shape)
@@ -36,7 +36,7 @@ def _lookup(weights, ids, flat_ids, op_version="lookup_table"):
 def _get_grad(weights, ids, flat_ids, op_version="lookup_table"):
     w_shape = weights.shape
     w_grad = np.zeros((w_shape), dtype=weights.dtype)
-    out_shape = list(ids.shape[:-1]) if op_version is "lookup_table" else list(
+    out_shape = list(ids.shape[:-1]) if op_version == "lookup_table" else list(
         ids.shape)
     out_grad_shape = (np.prod(out_shape), w_shape[-1])
     out_grad = weights[flat_ids].reshape(out_grad_shape)

python/paddle/fluid/tests/unittests/test_max_min_amax_amin_op.py

@@ -44,13 +44,13 @@ class TestMaxMinAmaxAminAPI(unittest.TestCase):
     def cal_np_out_and_gradient(self):
 
         def _cal_np_out_and_gradient(func):
-            if func is 'amax':
+            if func == 'amax':
                 out = np.amax(self.x_np, axis=self.axis, keepdims=self.keepdim)
-            elif func is 'amin':
+            elif func == 'amin':
                 out = np.amin(self.x_np, axis=self.axis, keepdims=self.keepdim)
-            elif func is 'max':
+            elif func == 'max':
                 out = np.max(self.x_np, axis=self.axis, keepdims=self.keepdim)
-            elif func is 'min':
+            elif func == 'min':
                 out = np.min(self.x_np, axis=self.axis, keepdims=self.keepdim)
             else:
                 print('This unittest only test amax/amin/max/min, but now is',
@@ -74,13 +74,13 @@ class TestMaxMinAmaxAminAPI(unittest.TestCase):
         _cal_np_out_and_gradient('min')
 
     def _choose_paddle_func(self, func, x):
-        if func is 'amax':
+        if func == 'amax':
             out = paddle.amax(x, self.axis, self.keepdim)
-        elif func is 'amin':
+        elif func == 'amin':
             out = paddle.amin(x, self.axis, self.keepdim)
-        elif func is 'max':
+        elif func == 'max':
             out = paddle.max(x, self.axis, self.keepdim)
-        elif func is 'min':
+        elif func == 'min':
             out = paddle.min(x, self.axis, self.keepdim)
         else:
             print('This unittest only test amax/amin/max/min, but now is', func)

python/paddle/fluid/tests/unittests/test_parallel_executor_fetch_feed.py

@@ -100,7 +100,7 @@ class TestFetchAndFeed(unittest.TestCase):
 
         for k, v in all_vars.items():
             if ('tmp' not in k) and (
-                    k[0] is not '_' or v.persistable
+                    k[0] != '_' or v.persistable
             ) and v.type == core.VarDesc.VarType.LOD_TENSOR:
                 fetch_list.append(k)
 

python/paddle/fluid/tests/unittests/test_real_imag_op.py

@@ -131,7 +131,7 @@ class TestRealAPI(unittest.TestCase):
                     res = paddle_apis[self.api](input_t).numpy()
                     np.testing.assert_array_equal(np_res, res)
                     res_t = input_t.real().numpy(
-                    ) if self.api is "real" else input_t.imag().numpy()
+                    ) if self.api == "real" else input_t.imag().numpy()
                     np.testing.assert_array_equal(np_res, res_t)
 
     def test_name_argument(self):