[CodeStyle][UP031] fix /test/legacy_test/* - part 10 (PaddlePaddle#…

…65564)

test/legacy_test/auto_parallel_autoconvert.py

@@ -150,12 +150,8 @@ def setUp(self):
         np.random.seed(2021)
 
     def tearDown(self):
-        os.remove(
-            f"./model_state_rank{str(paddle.distributed.get_rank())}.pdmodel"
-        )
-        os.remove(
-            f"./dist_attr_rank{str(paddle.distributed.get_rank())}.pdattr"
-        )
+        os.remove(f"./model_state_rank{paddle.distributed.get_rank()}.pdmodel")
+        os.remove(f"./dist_attr_rank{paddle.distributed.get_rank()}.pdattr")
 
     def test_mlp_mp2pp(self):
         set_default_distributed_context(None)
@@ -245,12 +241,8 @@ def setUp(self):
         np.random.seed(2021)
 
     def tearDown(self):
-        os.remove(
-            f"./model_state_rank{str(paddle.distributed.get_rank())}.pdmodel"
-        )
-        os.remove(
-            f"./dist_attr_rank{str(paddle.distributed.get_rank())}.pdattr"
-        )
+        os.remove(f"./model_state_rank{paddle.distributed.get_rank()}.pdmodel")
+        os.remove(f"./dist_attr_rank{paddle.distributed.get_rank()}.pdattr")
 
     def test_mlp_pp2mp(self):
         set_default_distributed_context(None)

test/legacy_test/auto_parallel_op_test.py

@@ -494,7 +494,7 @@ def check_eager_auto_parallel(self):
             # check eager auto parallel forward
             if len(actual_ret) != len(self.eager_forward_desire):
                 msg = (
-                    f"The eager auto parallel out tensor nums is different with eager out tensor nums on {str(self.place)}."
+                    f"The eager auto parallel out tensor nums is different with eager out tensor nums on {self.place}."
                     f'eager auto parallel out tensor nums = {len(actual_ret)}, eager out tensor nums = {len(self.eager_forward_desire)}. \n'
                 )
                 raise RuntimeError(msg)
@@ -713,7 +713,7 @@ def check_eager_auto_parallel(self):
             # check eager auto parallel forward
             if len(actual_forward_res) != len(self.eager_forward_desire):
                 msg = (
-                    f"The eager auto parallel out tensor nums is different with eager out tensor nums on {str(self.place)}."
+                    f"The eager auto parallel out tensor nums is different with eager out tensor nums on {self.place}."
                     f'eager auto parallel out tensor nums = {len(actual_forward_res)}, eager out tensor nums = {len(self.eager_forward_desire)}. \n'
                 )
                 raise RuntimeError(msg)
@@ -739,7 +739,7 @@ def check_eager_auto_parallel(self):
             # check eager auto parallel grad
             if len(actual_grad_res) != len(self.eager_grad_desire):
                 msg = (
-                    f"The eager auto parallel grad out tensor nums is different with eager grad out tensor nums on {str(self.place)}."
+                    f"The eager auto parallel grad out tensor nums is different with eager grad out tensor nums on {self.place}."
                     f'eager auto parallel grad out tensor nums = {len(actual_grad_res)}, eager grad out tensor nums = {len(self.eager_grad_desire)}. \n'
                 )
                 raise RuntimeError(msg)

test/legacy_test/benchmark.py

@@ -85,9 +85,7 @@ def timeit_output(self, iters=100):
         for place in places:
             elapses.append(self.timeit_output_with_place(place, iters))
         for place, elapse in zip(places, elapses):
-            print(
-                f"One pass of ({self.op_type}_op) at {str(place)} cost {elapse}"
-            )
+            print(f"One pass of ({self.op_type}_op) at {place} cost {elapse}")
 
     def timeit_grad_with_place(self, place, iters=100):
         inputs_to_check = self._get_input_names()
@@ -108,5 +106,5 @@ def timeit_grad(self, iters=100):
             elapses.append(self.timeit_grad_with_place(place, iters))
         for place, elapse in zip(places, elapses):
             print(
-                f"One pass of ({self.op_type}_grad_op) at {str(place)} cost {elapse}"
+                f"One pass of ({self.op_type}_grad_op) at {place} cost {elapse}"
             )

test/legacy_test/dist_fleet_sync_batch_norm.py

@@ -94,7 +94,7 @@ def train(args):
     rank = paddle.distributed.get_rank()
     filepath = os.path.join(
         args.data_dir,
-        f'input_{rank}_{args.only_forward}_{str(args.dtype)}_{args.layout}.npy',
+        f'input_{rank}_{args.only_forward}_{args.dtype}_{args.layout}.npy',
     )
     data = np.load(filepath)
 
@@ -108,7 +108,7 @@ def train(args):
     for i in range(0, len(sync_bn_fetches)):
         file_path = os.path.join(
             args.data_dir,
-            f'output_{rank}_{args.only_forward}_{str(args.dtype)}_{i}.npy',
+            f'output_{rank}_{args.only_forward}_{args.dtype}_{i}.npy',
         )
         np.save(file_path, sync_bn_fetches[i])
 

test/legacy_test/gradient_checker.py

@@ -447,7 +447,7 @@ def fail_test(msg):
         if not np.allclose(a, n, rtol, atol):
             msg = (
                 f'Jacobian mismatch for output {y_idx} in y '
-                f'with respect to input {x_idx} in x on {str(place)},\n'
+                f'with respect to input {x_idx} in x on {place},\n'
                 f'numerical:{n}\nanalytical:{a}\n'
             )
             return fail_test(msg)

test/legacy_test/op.py

@@ -163,7 +163,7 @@ def __call__(self, *args, **kwargs):
                         new_attr.scalars.MergeFrom(item)
                 else:
                     raise NotImplementedError(
-                        f"A not supported attribute type: {str(attr.type)}."
+                        f"A not supported attribute type: {attr.type}."
                     )
         for attr_name, defalut_val in self.__extra_attrs__.items():
             user_defined_attr = kwargs.get(attr_name, None)
@@ -212,7 +212,7 @@ def __call__(self, *args, **kwargs):
                         new_attr.scalars.MergeFrom(item)
                 else:
                     raise NotImplementedError(
-                        f"A not supported attribute type: {str(attr_type)}."
+                        f"A not supported attribute type: {attr_type}."
                     )
 
         return op_desc

test/legacy_test/op_test.py

@@ -2936,7 +2936,7 @@ def _assert_is_close(
                     atol=atol,
                     equal_nan=False,
                     err_msg=(
-                        f"Operator {self.op_type} error, {msg_prefix} variable {name} (shape: {str(a.shape)}, dtype: {self.dtype}) max gradient diff over limit"
+                        f"Operator {self.op_type} error, {msg_prefix} variable {name} (shape: {a.shape}, dtype: {self.dtype}) max gradient diff over limit"
                     ),
                 )
             else:
@@ -3150,7 +3150,7 @@ def check_grad_with_place_for_static(
             analytic_grads,
             inputs_to_check,
             max_relative_error,
-            f"Gradient Check On {str(place)}",
+            f"Gradient Check On {place}",
             atol=atol,
         )
 
@@ -3425,7 +3425,7 @@ def check_grad_with_place(
                     dygraph_dygraph_grad,
                     inputs_to_check,
                     max_relative_error,
-                    f"Gradient Check On {str(place)}",
+                    f"Gradient Check On {place}",
                     atol=atol,
                 )
 
@@ -3465,7 +3465,7 @@ def check_grad_with_place(
                     pir_grad,
                     inputs_to_check,
                     max_relative_error,
-                    f"Gradient Check On {str(place)}",
+                    f"Gradient Check On {place}",
                     atol=atol,
                 )
 

test/legacy_test/prim_op_test.py

@@ -689,7 +689,7 @@ def check_static_comp(self):
         # check static forward
         if len(ret) != len(self.eager_desire):
             msg = (
-                f"The static comp forward api out tensor nums is different with eager forward api out tensor nums on {str(self.place)}."
+                f"The static comp forward api out tensor nums is different with eager forward api out tensor nums on {self.place}."
                 f'when enable_fw_comp is {self.enable_fw_comp}, static comp forward api out tensor nums = {len(ret)}, eager forward api out tensor nums = {len(self.eager_desire)}. \n'
             )
             raise RuntimeError(msg)
@@ -772,7 +772,7 @@ def check_jit_comp(self):
             # check jit comp forward
             if len(ret) != len(self.eager_desire):
                 msg = (
-                    f"The jit comp forward api out tensor nums is different with eager forward api out tensor nums on {str(self.place)}."
+                    f"The jit comp forward api out tensor nums is different with eager forward api out tensor nums on {self.place}."
                     f'when enable_fw_comp is {self.enable_fw_comp}, jit comp forward api out tensor nums = {len(ret)}, eager forward api out tensor nums = {len(self.eager_desire)}. \n'
                 )
                 raise RuntimeError(msg)
@@ -865,7 +865,7 @@ def check_jit_comp_with_cinn(self):
             # check jit comp forward
             if len(ret) != len(self.eager_desire):
                 msg = (
-                    f"The jit comp with cinn forward api out tensor nums is different with eager forward api out tensor nums on {str(self.place)}."
+                    f"The jit comp with cinn forward api out tensor nums is different with eager forward api out tensor nums on {self.place}."
                     f'when enable_fw_comp is {self.enable_fw_comp}, enable_cinn is {core.is_compiled_with_cinn() and self.enable_cinn}, jit comp forward api out tensor nums = {len(ret)}, eager forward api out tensor nums = {len(self.eager_desire)}. \n'
                 )
                 raise RuntimeError(msg)
@@ -1062,7 +1062,7 @@ def check_eager_comp(self):
             # check static forward
             if len(actual_ret) != len(self.eager_desire):
                 msg = (
-                    f"The eager comp grad out tensor nums is different with eager grad out tensor nums on {str(self.place)}."
+                    f"The eager comp grad out tensor nums is different with eager grad out tensor nums on {self.place}."
                     f'when enable_rev_comp is {self.enable_rev_comp}, eager comp grad api out tensor nums = {len(actual_ret)}, eager grad out tensor nums = {len(self.eager_desire)}. \n'
                 )
                 raise RuntimeError(msg)
@@ -1180,7 +1180,7 @@ def check_static_comp(self):
         # check static grad out
         if len(actual_ret) != len(self.eager_desire):
             msg = (
-                f"The static comp grad out tensor nums is different with eager grad out tensor nums on {str(self.place)}."
+                f"The static comp grad out tensor nums is different with eager grad out tensor nums on {self.place}."
                 f'when enable_fw_comp is {self.enable_fw_comp},enable_rev_comp is {self.enable_rev_comp}, static comp grad out tensor nums = {len(actual_ret)}, eager grad out tensor nums = {len(self.eager_desire)}. \n'
             )
             raise RuntimeError(msg)
@@ -1294,7 +1294,7 @@ def check_jit_comp(self):
             # check jit comp grad out
             if len(ret) != len(self.eager_desire):
                 msg = (
-                    f"The jit comp grad out tensor nums is different with eager grad out tensor nums on {str(self.place)}."
+                    f"The jit comp grad out tensor nums is different with eager grad out tensor nums on {self.place}."
                     f'when enable_fw_comp is {self.enable_fw_comp}, enable_rev_comp is {self.enable_rev_comp}, jit comp grad out tensor nums = {len(ret)}, eager grad out tensor nums = {len(self.eager_desire)}. \n'
                 )
                 raise RuntimeError(msg)
@@ -1421,7 +1421,7 @@ def check_jit_comp_with_cinn(self):
             # check jit comp grad out
             if len(ret) != len(self.eager_desire):
                 msg = (
-                    f"The jit comp with cinn grad out tensor nums is different with eager grad out tensor nums on {str(self.place)}."
+                    f"The jit comp with cinn grad out tensor nums is different with eager grad out tensor nums on {self.place}."
                     f'when enable_fw_comp is {self.enable_fw_comp}, enable_rev_comp is {self.enable_rev_comp}, enable_cinn is {self.enable_cinn and core.is_compiled_with_cinn()}, jit comp grad out tensor nums = {len(ret)}, eager grad out tensor nums = {len(self.eager_desire)}. \n'
                 )
                 raise RuntimeError(msg)

test/legacy_test/test_conv2d_op.py

@@ -34,13 +34,13 @@ def conv2d_forward_naive(
 ):
     if padding_algorithm not in ["SAME", "VALID", "EXPLICIT"]:
         raise ValueError(
-            f"Unknown Attr(padding_algorithm): '{str(padding_algorithm)}'. "
+            f"Unknown Attr(padding_algorithm): '{padding_algorithm}'. "
             "It can only be 'SAME' or 'VALID'."
         )
 
     if data_format not in ["NCHW", "NHWC"]:
         raise ValueError(
-            f"Unknown Attr(data_format): '{str(data_format)}' ."
+            f"Unknown Attr(data_format): '{data_format}' ."
             "It can only be 'NCHW' or 'NHWC'."
         )
 

test/legacy_test/test_conv2d_transpose_op.py

@@ -37,7 +37,7 @@ def conv2dtranspose_forward_naive(input_, filter_, attrs):
     padding_algorithm = attrs['padding_algorithm']
     if padding_algorithm not in ["SAME", "VALID", "EXPLICIT"]:
         raise ValueError(
-            f"Unknown Attr(padding_algorithm): '{str(padding_algorithm)}'. "
+            f"Unknown Attr(padding_algorithm): '{padding_algorithm}'. "
             "It can only be 'SAME' or 'VALID'."
         )
 

test/legacy_test/test_conv3d_op.py

@@ -37,13 +37,13 @@ def conv3d_forward_naive(
 ):
     if padding_algorithm not in ["SAME", "VALID", "EXPLICIT"]:
         raise ValueError(
-            f"Unknown Attr(padding_algorithm): '{str(padding_algorithm)}'. "
+            f"Unknown Attr(padding_algorithm): '{padding_algorithm}'. "
             "It can only be 'SAME' or 'VALID'."
         )
 
     if data_format not in ["NCDHW", "NDHWC"]:
         raise ValueError(
-            f"Unknown Attr(data_format): '{str(data_format)}' ."
+            f"Unknown Attr(data_format): '{data_format}' ."
             "It can only be 'NCDHW' or 'NDHWC'."
         )
 

test/legacy_test/test_conv3d_transpose_op.py

@@ -42,7 +42,7 @@ def conv3dtranspose_forward_naive(input_, filter_, attrs):
     padding_algorithm = attrs['padding_algorithm']
     if padding_algorithm not in ["SAME", "VALID", "EXPLICIT"]:
         raise ValueError(
-            f"Unknown Attr(padding_algorithm): '{str(padding_algorithm)}'. "
+            f"Unknown Attr(padding_algorithm): '{padding_algorithm}'. "
             "It can only be 'SAME' or 'VALID'."
         )
 

test/legacy_test/test_fused_dropout_add_op.py

@@ -101,9 +101,7 @@ def setUp(self):
             self.mode = mode
             self.seed = seed
 
-    cls_name = (
-        f"{parent.__name__}_{dtype}_{mode}_{str(training)}_{str(p)}_{str(seed)}"
-    )
+    cls_name = f"{parent.__name__}_{dtype}_{mode}_{training}_{p}_{seed}"
     TestFusedDropoutAddCase.__name__ = cls_name
     globals()[cls_name] = TestFusedDropoutAddCase
 

test/legacy_test/test_group_norm_op.py

@@ -209,7 +209,7 @@ def do_compare_between_place(self):
             gpu_grads,
             inputs_to_check,
             0.005,
-            f"Gradient Check On {str(place)}",
+            f"Gradient Check On {place}",
         )
 
     def test_check_grad(self):

test/legacy_test/test_poisson_nll_loss.py

@@ -34,14 +34,13 @@ def ref_poisson_nll_loss(
 ):
     if epsilon <= 0:
         raise ValueError(
-            "The value of `epsilon` in PoissonNLLLoss should be positive, but received %f, which is not allowed"
-            % epsilon
+            f"The value of `epsilon` in PoissonNLLLoss should be positive, but received {epsilon:f}, which is not allowed"
         )
 
     if reduction not in ['sum', 'mean', 'none']:
         raise ValueError(
             "The value of 'reduction' in SoftMarginLoss should be 'sum', 'mean' or 'none', but "
-            "received %s, which is not allowed." % reduction
+            f"received {reduction}, which is not allowed."
         )
     loss_out = 0
     if log_input:

test/legacy_test/test_pool2d_op.py

@@ -179,8 +179,8 @@ def _get_padding_with_SAME(input_shape, pool_size, pool_stride):
         padding_algorithm = padding_algorithm.upper()
         if padding_algorithm not in ["SAME", "VALID", "EXPLICIT"]:
             raise ValueError(
-                "Unknown Attr(padding_algorithm): '%s'. "
-                "It can only be 'SAME' or 'VALID'." % str(padding_algorithm)
+                f"Unknown Attr(padding_algorithm): '{padding_algorithm}'. "
+                "It can only be 'SAME' or 'VALID'."
             )
 
         if padding_algorithm == "VALID":

test/legacy_test/test_pool3d_op.py

@@ -63,8 +63,8 @@ def _get_padding_with_SAME(input_shape, pool_size, pool_stride):
         padding_algorithm = padding_algorithm.upper()
         if padding_algorithm not in ["SAME", "VALID", "EXPLICIT"]:
             raise ValueError(
-                "Unknown Attr(padding_algorithm): '%s'. "
-                "It can only be 'SAME' or 'VALID'." % str(padding_algorithm)
+                f"Unknown Attr(padding_algorithm): '{padding_algorithm}'. "
+                "It can only be 'SAME' or 'VALID'."
             )
 
         if padding_algorithm == "VALID":

test/legacy_test/test_sync_batch_norm_op.py

@@ -217,7 +217,7 @@ def _compare_impl(self, place, layout, only_forward):
         for id in range(core.get_cuda_device_count()):
             filepath = os.path.join(
                 self.data_dir.name,
-                f'input_{id}_{only_forward}_{str(self.dtype.__name__)}_{layout}.npy',
+                f'input_{id}_{only_forward}_{self.dtype.__name__}_{layout}.npy',
             )
             np.save(filepath, data[id * stride : (id + 1) * stride])
         data = create_or_get_tensor(

test/legacy_test/test_zero_dim_binary_api.py

@@ -168,7 +168,7 @@ def test_dygraph_binary(self):
             # 1) x is 0D, y is 0D
             x_np = np.random.randint(-10, 10, [])
             y_np = np.random.randint(-10, 10, [])
-            out_np = eval('np.%s(x_np, y_np)' % api.__name__)
+            out_np = eval(f'np.{api.__name__}(x_np, y_np)')
 
             x = paddle.to_tensor(x_np)
             y = paddle.to_tensor(y_np)
@@ -180,7 +180,7 @@ def test_dygraph_binary(self):
             # 2) x is ND, y is 0D
             x_np = np.random.randint(-10, 10, [3, 5])
             y_np = np.random.randint(-10, 10, [])
-            out_np = eval('np.%s(x_np, y_np)' % api.__name__)
+            out_np = eval(f'np.{api.__name__}(x_np, y_np)')
 
             x = paddle.to_tensor(x_np)
             y = paddle.to_tensor(y_np)
@@ -192,7 +192,7 @@ def test_dygraph_binary(self):
             # 3) x is 0D , y is ND
             x_np = np.random.randint(-10, 10, [])
             y_np = np.random.randint(-10, 10, [3, 5])
-            out_np = eval('np.%s(x_np, y_np)' % api.__name__)
+            out_np = eval(f'np.{api.__name__}(x_np, y_np)')
 
             x = paddle.to_tensor(x_np)
             y = paddle.to_tensor(y_np)