[CodeStyle] black -> ruff format migration - part 4

test/auto_parallel/hybrid_strategy/parallel_api.py

@@ -411,7 +411,6 @@ def parallel_model(self, layer):
                     or paddle.device.cuda.get_device_capability()[0] < 8
                 )
             ):
-
                 bck = 'p2p'
                 if self.config.context_parallel is True:
                     bck = 'p2p'

test/auto_parallel/hybrid_strategy/single_lora_model.py

@@ -305,7 +305,6 @@ def extra_repr(self):
 
 
 class LoRAModel(nn.Layer):
-
     def __init__(self, model, lora_config) -> None:
         super().__init__()
         self.model = self.get_lora_model(model, lora_config)

test/auto_parallel/hybrid_strategy/to_distributed_api_for_llama.py

@@ -428,7 +428,6 @@ def forward(
         hidden_states = inputs_embeds
 
         for idx, (decoder_layer) in enumerate(self.layers):
-
             layer_outputs = decoder_layer(
                 hidden_states,
                 position_ids,
@@ -505,7 +504,6 @@ def forward(self, hidden_states, tensor_parallel_output=None):
 
 
 class LlamaForCausalLM(paddle.nn.Layer):
-
     def __init__(
         self,
         param_prefix="",
@@ -537,7 +535,6 @@ def forward(
         attention_mask=None,
         labels=None,
     ):
-
         outputs = self.llama(
             input_ids,
             position_ids=position_ids,

test/auto_parallel/pir/auto_parallel_refined_recompute_pir_pass_unittest.py

@@ -18,7 +18,6 @@
 
 
 class TestRefinedRecomputeLlamaAuto(TestRecomputeLlamaAuto):
-
     def run_test_cases(self):
         self.config.recompute = True
         self.config.recompute_granularity = "full"

test/auto_parallel/pir/test_op_role.py

@@ -37,7 +37,6 @@ def test_single(self):
         with paddle.pir_utils.IrGuard():
             main_program = paddle.base.Program()
             with paddle.base.program_guard(main_program):
-
                 # op_role = -1
                 x0 = paddle.static.data(name='x0', shape=[1, 128, 512])
                 x1 = paddle.nn.functional.relu(x0)

test/auto_parallel/pir/test_pir_1f1b_plan.py

@@ -19,7 +19,6 @@
 
 
 class TestPIR1F1BPlan(unittest.TestCase):
-
     def test_standalone_executor_1f1b_plan_stage0(self):
         base.set_flags({'FLAGS_enable_pir_api': 1})
         config = {"num_micro_batches": 8, "pp_stage": 0, "pp_degree": 4}

test/auto_parallel/spmd_rules/test_einsum_rule.py

@@ -24,7 +24,6 @@
 
 # case: bmm
 class TestEinsumSPMDRule(unittest.TestCase):
-
     def setUp(self):
         self.init_data()
         self.init_parallel_setting()

test/cinn/fake_model/naive_multi_fc.py

@@ -15,7 +15,6 @@
 A fake model with multiple FC layers to test CINN on a more complex model.
 """
 
-
 import paddle
 from paddle import static
 

test/collective/new_api_per_op_and_group_intranode.py

@@ -89,7 +89,6 @@ def test_scatter(ep_group: Group, mode: str):
     m, n = 4096, 8192
 
     if local_rank == 0:
-
         scatter_list = [
             paddle.ones(shape=[m, n], dtype=paddle.float32) * (i + 1)
             for i in range(num_local_ranks)
@@ -124,7 +123,6 @@ def test_reduce(ep_group: Group, mode: str):
     dist.reduce(gbl_x, dst=0, group=ep_group)
 
     if local_rank == 0:
-
         res = paddle.ones(shape=[m, n], dtype=paddle.float32) * (
             num_local_ranks * (num_local_ranks + 1) / 2
         )
@@ -208,7 +206,6 @@ def test_all_reduce(ep_group: Group, mode: str):
 
 
 def test_primitive():
-
     dist.init_parallel_env()
 
     ranks = [0, 1]

test/dataset/test_image.py

@@ -17,6 +17,7 @@
 Description:
     This script test image resize,flip and chw.
 """
+
 import os
 import unittest
 

test/deprecated/legacy_test/test_conditional_block_deprecated.py

@@ -24,7 +24,6 @@
 
 
 class ConditionalBlockTest(unittest.TestCase):
-
     def test_forward(self):
         main_program = base.Program()
         startup_program = base.Program()

test/deprecated/legacy_test/test_inference_model_io_deprecated.py

@@ -161,7 +161,6 @@ def test_fit_line_inference_model(self):
 
 
 class TestSaveInferenceModel(unittest.TestCase):
-
     def test_save_inference_model(self):
         root_path = tempfile.TemporaryDirectory()
         MODEL_DIR = os.path.join(root_path.name, "inference_model2")

test/dygraph_to_static/test_convert_call.py

@@ -319,7 +319,6 @@ def test_class_patch_api(self):
 
 
 class TestMarkerUnified(Dy2StTestBase):
-
     def test_plain_function(self):
         def fn(x):
             return x
@@ -453,7 +452,6 @@ def fn(x):
     def test_nn_layer_subclass_skip_sot_only(self):
         @paddle.jit.marker.unified(for_sot=True, for_ast=False)
         class MyLayer(paddle.nn.Layer):
-
             def __init__(self):
                 super().__init__()
                 self.w = paddle.create_parameter(shape=[1], dtype='float32')
@@ -476,7 +474,6 @@ def forward(self, x):
     def test_nn_layer_subclass_skip_ast_only(self):
         @paddle.jit.marker.unified(for_sot=False, for_ast=True)
         class MyLayer(paddle.nn.Layer):
-
             def __init__(self):
                 super().__init__()
                 self.w = paddle.create_parameter(shape=[1], dtype='float32')
@@ -499,7 +496,6 @@ def forward(self, x):
     def test_nn_layer_subclass_skip_ast_and_sot(self):
         @paddle.jit.marker.unified()
         class MyLayer(paddle.nn.Layer):
-
             def __init__(self):
                 super().__init__()
                 self.w = paddle.create_parameter(shape=[1], dtype='float32')

test/dygraph_to_static/test_function_spec.py

@@ -25,7 +25,6 @@
 
 
 class TestFunctionSpec(unittest.TestCase):
-
     def test_constructor(self):
         foo_spec = FunctionSpec(foo_func)
         args_name = foo_spec.args_name

test/dygraph_to_static/test_pylayer.py

@@ -14,6 +14,7 @@
 
 """Tests for PyLayer of Dynamic-to-Static.
 Only test simple cases here."""
+
 import sys
 from pathlib import Path
 

test/ipu/distributed/test_dist_sample.py

@@ -31,6 +31,7 @@
 --print-topology=yes \
 python3.8 test/ipu/distributed/test_dist_sample.py
 '''
+
 '''
 Multi hosts:
 python3.8 -m paddle.distributed.launch \

test/ir/inference/auto_scan_test.py

@@ -846,11 +846,9 @@ def random_to_skip():
                         pir_main_program, startup_program
                     ),
                 ):
-
                     feed_dict = {}
                     feed_data = prog_config.get_feed_data()
                     for key, value in feed_data.items():
-
                         feed_dict[key] = value['data']
 
                     place = (

test/ir/inference/test_inference_predictor_run.py

@@ -39,7 +39,6 @@ def forward(self, x1, x2):
 )
 class TestPredictorRunWithTensor(unittest.TestCase):
     def setUp(self):
-
         self.temp_dir = tempfile.TemporaryDirectory()
         net = TestNet()
         model = paddle.jit.to_static(

test/ir/inference/test_trt_convert_argsort.py

@@ -115,7 +115,6 @@ def generate_dynamic_shape(self, attrs):
     def sample_predictor_configs(
         self, program_config, run_pir=False
     ) -> tuple[paddle_infer.Config, list[int], float]:
-
         def clear_dynamic_shape():
             self.dynamic_shape.max_input_shape = {}
             self.dynamic_shape.min_input_shape = {}

test/ir/inference/test_trt_convert_grid_sampler.py

@@ -125,7 +125,6 @@ def generate_dynamic_shape(self, attrs):
     def sample_predictor_configs(
         self, program_config, run_pir=False
     ) -> tuple[paddle_infer.Config, list[int], float]:
-
         def clear_dynamic_shape():
             self.dynamic_shape.max_input_shape = {}
             self.dynamic_shape.min_input_shape = {}