[CodeStyple][B011] replace assert false with raise AssertionError (#51935)

* replace assert false with AssertionError

* 修改配置文件多余的部分

paddle/fluid/eager/auto_code_generator/generator/eager_gen.py

@@ -829,9 +829,9 @@ class DygraphFunctionGeneratorBase(FunctionGeneratorBase):
                         backward_input_pos,
                     ]
                 else:
-                    assert (
-                        False
-                    ), f"Cannot find {backward_input_name} in forward position map"
+                    raise AssertionError(
+                        f"Cannot find {backward_input_name} in forward position map"
+                    )
 
         for backward_output in backward_returns_list:
             backward_output_name = backward_output[0]

paddle/fluid/eager/auto_code_generator/generator/python_c_gen.py

@@ -58,7 +58,9 @@ atype_to_parsing_function = {
 
 def FindParsingFunctionFromAttributeType(atype):
     if atype not in atype_to_parsing_function.keys():
-        assert False, f"Unable to find {atype} in atype_to_parsing_function."
+        raise AssertionError(
+            f"Unable to find {atype} in atype_to_parsing_function."
+        )
 
     return atype_to_parsing_function[atype]
 

pyproject.toml

@@ -32,6 +32,11 @@ select = [
     # Pyflakes
     "F401",
 
+    # Comprehensions
+    "C400",
+    "C401",
+    "C402",
+
     # Pyupgrade
     "UP001",
     "UP003",
@@ -62,6 +67,7 @@ select = [
     # Bugbear
     "B009",
     "B010",
+    "B011",
 ]
 unfixable = [
     "NPY001"

python/paddle/dataset/imikolov.py

@@ -108,7 +108,7 @@ def reader_creator(filename, word_idx, n, data_type):
                         continue
                     yield src_seq, trg_seq
                 else:
-                    assert False, 'Unknown data type'
+                    raise AssertionError('Unknown data type')
 
     return reader
 

python/paddle/distributed/auto_parallel/cost/base_cost.py

@@ -436,8 +436,10 @@ def build_dp_costs(
             elif var_name in dist_attr.outputs_dist_attrs:
                 dims_mapping = dist_attr.get_output_dims_mapping(var_name)
             else:
-                assert False, "cannot find dims_mapping for {} in {}".format(
-                    var_name, dist_attr
+                raise AssertionError(
+                    "cannot find dims_mapping for {} in {}".format(
+                        var_name, dist_attr
+                    )
                 )
 
             # dims_mapping = (

python/paddle/distributed/auto_parallel/dist_context.py

@@ -974,9 +974,9 @@ class DistributedContext:
 
     def validate_dist_attr_for_program(self):
         if not self._is_initialized:
-            assert (
-                False
-            ), "Program must be initialized before validating its distributed attributes"
+            raise AssertionError(
+                "Program must be initialized before validating its distributed attributes"
+            )
         for block in self.serial_main_program.blocks:
             for tensor in block.vars.values():
                 dist_tensor = self.get_dist_tensor_for_program(tensor)
@@ -988,13 +988,13 @@ class DistributedContext:
                 if (dist_tensor is not None) and (
                     not dist_tensor.validate_dist_attr()
                 ):
-                    assert (
-                        False
-                    ), "Tensor {} (id: {}, original_id: {}) has a wrong distributed attributes {}.".format(
-                        dist_tensor.serial_tensor.name,
-                        dist_tensor.serial_tensor.desc.id(),
-                        dist_tensor.serial_tensor.desc.original_id(),
-                        dist_tensor.dist_attr,
+                    raise AssertionError(
+                        "Tensor {} (id: {}, original_id: {}) has a wrong distributed attributes {}.".format(
+                            dist_tensor.serial_tensor.name,
+                            dist_tensor.serial_tensor.desc.id(),
+                            dist_tensor.serial_tensor.desc.original_id(),
+                            dist_tensor.dist_attr,
+                        )
                     )
             for op in block.ops:
                 dist_op = self.get_dist_op_for_program(op)
@@ -1004,13 +1004,13 @@ class DistributedContext:
                     dist_op.serial_op.type
                 )
                 if (dist_op is not None) and (not dist_op.validate_dist_attr()):
-                    assert (
-                        False
-                    ), "Operator {} (id: {}, original_id: {}) has a wrong distributed attributes {} .".format(
-                        dist_op.serial_op.type,
-                        dist_op.serial_op.desc.id(),
-                        dist_op.serial_op.desc.original_id(),
-                        dist_op.dist_attr,
+                    raise AssertionError(
+                        "Operator {} (id: {}, original_id: {}) has a wrong distributed attributes {} .".format(
+                            dist_op.serial_op.type,
+                            dist_op.serial_op.desc.id(),
+                            dist_op.serial_op.desc.original_id(),
+                            dist_op.dist_attr,
+                        )
                     )
         return True
 

python/paddle/distributed/auto_parallel/operators/common.py

@@ -186,7 +186,9 @@ def register_distributed_operator_impl(op_type, dist_impl):
         dist_impl.type = op_type
         dist_op_impl_container.register_impl(dist_impl)
     else:
-        assert False, "Must register distributed operator registry first."
+        raise AssertionError(
+            "Must register distributed operator registry first."
+        )
 
 
 def find_compatible_distributed_operator_impls(dist_op, fwd=True, partial=True):

python/paddle/distributed/auto_parallel/process_group.py

@@ -115,8 +115,8 @@ class ProcessGroup:
         if global_rank in self.ranks:
             return self.ranks.index(global_rank)
         else:
-            assert False, "Rank {} doesn't belong to this group".format(
-                global_rank
+            raise AssertionError(
+                "Rank {} doesn't belong to this group".format(global_rank)
             )
 
     def is_instantiate(self):
@@ -149,7 +149,7 @@ class ProcessGroup:
                     ring_id
                 )
             else:
-                assert False, "No CUDA device found"
+                raise AssertionError('No CUDA device found')
 
             # TODO(shenliang03): This is a temporary solution to solve the problem of
             # hang caused by cross-creation of new_group

python/paddle/distributed/auto_parallel/utils.py

@@ -1790,7 +1790,9 @@ def set_dist_op_desc_original_id(dist_op_desc, op_desc, dist_context):
         return
     # Third, print error infomation if we cannot find the original id
     else:
-        assert False, "Cannot find the original id in the distributed context"
+        raise AssertionError(
+            "Cannot find the original id in the distributed context"
+        )
 
 
 def to_list(value):

python/paddle/distributed/collective.py

@@ -304,7 +304,7 @@ def new_group(ranks=None, backend=None, timeout=_default_timeout):
                     ring_id
                 )
             else:
-                assert False, "no cuda device found"
+                raise AssertionError("no cuda device found")
         else:
             return gp
 

python/paddle/distributed/fleet/fleet.py

@@ -416,7 +416,9 @@ class Fleet:
         if not order:
             order = ['dp', 'pp', 'sharding', 'mp']
         if order[:].sort() != list(d_hybrid_degree.keys())[:].sort():
-            assert False, "The order of hybrid_config setting is incorrect."
+            raise AssertionError(
+                'The order of hybrid_config setting is incorrect.'
+            )
 
         hybrid_group_names = []
         dims = []

python/paddle/distributed/fleet/launch_utils.py

@@ -953,10 +953,10 @@ def get_device_proc_info(args):
         else:
             devices_per_proc = [x for x in range(0, args.nproc_per_node)]
     else:
-        assert (
-            False
-        ), "Can't support device_mode:{}, support only cpu|gpu|xpu now.".format(
-            device_mode
+        raise AssertionError(
+            "Can't support device_mode:{}, support only cpu|gpu|xpu now.".format(
+                device_mode
+            )
         )
 
     return (device_mode, devices_per_proc)

python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_optimizer.py

@@ -116,10 +116,9 @@ class AscendIRParser:
             )
             op_parser.apply(op)
         else:
-            assert (
-                False
-            ), "Op[%s] has not been registered, so we have to skip it" % (
-                op.type
+            raise AssertionError(
+                'Op[%s] has not been registered, so we have to skip it'
+                % op.type
             )
 
     def _parse_program(

python/paddle/distributed/fleet/meta_optimizers/ascend/ascend_parser.py

@@ -515,7 +515,7 @@ class SumParser(AscendParserBase):
     def _apply(self):
         len_list = len(self.op.input_arg_names)
         if len_list < 2:
-            assert False, "the size of input list must large or equal 2"
+            raise AssertionError("the size of input list must large or equal 2")
         x = self._get_ge_input(self.op.input_arg_names[0])
         y = self._get_ge_input(self.op.input_arg_names[1])
         sum = (
@@ -643,7 +643,7 @@ class MatMulParser(AscendParserBase):
                 .set_attr_bool("transpose_x2", transpose_y)
             )
         else:
-            assert False, "not support"
+            raise AssertionError("not support")
         return [matmul], [[0]]
 
 
@@ -681,7 +681,7 @@ class MulParser(AscendParserBase):
                     .set_input("x2", y, 0)
                 )
             else:
-                assert False, "not support"
+                raise AssertionError("not support")
         else:
             if len(shape_x1) == 3 and len(shape_x2) == 2:
                 assert x_num_col_dims == 2, "only support 2"
@@ -729,7 +729,7 @@ class MulParser(AscendParserBase):
                     .set_attr_vec_int32("perm", [1, 2, 0])
                 )
             else:
-                assert False, "not support"
+                raise AssertionError("not support")
 
         return [matmul], [[0]]
 

python/paddle/distributed/fleet/meta_optimizers/dgc_optimizer.py

@@ -107,7 +107,9 @@ class DGCMomentumOptimizer(Optimizer):
             elif isinstance(regularization, L2Decay):
                 regular_type = 2
             else:
-                assert False, 'regularization must be None|L1Decay|L2Deacy'
+                raise AssertionError(
+                    "regularization must be None|L1Decay|L2Deacy"
+                )
         return regular_type, regular_coeff
 
     def _is_use_dgc(self, param_var, grad_var):

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

@@ -105,7 +105,7 @@ def check(use_cuda):
 if __name__ == '__main__':
     try:
         check(use_cuda=False)
-        assert False
+        raise AssertionError()
     except Exception as e:
         print(e)
         print(type(e))
@@ -114,7 +114,7 @@ if __name__ == '__main__':
     if core.is_compiled_with_cuda():
         try:
             check(use_cuda=True)
-            assert False
+            raise AssertionError()
         except Exception as e:
             print(e)
             print(type(e))

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

@@ -96,7 +96,7 @@ def run_check():
     if paddle.is_compiled_with_cuda():
         try:
             check(use_cuda=True)
-            assert False
+            raise AssertionError()
         except Exception as e:
             print(e)
             print(type(e))
@@ -105,7 +105,7 @@ def run_check():
             assert type(e) == OSError or type(e) == RuntimeError
     try:
         check(use_cuda=False)
-        assert False
+        raise AssertionError()
     except Exception as e:
         print(e)
         print(type(e))

python/paddle/fluid/tests/unittests/ir/inference/auto_scan_test.py

@@ -462,7 +462,7 @@ class PassAutoScanTest(AutoScanTest):
                     min_success_num, successful_ran_programs
                 )
             )
-            assert False
+            raise AssertionError()
         used_time = time.time() - start_time
         if max_duration > 0 and used_time > max_duration:
             logging.error(
@@ -470,7 +470,7 @@ class PassAutoScanTest(AutoScanTest):
                     max_duration
                 )
             )
-            assert False
+            raise AssertionError()
 
     def run_test(self, quant=False, prog_configs=None):
         status = True

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

@@ -180,7 +180,7 @@ def matmul_head2(X, Y, head_number=1):
             z.append(np.matmul(x[i], y[i]))
         Z = np.concatenate((z), axis=2)
     else:
-        assert False, "ERROR: Not supported dimension!"
+        raise AssertionError("ERROR: Not supported dimension!")
     return Z
 
 

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

@@ -99,7 +99,7 @@ class TestNanInfCheckResult(unittest.TestCase):
             out = paddle.log(x)
             sys.stdout.flush()
             if add_assert:
-                assert False
+                raise AssertionError()
         except Exception as e:
             # Cannot catch the log in CUDA kernel.
             err_str_list = (

python/paddle/incubate/distributed/fleet/collective.py

@@ -301,7 +301,9 @@ class CollectiveOptimizer(DistributedOptimizer):
     def _check_condition(self, name, **kwargs):
         for k, v in kwargs.items():
             if v is True:
-                assert False, "you can't use %s and %s together" % (name, k)
+                raise AssertionError(
+                    "you can't use %s and %s together" % (name, k)
+                )
 
     def _check_collective_mode(self, main_program, optimizer, strategy):
         """

python/paddle/incubate/distributed/models/moe/moe_layer.py

@@ -384,12 +384,10 @@ class MoELayer(nn.Layer):
                     group=self.group,
                 )
             else:
-                assert (
-                    False
-                ), "We only support naive gate, \
-                                gshard gate and switch gate, \
-                                but you choose {} gate.".format(
-                    str(gate)
+                raise AssertionError(
+                    "We only support naive gate,                                 gshard gate and switch gate,                                 but you choose {} gate.".format(
+                        str(gate)
+                    )
                 )
         elif isinstance(gate, NaiveGate):
             self.top_k = gate.top_k

python/paddle/jit/dy2static/convert_operators.py

@@ -87,7 +87,7 @@ def _unpack_by_structure_paddle(target, structure):
         if isinstance(ele, list):
             ret.append(unpack_by_structure(target[idx], ele))
             continue
-        assert False, "structure element must be 1 or list"
+        raise AssertionError("structure element must be 1 or list")
     return ret
 
 

python/paddle/nn/layer/transformer.py

@@ -1317,9 +1317,9 @@ class Transformer(Layer):
                 encoder_bias_attr = [bias_attr[0], bias_attr[-1]]
                 decoder_bias_attr = bias_attr
             else:
-                assert (
-                    False
-                ), "length of bias_attr should be 1 or 2 or 3 when it is a list/tuple"
+                raise AssertionError(
+                    "length of bias_attr should be 1 or 2 or 3 when it is a list/tuple"
+                )
         else:
             encoder_bias_attr = bias_attr
             decoder_bias_attr = bias_attr
@@ -1339,9 +1339,9 @@ class Transformer(Layer):
                 encoder_weight_attr = [weight_attr[0], weight_attr[-1]]
                 decoder_weight_attr = weight_attr
             else:
-                assert (
-                    False
-                ), "length of weight_attr should be 1 or 2 or 3 when it is a list/tuple"
+                raise AssertionError(
+                    "length of weight_attr should be 1 or 2 or 3 when it is a list/tuple"
+                )
         else:
             encoder_weight_attr = weight_attr
             decoder_weight_attr = weight_attr

python/paddle/text/datasets/imikolov.py

@@ -168,7 +168,7 @@ class Imikolov(Dataset):
                         continue
                     self.data.append((src_seq, trg_seq))
                 else:
-                    assert False, 'Unknow data type'
+                    raise AssertionError('Unknow data type')
 
     def __getitem__(self, idx):
         return tuple([np.array(d) for d in self.data[idx]])