[Type Hints] 为公开 API 标注类型提示信息

[megemini]

commit bff34fb

⚠️提示⚠️ python/paddle/distributed 模块难度稍高，可先认领其他模块任务 🤟🤟🤟

🔚 第 1 批 🎉

序号	文件	API 数量	认领人 Github id	PR 链接
✅A-1	python/paddle/tensor/array.py	4	✅@zrr1999	#65009
✅A-2	python/paddle/tensor/attribute.py	7	✅@zrr1999	#65255
✅A-3	python/paddle/tensor/creation.py	28	✅@zrr1999	#65082
✅A-4	python/paddle/tensor/einsum.py	7	✅@zrr1999	#65255
✅A-5	python/paddle/tensor/linalg.py	40	✅@gouzil	#65274
✅A-6	python/paddle/tensor/logic.py	35	✅@Asthestarsfalll	#65300
✅A-7	python/paddle/tensor/manipulation.py	77	✅@Asthestarsfalll	#65351
✅A-8	python/paddle/tensor/math.py	192	✅@SigureMo	#65073
✅A-9	python/paddle/tensor/ops.py	43	✅@gouzil	#65249
✅A-10	python/paddle/tensor/random.py	15	✅@ooooo-create	#65272
✅A-11	python/paddle/tensor/search.py	16	✅@ooooo-create	#65354
✅A-12	python/paddle/tensor/stat.py	9	✅@ooooo-create	#65337
✅A-13	python/paddle/tensor/to_string.py	2	✅@gouzil	#65042
✅A-14	python/paddle/nn/layer/activation.py	11	✅@ooooo-create	#65372
✅A-15	python/paddle/nn/layer/common.py	20	✅@megemini	#65197
✅A-16	python/paddle/nn/layer/container.py	2	✅@SigureMo 🙋@liyongchao911	#65190
✅A-17	python/paddle/nn/layer/conv.py	7	✅@liyongchao911	#65183
✅A-18	python/paddle/nn/layer/distance.py	2	✅@liyongchao911	#65127
✅A-19	python/paddle/nn/layer/layers.py	1	✅@SigureMo 🙋@liyongchao911	#65190
✅A-20	python/paddle/nn/layer/loss.py	21	✅@Asthestarsfalll	#65376
✅A-21	python/paddle/nn/layer/norm.py	9	✅@Asthestarsfalll	#65454
✅A-22	python/paddle/nn/layer/pooling.py	18	✅@Asthestarsfalll	#65460
✅A-23	python/paddle/nn/layer/rnn.py	2	✅@Asthestarsfalll	#65375
✅A-24	python/paddle/nn/layer/transformer.py	4	✅@Asthestarsfalll	#65457
✅A-25	python/paddle/nn/layer/vision.py	4	✅@Asthestarsfalll	#65455
✅A-26	python/paddle/vision/transforms/transforms.py	22	✅@ooooo-create	#65378
✅A-27	python/paddle/nn/initializer/assign.py	3	✅@gouzil	#65206
✅A-28	python/paddle/nn/initializer/bilinear.py	2	✅@gouzil	#65206
✅A-29	python/paddle/nn/initializer/constant.py	3	✅@DrRyanHuang	#65095
✅A-30	python/paddle/nn/initializer/dirac.py	2	✅@gouzil	#65087
✅A-31	python/paddle/nn/initializer/initializer.py	2	✅@gouzil	#65087
✅A-32	python/paddle/nn/initializer/kaiming.py	5	✅@gouzil	#65206
✅A-33	python/paddle/nn/initializer/normal.py	5	✅@gouzil	#65206
✅A-34	python/paddle/nn/initializer/orthogonal.py	2	✅@DrRyanHuang	#65125
✅A-35	python/paddle/nn/initializer/uniform.py	3	✅@gouzil	#65206
✅A-36	python/paddle/nn/initializer/xavier.py	4	✅@gouzil	#65206
✅A-37	python/paddle/optimizer/adadelta.py	2	✅@ooooo-create	#65464
✅A-38	python/paddle/optimizer/adagrad.py	2	✅@ooooo-create	#65464
✅A-39	python/paddle/optimizer/adam.py	2	✅@ooooo-create	#65076
✅A-40	python/paddle/optimizer/adamax.py	2	✅@ooooo-create	#65236
✅A-41	python/paddle/optimizer/adamw.py	2	✅@ooooo-create	#65236
✅A-42	python/paddle/optimizer/asgd.py	2	✅@ooooo-create	#65236
✅A-43	python/paddle/optimizer/lamb.py	2	✅@gouzil	#65247
✅A-44	python/paddle/optimizer/lbfgs.py	2	✅@enkilee	#65308
✅A-45	python/paddle/optimizer/momentum.py	2	✅@enkilee	#65284
✅A-46	python/paddle/optimizer/nadam.py	2	✅@enkilee	#65273
✅A-47	python/paddle/optimizer/optimizer.py	1	✅@ooooo-create	#65076
✅A-48	python/paddle/optimizer/radam.py	2	✅@DrRyanHuang	#65085
✅A-49	python/paddle/optimizer/rmsprop.py	2	✅@DrRyanHuang	#65085
✅A-50	python/paddle/optimizer/rprop.py	2	✅@DrRyanHuang	#65085
✅A-51	python/paddle/optimizer/sgd.py	2	✅@ooooo-create 🙋@DrRyanHuang	#65076
✅A-52	python/paddle/hapi/model.py	2	✅@ooooo-create	#65755
✅A-53	python/paddle/hapi/model_summary.py	1	✅@DrRyanHuang	#65086
✅A-54	python/paddle/nn/functional/activation.py	36	✅@gsq7474741	#65191
✅A-55	python/paddle/nn/functional/common.py	15	✅@gsq7474741	#65191
✅A-56	python/paddle/nn/functional/conv.py	6	✅@gsq7474741	#65191
✅A-57	python/paddle/nn/functional/distance.py	2	✅@DrRyanHuang	#65071
✅A-58	python/paddle/nn/functional/extension.py	4	✅@Asthestarsfalll	#65380
✅A-59	python/paddle/nn/functional/flash_attention.py	6	✅@Asthestarsfalll	#65380
✅A-60	python/paddle/nn/functional/input.py	2	✅@sunzhongkai588	#65317
✅A-61	python/paddle/nn/functional/loss.py	29	🙋@gsq7474741 ✅@Asthestarsfalll	#65376
✅A-62	python/paddle/nn/functional/norm.py	6	🙋@gsq7474741 ✅@Asthestarsfalll	#65454
✅A-63	python/paddle/nn/functional/pooling.py	17	✅@Asthestarsfalll	#65460
✅A-64	python/paddle/nn/functional/sparse_attention.py	1	✅@Liyulingyue	#65064
✅A-65	python/paddle/nn/functional/vision.py	5	🙋@gsq7474741 ✅@Asthestarsfalll	#65455
✅A-66	python/paddle/base/dygraph/math_op_patch.py	12	✅@SigureMo	#65201
✅A-67	python/paddle/base/dygraph/tensor_patch_methods.py	20	✅@SigureMo	#65201
✅A-68	python/paddle/regularizer.py	2	✅@DrRyanHuang	#65226
✅A-69	python/paddle/optimizer/lr.py	18	✅@SigureMo	#65209
✅A-70	python/paddle/hub.py	3	✅@SigureMo	#65238
✅A-71	python/paddle/sysconfig.py	2	✅@SigureMo	#65238
✅A-72	setup.py & python/setup.pyi	8	✅@SigureMo	#65244
✅A-73	python/paddle/vision/models/alexnet.py	2	✅@DrRyanHuang	#65283
✅A-74	python/paddle/vision/models/densenet.py	6	✅@Asthestarsfalll	#65486
✅A-75	python/paddle/vision/models/googlenet.py	2	✅@DrRyanHuang	#65290
✅A-76	python/paddle/vision/models/inceptionv3.py	2	✅@DrRyanHuang	#65292
✅A-77	python/paddle/vision/models/lenet.py	1	✅@DrRyanHuang	#65283
✅A-78	python/paddle/vision/models/mobilenetv1.py	2	✅@DrRyanHuang	#65323
✅A-79	python/paddle/vision/models/mobilenetv2.py	2	✅@DrRyanHuang	#65326
✅A-80	python/paddle/vision/models/mobilenetv3.py	4	✅@enkilee	#65366
✅A-81	python/paddle/vision/models/resnet.py	14	✅@Asthestarsfalll	#65487
✅A-82	python/paddle/vision/models/shufflenetv2.py	8	✅@Asthestarsfalll	#65559
✅A-83	python/paddle/vision/transforms/functional.py	16	✅@Asthestarsfalll	#65560
✅A-84	python/paddle/vision/models/squeezenet.py	3	✅@DrRyanHuang	#65332
✅A-85	python/paddle/vision/models/vgg.py	5	✅@86kkd	#65381
✅A-86	python/paddle/vision/datasets/cifar.py	2	✅@86kkd	#65386
✅A-87	python/paddle/vision/datasets/flowers.py	1	✅@enkilee	#65504
✅A-88	python/paddle/vision/datasets/folder.py	2	✅@enkilee	#65532
✅A-89	python/paddle/vision/datasets/mnist.py	2	✅@enkilee	#65553
✅A-90	python/paddle/vision/datasets/voc2012.py	1	✅@Asthestarsfalll	#65567
✅A-91	python/paddle/metric/metrics.py	6	✅@Asthestarsfalll	#65566
✅A-92	python/paddle/vision/image.py	3	✅@86kkd	#65386
✅A-93	python/paddle/vision/ops.py	18	✅@Asthestarsfalll	#65568
✅A-94	python/paddle/signal.py	2	✅@Asthestarsfalll	#65569
✅A-95	python/paddle/fft.py	22	✅@Asthestarsfalll	#65570
✅A-96	python/paddle/hapi/callbacks.py	8	✅@zrr1999	#65777
✅A-97	python/paddle/io/dataloader/batch_sampler.py	2	✅@SigureMo	#66005
✅A-98	python/paddle/io/dataloader/dataset.py	8	✅@SigureMo	#65779
✅A-99	python/paddle/io/dataloader/sampler.py	5	✅@SigureMo	#66005
✅A-100	python/paddle/io/dataloader/worker.py	1	✅@ooooo-create	#65645

🔚 第 2 批 🎉

序号	文件	API 数量	认领人 Github id	PR 链接
✅B-01	python/paddle/io/reader.py	1	✅@enkilee	#65587
✅B-02	python/paddle/distribution/bernoulli.py	2	✅@Asthestarsfalll	#65727
✅B-03	python/paddle/distribution/beta.py	3	✅@enkilee	#65600
✅B-04	python/paddle/distribution/binomial.py	2	✅@Asthestarsfalll	#65727
✅B-05	python/paddle/distribution/categorical.py	3	✅@enkilee	#65838
✅B-06	python/paddle/distribution/cauchy.py	2	✅@megemini	#65765
✅B-07	python/paddle/distribution/chi2.py	1	✅@megemini	#65766
✅B-08	python/paddle/distribution/continuous_bernoulli.py	2	✅@megemini	#65767
✅B-09	python/paddle/distribution/dirichlet.py	2	✅@megemini	#65768
✅B-10	python/paddle/distribution/distribution.py	1	✅@megemini	#65769
✅B-11	python/paddle/distribution/exponential.py	3	✅@megemini	#65770
✅B-12	python/paddle/distribution/exponential_family.py	2	✅@megemini	#65771
✅B-13	python/paddle/distribution/gamma.py	3	✅@megemini	#65772
✅B-14	python/paddle/distribution/geometric.py	2	✅@megemini	#65773
✅B-15	python/paddle/distribution/gumbel.py	2	✅@megemini	#65774
✅B-16	python/paddle/distribution/independent.py	2	✅@megemini	#65775
✅B-17	python/paddle/distribution/kl.py	2	✅@megemini	#65776
✅B-18	python/paddle/distribution/laplace.py	2	✅@ooooo-create	#65784
✅B-19	python/paddle/distribution/lkj_cholesky.py	1	✅@ooooo-create	#65785
✅B-20	python/paddle/distribution/lognormal.py	4	✅@enkilee	#65843
✅B-21	python/paddle/distribution/multinomial.py	3	✅@enkilee	#65844
✅B-22	python/paddle/distribution/multivariate_normal.py	2	✅@enkilee	#65847
✅B-23	python/paddle/distribution/normal.py	2	✅@enkilee	#65849
✅B-24	python/paddle/distribution/poisson.py	2	✅@enkilee	#65852
✅B-25	python/paddle/distribution/student_t.py	3	✅@enkilee	#65853
✅B-26	python/paddle/distribution/transform.py	13	✅@enkilee	#65912
✅B-27	python/paddle/distribution/ transformed_distribution.py	4	✅@enkilee	#65912
✅B-28	python/paddle/distribution/uniform.py	2	✅@NKNaN	#65660
✅B-29	python/paddle/distribution/variable.py	2	✅@NKNaN	#65620
✅B-30	python/paddle/device/__init__.py	22	✅@enkilee	#66077
✅B-31	python/paddle/device/cuda/__init__.py	14	✅@enkilee	#66090
✅B-32	python/paddle/device/xpu/__init__.py	1	✅@enkilee	#66090
✅B-33	python/paddle/amp/amp_lists.py	2	✅@enkilee	#65633
✅B-34	python/paddle/amp/auto_cast.py	7	✅@enkilee	#66119
✅B-35	python/paddle/amp/debugging.py	10	✅@enkilee	#66127
✅B-36	python/paddle/amp/grad_scaler.py	4	✅@enkilee	#66189
✅B-37	python/paddle/amp/__init__.py	2	✅@enkilee	#65633
✅B-38	python/paddle/autograd/autograd.py	2	🙋@Turingg ✅@enkilee	#67179
✅B-39	python/paddle/autograd/saved_tensors_hooks.py	1	🙋@DrRyanHuang ✅@enkilee	#67179
✅B-40	python/paddle/autograd/backward_mode.py	1	✅@tlxd	#66277
✅B-41	python/paddle/autograd/ir_backward.py	3	✅@Luohongzhige	#66890
✅B-42	python/paddle/autograd/py_layer.py	2	✅@Fripping	#66328
✅B-43	python/paddle/framework/framework.py	2	✅@zrr1999	#65777
✅B-44	python/paddle/base/dygraph/base.py	7	✅@SigureMo	#66006
✅B-45	python/paddle/framework/io.py	4	🙋@Luohongzhige ✅@SigureMo	#66654
✅B-46	python/paddle/framework/io_utils.py	3	🙋@Luohongzhige ✅@SigureMo	#66654
✅B-47	python/paddle/framework/random.py	5	✅@SigureMo	#66306
✅B-48	python/paddle/cost_model/cost_model.py	1	✅@Luohongzhige	#66890
✅B-49	python/paddle/base/layer_helper.py	1	✅@ooooo-create	#66639
✅B-50	python/paddle/static/input.py	3	✅@ooooo-create	#67047
✅B-51	python/paddle/static/io.py	16	✅@ooooo-create	#67047
✅B-52	python/paddle/onnx/export.py	1	🙋@ooooo-create ✅@enkilee	#66862
✅B-53	python/paddle/utils/cpp_extension/cpp_extension.py	2	✅@megemini	#65818
✅B-54	python/paddle/utils/cpp_extension/ extension_utils.py	3	✅@megemini	#65819
✅B-55	python/paddle/utils/install_check.py	1	✅@megemini	#65821
✅B-56	python/paddle/utils/lazy_import.py	1	✅@megemini	#65822
✅B-57	python/paddle/utils/dlpack.py	2	✅@megemini	#65823
✅B-58	python/paddle/utils/download.py	1	✅@megemini	#65824
✅B-59	python/paddle/text/viterbi_decode.py	2	✅@enkilee	#65919
✅B-60	python/paddle/text/datasets/conll05.py	1	✅@enkilee	#65993
✅B-61	python/paddle/text/datasets/imdb.py	1	✅@enkilee	#66037
✅B-62	python/paddle/text/datasets/imikolov.py	1	✅@enkilee	#66040
✅B-63	python/paddle/text/datasets/movielens.py	1	✅@enkilee	#66054
✅B-64	python/paddle/text/datasets/uci_housing.py	1	✅@enkilee	#66057
✅B-65	python/paddle/text/datasets/wmt14.py	1	✅@enkilee	#66058
✅B-66	python/paddle/text/datasets/wmt16.py	1	✅@enkilee	#66058
✅B-67	python/paddle/sparse/binary.py	10	✅@megemini	#65865
✅B-68	python/paddle/sparse/creation.py	2	✅@megemini	#65866
✅B-69	python/paddle/sparse/multiary.py	1	✅@megemini	#65867
✅B-70	python/paddle/sparse/unary.py	25	✅@megemini	#65868
✅B-71	python/paddle/sparse/nn/layer/activation.py	4	✅@megemini	#65869
✅B-72	python/paddle/sparse/nn/layer/conv.py	4	✅@megemini	#65870
✅B-73	python/paddle/sparse/nn/layer/norm.py	2	✅@megemini	#65871
✅B-74	python/paddle/sparse/nn/layer/pooling.py	1	✅@megemini	#65872
✅B-75	python/paddle/sparse/nn/functional/activation.py	4	✅@megemini	#65873
✅B-76	python/paddle/sparse/nn/functional/conv.py	6	✅@megemini	#65874
✅B-77	python/paddle/sparse/nn/functional/pooling.py	1	✅@megemini	#65875
✅B-78	python/paddle/sparse/nn/functional/transformer.py	1	✅@megemini	#65876
✅B-79	python/paddle/profiler/profiler.py	11	✅@megemini 🙋@Luohongzhige	#67391
✅B-80	python/paddle/profiler/profiler_statistic.py	2	✅@megemini 🙋@Luohongzhige	#67391
✅B-81	python/paddle/profiler/utils.py	3	✅@megemini 🙋@Luohongzhige	#67391
✅B-82	python/paddle/nn/quant/quant_layers.py	13	✅@megemini	#65803
✅B-83	python/paddle/nn/quant/quantized_linear.py	4	✅@megemini	#65805
✅B-84	python/paddle/nn/quant/stub.py	1	✅@megemini	#65807
✅B-85	python/paddle/nn/utils/clip_grad_norm_.py	1	✅@megemini	#65808
✅B-86	python/paddle/nn/utils/clip_grad_value_.py	1	✅@megemini	#65809
✅B-87	python/paddle/nn/utils/spectral_norm_hook.py	1	✅@megemini	#65810
✅B-88	python/paddle/nn/utils/transform_parameters.py	2	✅@megemini	#65811
✅B-89	python/paddle/nn/utils/weight_norm_hook.py	2	✅@megemini	#65812
✅B-90	python/paddle/inference/wrapper.py	7	🙋@Luohongzhige ✅@enkilee	#67366
✅B-91	python/paddle/check_import_scipy.py	1	✅@crazyxiaoxi	#66280
✅B-92	python/paddle/batch.py	1	✅@Caogration	#66295
✅B-93	python/paddle/reader/decorator.py	10	✅@SigureMo	#66305
✅B-94	python/paddle/hapi/dynamic_flops.py	3	🙋@Luohongzhige ✅@enkilee	#67204
✅B-95	python/paddle/hapi/static_flops.py	1	🙋@Wizard-ZP
✅B-96	python/paddle/base/framework.py	4	✅@SigureMo	#66301
✅B-97	python/paddle/distributed/collective.py	4	✅@enkilee	#66392
✅B-98	python/paddle/distributed/entry_attr.py	3	✅@enkilee	#66394
✅B-99	python/paddle/distributed/parallel.py	7	✅@enkilee	#66432
✅B-100	python/paddle/distributed/parallel_with_gloo.py	3	✅@enkilee	#66473

🔚 第 3 批 🎉

序号	文件	API 数量	认领人 Github id	PR 链接
✅C-1	python/paddle/distributed/spawn.py	1	✅@megemini 🙋@Luohongzhige	#67428
✅C-2	python/paddle/distributed/rpc/rpc.py	7	✅@megemini 🙋@Luohongzhige	#67428
✅C-3	python/paddle/distributed/auto_parallel/api.py	4	✅@megemini 🙋@Luohongzhige	#67428
✅C-4	python/paddle/distributed/auto_parallel/ interface.py	9	🚧@lwkhahaha	#66710
✅C-5	python/paddle/distributed/auto_parallel/ process_mesh.py	1	✅@megemini	#66985
✅C-6	python/paddle/distributed/auto_parallel/random.py	1	✅@megemini	#66985
✅C-7	python/paddle/distributed/auto_parallel/ strategy.py	2	🚧@lwkhahaha	#66710
✅C-8	python/paddle/distributed/auto_parallel/static/ engine.py	1	✅@megemini	#66989
✅C-9	python/paddle/distributed/auto_parallel/ placement_type.py	3	🚧@lwkhahaha	#66710
✅C-10	python/paddle/distributed/checkpoint/ load_state_dict.py	1	✅@megemini	#66986
✅C-11	python/paddle/distributed/checkpoint/ save_state_dict.py	1	✅@megemini	#66986
✅C-12	python/paddle/distributed/communication/ all_gather.py	3	✅@megemini	#66051
✅C-13	python/paddle/distributed/communication/ all_reduce.py	3	✅@enkilee	#66505
✅C-14	python/paddle/distributed/communication/ all_to_all.py	3	✅@enkilee	#66505
✅C-15	python/paddle/distributed/communication/ batch_isend_irecv.py	2	🙋@Lans1ot ✅@enkilee	#66572
✅C-16	python/paddle/distributed/communication/ broadcast.py	3	🙋@Lans1ot ✅@enkilee	#66575
✅C-17	python/paddle/distributed/communication/gather.py	2	✅@BHmingyang	#66276
✅C-18	python/paddle/distributed/communication/group.py	6	🙋@lwkhahaha ✅@Lans1ot	#67677
✅C-19	python/paddle/distributed/communication/recv.py	3	✅@Lans1ot	#66694
✅C-20	python/paddle/distributed/communication/reduce.py	3	✅@megemini 🙋@successfulbarrier	#66803
✅C-21	python/paddle/distributed/communication/ reduce_scatter.py	3	✅@Lans1ot 🙋@Whsjrczr	#66864
✅C-22	python/paddle/distributed/communication/scatter.py	3	✅@Lans1ot 🙋@Whsjrczr	#66864
✅C-23	python/paddle/distributed/communication/send.py	3	✅@Lans1ot 🙋@Whsjrczr	#66864
✅C-24	python/paddle/distributed/communication/stream/ all_gather.py	1	✅@Lans1ot 🙋@Whsjrczr	#66864
✅C-25	python/paddle/distributed/communication/stream/ all_reduce.py	1	🙋@Whsjrczr ✅@enkilee	#67112
✅C-26	python/paddle/distributed/communication/stream/ all_to_all.py	2	🙋@Whsjrczr ✅@enkilee	#67112
✅C-27	python/paddle/distributed/communication/stream/ broadcast.py	1	✅@megemini	#66993
✅C-28	python/paddle/distributed/communication/stream/ gather.py	1	✅@megemini	#66993
✅C-29	python/paddle/distributed/communication/stream/ recv.py	1	✅@megemini	#66993
✅C-30	python/paddle/distributed/communication/stream/ reduce.py	1	✅@megemini	#66993
✅C-31	python/paddle/distributed/communication/stream/ reduce_scatter.py	1	✅@megemini	#66993
✅C-32	python/paddle/distributed/communication/stream/ scatter.py	1	✅@megemini	#66993
✅C-33	python/paddle/distributed/communication/stream/ send.py	1	✅@megemini	#66993
✅C-34	python/paddle/distributed/fleet/fleet.py	4	✅@Luohongzhige	#67624
✅C-35	python/paddle/distributed/fleet/launch.py	3	🙋@Luohongzhige
✅C-36	python/paddle/distributed/fleet/launch_utils.py	1
✅C-37	python/paddle/distributed/fleet/model.py	2
✅C-38	python/paddle/distributed/fleet/optimizer.py	2
✅C-39	python/paddle/distributed/fleet/scaler.py	2
✅C-40	python/paddle/distributed/fleet/base/ distributed_strategy.py	1	✅@Whsjrczr	#67405
✅C-41	python/paddle/distributed/fleet/base/ role_maker.py	3	✅@Whsjrczr	#67439
✅C-42	python/paddle/distributed/fleet/base/topology.py	2	✅@Whsjrczr	#67439
✅C-43	python/paddle/distributed/fleet/base/ util_factory.py	1	✅@Whsjrczr	#67469
✅C-44	python/paddle/distributed/fleet/data_generator/ data_generator.py	2	✅@Whsjrczr	#67469
✅C-45	python/paddle/distributed/fleet/dataset/ dataset.py	5	✅@megemini 🙋@lwkhahaha	#66749
✅C-46	python/paddle/distributed/fleet/dataset/ index_dataset.py	1	✅@megemini	#66760
✅C-47	python/paddle/distributed/fleet/utils/fs.py	2	✅@megemini	#66766
✅C-48	python/paddle/distributed/fleet/utils/ hybrid_parallel_inference.py	1	🙋@megemini
✅C-49	python/paddle/distributed/fleet/utils/ mix_precision_utils.py	1	🙋@megemini
✅C-50	python/paddle/distributed/fleet/utils/ps_util.py	1	✅@megemini	#66770
✅C-51	python/paddle/distributed/fleet/utils/ sequence_parallel_utils.py	1	🙋@megemini
✅C-52	python/paddle/distributed/fleet/utils/ __init__.py	1	✅@megemini	#66771
✅C-53	python/paddle/distributed/launch/main.py	1	✅@megemini	#66994
✅C-54	python/paddle/distributed/sharding/ group_sharded.py	2	✅@megemini	#66994
✅C-55	python/paddle/incubate/autotune.py	1	✅@megemini	#66009
✅C-56	python/paddle/incubate/asp/asp.py	6	✅@megemini	#66010
✅C-57	python/paddle/incubate/asp/ supported_layer_list.py	2	✅@megemini	#66011
✅C-58	python/paddle/incubate/asp/utils.py	10	✅@megemini	#66012
✅C-59	python/paddle/incubate/autograd/functional.py	6	✅@megemini	#66013
✅C-60	python/paddle/incubate/autograd/primapi.py	4	✅@megemini	#66016
✅C-61	python/paddle/incubate/autograd/primx.py	1	✅@megemini	#66015
✅C-62	python/paddle/incubate/autograd/utils.py	3	✅@megemini	#66014
✅C-63	python/paddle/incubate/framework/random.py	3	✅@megemini	#66028
✅C-64	python/paddle/incubate/layers/nn.py	15	✅@megemini	#66029
✅C-65	python/paddle/incubate/multiprocessing/ reductions.py	1	✅@megemini	#66030
✅C-66	python/paddle/incubate/nn/loss.py	1	✅@uanu2002	#66270
✅C-67	python/paddle/incubate/nn/functional/ blha_get_max_len.py	1	✅@MikhayEeer	#66616
✅C-68	python/paddle/incubate/nn/functional/ block_multihead_attention.py	2	🙋@lwkhahaha ✅@Lans1ot	#67677
✅C-69	python/paddle/incubate/nn/functional/ fused_dot_product_attention.py	1	✅@MikhayEeer	#66616
✅C-70	python/paddle/incubate/nn/functional/ fused_dropout_add.py	1	✅@Jeff114514	#66279
✅C-71	python/paddle/incubate/nn/functional/ fused_ec_moe.py	1	✅@MikhayEeer	#66616
✅C-72	python/paddle/incubate/nn/functional/ fused_gate_attention.py	1	✅@MikhayEeer	#66616
✅C-73	python/paddle/incubate/nn/functional/ fused_layer_norm.py	1	✅@haoyu2022	#67159
✅C-74	python/paddle/incubate/nn/functional/ fused_matmul_bias.py	3	✅@Betelgeu	#66656
✅C-75	python/paddle/incubate/nn/functional/ fused_rms_norm.py	1	✅@haoyu2022	#67555
✅C-76	python/paddle/incubate/nn/functional/ fused_rotary_position_embedding.py	1	✅@haoyu2022	#67556
✅C-77	python/paddle/incubate/nn/functional/ fused_transformer.py	4	🙋@lwkhahaha ✅@Lans1ot	#67677
✅C-78	python/paddle/incubate/nn/functional/ masked_multihead_attention.py	1	✅@haoyu2022	#67558
✅C-79	python/paddle/incubate/nn/functional/swiglu.py	1	✅@Turingg	#66987
✅C-80	python/paddle/incubate/nn/functional/ variable_length_memory_efficient_attention.py	1	✅@inaomIIsfarell	#67197
✅C-81	python/paddle/incubate/nn/layer/ fused_dropout_add.py	1	✅@Lans1ot	#67233
✅C-82	python/paddle/incubate/nn/layer/ fused_dropout_nd.py	1
✅C-83	python/paddle/incubate/nn/layer/fused_ec_moe.py	1	🙋@Whsjrczr ✅@enkilee	#67143
✅C-84	python/paddle/incubate/nn/layer/fused_linear.py	1	🙋@brcarry ✅@enkilee	#67147
✅C-85	python/paddle/incubate/nn/layer/ fused_transformer.py	5	🙋@lwkhahaha ✅@enkilee	#67178
✅C-86	python/paddle/incubate/operators/ graph_khop_sampler.py	1	✅@inaomIIsfarell	#67197
✅C-87	python/paddle/incubate/operators/ graph_reindex.py	1	✅@Wizard-ZP	#66475
✅C-88	python/paddle/incubate/operators/ graph_sample_neighbors.py	1	✅@Sekiro-x	#67104
✅C-89	python/paddle/incubate/operators/ graph_send_recv.py	1	✅@Sekiro-x	#67104
✅C-90	python/paddle/incubate/operators/resnet_unit.py	2	✅@inaomIIsfarell	#66793
✅C-91	python/paddle/incubate/operators/ softmax_mask_fuse.py	1	✅@inaomIIsfarell	#66867
✅C-92	python/paddle/incubate/operators/ softmax_mask_fuse_upper_triangle.py	1	✅@inaomIIsfarell	#66867
✅C-93	python/paddle/incubate/operators/unzip.py	1	✅@inaomIIsfarell	#66966
✅C-94	python/paddle/incubate/optimizer/ distributed_fused_lamb.py	1
✅C-95	python/paddle/incubate/optimizer/lookahead.py	1	✅@inaomIIsfarell	#67448
✅C-96	python/paddle/incubate/optimizer/modelaverage.py	1	✅@inaomIIsfarell	#67448
✅C-97	python/paddle/incubate/optimizer/ gradient_merge.py	1
✅C-98	python/paddle/incubate/optimizer/ lars_momentum.py	1
✅C-99	python/paddle/incubate/optimizer/lbfgs.py	1	✅@inaomIIsfarell	#67448
✅C-100	python/paddle/incubate/optimizer/pipeline.py	1
✅C-101	python/paddle/incubate/optimizer/recompute.py	1
✅C-102	python/paddle/incubate/optimizer/functional/ bfgs.py	1	✅@Lans1ot	#67233
✅C-103	python/paddle/incubate/optimizer/functional/ lbfgs.py	1	✅@Lans1ot	#67233
✅C-104	python/paddle/incubate/passes/ fuse_resnet_unit_pass.py:fuse_resnet_unit_pass	1
✅C-105	python/paddle/incubate/tensor/math.py	4	✅@Lans1ot	#67233
✅C-106	python/paddle/base/backward.py	2	✅@megemini	#67132
✅C-107	python/paddle/base/compiler.py	4	✅@megemini 🙋@haoyu2022 🙋@lwkhahaha	#67767
✅C-108	python/paddle/base/data_feed_desc.py	1
✅C-109	python/paddle/base/data_feeder.py	1	✅@megemini	#67132
✅C-110	python/paddle/base/dataset.py	3	🙋@lwkhahaha
✅C-111	python/paddle/base/executor.py	3	🙋@lwkhahaha ✅@SigureMo	#66996
✅C-112	python/paddle/base/initializer.py	1	✅@SigureMo	#67001
✅C-113	python/paddle/base/lod_tensor.py	2
✅C-114	python/paddle/base/param_attr.py	2	✅@SigureMo	#67001
✅C-115	python/paddle/geometric/math.py	4	🙋@haoyu2022 🙋@lwkhahaha ✅@enkilee	#67644
✅C-116	python/paddle/geometric/reindex.py	2	✅@successfulbarrier	#66792
✅C-117	python/paddle/geometric/sampling/neighbors.py	2	✅@successfulbarrier	#66792
✅C-118	python/paddle/geometric/message_passing/ send_recv.py	3	🙋@lwkhahaha ✅@enkilee	#67644
✅C-119	python/paddle/quantization/config.py	1	✅@enkilee	#66684
✅C-120	python/paddle/quantization/base_quanter.py	1	✅@enkilee	#66686
✅C-121	python/paddle/quantization/base_observer.py	1	✅@enkilee	#66693
✅C-122	python/paddle/quantization/factory.py	1	✅@enkilee	#66693
✅C-123	python/paddle/quantization/ptq.py	1	✅@enkilee	#66693
✅C-124	python/paddle/quantization/qat.py	1	✅@enkilee	#66693
✅C-125	python/paddle/audio/backends/init_backend.py	3	✅@SigureMo	#67002
✅C-126	python/paddle/audio/backends/wave_backend.py	3	✅@SigureMo	#67002
✅C-127	python/paddle/audio/datasets/esc50.py	1	✅@enkilee	#67067
✅C-128	python/paddle/audio/datasets/tess.py	1	✅@enkilee	#67067
✅C-129	python/paddle/audio/features/layers.py	4	✅@enkilee	#67079
✅C-130	python/paddle/audio/functional/functional.py	7	✅@enkilee	#67079
✅C-131	python/paddle/audio/functional/window.py	1	✅@enkilee	#67079
✅C-132	python/paddle/nn/clip.py	3	✅@megemini	#67031
✅C-133	python/paddle/nn/decode.py	2	✅@megemini	#67031
✅C-134	python/paddle/nn/initializer/lazy_init.py::LazyGuard	1	✅@megemini	#67031
✅C-135	python/paddle/distributed/fleet/layers/mpu/mp_ops.py::split	1	✅@megemini	#67089
✅C-136	python/paddle/distributed/fleet/recompute/ recompute.py::recompute_sequential	1	✅@megemini	#67089
✅C-137	python/paddle/distributed/fleet/recompute/ recompute_hybrid.py::recompute_hybrid	1	✅@megemini	#67089

注意：上述 API 数量仅为参考，若多个模块之间相互引用，会导致统计数量增多。

---

⭐️ 提交PR 模版 ⭐️：

• // ------- PR 标题 --------

[Typing][A-1] Add type annotations for `paddle/tensor/array.py`

或者多个任务：

[Typing][A-1,A-2,A-3] Add type annotations for `paddle/tensor/*`

⭐️ 认领方式 ⭐️：
请大家以 comment 的形式认领任务，如：

【报名】：A-1、A-3

状态介绍：
✅：已经完全迁移，所有单测都OK！
🟢：审核完毕待合入，合入之后完全迁移！
🔵：可认领！
🟡：当前阶段不需要人力继续跟进，下阶段推进
🚧：迁移中，单测还没有过，还没有审核完。

大致正常流程为:
🔵 -> 🚧 -> 🟢 -> ✅

异常流程为:
🔵 -> 🚧 -> 🟡

看板信息

📊任务数量	🔵可认领	🚧迁移中	🟢待合入	✅完成	🟡下阶段推进	🏁完成率
337	0	0	0	337	0	100.0%

排名不分先后 @zrr1999(6) @gouzil(12) @Asthestarsfalll(25) @SigureMo(23) @ooooo-create(20) @megemini(86) @liyongchao911(2) @DrRyanHuang(15) @enkilee(65) @gsq7474741(3) @sunzhongkai588(1) @Liyulingyue(1) @86kkd(3) @NKNaN(2) @tlxd(1) @Luohongzhige(3) @Fripping(1) @crazyxiaoxi(1) @Caogration(1) @BHmingyang(1) @Lans1ot(12) @Whsjrczr(5) @uanu2002(1) @MikhayEeer(4) @Jeff114514(1) @haoyu2022(4) @Betelgeu(1) @Turingg(1) @inaomIIsfarell(9) @Wizard-ZP(1) @Sekiro-x(2) @successfulbarrier(2)

[megemini]

✨️ 大家好！✨️

此次任务为 为 Paddle 框架 API 添加类型提示（Type Hints） 的子任务。

即，将原本的 裸 函数：

def log(x, name=None):
    ...

标注为：

def log(x: paddle.Tensor, name: str | None = None) -> paddle.Tensor:
    ...

Python 在 3.5 版本通过 PEP 484 – Type Hints 正式规范了 类型提示 功能，可以提升开发者的使用体验并提高代码质量。Paddle 目前最低支持的 Python 版本 3.8 已经可以较好的支持 类型提示，特发起此次任务，旨在完成 Paddle 目前公开 API 的类型标注！

欢迎大家参与! 非常感谢！：） 🎉🎉🎉

此次参与的流程大致为：

• 任务认领
• 修改接口
• 提交 PR
• 任务收尾

✨ 点击下列标题查看详情！✨

✨ 任务认领

直接在 ISSUE 下回复认领的任务 ID 即可，如：

【报名】：A-25

✨ 修改接口

Python 的类型标注是个较为庞杂的体系，此次任务主要做以下几个事情：

• 添加接口的类型标注
• 统一接口的类型标注与文档中的类型说明
• 通过类型检查工具对于相关接口示例代码的类型检测

➡️ 参考示例

以 paddle.log 这个接口为例，原代码为：

def log(x, name=None):
    r"""
    Calculates the natural log of the given input Tensor, element-wise.

    .. math::

        Out = \ln(x)

    Args:
        x (Tensor): Input Tensor. Must be one of the following types: int32, int64, float16, bfloat16, float32, float64, complex64, complex128.
        name (str|None): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name`

    Returns:
        Tensor: The natural log of the input Tensor computed element-wise.

    Examples:
        ...
    """
    ...

需要修改为：

from __future__ import annotations

...

def log(x: paddle.Tensor, name: str | None = None) -> paddle.Tensor:
    r"""
    Calculates the natural log of the given input Tensor, element-wise.

    .. math::

        Out = \ln(x)

    Args:
        x (Tensor): Input Tensor. Must be one of the following types: int32, int64, float16, bfloat16, float32, float64, complex64, complex128.
        name (str|None, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name`

    Returns:
        Tensor: The natural log of the input Tensor computed element-wise.

    Examples:
        ...
    """
    ...

此处需要注意以下几个地方：

• 添加 from __future__ import annotations

  由于目前 Paddle 的最低 Python 支持版本为 3.8，而此次任务希望尽可能的使用较新 Python 版本的标注特性，因此，有必要添加此模块。

• 为 def log(x, name=None) 添加类型标注

  输入参数与输出参数均需要添加。

• 对齐 docstring 中的类型与实际参数类型

  此处，name=None ，实际的参数标注为 name: str | None = None，对应 docstring 应为 name (str|None, optional) 。

  注意，Python 中原有的类型 Optional 与 docstring 中的 optional 意义不同：

  • 前者，表示输入可以为 None
  • 后者，表示此参数有默认值。此默认值可以是 None ，也可以是任意值。

  另外，docstring 的写法应注意：

  • Args 尽量保持简洁，如 paddle.Tensor 可写为 Tensor
  • Returns 的格式应写为： return type, description 的形式，如 Tensor, The natural log of the input Tensor computed element-wise.

更多详细的说明，请参考本 ISSUE 下面的 《标注 Q&A》 与 《常用类型参照》。

➡️ 相关工具

• https://github.com/megemini/ArgsTyping

利用这个工具，可以初步的进行类型标注，如：

> python args_typing.py -i /home/shun/Documents/Projects/paddle/megemini/Paddle/python/paddle/tensor/math.py

注意：此工具通过解析 docstring 中的 Args/Parameters 与 Returns/Yields 进行类型标注，因此，存在标注错误与不完整的可能。

• tools/type_checking.py

利用这个工具，可以在本地对修改的接口进行检查，如：

> python type_checking.py paddle.abs

注意：此用法依赖 PR #64991 的完成。

✨ 提交 PR

每个任务需要提交至少一个 PR：

PR 标题：

• [Typing][A-1] Add type annotations for paddle/tensor/array.py

一个 PR 里提交多个任务可以使用

• [Typing][A-1,A-2,A-3] Add type annotations for paddle/tensor/*

上面的 xxx 可以是其他补充信息，如，多次提交 PR 的话，可以补充此 PR 的主要文件。

注意：标题中请务必标注 [Typing] ，以触发 CI 流水线检查。另外，请务必统一标题格式，以方便后续进行统计。

提交 PR 可直接复制以下模板，修改相应的 xxx 部分，也可补充说明：

<!-- TemplateReference: https://github.com/PaddlePaddle/Paddle/wiki/PULL-REQUEST-TEMPLATE--REFERENCE -->
<!-- Demo: https://github.com/PaddlePaddle/Paddle/pull/24810 -->

### PR Category
<!-- One of [ User Experience | Execute Infrastructure | Operator Mechanism | CINN | Custom Device | Performance Optimization | Distributed Strategy | Parameter Server | Communication Library | Auto Parallel | Inference | Environment Adaptation ] -->
User Experience

### PR Types
<!-- One of [ New features | Bug fixes | Improvements | Performance | BC Breaking | Deprecations | Docs | Devs | Not User Facing | Security | Deprecations | Others ] -->
Improvements

### Description
<!-- Describe what you’ve done -->

类型标注：

- xxx.py
- xxx.py

### Related links
 
- https://github.com/PaddlePaddle/Paddle/issues/65008

@SigureMo @megemini 

另外，由于类型标注存在接口依赖的可能，因此，如果 PR 由于其他接口而阻塞，请告知 reviewer 安排处理。

✨ 任务收尾

PR 提交之后，需要在 CI 流水线中确认：

• PR-CI-Static-Check

  • 是否修改的文件，其中 所有 的 API 都已进行测试 type checking。
  • 是否上面 所有 的测试都已通过。

最后，任务收尾：

• Merge/Close Paddle 代码的 PR

顺便提醒 reviewer 在此 ISSUE 中 check 任务的状态～

至此，一个任务就算是圆满完工！🎉🎉🎉

最后，再次感谢大家的参与与贡献 ～ 🏆️🏆️🏆️

参考项目：

• https://github.com/cattidea/paddlepaddle-stubs

优秀 PR 赏析：

• [Typing] Add type annotations for paddle.jit #64867
• [Typing] Add type annotations for base decorators #64954

关联链接：

• 为 Paddle 框架 API 添加类型提示（Type Hints）Tracking Issue #63597
• 【Hackathon 6th】为 Paddle 框架 API 添加类型提示（Type Hints） community#858
• 为 Paddle 框架 API 添加类型提示（Type Hints）
• https://github.com/megemini/ArgsTyping

Python 文档：

• PEP 484 – Type Hints
• Typing PEPs
• Static Typing with Python

@SigureMo @zrr1999 @Asthestarsfalll @gouzil @gsq7474741 @sunzhongkai588 @luotao1

[megemini]

标注 Q&A

问: 我该如何下手？

答：Python 的类型标注特性一直在完善，目前已经是个相对庞大的体系了。

可以先学习一下 Python 官方的文档：Static Typing with Python，熟悉一下相关的 PEP 。

以 通过 CI 检查 作为最基础的实现目标。

另外，目前 Paddle 添加了 _typing 模块，对于一些常用的公用类型做了统一整理，如：

# python/paddle/_typing/layout.py
DataLayout2D: TypeAlias = Literal["NCHW", "NHCW"]
DataLayout3D: TypeAlias = Literal["NCDHW", "NDHWC"]

标注时应尽量使用 _typing 模块中的类型，以方便后续维护。

问: docstring 中的 Args 与 type annotation 有什么区别？

答：Paddle 之前的版本未统一进行类型标注，而在 docstring 中描述了参数类型。
docstring 中 Args 的参数类型以方便用户理解为目的，在与 type annotation 不冲突的前提下，可以保持简洁。如：

def test(a: int | list[int] | tuple[int, ...]) -> None:
    """
    ...
    
    Args:
        a (int|list|tuple): xxx

    Returns:
        None, xxx

    ...
    """

问: docstring 中的 Args 与 type annotation 不一致怎么办？

答：首先需要保证 type annotation 的正确性，如果 docstring 原有 Args 中的类型不正确，需要进行修改，并且，同时检查此接口的 中文文档 (即 docs)是否正确，如发现错误，需要对 docs 单独提 PR 进行修改。

问: 该使用 Union 还是 | ？

答：尽可能的使用 |。

由于目前 Paddle 支持的 Python 最低版本为 3.8 ，因此，| 只能在类型标注的情况下使用，而不能在表达式中使用，如：

from __future__ import annotations
def test(a: int | str): ...

而在表达式中仍使用 Union ：

from typing import Union
t = Union[int, str]

问: 如果测试无法通过怎么办？

答：可以使用 # type: ignore 进行规避。

此次任务通过工具 (如 mypy) 对接口的示例代码进行检查，进而保证类型标注的正确性。

类型标注的过程中，难免产生接口依赖问题，如果依赖的是 私有接口 或 外部接口 ，则可以使用 # type: ignore 规避相应的类型检查，如：

>>> import abcde # type: ignore
>>> print('ok')

或者规避整个代码检查：

>>> # type: ignore
>>> import abcde
>>> print('ok')

问: 能否使用 Any 类型？

答：可以，但应尽量避免。

问: 如果出现 circular import 错误怎么办？

答：出现此情况可以参考以下处理方法：

• 添加 from __future__ import annotations

• 将类型单独通过 typing.TYPE_CHECKING 引入，如：

  from typing import TYPE_CHECKING
  if TYPE_CHECKING:
      import paddle.xxx as xxx
      
  def tmp() -> xxx: ...

  另外，如果标注的类型仅用作 type hints，也尽可能的使用 TYPE_CHECKING ，以减少不必要的模块导入。

问: 使用 Tensor 还是 Variable？

答：尽量使用 Tensor ，不将静态图的 Variable/Value 概念暴露给用户。

更详细的讨论可以参考 PaddlePaddle/community#858 (comment)

问: 如果遇到需要根据不同输入类型有不同输出类型的函数怎么办？

答：出现此情况可以参考以下处理方法：

• 添加 from typing import overload

• 标注多个同名函数，并用装饰器装饰，如：

  from typing import overload
      
  @overload
  def array_length(array: list[Any]) -> int:...
  
  @overload
  def array_length(array: paddle.Tensor) -> paddle.Tensor:...
  
  def array_length(array): ... # 具体实现的代码，不再进行标注

问: 什么时候用 Sequence ，什么时候用 list 和 tuple？

答：Python 的 PEP 中有提示：

Note: Dict, DefaultDict, List, Set and FrozenSet are mainly useful for annotating return values. For arguments, prefer the abstract collection types defined below, e.g. Mapping, Sequence or AbstractSet.

也就是说，输入中用 Sequence ，返回值用 list 。

但是，如果代码中使用到了 list 的方法，如 append ，或者明确表示此输入只能是 list ，则不应再使用 Sequence 。

问: 标注的时候用 Tensor 还是 paddle.Tensor？

答：两者皆可。

若文件中出现较多 paddle.Tensor ，出于简洁的考虑，可以使用 Tensor 代替，但是需要在导入包时注意：

if TYPE_CHECKING:
    from paddle import Tensor

可参考讨论：#65073 (comment)

问: 该用 paddle.framework.Block 还是 paddle.pir.Block？

答：统一使用 paddle.pir.Block。

可参考讨论：#65095 (comment)

[megemini]

python 3.8 至 python 3.9 类型标注映射表

旧类型	新类型
typing.Tuple	tuple
typing.List	list
typing.Dict	dict
typing.Set	set
typing.FrozenSet	frozenset
typing.Type	type
typing.Deque	collections.deque
typing.DefaultDict	collections.defaultdict
typing.OrderedDict	collections.OrderedDict
typing.Counter	collections.Counter
typing.ChainMap	collections.ChainMap
typing.Awaitable	collections.abc.Awaitable
typing.Coroutine	collections.abc.Coroutine
typing.AsyncIterable	collections.abc.AsyncIterable
typing.AsyncIterator	collections.abc.AsyncIterator
typing.AsyncGenerator	collections.abc.AsyncGenerator
typing.Iterable	collections.abc.Iterable
typing.Iterator	collections.abc.Iterator
typing.Generator	collections.abc.Generator
typing.Reversible	collections.abc.Reversible
typing.Container	collections.abc.Container
typing.Collection	collections.abc.Collection
typing.Callable	collections.abc.Callable
typing.AbstractSet	collections.abc.Set
typing.MutableSet	collections.abc.MutableSet
typing.Mapping	collections.abc.Mapping
typing.MutableMapping	collections.abc.MutableMapping
typing.Sequence	collections.abc.Sequence
typing.MutableSequence	collections.abc.MutableSequence
typing.MappingView	collections.abc.MappingView
typing.KeysView	collections.abc.KeysView
typing.ItemsView	collections.abc.ItemsView
typing.ValuesView	collections.abc.ValuesView
typing.ContextManager	contextlib.AbstractContextManager
typing.AsyncContextManager	contextlib.AbstractAsyncContextManager
typing.Pattern	re.Pattern
typing.re.Pattern	re.Pattern
typing.Match	re.Match
typing.re.Match	re.Match

常用类型标注参照

变量	标注
name=None	name: str | None = None