Add distributions of normal and uniform (#18023)

* add_distributions_of_normal_and_uniform

* paddle/fluid/API.spec

* modify API.spec

* modified paddle/fluid/API.spec, test=develop

* modify paddle/fluid/API.spec, test=develop

* modify paddle/fluid/API.spec, test=develop

* fix some comment, test=develop

* modify API.spec, test=develop

* add comment for init function, modify hard code, test=develop

* modify API.spec, test=develop

* modify API.spec, test=develop

* make unit test function shorter, test=develop

* modify paddle/fluid/API.spec

paddle/fluid/API.spec

@@ -407,6 +407,18 @@ paddle.fluid.layers.piecewise_decay (ArgSpec(args=['boundaries', 'values'], vara
 paddle.fluid.layers.noam_decay (ArgSpec(args=['d_model', 'warmup_steps'], varargs=None, keywords=None, defaults=None), ('document', 'fd57228fb76195e66bbcc8d8e42c494d'))
 paddle.fluid.layers.cosine_decay (ArgSpec(args=['learning_rate', 'step_each_epoch', 'epochs'], varargs=None, keywords=None, defaults=None), ('document', 'f0d65d8c89d0fe78051ca689daa15e35'))
 paddle.fluid.layers.linear_lr_warmup (ArgSpec(args=['learning_rate', 'warmup_steps', 'start_lr', 'end_lr'], varargs=None, keywords=None, defaults=None), ('document', 'dc7292c456847ba41cfd318e9f7f4363'))
+paddle.fluid.layers.Uniform ('paddle.fluid.layers.distributions.Uniform', ('document', 'af70e7003f437e7a8a9e28cded35c433'))
+paddle.fluid.layers.Uniform.__init__ (ArgSpec(args=['self', 'low', 'high'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
+paddle.fluid.layers.Uniform.entropy (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'ba59f9ce77af3c93e2b4c8af1801a24e'))
+paddle.fluid.layers.Uniform.kl_divergence (ArgSpec(args=['self', 'other'], varargs=None, keywords=None, defaults=None), ('document', '3baee52abbed82d47e9588d9dfe2f42f'))
+paddle.fluid.layers.Uniform.log_prob (ArgSpec(args=['self', 'value'], varargs=None, keywords=None, defaults=None), ('document', 'b79091014ceaffb6a7372a198a341c23'))
+paddle.fluid.layers.Uniform.sample (ArgSpec(args=['self', 'shape', 'seed'], varargs=None, keywords=None, defaults=(0,)), ('document', 'adac334af13f6984e991b3ecf12b8cb7'))
+paddle.fluid.layers.Normal ('paddle.fluid.layers.distributions.Normal', ('document', '3265262d0d8b3b32c6245979a5cdced9'))
+paddle.fluid.layers.Normal.__init__ (ArgSpec(args=['self', 'loc', 'scale'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
+paddle.fluid.layers.Normal.entropy (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'd2db47b1e62c037a2570fc526b93f518'))
+paddle.fluid.layers.Normal.kl_divergence (ArgSpec(args=['self', 'other'], varargs=None, keywords=None, defaults=None), ('document', '2e8845cdf1129647e6fa6e816876cd3b'))
+paddle.fluid.layers.Normal.log_prob (ArgSpec(args=['self', 'value'], varargs=None, keywords=None, defaults=None), ('document', 'b79091014ceaffb6a7372a198a341c23'))
+paddle.fluid.layers.Normal.sample (ArgSpec(args=['self', 'shape', 'seed'], varargs=None, keywords=None, defaults=(0,)), ('document', 'adac334af13f6984e991b3ecf12b8cb7'))
 paddle.fluid.contrib.InitState ('paddle.fluid.contrib.decoder.beam_search_decoder.InitState', ('document', '3afd1f84232718e628e9e566941c5f05'))
 paddle.fluid.contrib.InitState.__init__ (ArgSpec(args=['self', 'init', 'shape', 'value', 'init_boot', 'need_reorder', 'dtype'], varargs=None, keywords=None, defaults=(None, None, 0.0, None, False, 'float32')), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.contrib.StateCell ('paddle.fluid.contrib.decoder.beam_search_decoder.StateCell', ('document', 'ecd0066c02867d445d7b461e28220c50'))

python/paddle/fluid/layers/__init__.py

@@ -34,6 +34,7 @@ from . import metric_op
 from .metric_op import *
 from .learning_rate_scheduler import *
 from .collective import *
+from .distributions import *
 
 __all__ = []
 __all__ += nn.__all__
@@ -45,3 +46,4 @@ __all__ += device.__all__
 __all__ += detection.__all__
 __all__ += metric_op.__all__
 __all__ += learning_rate_scheduler.__all__
+__all__ += distributions.__all__