doc merge, test=document_fix (#20464)

paddle/fluid/API.spec

@@ -35,16 +35,16 @@ paddle.fluid.Executor.run (ArgSpec(args=['self', 'program', 'feed', 'fetch_list'
 paddle.fluid.Executor.train_from_dataset (ArgSpec(args=['self', 'program', 'dataset', 'scope', 'thread', 'debug', 'fetch_list', 'fetch_info', 'print_period', 'fetch_handler'], varargs=None, keywords=None, defaults=(None, None, None, 0, False, None, None, 100, None)), ('document', '73024c79f46b4f14f1060edeaa4919c8'))
 paddle.fluid.global_scope (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'f65788d9ead293ada47551339df12203'))
 paddle.fluid.scope_guard (ArgSpec(args=['scope'], varargs=None, keywords=None, defaults=None), ('document', '02fcfc1eda07c03a84ed62422366239c'))
-paddle.fluid.DistributeTranspiler ('paddle.fluid.transpiler.distribute_transpiler.DistributeTranspiler', ('document', 'b2b19821c5dffcd11473d6a4eef089af'))
+paddle.fluid.DistributeTranspiler ('paddle.fluid.transpiler.distribute_transpiler.DistributeTranspiler', ('document', '5152a3ed0544d4d9600fb53a73f15c38'))
 paddle.fluid.DistributeTranspiler.__init__ (ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.DistributeTranspiler.get_pserver_program (ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None), ('document', 'b1951949c6d21698290aa8ac69afee32'))
 paddle.fluid.DistributeTranspiler.get_pserver_programs (ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None), ('document', 'c89fc350f975ef827f5448d68af388cf'))
 paddle.fluid.DistributeTranspiler.get_startup_program (ArgSpec(args=['self', 'endpoint', 'pserver_program', 'startup_program'], varargs=None, keywords=None, defaults=(None, None)), ('document', '90a40b80e0106f69262cc08b861c3e39'))
-paddle.fluid.DistributeTranspiler.get_trainer_program (ArgSpec(args=['self', 'wait_port'], varargs=None, keywords=None, defaults=(True,)), ('document', '0e47f020304e2b824e87ff03475c17cd'))
-paddle.fluid.DistributeTranspiler.transpile (ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode', 'startup_program', 'current_endpoint'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True, None, '127.0.0.1:6174')), ('document', '418c7e8b268e9be4104f2809e654c2f7'))
+paddle.fluid.DistributeTranspiler.get_trainer_program (ArgSpec(args=['self', 'wait_port'], varargs=None, keywords=None, defaults=(True,)), ('document', '27ed6451913b6ab341bd0d1a36b3f8c1'))
+paddle.fluid.DistributeTranspiler.transpile (ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode', 'startup_program', 'current_endpoint'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True, None, '127.0.0.1:6174')), ('document', '13c09537f7a5660c528242eb370bb4c7'))
 paddle.fluid.memory_optimize (ArgSpec(args=['input_program', 'skip_opt_set', 'print_log', 'level', 'skip_grads'], varargs=None, keywords=None, defaults=(None, False, 0, True)), ('document', '2be29dc8ecdec9baa7728fb0c7f80e24'))
 paddle.fluid.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,)), ('document', '2be29dc8ecdec9baa7728fb0c7f80e24'))
-paddle.fluid.DistributeTranspilerConfig ('paddle.fluid.transpiler.distribute_transpiler.DistributeTranspilerConfig', ('document', 'beac6f89fe97eb8c66a25de5a09c56d2'))
+paddle.fluid.DistributeTranspilerConfig ('paddle.fluid.transpiler.distribute_transpiler.DistributeTranspilerConfig', ('document', 'eb4db3a7a7a2099bd5eac034a8f4b51b'))
 paddle.fluid.DistributeTranspilerConfig.__init__ (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.ParallelExecutor ('paddle.fluid.parallel_executor.ParallelExecutor', ('document', 'dbff7bd7d365d755cec5ce977aa9db83'))
 paddle.fluid.ParallelExecutor.__init__ (ArgSpec(args=['self', 'use_cuda', 'loss_name', 'main_program', 'share_vars_from', 'exec_strategy', 'build_strategy', 'num_trainers', 'trainer_id', 'scope'], varargs=None, keywords=None, defaults=(None, None, None, None, None, 1, 0, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
@@ -254,8 +254,8 @@ paddle.fluid.layers.elementwise_pow (ArgSpec(args=['x', 'y', 'axis', 'act', 'nam
 paddle.fluid.layers.elementwise_mod (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '4101ee1f9280f00dce54054ccc434890'))
 paddle.fluid.layers.elementwise_floordiv (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '67e6101c31314d4082621e8e443cfb68'))
 paddle.fluid.layers.uniform_random_batch_size_like (ArgSpec(args=['input', 'shape', 'dtype', 'input_dim_idx', 'output_dim_idx', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=('float32', 0, 0, -1.0, 1.0, 0)), ('document', 'cfa120e583cd4a5bfa120c8a26f98a28'))
-paddle.fluid.layers.gaussian_random (ArgSpec(args=['shape', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', 'ebbf399d4e03190ce5dc9488f05c92f4'))
-paddle.fluid.layers.sampling_id (ArgSpec(args=['x', 'min', 'max', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', 'c39b647b6cf08e058d96ee503d5284fe'))
+paddle.fluid.layers.gaussian_random (ArgSpec(args=['shape', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', 'dd4ddb66c78a2564e5d1e0e345d8286f'))
+paddle.fluid.layers.sampling_id (ArgSpec(args=['x', 'min', 'max', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', '2490492db3b41af9144bb1539e4e9116'))
 paddle.fluid.layers.gaussian_random_batch_size_like (ArgSpec(args=['input', 'shape', 'input_dim_idx', 'output_dim_idx', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0, 0, 0.0, 1.0, 0, 'float32')), ('document', '2aed0f546f220364fb1da724a3176f74'))
 paddle.fluid.layers.sum (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', 'f4b60847cb0f1ae00823ba6fb1b11310'))
 paddle.fluid.layers.slice (ArgSpec(args=['input', 'axes', 'starts', 'ends'], varargs=None, keywords=None, defaults=None), ('document', '8c622791994a0d657d8c6c9cefa5bf34'))
@@ -900,24 +900,24 @@ paddle.fluid.dygraph.CosineDecay.create_lr_var (ArgSpec(args=['self', 'lr'], var
 paddle.fluid.dygraph.CosineDecay.step (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.dygraph.BackwardStrategy ('paddle.fluid.core_avx.BackwardStrategy', ('document', '4fcdc2c2d0c162f3840737abda39eb27'))
 paddle.fluid.dygraph.BackwardStrategy.__init__ __init__(self: paddle.fluid.core_avx.BackwardStrategy) -> None
-paddle.fluid.transpiler.DistributeTranspiler ('paddle.fluid.transpiler.distribute_transpiler.DistributeTranspiler', ('document', 'b2b19821c5dffcd11473d6a4eef089af'))
+paddle.fluid.transpiler.DistributeTranspiler ('paddle.fluid.transpiler.distribute_transpiler.DistributeTranspiler', ('document', '5152a3ed0544d4d9600fb53a73f15c38'))
 paddle.fluid.transpiler.DistributeTranspiler.__init__ (ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.transpiler.DistributeTranspiler.get_pserver_program (ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None), ('document', 'b1951949c6d21698290aa8ac69afee32'))
 paddle.fluid.transpiler.DistributeTranspiler.get_pserver_programs (ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None), ('document', 'c89fc350f975ef827f5448d68af388cf'))
 paddle.fluid.transpiler.DistributeTranspiler.get_startup_program (ArgSpec(args=['self', 'endpoint', 'pserver_program', 'startup_program'], varargs=None, keywords=None, defaults=(None, None)), ('document', '90a40b80e0106f69262cc08b861c3e39'))
-paddle.fluid.transpiler.DistributeTranspiler.get_trainer_program (ArgSpec(args=['self', 'wait_port'], varargs=None, keywords=None, defaults=(True,)), ('document', '0e47f020304e2b824e87ff03475c17cd'))
-paddle.fluid.transpiler.DistributeTranspiler.transpile (ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode', 'startup_program', 'current_endpoint'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True, None, '127.0.0.1:6174')), ('document', '418c7e8b268e9be4104f2809e654c2f7'))
+paddle.fluid.transpiler.DistributeTranspiler.get_trainer_program (ArgSpec(args=['self', 'wait_port'], varargs=None, keywords=None, defaults=(True,)), ('document', '27ed6451913b6ab341bd0d1a36b3f8c1'))
+paddle.fluid.transpiler.DistributeTranspiler.transpile (ArgSpec(args=['self', 'trainer_id', 'program', 'pservers', 'trainers', 'sync_mode', 'startup_program', 'current_endpoint'], varargs=None, keywords=None, defaults=(None, '127.0.0.1:6174', 1, True, None, '127.0.0.1:6174')), ('document', '13c09537f7a5660c528242eb370bb4c7'))
 paddle.fluid.transpiler.memory_optimize (ArgSpec(args=['input_program', 'skip_opt_set', 'print_log', 'level', 'skip_grads'], varargs=None, keywords=None, defaults=(None, False, 0, True)), ('document', '2be29dc8ecdec9baa7728fb0c7f80e24'))
 paddle.fluid.transpiler.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,)), ('document', '2be29dc8ecdec9baa7728fb0c7f80e24'))
 paddle.fluid.transpiler.HashName ('paddle.fluid.transpiler.ps_dispatcher.HashName', ('document', '8190ddc66ee412441f5d97fd3f702bdd'))
 paddle.fluid.transpiler.HashName.__init__ (ArgSpec(args=['self', 'pserver_endpoints'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.transpiler.HashName.dispatch (ArgSpec(args=['self', 'varlist'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.transpiler.HashName.reset (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
+paddle.fluid.transpiler.HashName.dispatch (ArgSpec(args=['self', 'varlist'], varargs=None, keywords=None, defaults=None), ('document', '2c7e0027f15f5379895095cc600e1866'))
+paddle.fluid.transpiler.HashName.reset (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '218e30adcf523fd0044674a31075905b'))
 paddle.fluid.transpiler.RoundRobin ('paddle.fluid.transpiler.ps_dispatcher.RoundRobin', ('document', 'c124359054923c614758c3fbbf666290'))
 paddle.fluid.transpiler.RoundRobin.__init__ (ArgSpec(args=['self', 'pserver_endpoints'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.transpiler.RoundRobin.dispatch (ArgSpec(args=['self', 'varlist'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.transpiler.RoundRobin.reset (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.transpiler.DistributeTranspilerConfig ('paddle.fluid.transpiler.distribute_transpiler.DistributeTranspilerConfig', ('document', 'beac6f89fe97eb8c66a25de5a09c56d2'))
+paddle.fluid.transpiler.RoundRobin.dispatch (ArgSpec(args=['self', 'varlist'], varargs=None, keywords=None, defaults=None), ('document', '7390e2350e50717d48540476d197b9f7'))
+paddle.fluid.transpiler.RoundRobin.reset (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '218e30adcf523fd0044674a31075905b'))
+paddle.fluid.transpiler.DistributeTranspilerConfig ('paddle.fluid.transpiler.distribute_transpiler.DistributeTranspilerConfig', ('document', 'eb4db3a7a7a2099bd5eac034a8f4b51b'))
 paddle.fluid.transpiler.DistributeTranspilerConfig.__init__ (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.nets.simple_img_conv_pool (ArgSpec(args=['input', 'num_filters', 'filter_size', 'pool_size', 'pool_stride', 'pool_padding', 'pool_type', 'global_pooling', 'conv_stride', 'conv_padding', 'conv_dilation', 'conv_groups', 'param_attr', 'bias_attr', 'act', 'use_cudnn'], varargs=None, keywords=None, defaults=(0, 'max', False, 1, 0, 1, 1, None, None, None, True)), ('document', '5e89c978199c4ecce2b26d5fed1ec52b'))
 paddle.fluid.nets.sequence_conv_pool (ArgSpec(args=['input', 'num_filters', 'filter_size', 'param_attr', 'act', 'pool_type', 'bias_attr'], varargs=None, keywords=None, defaults=(None, 'sigmoid', 'max', None)), ('document', 'b2d435f782ac8ea3ca480b8d24e7f5b4'))

paddle/fluid/operators/sampling_id_op.cc

@@ -61,7 +61,7 @@ A layer for sampling id from multinomial distribution from the
         "seed",
         "Random seed used for the random number engine. "
         "0 means use a seed generated by the system."
-        "Note that if seed is not 0, this operator will always "
+        "Note that if seed is not 0, this operator will "
         "generate the same random numbers every time. (int, default 0).")
         .SetDefault(0);
   }

paddle/fluid/pybind/pybind.cc

@@ -1485,7 +1485,7 @@ All parameter, weight, gradient are variables in Paddle.
             self.num_iteration_per_run_ = num_iteration_per_run;
           },
           R"DOC(This config that how many iteration the executor will run when
-                user call pe.run() in python
+                user call exe.run() in python
               )DOC")
       .def_property("_dry_run",
                     [](const ExecutionStrategy &self) { return self.dry_run_; },

python/paddle/fluid/transpiler/distribute_transpiler.py

@@ -130,7 +130,7 @@ def slice_variable(var_list, slice_count, min_block_size):
 
 class DistributeTranspilerConfig(object):
     """
-    A configuration class that provide support for distributed jobs.
+    A configuration class that provide support for transpiler distributed jobs.
     Some important parameters are explained as follows:
 
 
@@ -232,7 +232,7 @@ class DistributeTranspiler(object):
     **DistributeTranspiler**
 
     Convert the fluid program to distributed data-parallelism programs.
-    Supports two modes: pserver mode and nccl2 mode.
+    Supports two modes: parameter server(pserver) mode and nccl2 mode.
 
     In pserver mode, the main_program will be transformed to use a remote
     parameter server to do parameter optimization. And the optimization
@@ -247,8 +247,8 @@ class DistributeTranspiler(object):
     Examples:
         .. code-block:: python
 
-            x = fluid.layers.data(name='x', shape=[13], dtype='float32')
-            y = fluid.layers.data(name='y', shape=[1], dtype='float32')
+            x = fluid.data(name='x', shape=[13], dtype='float32')
+            y = fluid.data(name='y', shape=[1], dtype='float32')
             y_predict = fluid.layers.fc(input=x, size=1, act=None)
 
             cost = fluid.layers.square_error_cost(input=y_predict, label=y)
@@ -500,7 +500,7 @@ class DistributeTranspiler(object):
                   startup_program=None,
                   current_endpoint="127.0.0.1:6174"):
         """
-        Run the transpiler. Transpile the input program.
+        Transpile the input program to distributed programs with config and arguments.
 
         Args:
             trainer_id (int): id for current trainer worker, if you have

python/paddle/fluid/transpiler/ps_dispatcher.py

@@ -31,6 +31,9 @@ class PSDispatcher(object):
         return self._eps
 
     def reset(self):
+        """
+        reset the step counter, set it zero.
+        """
         self._step = 0
 
     def dispatch(self, varlist):
@@ -69,6 +72,12 @@ class HashName(PSDispatcher):
         return hash(block_str) % total
 
     def dispatch(self, varlist):
+        """
+        use `HashName` method to dispatch variables with each parameter server.
+        Args:
+            varlist (list): a list of Variables
+
+        """
         eplist = []
         for var in varlist:
             server_id = self._hash_block(var.name(), len(self._eps))
@@ -100,6 +109,12 @@ class RoundRobin(PSDispatcher):
         super(self.__class__, self).__init__(pserver_endpoints)
 
     def dispatch(self, varlist):
+        """
+        use `RoundRobin` method to dispatch variables with each parameter server.
+        Args:
+            varlist (list): a list of Variables
+
+        """
         eplist = []
         for var in varlist:
             server_for_param = self._eps[self._step]