fix distributed_transpiler.py api test=develop (#17668)

paddle/fluid/API.spec

@@ -22,10 +22,10 @@ paddle.fluid.Executor.train_from_dataset (ArgSpec(args=['self', 'program', 'data
 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', '6e19f92e2f185320a3a86b77e85eb3b3'))
 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', '292ab72977afbe58e6a3bde175452680'))
-paddle.fluid.DistributeTranspiler.get_pserver_programs (ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None), ('document', '78f4949aedf317666a89ca74b3748ba8'))
+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', 'd796fc0c8d51503b556fcf6dc15c4f0c'))
-paddle.fluid.DistributeTranspiler.get_trainer_program (ArgSpec(args=['self', 'wait_port'], varargs=None, keywords=None, defaults=(True,)), ('document', '736330e31a7a54abccc0c7fd9119d9ff'))
+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.memory_optimize (ArgSpec(args=['input_program', 'skip_opt_set', 'print_log', 'level', 'skip_grads'], varargs=None, keywords=None, defaults=(None, False, 0, False)), ('document', '2348247f684bfd5bb9466470f35be064'))
 paddle.fluid.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd38c5b8b2b2e0bb19bcf1b581a80a7e4'))
@@ -424,10 +424,10 @@ paddle.fluid.contrib.multi_upload (ArgSpec(args=['client', 'hdfs_path', 'local_p
 paddle.fluid.contrib.extend_with_decoupled_weight_decay (ArgSpec(args=['base_optimizer'], varargs=None, keywords=None, defaults=None), ('document', 'a1095dfd4ec725747f662d69cd7659d4'))
 paddle.fluid.contrib.mixed_precision.decorate (ArgSpec(args=['optimizer', 'init_loss_scaling', 'incr_every_n_steps', 'decr_every_n_nan_or_inf', 'incr_ratio', 'decr_ratio', 'use_dynamic_loss_scaling'], varargs=None, keywords=None, defaults=(1.0, 1000, 2, 2.0, 0.8, False)), ('document', 'bdb8f9dbb0d94b3957272c53eeee9818'))
 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', '292ab72977afbe58e6a3bde175452680'))
-paddle.fluid.transpiler.DistributeTranspiler.get_pserver_programs (ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None), ('document', '78f4949aedf317666a89ca74b3748ba8'))
+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', 'd796fc0c8d51503b556fcf6dc15c4f0c'))
-paddle.fluid.transpiler.DistributeTranspiler.get_trainer_program (ArgSpec(args=['self', 'wait_port'], varargs=None, keywords=None, defaults=(True,)), ('document', '736330e31a7a54abccc0c7fd9119d9ff'))
+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.memory_optimize (ArgSpec(args=['input_program', 'skip_opt_set', 'print_log', 'level', 'skip_grads'], varargs=None, keywords=None, defaults=(None, False, 0, False)), ('document', '2348247f684bfd5bb9466470f35be064'))
 paddle.fluid.transpiler.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd38c5b8b2b2e0bb19bcf1b581a80a7e4'))

python/paddle/fluid/transpiler/distribute_transpiler.py

@@ -649,6 +649,18 @@ class DistributeTranspiler(object):
 
         Returns:
             Program: trainer side program.
+
+        Examples:
+            .. code-block:: python
+
+              import paddle.fluid as fluid
+              #this is an example, find available endpoints in your case
+              pserver_endpoints = "192.168.0.1:6174,192.168.0.2:6174"
+              trainer_id = 0
+              trainers = 4
+              t = fluid.DistributeTranspiler()
+              t.transpile(trainer_id, trainers=trainers, pservers=pserver_endpoints)
+              trainer_program = t.get_trainer_program()
         """
         # remove optimize ops and add a send op to main_program
         # FIXME(typhoonzero): Also ops like clip_gradient, lrn_decay?
@@ -774,6 +786,20 @@ class DistributeTranspiler(object):
 
         Returns:
             Program: the program for current parameter server to run.
+
+        Examples:
+            .. code-block:: python
+
+              import paddle.fluid as fluid
+              #this is an example, find available endpoints in your case
+              pserver_endpoints = "192.168.0.1:6174,192.168.0.2:6174"
+              current_endpoint = "192.168.0.1:6174"
+              trainer_id = 0
+              trainers = 4
+              t = fluid.DistributeTranspiler()
+              t.transpile(
+                   trainer_id, pservers=pserver_endpoints, trainers=trainers)
+              pserver_program = t.get_pserver_program(current_endpoint)
         """
         # TODO(panyx0718): Revisit this assumption. what if #blocks > #pservers.
         # NOTE: assume blocks of the same variable is not distributed
@@ -1017,6 +1043,20 @@ class DistributeTranspiler(object):
 
         Returns:
             tuple: (main_program, startup_program), of type "Program"
+
+        Examples:
+            .. code-block:: python
+
+              import paddle.fluid as fluid
+              #this is an example, find available endpoints in your case
+              pserver_endpoints = "192.168.0.1:6174,192.168.0.2:6174"
+              current_endpoint = "192.168.0.1:6174"
+              trainer_id = 0
+              trainers = 4
+              t = fluid.DistributeTranspiler()
+              t.transpile(
+                   trainer_id, pservers=pserver_endpoints, trainers=trainers)
+              pserver_program, pserver_startup_program = t.get_pserver_programs(current_endpoint)
         """
         pserver_prog = self.get_pserver_program(endpoint)
         pserver_startup = self.get_startup_program(