improve the API Sample of DataFeeder, memory_optimize and release_memory (#17374)

* improve the API Sample of DataFeeder, memory_optimize and release_memory, test=develop

* update API.spec, test=develop, test=document_preview

* tweak the code format of feed API, test=develop

*  update API.spec, test=develop

* improve doc for DataFeeder and default_main_program, test=develop

paddle/fluid/API.spec

@@ -7,7 +7,7 @@ paddle.fluid.Program.list_vars (ArgSpec(args=['self'], varargs=None, keywords=No
 paddle.fluid.Program.parse_from_string (ArgSpec(args=['binary_str'], varargs=None, keywords=None, defaults=None), ('document', 'b6a7ffb239a30bf2ce58cfaca8d8b8d5'))
 paddle.fluid.Program.to_string (ArgSpec(args=['self', 'throw_on_error', 'with_details'], varargs=None, keywords=None, defaults=(False,)), ('document', '89acca639baf00f3ad08b9d827e81706'))
 paddle.fluid.default_startup_program (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'ba609cb02e4e55e8d626723567ef1778'))
-paddle.fluid.default_main_program (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '5430f54ab4895f9f47db6bebbaf71659'))
+paddle.fluid.default_main_program (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '06a5a8f649dfb8496c1f683c909db375'))
 paddle.fluid.program_guard (ArgSpec(args=['main_program', 'startup_program'], varargs=None, keywords=None, defaults=(None,)), ('document', 'ae5f806f082cfaeaa5194cacc253a5e4'))
 paddle.fluid.name_scope (ArgSpec(args=['prefix'], varargs=None, keywords=None, defaults=(None,)), ('document', '61660461e1f44e0480ca22fa8a482c41'))
 paddle.fluid.cuda_places (ArgSpec(args=['device_ids'], varargs=None, keywords=None, defaults=(None,)), ('document', '7f3068b82fc427bfa04b1af953610992'))
@@ -27,8 +27,8 @@ paddle.fluid.DistributeTranspiler.get_pserver_programs (ArgSpec(args=['self', 'e
 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.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', '06ce55338dfe96311ad1078235ab3bf4'))
-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', 'eda17d0f1639bc6ca215cecf87f588a4'))
-paddle.fluid.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,)), ('document', 'ac4114d3df16264f1946deb3a8434a6f'))
+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', '3f11d536c8039c7b5fd57970078c344b'))
+paddle.fluid.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b524b73e10f9ccdfa6d189e2e535fc17'))
 paddle.fluid.DistributeTranspilerConfig.__init__ 
 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'))
 paddle.fluid.ParallelExecutor.drop_local_exe_scopes (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '80d857dc626612e2b2460d0154551e95'))
@@ -428,8 +428,8 @@ paddle.fluid.transpiler.DistributeTranspiler.get_pserver_programs (ArgSpec(args=
 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.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', '06ce55338dfe96311ad1078235ab3bf4'))
-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', 'eda17d0f1639bc6ca215cecf87f588a4'))
-paddle.fluid.transpiler.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,)), ('document', 'ac4114d3df16264f1946deb3a8434a6f'))
+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', '3f11d536c8039c7b5fd57970078c344b'))
+paddle.fluid.transpiler.release_memory (ArgSpec(args=['input_program', 'skip_opt_set'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b524b73e10f9ccdfa6d189e2e535fc17'))
 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'))
@@ -535,9 +535,9 @@ paddle.fluid.CUDAPinnedPlace.__init__ __init__(self: paddle.fluid.core.CUDAPinne
 paddle.fluid.ParamAttr.__init__ (ArgSpec(args=['self', 'name', 'initializer', 'learning_rate', 'regularizer', 'trainable', 'gradient_clip', 'do_model_average'], varargs=None, keywords=None, defaults=(None, None, 1.0, None, True, None, False)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.WeightNormParamAttr.__init__ (ArgSpec(args=['self', 'dim', 'name', 'initializer', 'learning_rate', 'regularizer', 'trainable', 'gradient_clip', 'do_model_average'], varargs=None, keywords=None, defaults=(None, None, None, 1.0, None, True, None, False)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.DataFeeder.__init__ (ArgSpec(args=['self', 'feed_list', 'place', 'program'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.DataFeeder.decorate_reader (ArgSpec(args=['self', 'reader', 'multi_devices', 'num_places', 'drop_last'], varargs=None, keywords=None, defaults=(None, True)), ('document', 'f8f3df23c5633c614db781a91b81fb62'))
-paddle.fluid.DataFeeder.feed (ArgSpec(args=['self', 'iterable'], varargs=None, keywords=None, defaults=None), ('document', '459e316301279dfd82001b46f0b8ffca'))
-paddle.fluid.DataFeeder.feed_parallel (ArgSpec(args=['self', 'iterable', 'num_places'], varargs=None, keywords=None, defaults=(None,)), ('document', '543863d1f9d4853758adb613b8659e85'))
+paddle.fluid.DataFeeder.decorate_reader (ArgSpec(args=['self', 'reader', 'multi_devices', 'num_places', 'drop_last'], varargs=None, keywords=None, defaults=(None, True)), ('document', 'be47d7e07824b4281da77472846955ac'))
+paddle.fluid.DataFeeder.feed (ArgSpec(args=['self', 'iterable'], varargs=None, keywords=None, defaults=None), ('document', 'ce65fe1d81dcd7067d5092a5667f35cc'))
+paddle.fluid.DataFeeder.feed_parallel (ArgSpec(args=['self', 'iterable', 'num_places'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c312743c910dda1c3a9c6637ac30187f'))
 paddle.fluid.clip.ErrorClipByValue.__init__ (ArgSpec(args=['self', 'max', 'min'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.clip.GradientClipByValue.__init__ (ArgSpec(args=['self', 'max', 'min'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.clip.GradientClipByNorm.__init__ (ArgSpec(args=['self', 'clip_norm'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))

python/paddle/fluid/data_feeder.py

@@ -149,6 +149,7 @@ class DataFeeder(object):
 
     ..  code-block:: python
 
+        import paddle.fluid as fluid
         place = fluid.CPUPlace()
         img = fluid.layers.data(name='image', shape=[1, 28, 28])
         label = fluid.layers.data(name='label', shape=[1], dtype='int64')
@@ -161,10 +162,16 @@ class DataFeeder(object):
 
     ..  code-block:: python
 
+        import paddle
+        import paddle.fluid as fluid
+        
         place=fluid.CUDAPlace(0)
+        data = fluid.layers.data(name='data', shape=[3, 224, 224], dtype='float32')
+        label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+        
         feeder = fluid.DataFeeder(place=place, feed_list=[data, label])
         reader = feeder.decorate_reader(
-            paddle.batch(flowers.train(), batch_size=16))
+                paddle.batch(paddle.dataset.flowers.train(), batch_size=16), multi_devices=False)
 
     Args:
         feed_list(list): The Variables or Variables'name that will
@@ -182,15 +189,34 @@ class DataFeeder(object):
     Examples:
         ..  code-block:: python
 
-            # ...
+
+            import numpy as np
+            import paddle
+            import paddle.fluid as fluid
+            
             place = fluid.CPUPlace()
-            feed_list = [
-                main_program.global_block().var(var_name) for var_name in feed_vars_name
-            ] # feed_vars_name is a list of variables' name.
-            feeder = fluid.DataFeeder(feed_list, place)
+            
+            def reader():
+                yield [np.random.random([4]).astype('float32'), np.random.random([3]).astype('float32')],
+            
+            main_program = fluid.Program()
+            startup_program = fluid.Program()
+            
+            with fluid.program_guard(main_program, startup_program):
+                data_1 = fluid.layers.data(name='data_1', shape=[1, 2, 2])
+                data_2 = fluid.layers.data(name='data_2', shape=[1, 1, 3])
+                out = fluid.layers.fc(input=[data_1, data_2], size=2)
+                # ...
+            
+            feeder = fluid.DataFeeder([data_1, data_2], place)
+                        
+            exe = fluid.Executor(place)
+            exe.run(startup_program)
             for data in reader():
                 outs = exe.run(program=main_program,
-                               feed=feeder.feed(data))
+                               feed=feeder.feed(data),
+                               fetch_list=[out])
+
     """
 
     def __init__(self, feed_list, place, program=None):
@@ -222,6 +248,23 @@ class DataFeeder(object):
 
         Returns:
             dict: the result of conversion.
+
+        Examples:
+            ..  code-block:: python
+
+                import numpy.random as random
+                import paddle.fluid as fluid
+                
+                def reader(limit=5):
+                    for i in range(limit):
+                        yield random.random([784]).astype('float32'), random.random([1]).astype('int64'), random.random([256]).astype('float32')
+                
+                data_1 = fluid.layers.data(name='data_1', shape=[1, 28, 28])
+                data_2 = fluid.layers.data(name='data_2', shape=[1], dtype='int64')
+                data_3 = fluid.layers.data(name='data_3', shape=[16, 16], dtype='float32')
+                feeder = fluid.DataFeeder(['data_1','data_2', 'data_3'], fluid.CPUPlace())
+                
+                result = feeder.feed(reader()) 
         """
         converter = []
         for lod_level, shape, dtype in six.moves.zip(
@@ -260,6 +303,32 @@ class DataFeeder(object):
 
         Notes:
             The number of devices and number of mini-batches must be same.
+
+        Examples:
+            ..  code-block:: python
+
+                import numpy.random as random
+                import paddle.fluid as fluid
+                
+                def reader(limit=10):
+                    for i in range(limit):
+                        yield [random.random([784]).astype('float32'), random.randint(10)],
+                
+                x = fluid.layers.data(name='x', shape=[1, 28, 28])
+                y = fluid.layers.data(name='y', shape=[1], dtype='int64')
+                
+                feeder = fluid.DataFeeder(['x','y'], fluid.CPUPlace())
+                place_num = 2
+                places = [fluid.CPUPlace() for x in range(place_num)]
+                data = []
+                exe = fluid.Executor(fluid.CPUPlace())
+                exe.run(fluid.default_startup_program())
+                program = fluid.CompiledProgram(fluid.default_main_program()).with_data_parallel(places=places)
+                for item in reader():
+                    data.append(item)
+                    if place_num == len(data):
+                        exe.run(program=program, feed=list(feeder.feed_parallel(data, place_num)), fetch_list=[])
+                        data = []
         """
         if isinstance(self.place, core.CUDAPlace):
             places = [
@@ -319,6 +388,29 @@ class DataFeeder(object):
 
         Raises:
             ValueError: If drop_last is False and the data batch cannot fit for devices.
+
+        Examples:
+            ..  code-block:: python
+
+                import numpy.random as random
+                import paddle
+                import paddle.fluid as fluid
+                
+                def reader(limit=5):
+                    for i in range(limit):
+                        yield (random.random([784]).astype('float32'), random.random([1]).astype('int64')),
+                
+                place=fluid.CUDAPlace(0)
+                data = fluid.layers.data(name='data', shape=[1, 28, 28], dtype='float32')
+                label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+                
+                feeder = fluid.DataFeeder(place=place, feed_list=[data, label])
+                reader = feeder.decorate_reader(reader, multi_devices=False)
+                
+                exe = fluid.Executor(place)
+                exe.run(fluid.default_startup_program())
+                for data in reader():
+                    exe.run(feed=data)
         """
 
         def __reader_creator__():

python/paddle/fluid/framework.py

@@ -3608,6 +3608,35 @@ def default_main_program():
 
     Returns:
         Program: main program
+
+    Examples:
+        ..  code-block:: python
+
+            import paddle.fluid as fluid
+            
+            # Sample Network:
+            data = fluid.layers.data(name='image', shape=[3, 224, 224], dtype='float32')
+            label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+            
+            conv1 = fluid.layers.conv2d(data, 4, 5, 1, act=None)
+            bn1 = fluid.layers.batch_norm(conv1, act='relu')
+            pool1 = fluid.layers.pool2d(bn1, 2, 'max', 2)
+            conv2 = fluid.layers.conv2d(pool1, 16, 5, 1, act=None)
+            bn2 = fluid.layers.batch_norm(conv2, act='relu')
+            pool2 = fluid.layers.pool2d(bn2, 2, 'max', 2)
+            
+            fc1 = fluid.layers.fc(pool2, size=50, act='relu')
+            fc2 = fluid.layers.fc(fc1, size=102, act='softmax')
+            
+            loss = fluid.layers.cross_entropy(input=fc2, label=label)
+            loss = fluid.layers.mean(loss)
+            opt = fluid.optimizer.Momentum(
+                learning_rate=0.1,
+                momentum=0.9,
+                regularization=fluid.regularizer.L2Decay(1e-4))
+            opt.minimize(loss)
+            
+            print(fluid.default_main_program())
     """
     return _main_program_
 

python/paddle/fluid/transpiler/memory_optimization_transpiler.py

@@ -509,6 +509,17 @@ def memory_optimize(input_program,
         level(int): If level=0, reuse if the shape is completely equal, o
     Returns:
         None
+    Examples:
+        ..  code-block:: python
+            
+            import paddle.fluid as fluid
+
+            # build network
+            # ...
+            
+            # deprecated API
+            fluid.release_memory(fluid.default_main_program())
+
     """
     sys.stderr.write('memory_optimize is deprecated. '
                      'Use CompiledProgram and Executor\n')
@@ -565,6 +576,18 @@ def release_memory(input_program, skip_opt_set=None):
         skip_opt_set(set): vars wil be skipped in memory optimze
     Returns:
         None
+   
+    Examples:
+        ..  code-block:: python
+
+            import paddle.fluid as fluid
+
+            # build network
+            # ...
+            
+            # deprecated API
+            fluid.release_memory(fluid.default_main_program())
+    
     """
     cfgs = _get_cfgs(input_program)
     input_program._is_mem_optimized = True