Merge pull request #13442 from reyoung/feature/remove_trainer_api

Move trainer to contrib

paddle/fluid/API.spec

@@ -35,19 +35,6 @@ paddle.fluid.Executor.close ArgSpec(args=['self'], varargs=None, keywords=None,
 paddle.fluid.Executor.run ArgSpec(args=['self', 'program', 'feed', 'fetch_list', 'feed_var_name', 'fetch_var_name', 'scope', 'return_numpy', 'use_program_cache'], varargs=None, keywords=None, defaults=(None, None, None, 'feed', 'fetch', None, True, False))
 paddle.fluid.global_scope ArgSpec(args=[], varargs=None, keywords=None, defaults=None)
 paddle.fluid.scope_guard ArgSpec(args=[], varargs='args', keywords='kwds', defaults=None)
-paddle.fluid.Trainer.__init__ ArgSpec(args=['self', 'train_func', 'optimizer_func', 'param_path', 'place', 'parallel', 'checkpoint_config'], varargs=None, keywords=None, defaults=(None, None, False, None))
-paddle.fluid.Trainer.save_inference_model ArgSpec(args=['self', 'param_path', 'feeded_var_names', 'target_var_indexes'], varargs=None, keywords=None, defaults=None)
-paddle.fluid.Trainer.save_params ArgSpec(args=['self', 'param_path'], varargs=None, keywords=None, defaults=None)
-paddle.fluid.Trainer.stop ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None)
-paddle.fluid.Trainer.test ArgSpec(args=['self', 'reader', 'feed_order'], varargs=None, keywords=None, defaults=None)
-paddle.fluid.Trainer.train ArgSpec(args=['self', 'num_epochs', 'event_handler', 'reader', 'feed_order'], varargs=None, keywords=None, defaults=(None, None))
-paddle.fluid.BeginEpochEvent.__init__ ArgSpec(args=['self', 'epoch_id'], varargs=None, keywords=None, defaults=None)
-paddle.fluid.EndEpochEvent.__init__ ArgSpec(args=['self', 'epoch_id'], varargs=None, keywords=None, defaults=None)
-paddle.fluid.BeginStepEvent.__init__ ArgSpec(args=['self', 'epoch_id', 'step_id'], varargs=None, keywords=None, defaults=None)
-paddle.fluid.EndStepEvent.__init__ ArgSpec(args=['self', 'epoch_id', 'step_id', 'metrics'], varargs=None, keywords=None, defaults=None)
-paddle.fluid.CheckpointConfig.__init__ ArgSpec(args=['self', 'checkpoint_dir', 'max_num_checkpoints', 'epoch_interval', 'step_interval'], varargs=None, keywords=None, defaults=(None, 3, 1, 10))
-paddle.fluid.Inferencer.__init__ ArgSpec(args=['self', 'infer_func', 'param_path', 'place', 'parallel'], varargs=None, keywords=None, defaults=(None, False))
-paddle.fluid.Inferencer.infer ArgSpec(args=['self', 'inputs', 'return_numpy'], varargs=None, keywords=None, defaults=(True,))
 paddle.fluid.DistributeTranspiler.__init__ ArgSpec(args=['self', 'config'], varargs=None, keywords=None, defaults=(None,))
 paddle.fluid.DistributeTranspiler.get_pserver_program ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None)
 paddle.fluid.DistributeTranspiler.get_pserver_programs ArgSpec(args=['self', 'endpoint'], varargs=None, keywords=None, defaults=None)

python/paddle/fluid/__init__.py

@@ -19,17 +19,8 @@ from .framework import *
 # import all class inside executor into fluid module
 from . import executor
 from .executor import *
-
 from . import trainer
-from .trainer import Trainer
-from .trainer import BeginEpochEvent
-from .trainer import EndEpochEvent
-from .trainer import BeginStepEvent
-from .trainer import EndStepEvent
-from .trainer import CheckpointConfig
-
 from . import inferencer
-from .inferencer import Inferencer
 
 from . import io
 from . import evaluator

python/paddle/fluid/contrib/inferencer.py

+#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import contextlib
+
+from .. import core
+
+from .. import executor
+from .. import framework
+from .. import io
+from .. import parallel_executor
+from .. import unique_name
+from .trainer import check_and_get_place
+
+__all__ = ['Inferencer', ]
+
+
+class Inferencer(object):
+    """
+    Inferencer High Level API.
+
+    Args:
+        infer_func (Python func): Infer function that will return predict Variable
+        param_path (str): The path where the inference model is saved by fluid.io.save_params
+        place (Place): place to do the inference
+        parallel (bool): use parallel_executor to run the inference, it will use multi CPU/GPU.
+
+    Examples:
+        .. code-block:: python
+
+            def inference_program():
+                x = fluid.layers.data(name='x', shape=[13], dtype='float32')
+                y_predict = fluid.layers.fc(input=x, size=1, act=None)
+                return y_predict
+
+            place = fluid.CPUPlace()
+            inferencer = fluid.Inferencer(
+                infer_func=inference_program, param_path="/tmp/model", place=place)
+
+    """
+
+    def __init__(self, infer_func, param_path, place=None, parallel=False):
+        self.param_path = param_path
+        self.scope = core.Scope()
+        self.parallel = parallel
+        self.place = check_and_get_place(place)
+
+        self.inference_program = framework.Program()
+        with framework.program_guard(self.inference_program):
+            with unique_name.guard():
+                self.predict_var = infer_func()
+
+        with self._prog_and_scope_guard():
+            # load params from param_path into scope
+            io.load_params(executor.Executor(self.place), param_path)
+
+        if parallel:
+            with self._prog_and_scope_guard():
+                self.exe = parallel_executor.ParallelExecutor(
+                    use_cuda=isinstance(self.place, core.CUDAPlace),
+                    loss_name=self.predict_var.name)
+        else:
+            self.exe = executor.Executor(self.place)
+
+        self.inference_program = self.inference_program.clone(for_test=True)
+
+    def infer(self, inputs, return_numpy=True):
+        """
+        Do Inference for Inputs
+
+        Args:
+            inputs (map): a map of {"input_name": input_var} that will be feed into the inference program
+            return_numpy (bool): transform return value into numpy or not
+
+        Returns:
+            Tensor or Numpy: the predict value of the inference model for the inputs
+
+        Examples:
+            .. code-block:: python
+
+                tensor_x = numpy.random.uniform(0, 10, [batch_size, 13]).astype("float32")
+                results = inferencer.infer({'x': tensor_x})
+        """
+        if not isinstance(inputs, dict):
+            raise ValueError(
+                "inputs should be a map of {'input_name': input_var}")
+
+        with self._prog_and_scope_guard():
+            results = self.exe.run(feed=inputs,
+                                   fetch_list=[self.predict_var.name],
+                                   return_numpy=return_numpy)
+
+        return results
+
+    @contextlib.contextmanager
+    def _prog_and_scope_guard(self):
+        with framework.program_guard(main_program=self.inference_program):
+            with executor.scope_guard(self.scope):
+                yield

python/paddle/fluid/inferencer.py

@@ -12,101 +12,5 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from __future__ import print_function
-
-import contextlib
-
-from . import core
-
-from . import executor
-from . import framework
-from . import io
-from . import parallel_executor
-from . import unique_name
-from .trainer import check_and_get_place
-
-__all__ = ['Inferencer', ]
-
-
-class Inferencer(object):
-    """
-    Inferencer High Level API.
-
-    Args:
-        infer_func (Python func): Infer function that will return predict Variable
-        param_path (str): The path where the inference model is saved by fluid.io.save_params
-        place (Place): place to do the inference
-        parallel (bool): use parallel_executor to run the inference, it will use multi CPU/GPU.
-
-    Examples:
-        .. code-block:: python
-
-            def inference_program():
-                x = fluid.layers.data(name='x', shape=[13], dtype='float32')
-                y_predict = fluid.layers.fc(input=x, size=1, act=None)
-                return y_predict
-
-            place = fluid.CPUPlace()
-            inferencer = fluid.Inferencer(
-                infer_func=inference_program, param_path="/tmp/model", place=place)
-
-    """
-
-    def __init__(self, infer_func, param_path, place=None, parallel=False):
-        self.param_path = param_path
-        self.scope = core.Scope()
-        self.parallel = parallel
-        self.place = check_and_get_place(place)
-
-        self.inference_program = framework.Program()
-        with framework.program_guard(self.inference_program):
-            with unique_name.guard():
-                self.predict_var = infer_func()
-
-        with self._prog_and_scope_guard():
-            # load params from param_path into scope
-            io.load_params(executor.Executor(self.place), param_path)
-
-        if parallel:
-            with self._prog_and_scope_guard():
-                self.exe = parallel_executor.ParallelExecutor(
-                    use_cuda=isinstance(self.place, core.CUDAPlace),
-                    loss_name=self.predict_var.name)
-        else:
-            self.exe = executor.Executor(self.place)
-
-        self.inference_program = self.inference_program.clone(for_test=True)
-
-    def infer(self, inputs, return_numpy=True):
-        """
-        Do Inference for Inputs
-
-        Args:
-            inputs (map): a map of {"input_name": input_var} that will be feed into the inference program
-            return_numpy (bool): transform return value into numpy or not
-
-        Returns:
-            Tensor or Numpy: the predict value of the inference model for the inputs
-
-        Examples:
-            .. code-block:: python
-
-                tensor_x = numpy.random.uniform(0, 10, [batch_size, 13]).astype("float32")
-                results = inferencer.infer({'x': tensor_x})
-        """
-        if not isinstance(inputs, dict):
-            raise ValueError(
-                "inputs should be a map of {'input_name': input_var}")
-
-        with self._prog_and_scope_guard():
-            results = self.exe.run(feed=inputs,
-                                   fetch_list=[self.predict_var.name],
-                                   return_numpy=return_numpy)
-
-        return results
-
-    @contextlib.contextmanager
-    def _prog_and_scope_guard(self):
-        with framework.program_guard(main_program=self.inference_program):
-            with executor.scope_guard(self.scope):
-                yield
+# NOTE: inferencer is moved into fluid.contrib.inferencer.
+__all__ = []

python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py

@@ -16,6 +16,16 @@ from __future__ import print_function
 
 import paddle
 import paddle.fluid as fluid
+import sys
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 import contextlib
 import numpy
 import unittest
@@ -57,11 +67,11 @@ def optimizer_func():
 def train(use_cuda, train_program, params_dirname, inference_model_dirname):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=train_program, place=place, optimizer_func=optimizer_func)
 
     def event_handler(event):
-        if isinstance(event, fluid.EndStepEvent):
+        if isinstance(event, EndStepEvent):
             if event.step == 10:
                 test_metrics = trainer.test(
                     reader=test_reader, feed_order=['x', 'y'])
@@ -91,7 +101,7 @@ def infer(use_cuda, inference_program, params_dirname=None):
         return
 
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
-    inferencer = fluid.Inferencer(
+    inferencer = Inferencer(
         infer_func=inference_program, param_path=params_dirname, place=place)
 
     batch_size = 10

python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py

@@ -14,11 +14,22 @@
 
 from __future__ import print_function
 
+import sys
+
 import paddle
 import paddle.fluid as fluid
+
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 import paddle.fluid.core as core
 import numpy
-import six
 import os
 import cifar10_small_test_set
 
@@ -106,7 +117,7 @@ def train(use_cuda, train_program, parallel, params_dirname):
         paddle.dataset.cifar.test10(), batch_size=BATCH_SIZE, drop_last=False)
 
     def event_handler(event):
-        if isinstance(event, fluid.EndStepEvent):
+        if isinstance(event, EndStepEvent):
             avg_cost, accuracy = trainer.test(
                 reader=test_reader, feed_order=['pixel', 'label'])
 
@@ -118,7 +129,7 @@ def train(use_cuda, train_program, parallel, params_dirname):
                 return
 
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=train_program,
         optimizer_func=optimizer_func,
         place=place,
@@ -133,7 +144,7 @@ def train(use_cuda, train_program, parallel, params_dirname):
 
 def infer(use_cuda, inference_program, parallel, params_dirname=None):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
-    inferencer = fluid.Inferencer(
+    inferencer = Inferencer(
         infer_func=inference_program,
         param_path=params_dirname,
         place=place,

python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py

@@ -14,11 +14,22 @@
 
 from __future__ import print_function
 
+import sys
+
 import paddle
 import paddle.fluid as fluid
+
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 import paddle.fluid.core as core
 import numpy
-import six
 import os
 import cifar10_small_test_set
 
@@ -83,7 +94,7 @@ def train(use_cuda, train_program, parallel, params_dirname):
         paddle.dataset.cifar.test10(), batch_size=BATCH_SIZE, drop_last=False)
 
     def event_handler(event):
-        if isinstance(event, fluid.EndStepEvent):
+        if isinstance(event, EndStepEvent):
             avg_cost, accuracy = trainer.test(
                 reader=test_reader, feed_order=['pixel', 'label'])
 
@@ -95,7 +106,7 @@ def train(use_cuda, train_program, parallel, params_dirname):
                 return
 
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=train_program,
         place=place,
         optimizer_func=optimizer_func,
@@ -110,7 +121,7 @@ def train(use_cuda, train_program, parallel, params_dirname):
 
 def infer(use_cuda, inference_program, parallel, params_dirname=None):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
-    inferencer = fluid.Inferencer(
+    inferencer = Inferencer(
         infer_func=inference_program,
         param_path=params_dirname,
         place=place,

python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/test_label_semantic_roles_newapi.py

@@ -16,6 +16,16 @@ from __future__ import print_function
 
 import paddle
 import paddle.fluid as fluid
+import sys
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 import numpy as np
 
 WORD_DICT, VERB_DICT, LABEL_DICT = paddle.dataset.conll05.get_dict()
@@ -149,7 +159,7 @@ def optimize_func():
 def train(use_cuda, train_program, params_dirname):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=train_program, place=place, optimizer_func=optimize_func)
 
     feed_order = [
@@ -164,7 +174,7 @@ def train(use_cuda, train_program, params_dirname):
     #        place)
 
     def event_handler(event):
-        if isinstance(event, fluid.EndEpochEvent):
+        if isinstance(event, EndEpochEvent):
             test_reader = paddle.batch(
                 paddle.dataset.conll05.test(), batch_size=BATCH_SIZE)
             avg_cost_set = trainer.test(
@@ -184,7 +194,7 @@ def train(use_cuda, train_program, params_dirname):
                 if math.isnan(float(avg_cost)):
                     sys.exit("got NaN loss, training failed.")
 
-        elif isinstance(event, fluid.EndStepEvent):
+        elif isinstance(event, EndStepEvent):
             print("Step {0}, Epoch {1} Metrics {2}".format(
                 event.step, event.epoch, list(map(np.array, event.metrics))))
             if event.step == 1:  # Run 2 iterations to speed CI
@@ -204,7 +214,7 @@ def train(use_cuda, train_program, params_dirname):
 
 def infer(use_cuda, inference_program, params_dirname):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
-    inferencer = fluid.Inferencer(
+    inferencer = Inferencer(
         inference_program, param_path=params_dirname, place=place)
 
     # Setup input by creating LoDTensor to represent sequence of words.

python/paddle/fluid/tests/book/high-level-api/machine_translation/test_machine_translation.py

@@ -13,17 +13,28 @@
 # limitations under the License.
 
 from __future__ import print_function
+
 import contextlib
+import sys
 
 import numpy as np
 import paddle
 import paddle.fluid as fluid
+
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 import paddle.fluid.framework as framework
 import paddle.fluid.layers as pd
 from paddle.fluid.executor import Executor
 from functools import partial
 import unittest
-import os
 
 dict_size = 30000
 source_dict_dim = target_dict_dim = dict_size
@@ -198,12 +209,12 @@ def train(use_cuda, is_sparse, is_local=True):
     ]
 
     def event_handler(event):
-        if isinstance(event, fluid.EndStepEvent):
+        if isinstance(event, EndStepEvent):
             print('pass_id=' + str(event.epoch) + ' batch=' + str(event.step))
             if event.step == 10:
                 trainer.stop()
 
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=partial(train_program, is_sparse),
         place=place,
         optimizer_func=optimizer_func)

python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py

@@ -14,14 +14,22 @@
 
 from __future__ import print_function
 
-import argparse
+import sys
+
 import paddle.fluid as fluid
+
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 import paddle.fluid.core as core
 import paddle
-import six
-import sys
 import numpy
-import unittest
 import math
 import sys
 import os
@@ -68,14 +76,14 @@ def optimizer_func():
 def train(use_cuda, train_program, parallel, params_dirname):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=train_program,
         place=place,
         optimizer_func=optimizer_func,
         parallel=parallel)
 
     def event_handler(event):
-        if isinstance(event, fluid.EndEpochEvent):
+        if isinstance(event, EndEpochEvent):
             test_reader = paddle.batch(
                 paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
             avg_cost, acc = trainer.test(
@@ -91,7 +99,7 @@ def train(use_cuda, train_program, parallel, params_dirname):
                     event.epoch + 1, avg_cost, acc))
                 if math.isnan(avg_cost):
                     sys.exit("got NaN loss, training failed.")
-        elif isinstance(event, fluid.EndStepEvent):
+        elif isinstance(event, EndStepEvent):
             print(
                 ("Step {0}, Epoch {1} Metrics {2}".format(
                     event.step, event.epoch,
@@ -112,7 +120,7 @@ def train(use_cuda, train_program, parallel, params_dirname):
 def infer(use_cuda, inference_program, parallel, params_dirname=None):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
-    inferencer = fluid.Inferencer(
+    inferencer = Inferencer(
         infer_func=inference_program,
         param_path=params_dirname,
         place=place,

python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py

@@ -14,14 +14,22 @@
 
 from __future__ import print_function
 
-import argparse
+import sys
+
 import paddle.fluid as fluid
+
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 import paddle.fluid.core as core
 import paddle
-import six
-import sys
 import numpy
-import unittest
 import math
 import sys
 import os
@@ -55,14 +63,14 @@ def optimizer_func():
 def train(use_cuda, train_program, params_dirname, parallel):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=train_program,
         place=place,
         optimizer_func=optimizer_func,
         parallel=parallel)
 
     def event_handler(event):
-        if isinstance(event, fluid.EndEpochEvent):
+        if isinstance(event, EndEpochEvent):
             test_reader = paddle.batch(
                 paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
             avg_cost, acc = trainer.test(
@@ -94,7 +102,7 @@ def train(use_cuda, train_program, params_dirname, parallel):
 def infer(use_cuda, inference_program, parallel, params_dirname=None):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
-    inferencer = fluid.Inferencer(
+    inferencer = Inferencer(
         infer_func=inference_program,
         param_path=params_dirname,
         place=place,

python/paddle/fluid/tests/book/high-level-api/recommender_system/test_recommender_system_newapi.py

@@ -19,6 +19,16 @@ import sys
 import numpy as np
 import paddle
 import paddle.fluid as fluid
+import sys
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 import paddle.fluid.layers as layers
 import paddle.fluid.nets as nets
 
@@ -164,7 +174,7 @@ def optimizer_func():
 def train(use_cuda, train_program, params_dirname):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=train_program, place=place, optimizer_func=optimizer_func)
 
     feed_order = [
@@ -173,7 +183,7 @@ def train(use_cuda, train_program, params_dirname):
     ]
 
     def event_handler(event):
-        if isinstance(event, fluid.EndStepEvent):
+        if isinstance(event, EndStepEvent):
             test_reader = paddle.batch(
                 paddle.dataset.movielens.test(), batch_size=BATCH_SIZE)
             avg_cost_set = trainer.test(
@@ -208,7 +218,7 @@ def train(use_cuda, train_program, params_dirname):
 
 def infer(use_cuda, inference_program, params_dirname):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
-    inferencer = fluid.Inferencer(
+    inferencer = Inferencer(
         inference_program, param_path=params_dirname, place=place)
 
     # Use the first data from paddle.dataset.movielens.test() as input.

python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_conv.py

@@ -16,6 +16,16 @@ from __future__ import print_function
 
 import paddle
 import paddle.fluid as fluid
+import sys
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 from functools import partial
 import numpy as np
 
@@ -72,13 +82,13 @@ def train(use_cuda, train_program, params_dirname):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
     word_dict = paddle.dataset.imdb.word_dict()
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=partial(train_program, word_dict),
         place=place,
         optimizer_func=optimizer_func)
 
     def event_handler(event):
-        if isinstance(event, fluid.EndEpochEvent):
+        if isinstance(event, EndEpochEvent):
             test_reader = paddle.batch(
                 paddle.dataset.imdb.test(word_dict), batch_size=BATCH_SIZE)
             avg_cost, acc = trainer.test(
@@ -96,7 +106,7 @@ def train(use_cuda, train_program, params_dirname):
                     event.epoch + 1, avg_cost, acc))
                 if math.isnan(avg_cost):
                     sys.exit("got NaN loss, training failed.")
-        elif isinstance(event, fluid.EndStepEvent):
+        elif isinstance(event, EndStepEvent):
             print("Step {0}, Epoch {1} Metrics {2}".format(
                 event.step, event.epoch, list(map(np.array, event.metrics))))
             if event.step == 1:  # Run 2 iterations to speed CI
@@ -119,7 +129,7 @@ def infer(use_cuda, inference_program, params_dirname=None):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
     word_dict = paddle.dataset.imdb.word_dict()
 
-    inferencer = fluid.Inferencer(
+    inferencer = Inferencer(
         infer_func=partial(inference_program, word_dict),
         param_path=params_dirname,
         place=place)

python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_dynamic_rnn.py

@@ -16,6 +16,16 @@ from __future__ import print_function
 
 import paddle
 import paddle.fluid as fluid
+import sys
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 from functools import partial
 import numpy as np
 
@@ -87,13 +97,13 @@ def train(use_cuda, train_program, params_dirname):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
     word_dict = paddle.dataset.imdb.word_dict()
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=partial(train_program, word_dict),
         place=place,
         optimizer_func=optimizer_func)
 
     def event_handler(event):
-        if isinstance(event, fluid.EndEpochEvent):
+        if isinstance(event, EndEpochEvent):
             test_reader = paddle.batch(
                 paddle.dataset.imdb.test(word_dict), batch_size=BATCH_SIZE)
             avg_cost, acc = trainer.test(
@@ -111,7 +121,7 @@ def train(use_cuda, train_program, params_dirname):
                     event.epoch + 1, avg_cost, acc))
                 if math.isnan(avg_cost):
                     sys.exit("got NaN loss, training failed.")
-        elif isinstance(event, fluid.EndStepEvent):
+        elif isinstance(event, EndStepEvent):
             print("Step {0}, Epoch {1} Metrics {2}".format(
                 event.step, event.epoch, list(map(np.array, event.metrics))))
             if event.step == 1:  # Run 2 iterations to speed CI
@@ -134,7 +144,7 @@ def infer(use_cuda, inference_program, params_dirname=None):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
     word_dict = paddle.dataset.imdb.word_dict()
 
-    inferencer = fluid.Inferencer(
+    inferencer = Inferencer(
         infer_func=partial(inference_program, word_dict),
         param_path=params_dirname,
         place=place)

python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_stacked_lstm.py

@@ -16,6 +16,16 @@ from __future__ import print_function
 
 import paddle
 import paddle.fluid as fluid
+import sys
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 from functools import partial
 import numpy as np
 
@@ -79,13 +89,13 @@ def train(use_cuda, train_program, params_dirname):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
     word_dict = paddle.dataset.imdb.word_dict()
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=partial(train_program, word_dict),
         place=place,
         optimizer_func=optimizer_func)
 
     def event_handler(event):
-        if isinstance(event, fluid.EndEpochEvent):
+        if isinstance(event, EndEpochEvent):
             test_reader = paddle.batch(
                 paddle.dataset.imdb.test(word_dict),
                 batch_size=BATCH_SIZE,
@@ -105,7 +115,7 @@ def train(use_cuda, train_program, params_dirname):
                     event.epoch + 1, avg_cost, acc))
                 if math.isnan(avg_cost):
                     sys.exit("got NaN loss, training failed.")
-        elif isinstance(event, fluid.EndStepEvent):
+        elif isinstance(event, EndStepEvent):
             print("Step {0}, Epoch {1} Metrics {2}".format(
                 event.step, event.epoch, list(map(np.array, event.metrics))))
             if event.step == 1:  # Run 2 iterations to speed CI
@@ -129,7 +139,7 @@ def infer(use_cuda, inference_program, params_dirname=None):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
     word_dict = paddle.dataset.imdb.word_dict()
 
-    inferencer = fluid.Inferencer(
+    inferencer = Inferencer(
         infer_func=partial(inference_program, word_dict),
         param_path=params_dirname,
         place=place)

python/paddle/fluid/tests/book/high-level-api/word2vec/test_word2vec_new_api.py

@@ -16,6 +16,16 @@ from __future__ import print_function
 
 import paddle
 import paddle.fluid as fluid
+import sys
+try:
+    from paddle.fluid.contrib.trainer import *
+    from paddle.fluid.contrib.inferencer import *
+except ImportError:
+    print(
+        "In the fluid 1.0, the trainer and inferencer are moving to paddle.fluid.contrib",
+        file=sys.stderr)
+    from paddle.fluid.trainer import *
+    from paddle.fluid.inferencer import *
 import numpy as np
 import math
 import sys
@@ -95,7 +105,7 @@ def train(use_cuda, train_program, params_dirname):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
 
     def event_handler(event):
-        if isinstance(event, fluid.EndStepEvent):
+        if isinstance(event, EndStepEvent):
             outs = trainer.test(
                 reader=test_reader,
                 feed_order=['firstw', 'secondw', 'thirdw', 'forthw', 'nextw'])
@@ -109,7 +119,7 @@ def train(use_cuda, train_program, params_dirname):
             if math.isnan(avg_cost):
                 sys.exit("got NaN loss, training failed.")
 
-    trainer = fluid.Trainer(
+    trainer = Trainer(
         train_func=train_program, optimizer_func=optimizer_func, place=place)
 
     trainer.train(
@@ -121,7 +131,7 @@ def train(use_cuda, train_program, params_dirname):
 
 def infer(use_cuda, inference_program, params_dirname=None):
     place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
-    inferencer = fluid.Inferencer(
+    inferencer = Inferencer(
         infer_func=inference_program, param_path=params_dirname, place=place)
 
     # Setup inputs by creating 4 LoDTensors representing 4 words. Here each word