diff --git a/python/paddle/fluid/__init__.py b/python/paddle/fluid/__init__.py
index 82bd5cd621e916054a10895fc04d6044e6f68576..ce1d92c309783e8dd2ad27bd5a293eb4abca7152 100644
--- a/python/paddle/fluid/__init__.py
+++ b/python/paddle/fluid/__init__.py
@@ -51,7 +51,6 @@ from .data import *
 from . import trainer_desc
 
 from . import io
-from . import evaluator
 from . import initializer
 from .initializer import set_global_initializer
 from . import layers
diff --git a/python/paddle/fluid/entry_attr.py b/python/paddle/fluid/entry_attr.py
deleted file mode 100644
index 29ab37a3f3f4cf5c57e4dbb8b96e973efea7a382..0000000000000000000000000000000000000000
--- a/python/paddle/fluid/entry_attr.py
+++ /dev/null
@@ -1,74 +0,0 @@
-#   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.
-
-__all__ = ['ProbabilityEntry', 'CountFilterEntry']
-
-
-class EntryAttr:
-    """
-    Examples:
-        .. code-block:: python
-
-            import paddle.fluid as fluid
-    """
-
-    def __init__(self):
-        self._name = None
-
-    def _to_attr(self):
-        """
-        Returns the attributes of this parameter.
-
-        Returns:
-            Parameter attributes(map): The attributes of this parameter.
-        """
-        raise NotImplementedError("EntryAttr is base class")
-
-
-class ProbabilityEntry(EntryAttr):
-    def __init__(self, probability):
-        super().__init__()
-
-        if not isinstance(probability, float):
-            raise ValueError("probability must be a float in (0,1)")
-
-        if probability <= 0 or probability >= 1:
-            raise ValueError("probability must be a float in (0,1)")
-
-        self._name = "probability_entry"
-        self._probability = probability
-
-    def _to_attr(self):
-        return ":".join([self._name, str(self._probability)])
-
-
-class CountFilterEntry(EntryAttr):
-    def __init__(self, count_filter):
-        super().__init__()
-
-        if not isinstance(count_filter, int):
-            raise ValueError(
-                "count_filter must be a valid integer greater than 0"
-            )
-
-        if count_filter < 0:
-            raise ValueError(
-                "count_filter must be a valid integer greater or equal than 0"
-            )
-
-        self._name = "count_filter_entry"
-        self._count_filter = count_filter
-
-    def _to_attr(self):
-        return ":".join([self._name, str(self._count_filter)])
diff --git a/python/paddle/fluid/evaluator.py b/python/paddle/fluid/evaluator.py
deleted file mode 100644
index a4d80ecbfed25f8e4fcbc24f76b87a6a4ebe0b2d..0000000000000000000000000000000000000000
--- a/python/paddle/fluid/evaluator.py
+++ /dev/null
@@ -1,120 +0,0 @@
-#   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.
-
-import warnings
-import numpy as np
-
-import paddle
-from . import layers
-from .framework import Program, Variable, program_guard
-from . import unique_name
-from .layer_helper import LayerHelper
-
-
-def _clone_var_(block, var):
-    assert isinstance(var, Variable)
-    return block.create_var(
-        name=var.name,
-        shape=var.shape,
-        dtype=var.dtype,
-        type=var.type,
-        lod_level=var.lod_level,
-        persistable=True,
-    )
-
-
-class Evaluator:
-    """
-    Warning: better to use the fluid.metrics.* things, more
-    flexible support via pure Python and Operator, and decoupled
-    with executor. Short doc are intended to urge new user
-    start from Metrics.
-
-    Base Class for all evaluators.
-
-    Args:
-        name(str): The name of evaluator. such as, "accuracy". Used for generate
-            temporary variable name.
-        main_program(Program, optional): The evaluator should be added to this
-            main_program. Default default_main_program()
-        startup_program(Program, optional):The parameter should be added to this
-            startup_program. Default default_startup_program()
-
-    Attributes:
-        states(list): The list of state variables. states will be reset to zero
-            when `reset` is invoked.
-        metrics(list): The list of metrics variables. They will be calculate
-            every mini-batch
-    """
-
-    def __init__(self, name, **kwargs):
-        warnings.warn(
-            "The %s is deprecated, because maintain a modified program inside evaluator cause bug easily, please use fluid.metrics.%s instead."
-            % (self.__class__.__name__, self.__class__.__name__),
-            Warning,
-        )
-        self.states = []
-        self.metrics = []
-        self.helper = LayerHelper(name, **kwargs)
-
-    def reset(self, executor, reset_program=None):
-        """
-        reset metric states at the begin of each pass/user specified batch
-
-        Args:
-            executor(Executor|ParallelExecutor): a executor for executing the reset_program
-            reset_program(Program): a single Program for reset process
-        """
-        if reset_program is None:
-            reset_program = Program()
-
-        with program_guard(main_program=reset_program):
-            for var in self.states:
-                assert isinstance(var, Variable)
-                g_var = _clone_var_(reset_program.current_block(), var)
-                layers.fill_constant(
-                    shape=g_var.shape, value=0.0, dtype=g_var.dtype, out=g_var
-                )
-
-        executor.run(reset_program)
-
-    def eval(self, executor, eval_program=None):
-        """
-        Evaluate the statistics merged by multiple mini-batches.
-        Args:
-            executor(Executor|ParallelExecutor): a executor for executing the eval_program
-            eval_program(Program): a single Program for eval process
-        """
-        raise NotImplementedError()
-
-    def _create_state(self, suffix, dtype, shape):
-        """
-        Create state variable.
-
-        Args:
-            suffix(str): the state suffix.
-            dtype(str|core.VarDesc.VarType): the state data type
-            shape(tuple|list): the shape of state
-
-        Returns: State variable
-
-        """
-        state = self.helper.create_variable(
-            name="_".join([unique_name.generate(self.helper.name), suffix]),
-            persistable=True,
-            dtype=dtype,
-            shape=shape,
-        )
-        self.states.append(state)
-        return state
diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py
index bd5049e74f29a99f71249160a5410923a1260bc5..f61b4bbe2339ec7c3d4de9d8395da4eaf5f8b481 100644
--- a/python/paddle/fluid/io.py
+++ b/python/paddle/fluid/io.py
@@ -27,7 +27,6 @@ import math
 import paddle
 from paddle.fluid import layers
 from paddle.fluid.executor import Executor, global_scope
-from paddle.fluid.evaluator import Evaluator
 from paddle.fluid.framework import (
     Program,
     Parameter,