【fluid clean】remove fluid.data (#50699)

* remove fluid.data

* fix typro

* fix somme unitest error

* fix conflicts

* fix sample code error

* fxi sample coder error

* fxi sample code error

* fxi sample code error

* fix xpu test error

* fix xpu test error

* Delete ps_pb2.py

* fix test error

* fix typro

* fix sample code error

* fix comments

* fix test norm op data

* fix sample code error

* fix conflicts

paddle/fluid/framework/reader.h

@@ -92,8 +92,6 @@ class ReaderBase {
   std::vector<proto::VarType::Type> var_types_;
 
   // Whether to check the shape and dtype of fed variables.
-  // For Backward compatibility, variables created by old API fluid.layers.data
-  // doesn't check shape but fluid.data checks.
   std::vector<bool> need_check_feed_;
 
  private:

python/paddle/fluid/__init__.py

@@ -46,8 +46,6 @@ from .data_feed_desc import *
 from . import dataset
 from .dataset import *
 
-from .data import *
-
 from . import trainer_desc
 
 from . import io
@@ -117,7 +115,6 @@ __all__ = (
         'initializer',
         'layers',
         'contrib',
-        'data',
         'dygraph',
         'enable_dygraph',
         'disable_dygraph',

python/paddle/fluid/contrib/layers/nn.py

@@ -567,8 +567,9 @@ def partial_concat(input, start_index=0, length=-1):
     Examples:
         .. code-block:: python
             import paddle.fluid as fluid
-            x = fluid.data(name="x", shape=[None,3], dtype="float32")
-            y = fluid.data(name="y", shape=[None,3], dtype="float32")
+            import paddle
+            x = paddle.randn(name="x", shape=[1,3], dtype="float32")
+            y = paddle.randn(name="y", shape=[1,3], dtype="float32")
             concat = fluid.contrib.layers.partial_concat(
                 [x, y], start_index=0, length=2)
     """
@@ -629,9 +630,12 @@ def partial_sum(input, start_index=0, length=-1):
         import paddle.fluid.layers as layers
         import paddle.fluid as fluid
         import numpy as np
-        x = fluid.data(name="x", shape=[None, 3], dtype="float32")
-        y = fluid.data(name="y", shape=[None, 3], dtype="float32")
-        sum = layers.partial_sum([x,y], start_index=0, length=2)
+        import paddle
+        paddle.enable_static()
+
+        x = paddle.static.data(name="x", shape=[2, 3], dtype="float32")
+        y = paddle.static.data(name="y", shape=[2, 3], dtype="float32")
+        sum = fluid.contrib.layers.partial_sum([x,y], start_index=0, length=2)
         place = fluid.CPUPlace()
         exe = fluid.Executor(place)
         xx = np.array([1,2,3,4,5,6]).reshape((2,3)).astype("float32")
@@ -898,7 +902,7 @@ def tdm_child(x, node_nums, child_nums, param_attr=None, dtype='int32'):
         import paddle.fluid as fluid
         import numpy as np
         paddle.enable_static()
-        x = fluid.data(name="x", shape=[None, 1], dtype="int32", lod_level=1)
+        x = paddle.static.data(name="x", shape=[None, 1], dtype="int32", lod_level=1)
         tree_info = [[0,0,0,1,2],
                      [0,1,0,3,4],[0,1,0,5,6],
                      [0,2,1,0,0],[1,2,1,0,0],[2,2,2,0,0],[3,2,2,0,0]]
@@ -1007,7 +1011,7 @@ def tdm_sampler(
         import paddle.fluid as fluid
         import numpy as np
         paddle.enable_static()
-        x = fluid.data(name="x", shape=[None, 1], dtype="int32", lod_level=1)
+        x = paddle.static.data(name="x", shape=[None, 1], dtype="int32", lod_level=1)
         travel_list = [[1, 3], [1, 4], [2, 5], [2, 6]] # leaf node's travel path, shape(leaf_node_num, layer_num)
         layer_list_flat = [[1], [2], [3], [4], [5], [6]] # shape(node_nums, 1)
 
@@ -1197,18 +1201,17 @@ def rank_attention(
     Examples:
         .. code-block:: python
            import paddle.fluid as fluid
-           import numpy as np
+           import paddle
+           paddle.enable_static()
 
-           input = fluid.data(name="input", shape=[None, 2], dtype="float32")
-           rank_offset = fluid.data(name="rank_offset", shape=[None, 7], dtype="int32")
+           input = paddle.static.data(name="input", shape=[None, 2], dtype="float32")
+           rank_offset = paddle.static.data(name="rank_offset", shape=[None, 7], dtype="int32")
            out = fluid.contrib.layers.rank_attention(input=input,
                                                      rank_offset=rank_offset,
                                                      rank_param_shape=[18,3],
                                                      rank_param_attr=
-                                                       fluid.ParamAttr(learning_rate=1.0,
-                                                                     name="ubm_rank_param.w_0",
-                                                                     initializer=
-                                                                     fluid.initializer.Xavier(uniform=False)),
+                                                     paddle.ParamAttr(learning_rate=1.0,
+                                                                     name="ubm_rank_param.w_0"),
                                                       max_rank=3,
                                                       max_size=0)
     """
@@ -1259,22 +1262,21 @@ def batch_fc(input, param_size, param_attr, bias_size, bias_attr, act=None):
     Examples:
         .. code-block:: python
            import paddle.fluid as fluid
+           import paddle
 
-           input = fluid.data(name="input", shape=[16, 2, 3], dtype="float32")
+           paddle.enable_static()
+
+           input = paddle.static.data(name="input", shape=[16, 2, 3], dtype="float32")
            out = fluid.contrib.layers.batch_fc(input=input,
                                                param_size=[16, 3, 10],
                                                param_attr=
-                                                 fluid.ParamAttr(learning_rate=1.0,
-                                                               name="w_0",
-                                                               initializer=
-                                                               fluid.initializer.Xavier(uniform=False)),
+                                               paddle.ParamAttr(learning_rate=1.0,
+                                                               name="w_0"),
                                                bias_size=[16, 10],
                                                bias_attr=
-                                                 fluid.ParamAttr(learning_rate=1.0,
-                                                               name="b_0",
-                                                               initializer=
-                                                               fluid.initializer.Xavier(uniform=False)),
-                                                   act="relu")
+                                               paddle.ParamAttr(learning_rate=1.0,
+                                                               name="b_0"),
+                                               act="relu")
     """
 
     helper = LayerHelper("batch_fc", **locals())
@@ -1380,10 +1382,12 @@ def bilateral_slice(x, guide, grid, has_offset, name=None):
         .. code-block:: python
 
             import paddle.fluid as fluid
+            import paddle
+            paddle.enable_static()
 
-            x = fluid.data(name='x', shape=[None, 3, 101, 60], dtype='float32')
-            guide = fluid.data(name='guide', shape=[None, 101, 60], dtype='float32')
-            grid = fluid.data(name='grid', shape=[None, 12, 8, 10, 6], dtype='float32')
+            x = paddle.randn(name='x', shape=[1, 3, 101, 60], dtype='float32')
+            guide = paddle.randn(name='guide', shape=[1, 101, 60], dtype='float32')
+            grid = paddle.randn(name='grid', shape=[1, 12, 8, 10, 6], dtype='float32')
 
             # without offset
             output = fluid.contrib.bilateral_slice(x, guide, grid, has_offset=False)

python/paddle/fluid/data.py

-#   Copyright (c) 2019 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 numpy as np
-
-from paddle.fluid import core
-from paddle.fluid.layer_helper import LayerHelper
-from paddle.fluid.data_feeder import check_dtype, check_type
-from ..utils import deprecated
-from paddle.fluid.framework import static_only
-
-__all__ = ['data']
-
-
-@static_only
-@deprecated(since="2.0.0", update_to="paddle.static.data")
-def data(name, shape, dtype='float32', lod_level=0):
-    """
-    **Data Layer**
-
-    This function creates a variable on the global block. The global variable
-    can be accessed by all the following operators in the graph. The variable
-    is a placeholder that could be fed with input, such as Executor can feed
-    input into the variable.
-
-    Note:
-        `paddle.fluid.layers.data` is deprecated. It will be removed in a
-        future version. Please use this `paddle.fluid.data`.
-
-        The `paddle.fluid.layers.data` set shape and dtype at compile time but
-        does NOT check the shape or the dtype of fed data, this
-        `paddle.fluid.data` checks the shape and the dtype of data fed by
-        Executor or ParallelExecutor during run time.
-
-        To feed variable size inputs, users can set None or -1 on the variable
-        dimension when using :code:`paddle.fluid.data`, or feed variable size
-        inputs directly to :code:`paddle.fluid.layers.data` and PaddlePaddle
-        will fit the size accordingly.
-
-        The default :code:`stop_gradient` attribute of the Variable created by
-        this API is true, which means the gradient won't be passed backward
-        through the data Variable. Set :code:`var.stop_gradient = False` If
-        user would like to pass backward gradient.
-
-    Args:
-       name (str): The name/alias of the variable, see :ref:`api_guide_Name`
-           for more details.
-       shape (list|tuple): List|Tuple of integers declaring the shape. You can
-           set "None" or -1 at a dimension to indicate the dimension can be of any
-           size. For example, it is useful to set changeable batch size as "None" or -1.
-       dtype (np.dtype|VarType|str, optional): The type of the data. Supported
-           dtype: bool, float16, float32, float64, int8, int16, int32, int64,
-           uint8. Default: float32.
-       lod_level (int, optional): The LoD level of the LoDTensor. Usually users
-           don't have to set this value. For more details about when and how to
-           use LoD level, see :ref:`user_guide_lod_tensor` . Default: 0.
-
-    Returns:
-        Variable: The global variable that gives access to the data.
-
-    Examples:
-        .. code-block:: python
-
-          import paddle
-          import paddle.fluid as fluid
-          import numpy as np
-          paddle.enable_static()
-
-          # Creates a variable with fixed size [3, 2, 1]
-          # User can only feed data of the same shape to x
-          x = fluid.data(name='x', shape=[3, 2, 1], dtype='float32')
-
-          # Creates a variable with changeable batch size -1.
-          # Users can feed data of any batch size into y,
-          # but size of each data sample has to be [2, 1]
-          y = fluid.data(name='y', shape=[-1, 2, 1], dtype='float32')
-
-          z = x + y
-
-          # In this example, we will feed x and y with np-ndarray "1"
-          # and fetch z, like implementing "1 + 1 = 2" in PaddlePaddle
-          feed_data = np.ones(shape=[3, 2, 1], dtype=np.float32)
-
-          exe = fluid.Executor(fluid.CPUPlace())
-          out = exe.run(fluid.default_main_program(),
-                        feed={
-                            'x': feed_data,
-                            'y': feed_data
-                        },
-                        fetch_list=[z.name])
-
-          # np-ndarray of shape=[3, 2, 1], dtype=float32, whose elements are 2
-          print(out)
-
-    """
-    helper = LayerHelper('data', **locals())
-
-    check_type(name, 'name', (bytes, str), 'data')
-    check_type(shape, 'shape', (list, tuple), 'data')
-
-    shape = list(shape)
-    for i in range(len(shape)):
-        if shape[i] is None:
-            shape[i] = -1
-
-    return helper.create_global_variable(
-        name=name,
-        shape=shape,
-        dtype=dtype,
-        type=core.VarDesc.VarType.LOD_TENSOR,
-        stop_gradient=True,
-        lod_level=lod_level,
-        is_data=True,
-        need_check_feed=True,
-    )

python/paddle/fluid/data_feeder.py

@@ -347,8 +347,8 @@ class DataFeeder:
             startup_program = fluid.Program()
 
             with fluid.program_guard(main_program, startup_program):
-                data_1 = fluid.data(name='data_1', shape=[None, 2, 2], dtype='float32')
-                data_2 = fluid.data(name='data_2', shape=[None, 1, 3], dtype='float32')
+                data_1 = paddle.static.data(name='data_1', shape=[None, 2, 2], dtype='float32')
+                data_2 = paddle.static.data(name='data_2', shape=[None, 1, 3], dtype='float32')
                 out = paddle.static.nn.fc(x=[data_1, data_2], size=2)
                 # ...
             feeder = fluid.DataFeeder([data_1, data_2], place)
@@ -414,9 +414,9 @@ class DataFeeder:
                     for i in range(1, limit + 1):
                         yield np.ones([6]).astype('float32') * i , np.ones([1]).astype('int64') * i, np.random.random([9]).astype('float32')
 
-                data_1 = fluid.data(name='data_1', shape=[None, 2, 1, 3])
-                data_2 = fluid.data(name='data_2', shape=[None, 1], dtype='int64')
-                data_3 = fluid.data(name='data_3', shape=[None, 3, 3], dtype='float32')
+                data_1 = paddle.static.data(name='data_1', shape=[None, 2, 1, 3])
+                data_2 = paddle.static.data(name='data_2', shape=[None, 1], dtype='int64')
+                data_3 = paddle.static.data(name='data_3', shape=[None, 3, 3], dtype='float32')
                 feeder = fluid.DataFeeder(['data_1','data_2', 'data_3'], fluid.CPUPlace())
 
 
@@ -482,8 +482,8 @@ class DataFeeder:
                             yield np.ones([4]) * factor + base, np.ones([4]) * factor + base + 5
                     return _reader()
 
-                x = fluid.data(name='x', shape=[None, 2, 2])
-                y = fluid.data(name='y', shape=[None, 2, 2], dtype='float32')
+                x = paddle.static.data(name='x', shape=[None, 2, 2])
+                y = paddle.static.data(name='y', shape=[None, 2, 2], dtype='float32')
 
                 z = paddle.add(x, y)
 
@@ -582,8 +582,8 @@ class DataFeeder:
                 places = [fluid.CPUPlace() for _ in range(place_num)]
 
                 # a simple network sample
-                data = fluid.data(name='data', shape=[None, 4, 4], dtype='float32')
-                label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+                data = paddle.static.data(name='data', shape=[None, 4, 4], dtype='float32')
+                label = paddle.static.data(name='label', shape=[None, 1], dtype='int64')
                 hidden = paddle.static.nn.fc(x=data, size=10)
 
                 feeder = fluid.DataFeeder(place=places[0], feed_list=[data, label])

python/paddle/fluid/executor.py

@@ -1687,7 +1687,7 @@ class Executor:
 
         compiled = isinstance(program, compiler.CompiledProgram)
 
-        # Check if fluid.data() variable no feed data
+        # Check if paddle.static.data() variable no feed data
         if use_prune:
             if compiled:
                 global_block = program._program.global_block()

python/paddle/fluid/framework.py

@@ -2072,9 +2072,9 @@ class Variable(metaclass=VariableMetaClass):
         Examples:
           .. code-block:: python
 
-          import paddle.fluid as fluid
+          import paddle
 
-          x = fluid.data(name="x", shape=[-1, 23, 48], dtype='float32')
+          x = paddle.static.data(name="x", shape=[-1, 23, 48], dtype='float32')
           print(x.grad_name) # output is ``x@GRAD``
 
         """

python/paddle/fluid/io.py

@@ -190,8 +190,8 @@ def save_inference_model(
             path = "./infer_model"
 
             # User defined network, here a softmax regession example
-            image = fluid.data(name='img', shape=[None, 28, 28], dtype='float32')
-            label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+            image = paddle.static.data(name='img', shape=[None, 28, 28], dtype='float32')
+            label = paddle.static.data(name='label', shape=[None, 1], dtype='int64')
             feeder = fluid.DataFeeder(feed_list=[image, label], place=fluid.CPUPlace())
             predict = paddle.static.nn.fc(x=image, size=10, activation='softmax')
 

python/paddle/fluid/layers/control_flow.py

@@ -335,7 +335,7 @@ class StaticRNN:
 
             vocab_size, hidden_size=10000, 200
             paddle.enable_static()
-            x = fluid.data(name="x", shape=[None, 1, 1], dtype='int64')
+            x = paddle.static.data(name="x", shape=[None, 1, 1], dtype='int64')
             # create word sequence
             x_emb = layers.embedding(
                 input=x,
@@ -426,7 +426,7 @@ class StaticRNN:
 
                 vocab_size, hidden_size=10000, 200
                 paddle.enable_static()
-                x = fluid.data(name="x", shape=[None, 1, 1], dtype='int64')
+                x = paddle.static.data(name="x", shape=[None, 1, 1], dtype='int64')
                 # create word sequence
                 x_emb = layers.embedding(
                         input=x,
@@ -455,7 +455,7 @@ class StaticRNN:
                 import paddle.fluid.layers as layers
                 vocab_size, hidden_size=10000, 200
                 paddle.enable_static()
-                x = fluid.data(name="x", shape=[None, 1, 1], dtype='int64')
+                x = paddle.static.data(name="x", shape=[None, 1, 1], dtype='int64')
                 # create word sequence
                 x_emb = layers.embedding(
                         input=x,
@@ -558,7 +558,7 @@ class StaticRNN:
 
                 vocab_size, hidden_size=10000, 200
                 paddle.enable_static()
-                x = fluid.data(name="x", shape=[None, 1, 1], dtype='int64')
+                x = paddle.static.data(name="x", shape=[None, 1, 1], dtype='int64')
                 # create word sequence
                 x_emb = layers.embedding(
                         input=x,
@@ -611,7 +611,7 @@ class StaticRNN:
 
                 vocab_size, hidden_size=10000, 200
                 paddle.enable_static()
-                x = fluid.data(name="x", shape=[None, 1, 1], dtype='int64')
+                x = paddle.static.data(name="x", shape=[None, 1, 1], dtype='int64')
                 # create word sequence
                 x_emb = layers.embedding(
                         input=x,
@@ -673,7 +673,7 @@ class StaticRNN:
 
                 vocab_size, hidden_size=10000, 200
                 paddle.enable_static()
-                x = fluid.data(name="x", shape=[None, 1, 1], dtype='int64')
+                x = paddle.static.data(name="x", shape=[None, 1, 1], dtype='int64')
                 # create word sequence
                 x_emb = layers.embedding(
                         input=x,
@@ -955,7 +955,7 @@ class While:
             i = paddle.full(shape=[1], dtype='int64', fill_value=0)
             loop_len = paddle.full(shape=[1], dtype='int64', fill_value=10)
             one = paddle.full(shape=[1], dtype='float32', fill_value=1)
-            data = fluid.data(name='data', shape=[1], dtype='float32')
+            data = paddle.static.data(name='data', shape=[1], dtype='float32')
             sums = paddle.full(shape=[1], dtype='float32', fill_value=0)  # Define the variable to be obtained ouside of While, which name should be different from the variable inside the While to be obtained
 
             cond = paddle.less_than(x=i, y=loop_len)

python/paddle/fluid/layers/math_op_patch.py

@@ -183,13 +183,13 @@ def monkey_patch_variable():
             In Static Graph Mode:
 
             .. code-block:: python
-
+                import paddle
                 import paddle.fluid as fluid
-
+                paddle.enable_static()
                 startup_prog = fluid.Program()
                 main_prog = fluid.Program()
                 with fluid.program_guard(startup_prog, main_prog):
-                    original_variable = fluid.data(name = "new_variable", shape=[2,2], dtype='float32')
+                    original_variable = paddle.static.data(name = "new_variable", shape=[2,2], dtype='float32')
                     new_variable = original_variable.astype('int64')
                     print("new var's dtype is: {}".format(new_variable.dtype))
 

python/paddle/fluid/layers/nn.py

@@ -206,7 +206,7 @@ def embedding(
           import paddle
           paddle.enable_static()
 
-          data = fluid.data(name='x', shape=[None, 1], dtype='int64')
+          data = paddle.static.data(name='x', shape=[None, 1], dtype='int64')
 
           # example 1
           emb_1 = paddle.static.nn.embedding(input=data, size=[128, 64])
@@ -572,7 +572,7 @@ def reduce_sum(input, dim=None, keep_dim=False, name=None):
             #    [[0.2, 0.3, 0.5, 0.9]
             #     [0.1, 0.2, 0.6, 0.7]]
             # Each example is followed by the corresponding output tensor.
-            x = fluid.data(name='x', shape=[2, 4], dtype='float32')
+            x = paddle.static.data(name='x', shape=[2, 4], dtype='float32')
             fluid.layers.nn.reduce_sum(x)  # [3.5]
             fluid.layers.nn.reduce_sum(x, dim=0)  # [0.3, 0.5, 1.1, 1.6]
             fluid.layers.nn.reduce_sum(x, dim=-1)  # [1.9, 1.6]
@@ -582,7 +582,7 @@ def reduce_sum(input, dim=None, keep_dim=False, name=None):
             #      [[[1, 2], [3, 4]],
             #      [[5, 6], [7, 8]]]
             # Each example is followed by the corresponding output tensor.
-            y = fluid.data(name='y', shape=[2, 2, 2], dtype='float32')
+            y = paddle.static.data(name='y', shape=[2, 2, 2], dtype='float32')
             fluid.layers.nn.reduce_sum(y, dim=[1, 2]) # [10, 26]
             fluid.layers.nn.reduce_sum(y, dim=[0, 1]) # [16, 20]
 

python/paddle/fluid/nets.py

@@ -111,7 +111,7 @@ def simple_img_conv_pool(
             import paddle.fluid as fluid
             import paddle
             paddle.enable_static()
-            img = fluid.data(name='img', shape=[100, 1, 28, 28], dtype='float32')
+            img = paddle.static.data(name='img', shape=[100, 1, 28, 28], dtype='float32')
             conv_pool = fluid.nets.simple_img_conv_pool(input=img,
                                                         filter_size=5,
                                                         num_filters=20,
@@ -214,7 +214,7 @@ def img_conv_group(
             import paddle
             paddle.enable_static()
 
-            img = fluid.data(name='img', shape=[None, 1, 28, 28], dtype='float32')
+            img = paddle.static.data(name='img', shape=[None, 1, 28, 28], dtype='float32')
             conv_pool = fluid.nets.img_conv_group(input=img,
                                                   conv_padding=1,
                                                   conv_num_filter=[3, 3],
@@ -331,7 +331,7 @@ def sequence_conv_pool(
             input_dim = 100 #len(word_dict)
             emb_dim = 128
             hid_dim = 512
-            data = fluid.data(name="words", shape=[None, 1], dtype="int64", lod_level=1)
+            data = paddle.static.data(name="words", shape=[None, 1], dtype="int64", lod_level=1)
             emb = fluid.layers.embedding(input=data, size=[input_dim, emb_dim], is_sparse=True)
             seq_conv = fluid.nets.sequence_conv_pool(input=emb,
                                                      num_filters=hid_dim,
@@ -391,7 +391,7 @@ def glu(input, dim=-1):
             import paddle
             paddle.enable_static()
 
-            data = fluid.data(
+            data = paddle.static.data(
                 name="words", shape=[-1, 6, 3, 9], dtype="float32")
             # shape of output: [-1, 3, 3, 9]
             output = fluid.nets.glu(input=data, dim=1)
@@ -472,9 +472,9 @@ def scaled_dot_product_attention(
             import paddle
             paddle.enable_static()
 
-            queries = fluid.data(name="queries", shape=[3, 5, 9], dtype="float32")
-            keys = fluid.data(name="keys", shape=[3, 6, 9], dtype="float32")
-            values = fluid.data(name="values", shape=[3, 6, 10], dtype="float32")
+            queries = paddle.static.data(name="queries", shape=[3, 5, 9], dtype="float32")
+            keys = paddle.static.data(name="keys", shape=[3, 6, 9], dtype="float32")
+            values = paddle.static.data(name="values", shape=[3, 6, 10], dtype="float32")
             contexts = fluid.nets.scaled_dot_product_attention(queries, keys, values)
             contexts.shape  # [3, 5, 10]
     """

python/paddle/fluid/optimizer.py

@@ -2036,7 +2036,7 @@ class AdagradOptimizer(Optimizer):
 
             paddle.enable_static()
             np_inp = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
-            inp = fluid.data(name="inp", shape=[2, 2])
+            inp = paddle.static.data(name="inp", shape=[2, 2], dtype="float32")
             out = paddle.static.nn.fc(inp, size=3)
             out = paddle.sum(out)
             optimizer = fluid.optimizer.AdagradOptimizer(learning_rate=0.2)
@@ -2228,8 +2228,8 @@ class AdamOptimizer(Optimizer):
             place = fluid.CPUPlace()
             main = fluid.Program()
             with fluid.program_guard(main):
-                x = fluid.data(name='x', shape=[None, 13], dtype='float32')
-                y = fluid.data(name='y', shape=[None, 1], dtype='float32')
+                x = paddle.static.data(name='x', shape=[None, 13], dtype='float32')
+                y = paddle.static.data(name='y', shape=[None, 1], dtype='float32')
                 y_predict = paddle.static.nn.fc(x, size=1, activation=None)
                 cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y)
                 avg_cost = paddle.mean(cost)
@@ -2257,8 +2257,8 @@ class AdamOptimizer(Optimizer):
             place = fluid.CPUPlace()
             main = fluid.Program()
             with fluid.program_guard(main):
-                x = fluid.data(name='x', shape=[None, 13], dtype='float32')
-                y = fluid.data(name='y', shape=[None, 1], dtype='float32')
+                x = paddle.static.data(name='x', shape=[None, 13], dtype='float32')
+                y = paddle.static.data(name='y', shape=[None, 1], dtype='float32')
                 y_predict = paddle.static.nn.fc(x, size=1, activation=None)
                 cost = paddle.nn.functional.square_error_cost(input=y_predict, label=y)
                 avg_cost = paddle.mean(cost)
@@ -2292,8 +2292,8 @@ class AdamOptimizer(Optimizer):
                     div_res = global_step / decay_steps
                     decayed_beta1 = beta1_init * (decay_rate**div_res)
                     decayed_beta2 = beta2_init * (decay_rate**div_res)
-                    fluid.layers.assign(decayed_beta1, beta1)
-                    fluid.layers.assign(decayed_beta2, beta2)
+                    paddle.assign(decayed_beta1, beta1)
+                    paddle.assign(decayed_beta2, beta2)
 
                     return beta1, beta2, epsilon
 
@@ -2651,7 +2651,7 @@ class AdamaxOptimizer(Optimizer):
           train_program = fluid.Program()
           startup_program = fluid.Program()
           with fluid.program_guard(train_program, startup_program):
-              data = fluid.data(name='X', shape=[None, 1], dtype='float32')
+              data = paddle.static.data(name='X', shape=[None, 1], dtype='float32')
               hidden = paddle.static.nn.fc(x=data, size=10)
               loss = paddle.mean(hidden)
               adam = fluid.optimizer.AdamaxOptimizer(learning_rate=0.2)
@@ -2994,7 +2994,7 @@ class DecayedAdagradOptimizer(Optimizer):
             import paddle.fluid as fluid
 
             paddle.enable_static()
-            x = fluid.data(name='x', shape=[None, 10], dtype='float32')
+            x = paddle.static.data(name='x', shape=[None, 10], dtype='float32')
             trans = paddle.static.nn.fc(x, 100)
             cost = paddle.mean(trans)
             optimizer = fluid.optimizer.DecayedAdagradOptimizer(learning_rate=0.2)
@@ -3118,7 +3118,7 @@ class AdadeltaOptimizer(Optimizer):
             import paddle.fluid as fluid
 
             paddle.enable_static()
-            image = fluid.data(name='image', shape=[None, 28], dtype='float32')
+            image = paddle.static.data(name='image', shape=[None, 28], dtype='float32')
             fc = paddle.static.nn.fc(image, size=10)
             cost = paddle.mean(fc)
             optimizer = fluid.optimizer.Adadelta(
@@ -3747,7 +3747,7 @@ class LambOptimizer(AdamOptimizer):
             import paddle.fluid as fluid
             paddle.enable_static()
 
-            data = fluid.data(name='x', shape=[-1, 5], dtype='float32')
+            data = paddle.static.data(name='x', shape=[-1, 5], dtype='float32')
             hidden = paddle.static.nn.fc(x=data, size=10)
             cost = paddle.mean(hidden)
 
@@ -3964,7 +3964,7 @@ class ModelAverage(Optimizer):
         startup_program = fluid.Program()
         with fluid.program_guard(train_program, startup_program):
             # build net
-            data = fluid.data(name='X', shape=[None, 1], dtype='float32')
+            data = paddle.static.data(name='X', shape=[None, 1], dtype='float32')
             hidden = paddle.static.nn.fc(x=data, size=10)
             loss = paddle.mean(hidden)
             optimizer = fluid.optimizer.Momentum(learning_rate=0.2, momentum=0.1)
@@ -4143,7 +4143,7 @@ class ModelAverage(Optimizer):
             startup_program = fluid.Program()
             with fluid.program_guard(train_program, startup_program):
                 # build net
-                data = fluid.data(name='X', shape=[None, 1], dtype='float32')
+                data = paddle.static.data(name='X', shape=[None, 1], dtype='float32')
                 hidden = paddle.static.nn.fc(x=data, size=10)
                 loss = paddle.mean(hidden)
                 optimizer = fluid.optimizer.Momentum(learning_rate=0.2, momentum=0.1)
@@ -4199,7 +4199,7 @@ class ModelAverage(Optimizer):
             startup_program = fluid.Program()
             with fluid.program_guard(train_program, startup_program):
                 # build net
-                data = fluid.data(name='X', shape=[None, 1], dtype='float32')
+                data = paddle.static.data(name='X', shape=[None, 1], dtype='float32')
                 hidden = paddle.static.nn.fc(x=data, size=10)
                 loss = paddle.mean(hidden)
                 optimizer = fluid.optimizer.Momentum(learning_rate=0.2, momentum=0.1)

python/paddle/fluid/profiler.py

@@ -84,10 +84,11 @@ def npu_profiler(output_file, config=None):
             import paddle.fluid as fluid
             import paddle.fluid.profiler as profiler
             import numpy as np
+            import paddle
 
             epoc = 8
             dshape = [4, 3, 28, 28]
-            data = fluid.data(name='data', shape=[None, 3, 28, 28], dtype='float32')
+            data = paddle.static.data(name='data', shape=[None, 3, 28, 28], dtype='float32')
             conv = paddle.static.nn.conv2d(data, 20, 3, stride=[1, 1], padding=[1, 1])
 
             place = fluid.NPUPlace(0)
@@ -337,7 +338,7 @@ def profiler(
 
             epoc = 8
             dshape = [4, 3, 28, 28]
-            data = fluid.data(name='data', shape=[None, 3, 28, 28], dtype='float32')
+            data = paddle.static.data(name='data', shape=[None, 3, 28, 28], dtype='float32')
             conv = paddle.static.nn.conv2d(data, 20, 3, stride=[1, 1], padding=[1, 1])
 
             place = fluid.CPUPlace()

python/paddle/fluid/reader.py

@@ -655,7 +655,7 @@ class DataLoader:
 
         Args:
             feed_list (list(Tensor)|tuple(Tensor)): feed Tensor list.
-                The Tensors should be created by :code:`fluid.data()`.
+                The Tensors should be created by :code:`paddle.static.data()`.
             capacity (int): capacity of the queue maintained in DataLoader.
                 The unit is batch number. Set larger capacity if your reader
                 is fast.
@@ -1651,8 +1651,8 @@ class PyReader(DataLoaderBase):
                        yield fake_image, fake_label
                return reader
 
-           image = fluid.data(name='image', shape=[None, 784, 784], dtype='float32')
-           label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+           image = paddle.static.data(name='image', shape=[None, 784, 784], dtype='float32')
+           label = paddle.static.data(name='label', shape=[None, 1], dtype='int64')
 
            reader = fluid.io.PyReader(feed_list=[image, label],
                                       capacity=4,
@@ -1708,8 +1708,8 @@ class PyReader(DataLoaderBase):
                        yield fake_image, fake_label
                return reader
 
-           image = fluid.data(name='image', shape=[None, 784, 784], dtype='float32')
-           label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+           image = paddle.static.data(name='image', shape=[None, 784, 784], dtype='float32')
+           label = paddle.static.data(name='label', shape=[None, 1], dtype='int64')
            reader = fluid.io.PyReader(feed_list=[image, label], capacity=4, iterable=True, return_list=False)
 
            user_defined_reader = reader_creator_random_image(784, 784)
@@ -1800,7 +1800,7 @@ class PyReader(DataLoaderBase):
                     for i in range(5):
                         yield np.random.uniform(low=0, high=255, size=[784, 784]),
 
-                image = fluid.data(name='image', shape=[None, 784, 784], dtype='float32')
+                image = paddle.static.data(name='image', shape=[None, 784, 784], dtype='float32')
                 reader = fluid.io.PyReader(feed_list=[image], capacity=4, iterable=False)
                 reader.decorate_sample_list_generator(
                     paddle.batch(generator, batch_size=BATCH_SIZE))
@@ -1837,7 +1837,7 @@ class PyReader(DataLoaderBase):
                     for i in range(5):
                         yield np.random.uniform(low=0, high=255, size=[784, 784]),
 
-                image = fluid.data(name='image', shape=[None, 784, 784], dtype='float32')
+                image = paddle.static.data(name='image', shape=[None, 784, 784], dtype='float32')
                 reader = fluid.io.PyReader(feed_list=[image], capacity=4, iterable=False)
                 reader.decorate_sample_list_generator(
                     paddle.batch(generator, batch_size=BATCH_SIZE))
@@ -1908,8 +1908,8 @@ class PyReader(DataLoaderBase):
                             yield fake_image, fake_label
                     return generator
 
-                image = fluid.data(name='image', shape=[None, 784, 784], dtype='float32')
-                label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+                image = paddle.static.data(name='image', shape=[None, 784, 784], dtype='float32')
+                label = paddle.static.data(name='label', shape=[None, 1], dtype='int64')
                 reader = fluid.io.PyReader(feed_list=[image, label], capacity=4, iterable=True)
 
                 user_defined_generator = random_image_and_label_generator(784, 784)
@@ -1975,8 +1975,8 @@ class PyReader(DataLoaderBase):
                             yield fake_image, fake_label
                     return generator
 
-                image = fluid.data(name='image', shape=[None, 784, 784], dtype='float32')
-                label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+                image = paddle.static.data(name='image', shape=[None, 784, 784], dtype='float32')
+                label = paddle.static.data(name='label', shape=[None, 1], dtype='int64')
                 reader = fluid.io.PyReader(feed_list=[image, label], capacity=4, iterable=True)
 
                 user_defined_generator = random_image_and_label_generator(784, 784)
@@ -2043,8 +2043,8 @@ class PyReader(DataLoaderBase):
                             yield batch_image, batch_label
                     return generator
 
-                image = fluid.data(name='image', shape=[None, 784, 784], dtype='float32')
-                label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+                image = paddle.static.data(name='image', shape=[None, 784, 784], dtype='float32')
+                label = paddle.static.data(name='label', shape=[None, 1], dtype='int64')
                 reader = fluid.io.PyReader(feed_list=[image, label], capacity=4, iterable=True)
 
                 user_defined_generator = random_image_and_label_generator(784, 784)

python/paddle/fluid/tests/test_detection.py

@@ -85,17 +85,19 @@ class TestGenerateProposals(LayerTest):
         variances_np = np.ones((4, 4, 3, 4)).astype('float32')
 
         with self.static_graph():
-            scores = fluid.data(
+            scores = paddle.static.data(
                 name='scores', shape=[2, 3, 4, 4], dtype='float32'
             )
-            bbox_deltas = fluid.data(
+            bbox_deltas = paddle.static.data(
                 name='bbox_deltas', shape=[2, 12, 4, 4], dtype='float32'
             )
-            im_info = fluid.data(name='im_info', shape=[2, 3], dtype='float32')
-            anchors = fluid.data(
+            im_info = paddle.static.data(
+                name='im_info', shape=[2, 3], dtype='float32'
+            )
+            anchors = paddle.static.data(
                 name='anchors', shape=[4, 4, 3, 4], dtype='float32'
             )
-            variances = fluid.data(
+            variances = paddle.static.data(
                 name='var', shape=[4, 4, 3, 4], dtype='float32'
             )
             rois, roi_probs, rois_num = paddle.vision.ops.generate_proposals(
@@ -175,8 +177,12 @@ class TestDistributeFpnProposals(LayerTest):
         rois_np = np.random.rand(10, 4).astype('float32')
         rois_num_np = np.array([4, 6]).astype('int32')
         with self.static_graph():
-            rois = fluid.data(name='rois', shape=[10, 4], dtype='float32')
-            rois_num = fluid.data(name='rois_num', shape=[None], dtype='int32')
+            rois = paddle.static.data(
+                name='rois', shape=[10, 4], dtype='float32'
+            )
+            rois_num = paddle.static.data(
+                name='rois_num', shape=[None], dtype='int32'
+            )
             (
                 multi_rois,
                 restore_ind,
@@ -230,7 +236,7 @@ class TestDistributeFpnProposals(LayerTest):
     def test_distribute_fpn_proposals_error(self):
         program = Program()
         with program_guard(program):
-            fpn_rois = fluid.data(
+            fpn_rois = paddle.static.data(
                 name='data_error', shape=[10, 4], dtype='int32', lod_level=1
             )
             self.assertRaises(

python/paddle/fluid/tests/unittests/asp/asp_pruning_base.py

@@ -31,10 +31,12 @@ class TestASPHelperPruningBase(unittest.TestCase):
         self.startup_program = fluid.Program()
 
         def build_model():
-            img = fluid.data(
+            img = paddle.static.data(
                 name='img', shape=[None, 3, 32, 32], dtype='float32'
             )
-            label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+            label = paddle.static.data(
+                name='label', shape=[None, 1], dtype='int64'
+            )
             hidden = paddle.static.nn.conv2d(
                 input=img, num_filters=4, filter_size=3, padding=2, act="relu"
             )

python/paddle/fluid/tests/unittests/asp/test_asp_customized_pruning.py

@@ -196,10 +196,12 @@ class TestASPStaticCustomerizedPruneFunc(unittest.TestCase):
         self.customer_prefix = "customer_layer"
 
         def build_model():
-            img = fluid.data(
+            img = paddle.static.data(
                 name='img', shape=[None, 3, 32, 32], dtype='float32'
             )
-            label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+            label = paddle.static.data(
+                name='label', shape=[None, 1], dtype='int64'
+            )
             hidden = paddle.static.nn.conv2d(
                 input=img, num_filters=4, filter_size=3, padding=2, act="relu"
             )

python/paddle/fluid/tests/unittests/asp/test_asp_optimize_static.py

@@ -31,10 +31,12 @@ class TestASPStaticOptimize(unittest.TestCase):
         self.startup_program = fluid.Program()
 
         def build_model():
-            img = fluid.data(
+            img = paddle.static.data(
                 name='img', shape=[None, 3, 24, 24], dtype='float32'
             )
-            label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+            label = paddle.static.data(
+                name='label', shape=[None, 1], dtype='int64'
+            )
             hidden = paddle.static.nn.conv2d(
                 input=img, num_filters=4, filter_size=3, padding=2, act="relu"
             )

python/paddle/fluid/tests/unittests/asp/test_asp_pruning_static.py

@@ -31,10 +31,12 @@ class TestASPStaticPruningBase(unittest.TestCase):
         self.startup_program = fluid.Program()
 
         def build_model():
-            img = fluid.data(
+            img = paddle.static.data(
                 name='img', shape=[None, 3, 24, 24], dtype='float32'
             )
-            label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+            label = paddle.static.data(
+                name='label', shape=[None, 1], dtype='int64'
+            )
             hidden = paddle.static.nn.conv2d(
                 input=img, num_filters=2, filter_size=3, padding=2, act="relu"
             )

python/paddle/fluid/tests/unittests/asp/test_asp_save_load.py

@@ -128,10 +128,12 @@ class TestASPStaticOptimize(unittest.TestCase):
         self.startup_program = fluid.Program()
 
         def build_model():
-            img = fluid.data(
+            img = paddle.static.data(
                 name='img', shape=[None, 3, 32, 32], dtype='float32'
             )
-            label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+            label = paddle.static.data(
+                name='label', shape=[None, 1], dtype='int64'
+            )
             hidden = paddle.static.nn.conv2d(
                 input=img, num_filters=4, filter_size=3, padding=2, act="relu"
             )

python/paddle/fluid/tests/unittests/auto_checkpoint_utils.py

@@ -65,8 +65,12 @@ class AutoCheckpointBase(unittest.TestCase):
         self, exe, main_prog, startup_prog, minimize=True, iterable=True
     ):
         def simple_net():
-            image = fluid.data(name='image', shape=[-1, 4, 4], dtype='float32')
-            label = fluid.data(name='label', shape=[-1, 1], dtype='int64')
+            image = paddle.static.data(
+                name='image', shape=[-1, 4, 4], dtype='float32'
+            )
+            label = paddle.static.data(
+                name='label', shape=[-1, 1], dtype='int64'
+            )
 
             fc_tmp = paddle.static.nn.fc(image, size=CLASS_NUM)
             cross_entropy = paddle.nn.functional.softmax_with_cross_entropy(

python/paddle/fluid/tests/unittests/collective/fleet/static_model_parallel_by_col.py

@@ -71,7 +71,7 @@ def create_model(data, rank):
 class TestModelParallel(TestDistRunnerBase):
     def get_model(self, batch_size=2, use_dgc=False, dist_strategy=None):
         # Input data
-        data_in = fluid.data(
+        data_in = paddle.static.data(
             name='data_in', shape=[batch_size, IN_SIZE], dtype=DTYPE
         )
 

python/paddle/fluid/tests/unittests/collective/fleet/static_model_parallel_by_row.py

@@ -75,7 +75,7 @@ def create_model(data, rank):
 class TestModelParallel(TestDistRunnerBase):
     def get_model(self, batch_size=2, use_dgc=False, dist_strategy=None):
         # Input data
-        data_in = fluid.data(
+        data_in = paddle.static.data(
             name='data_in', shape=[batch_size, IN_SIZE], dtype=DTYPE
         )
 

python/paddle/fluid/tests/unittests/collective/fleet/static_model_parallel_embedding.py

@@ -65,7 +65,7 @@ def create_model(data, rank):
 class TestModelParallel(TestDistRunnerBase):
     def get_model(self, batch_size=2, use_dgc=False, dist_strategy=None):
         # Input data
-        data_in = fluid.data(
+        data_in = paddle.static.data(
             name='data_in', shape=[batch_size, IN_SIZE], dtype=DTYPE
         )
 

python/paddle/fluid/tests/unittests/collective/fleet/test_fleet_checkpoint.py

@@ -35,8 +35,10 @@ class FleetTest(unittest.TestCase):
         role = role_maker.PaddleCloudRoleMaker(is_collective=True)
         fleet.init(role)
 
-        image = fluid.data(name='img', shape=[None, 28, 28], dtype='float32')
-        label = fluid.data(name='label', shape=[None, 1], dtype='int64')
+        image = paddle.static.data(
+            name='img', shape=[None, 28, 28], dtype='float32'
+        )
+        label = paddle.static.data(name='label', shape=[None, 1], dtype='int64')
         feeder = fluid.DataFeeder(
             feed_list=[image, label], place=fluid.CPUPlace()
         )

python/paddle/fluid/tests/unittests/distribution/test_distribution_categorical.py

@@ -103,13 +103,13 @@ class CategoricalTest(unittest.TestCase):
 
     def init_static_data(self, batch_size, dims):
         with fluid.program_guard(self.test_program):
-            self.logits_static = fluid.data(
+            self.logits_static = paddle.static.data(
                 name='logits', shape=self.logits_shape, dtype='float32'
             )
-            self.other_logits_static = fluid.data(
+            self.other_logits_static = paddle.static.data(
                 name='other_logits', shape=self.logits_shape, dtype='float32'
             )
-            self.value_static = fluid.data(
+            self.value_static = paddle.static.data(
                 name='value', shape=self.value_shape, dtype='int64'
             )
 
@@ -211,13 +211,13 @@ class CategoricalTest2(CategoricalTest):
 
     def init_static_data(self, batch_size, dims):
         with fluid.program_guard(self.test_program):
-            self.logits_static = fluid.data(
+            self.logits_static = paddle.static.data(
                 name='logits', shape=self.logits_shape, dtype='float64'
             )
-            self.other_logits_static = fluid.data(
+            self.other_logits_static = paddle.static.data(
                 name='other_logits', shape=self.logits_shape, dtype='float64'
             )
-            self.value_static = fluid.data(
+            self.value_static = paddle.static.data(
                 name='value', shape=self.value_shape, dtype='int64'
             )
 
@@ -234,7 +234,7 @@ class CategoricalTest3(CategoricalTest):
         with fluid.program_guard(self.test_program):
             self.logits_static = self.logits_np
             self.other_logits_static = self.other_logits_np
-            self.value_static = fluid.data(
+            self.value_static = paddle.static.data(
                 name='value', shape=self.value_shape, dtype='int64'
             )
 
@@ -263,7 +263,7 @@ class CategoricalTest4(CategoricalTest):
         with fluid.program_guard(self.test_program):
             self.logits_static = self.logits_np
             self.other_logits_static = self.other_logits_np
-            self.value_static = fluid.data(
+            self.value_static = paddle.static.data(
                 name='value', shape=self.value_shape, dtype='int64'
             )
 
@@ -344,7 +344,7 @@ class CategoricalTest8(CategoricalTest):
         with fluid.program_guard(self.test_program):
             self.logits_static = self.logits_np.tolist()
             self.other_logits_static = self.other_logits_np.tolist()
-            self.value_static = fluid.data(
+            self.value_static = paddle.static.data(
                 name='value', shape=self.value_shape, dtype='int64'
             )
 
@@ -361,7 +361,7 @@ class CategoricalTest9(CategoricalTest):
         with fluid.program_guard(self.test_program):
             self.logits_static = tuple(self.logits_np.tolist())
             self.other_logits_static = tuple(self.other_logits_np.tolist())
-            self.value_static = fluid.data(
+            self.value_static = paddle.static.data(
                 name='value', shape=self.value_shape, dtype='int64'
             )
 

python/paddle/fluid/tests/unittests/dygraph_to_static/test_static_analysis.py

@@ -108,7 +108,7 @@ def func_to_test5():
     a = inner_int_func()
     b = inner_bool_float_func(3)
     c = inner_unknown_func(None)
-    d = paddle.fluid.data('x', [1, 2])
+    d = paddle.static.data('x', [1, 2])
 
 
 result_var_type5 = {

python/paddle/fluid/tests/unittests/ipu/test_fill_any_like_op_ipu.py

@@ -69,7 +69,7 @@ class TestCase1(TestBase):
 class TestError(TestBase):
     @IPUOpTest.static_graph
     def build_model(self):
-        x = paddle.fluid.data('x', [-1, 3, 13], 'float32')
+        x = paddle.static.data('x', [-1, 3, 13], 'float32')
         x_fill = paddle.full_like(x, **self.attrs)
         out = paddle.add(x_fill, x_fill)
         self.fetch_list = [out.name]

python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_cpu_bfloat16_pass.py

@@ -26,7 +26,7 @@ class TestMKLDNNCpuBfloat16Pass(InferencePassTest):
     def setUp(self):
         self.init_data()
         with fluid.program_guard(self.main_program, self.startup_program):
-            x = fluid.data(
+            x = paddle.static.data(
                 name='x', shape=[-1] + self.shape_x, dtype=self.d_type
             )
 

python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_elt_act_fuse_pass.py

@@ -31,10 +31,10 @@ class ElementwiseActivationMkldnnFusePassTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data_A = fluid.data(
+            data_A = paddle.static.data(
                 name="data_A", shape=[-1, 3, 100, 100], dtype="float32"
             )
-            data_B = fluid.data(
+            data_B = paddle.static.data(
                 name="data_B", shape=[-1, 3, 100, 100], dtype="float32"
             )
             elt_out = self.operand(data_A, data_B)

python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_matmul_op_output_fuse_pass.py

@@ -32,10 +32,10 @@ class TestMKLDNNMatmulFuseOp(InferencePassTest):
 
     def make_network(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            x = fluid.data(
+            x = paddle.static.data(
                 name='x', shape=[-1] + self.shape_x, dtype=self.d_type
             )
-            y = fluid.data(
+            y = paddle.static.data(
                 name='y', shape=[-1] + self.shape_y, dtype=self.d_type
             )
             out = paddle.matmul(x, y)
@@ -74,10 +74,10 @@ class TestMKLDNNMatmulOtherDimsFuseOp(TestMKLDNNMatmulFuseOp):
 class TestMKLDNNMatmulOpNotFusedWrongTransposeAxis(TestMKLDNNMatmulFuseOp):
     def make_network(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            x = fluid.data(
+            x = paddle.static.data(
                 name='x', shape=[-1] + self.shape_x, dtype=self.d_type
             )
-            y = fluid.data(
+            y = paddle.static.data(
                 name='y', shape=[-1] + self.shape_y, dtype=self.d_type
             )
             out = paddle.matmul(x, y)
@@ -97,10 +97,10 @@ class TestMKLDNNMatmulOpNotFusedBreakPattern(TestMKLDNNMatmulFuseOp):
 
     def make_network(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            x = fluid.data(
+            x = paddle.static.data(
                 name='x', shape=[-1] + self.shape_x, dtype=self.d_type
             )
-            y = fluid.data(
+            y = paddle.static.data(
                 name='y', shape=[-1] + self.shape_y, dtype=self.d_type
             )
             out = paddle.matmul(x, y)

python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_reshape_transpose_matmul_v2_fuse_pass.py

@@ -29,7 +29,7 @@ class TestReshapeTransposeMatmulV2OneDNNFusePass(InferencePassTest):
         self.pass_name = 'reshape_transpose_matmul_mkldnn_fuse_pass'
 
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=self.data_shape, dtype="float32"
             )
             weight = paddle.create_parameter(

python/paddle/fluid/tests/unittests/ir/inference/test_trt_activation_pass.py

@@ -37,7 +37,7 @@ class TensorRTSubgraphPassActivationTest(InferencePassTest):
     def setUp(self):
         self.setUpTensorRTParam()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, 32, 32], dtype="float32"
             )
             act_out = self.append_act(data)

python/paddle/fluid/tests/unittests/ir/inference/test_trt_conv3d_op.py

@@ -28,7 +28,7 @@ class TensorRTSubgraphPassConv3dTest(InferencePassTest):
         self.init_params()
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 3, 6, 32, 32], dtype="float32"
             )
             conv_out = paddle.static.nn.conv3d(
@@ -112,7 +112,7 @@ class DynamicShapeTensorRTSubgraphPassConv3dTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, -1, -1, -1], dtype="float32"
             )
             conv_out = paddle.static.nn.conv3d(

python/paddle/fluid/tests/unittests/ir/inference/test_trt_conv3d_transpose_op.py

@@ -27,7 +27,7 @@ class TensorRTSubgraphPassConv3dTransposeTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 4, 4, 32, 32], dtype="float32"
             )
             conv_out = paddle.static.nn.conv3d_transpose(
@@ -94,7 +94,7 @@ class DynamicShapeTensorRTSubgraphPassConv3dTransposeTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, -1, -1, -1], dtype="float32"
             )
             conv_out = paddle.static.nn.conv3d_transpose(

python/paddle/fluid/tests/unittests/ir/inference/test_trt_conv_pass.py

@@ -30,7 +30,7 @@ class TensorRTSubgraphPassConvTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, 64, 64], dtype="float32"
             )
             conv_out = paddle.static.nn.conv2d(
@@ -108,7 +108,7 @@ class TensorRTSubgraphPassConvTransposeTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, 64, 64], dtype="float32"
             )
             conv_out = paddle.static.nn.conv2d_transpose(
@@ -207,7 +207,7 @@ class DynamicShapeTensorRTSubgraphPassConvTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, -1, -1], dtype="float32"
             )
             conv_out = paddle.static.nn.conv2d(

python/paddle/fluid/tests/unittests/ir/inference/test_trt_conv_quant_dequant_pass.py

@@ -29,11 +29,13 @@ class QuantDequantTensorRTSubgraphPassConvTest(QuantDequantTest):
         self.set_params()
 
         def network():
-            self.data = fluid.data(
+            self.data = paddle.static.data(
                 name='data', shape=[1, 28, 28], dtype='float32'
             )
             data_reshape = paddle.reshape(self.data, shape=[1, 4, 14, 14])
-            self.label = fluid.data(name='label', shape=[1, 1], dtype='int64')
+            self.label = paddle.static.data(
+                name='label', shape=[1, 1], dtype='int64'
+            )
             label_shape = paddle.reshape(self.label, shape=[1, 1, 1])
             conv_out = paddle.static.nn.conv2d(
                 input=data_reshape,
@@ -144,11 +146,13 @@ class DynamicShapeQuantDequantTensorRTSubgraphPassConvTest(QuantDequantTest):
         self.set_params()
 
         def network():
-            self.data = fluid.data(
+            self.data = paddle.static.data(
                 name='data', shape=[1, 28, 28], dtype='float32'
             )
             data_reshape = paddle.reshape(self.data, shape=[1, 4, 14, 14])
-            self.label = fluid.data(name='label', shape=[1, 1], dtype='int64')
+            self.label = paddle.static.data(
+                name='label', shape=[1, 1], dtype='int64'
+            )
             label_shape = paddle.reshape(self.label, shape=[1, 1, 1])
             conv_out = paddle.static.nn.conv2d(
                 input=data_reshape,
@@ -243,11 +247,13 @@ class QuantDequantTensorRTSubgraphPassConvTransposeTest(QuantDequantTest):
         self.set_params()
 
         def network():
-            self.data = fluid.data(
+            self.data = paddle.static.data(
                 name='data', shape=[1, 28, 28], dtype='float32'
             )
             data_reshape = paddle.reshape(self.data, shape=[1, 4, 14, 14])
-            self.label = fluid.data(name='label', shape=[1, 1], dtype='int64')
+            self.label = paddle.static.data(
+                name='label', shape=[1, 1], dtype='int64'
+            )
             label_shape = paddle.reshape(self.label, shape=[1, 1, 1])
             conv_out = paddle.static.nn.conv2d_transpose(
                 input=data_reshape,

python/paddle/fluid/tests/unittests/ir/inference/test_trt_deformable_conv.py

@@ -30,13 +30,13 @@ class TRTDeformableConvTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            input = fluid.data(
+            input = paddle.static.data(
                 name='input', shape=self.input_size, dtype=self.dtype
             )
-            offset = fluid.data(
+            offset = paddle.static.data(
                 name='offset', shape=self.offset_size, dtype=self.dtype
             )
-            mask = fluid.data(
+            mask = paddle.static.data(
                 name='mask', shape=self.mask_size, dtype=self.dtype
             )
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_dynamic_shape.py

@@ -26,7 +26,7 @@ from paddle.fluid.core import AnalysisConfig
 class TRTDynamicShapeTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 3, 16, 16], dtype="float32"
             )
             out = paddle.static.nn.conv2d(

python/paddle/fluid/tests/unittests/ir/inference/test_trt_elementwise_op.py

@@ -29,10 +29,10 @@ from paddle.fluid.core import AnalysisConfig, PassVersionChecker
 class TensorRTSubgraphPassElementwiseBroadcastTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data1 = fluid.data(
+            data1 = paddle.static.data(
                 name="data1", shape=[-1, 3, 64, 64], dtype="float32"
             )
-            data2 = fluid.data(
+            data2 = paddle.static.data(
                 name="data2", shape=[-1, 3, 64, 1], dtype="float32"
             )
             eltwise_out = self.append_eltwise(data1, data2)

python/paddle/fluid/tests/unittests/ir/inference/test_trt_fc_fuse_pass.py

@@ -26,7 +26,7 @@ from paddle.fluid.core import AnalysisConfig
 class FCFusePassTRTTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[32, 128, 2, 2], dtype="float32"
             )
             fc_out1 = paddle.static.nn.fc(
@@ -56,7 +56,7 @@ class FCFusePassTRTTest(InferencePassTest):
 class FCFusePassTRTStaticDims4Cols1Test(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[32, 128, 32, 8], dtype="float32"
             )
             fc_out1 = paddle.static.nn.fc(
@@ -84,7 +84,7 @@ class FCFusePassTRTStaticDims4Cols1Test(InferencePassTest):
 class FCFusePassTRTStaticDims4Cols2Test(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[3, 24, 16, 16], dtype="float32"
             )
             fc_out1 = paddle.static.nn.fc(
@@ -112,7 +112,9 @@ class FCFusePassTRTStaticDims4Cols2Test(InferencePassTest):
 class FCFusePassTRTDynamicDims2Test(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[32, 128], dtype="float32")
+            data = paddle.static.data(
+                name="data", shape=[32, 128], dtype="float32"
+            )
             fc_out1 = paddle.static.nn.fc(
                 x=data, size=64, num_flatten_dims=1, activation="relu"
             )
@@ -144,7 +146,9 @@ class FCFusePassTRTDynamicDims2Test(InferencePassTest):
 class FCFusePassTRTDynamicDims3Cols1Test(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[32, 128, 32], dtype="float32")
+            data = paddle.static.data(
+                name="data", shape=[32, 128, 32], dtype="float32"
+            )
             fc_out1 = paddle.static.nn.fc(
                 x=data, size=64, num_flatten_dims=1, activation="relu"
             )
@@ -176,7 +180,9 @@ class FCFusePassTRTDynamicDims3Cols1Test(InferencePassTest):
 class FCFusePassTRTDynamicDims3Cols2Test(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[32, 128, 32], dtype="float32")
+            data = paddle.static.data(
+                name="data", shape=[32, 128, 32], dtype="float32"
+            )
             fc_out1 = paddle.static.nn.fc(
                 x=data, size=64, num_flatten_dims=2, activation="relu"
             )
@@ -208,7 +214,7 @@ class FCFusePassTRTDynamicDims3Cols2Test(InferencePassTest):
 class FCFusePassTRTDynamicDims4Cols1Test(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[32, 12, 4, 6], dtype="float32"
             )
             fc_out1 = paddle.static.nn.fc(
@@ -244,7 +250,7 @@ class FCFusePassTRTDynamicDims4Cols1Test(InferencePassTest):
 class FCFusePassTRTDynamicDims4Cols2Test(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[32, 128, 32, 32], dtype="float32"
             )
             fc_out1 = paddle.static.nn.fc(
@@ -280,7 +286,7 @@ class FCFusePassTRTDynamicDims4Cols2Test(InferencePassTest):
 class FCFusePassTRTDynamicDims4Cols3Test(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[32, 128, 32, 32], dtype="float32"
             )
             fc_out1 = paddle.static.nn.fc(

python/paddle/fluid/tests/unittests/ir/inference/test_trt_fc_fuse_quant_dequant_pass.py

@@ -27,10 +27,12 @@ from paddle.fluid.core import AnalysisConfig, PassVersionChecker
 class FCQuantDequantFusePassTRTDims3Cols1Test(QuantDequantTest):
     def setUp(self):
         def network():
-            self.data = fluid.data(
+            self.data = paddle.static.data(
                 name='data', shape=[1, 28, 28], dtype='float32'
             )
-            self.label = fluid.data(name='label', shape=[1, 1], dtype='int64')
+            self.label = paddle.static.data(
+                name='label', shape=[1, 1], dtype='int64'
+            )
             fc_out = paddle.static.nn.fc(
                 x=self.data,
                 size=10,
@@ -98,10 +100,12 @@ class FCQuantDequantFusePassTRTDims3Cols1Test(QuantDequantTest):
 class FCQuantDequantFusePassTRTDims3Cols2Test(QuantDequantTest):
     def setUp(self):
         def network():
-            self.data = fluid.data(
+            self.data = paddle.static.data(
                 name='data', shape=[1, 28, 28], dtype='float32'
             )
-            self.label = fluid.data(name='label', shape=[1, 1], dtype='int64')
+            self.label = paddle.static.data(
+                name='label', shape=[1, 1], dtype='int64'
+            )
             fc_out = paddle.static.nn.fc(
                 x=self.data,
                 size=28,
@@ -170,10 +174,12 @@ class FCQuantDequantFusePassTRTDims3Cols2Test(QuantDequantTest):
 class FCQuantDequantFusePassTRTDims3Cols3Test(QuantDequantTest):
     def setUp(self):
         def network():
-            self.data = fluid.data(
+            self.data = paddle.static.data(
                 name='data', shape=[1, 28, 28], dtype='float32'
             )
-            self.label = fluid.data(name='label', shape=[1, 1], dtype='int64')
+            self.label = paddle.static.data(
+                name='label', shape=[1, 1], dtype='int64'
+            )
             label_shape = paddle.reshape(self.label, shape=[1, 1, 1])
             reshape_out = paddle.reshape(self.data, shape=[1, 14, 14, 4])
             fc_out = paddle.static.nn.fc(

python/paddle/fluid/tests/unittests/ir/inference/test_trt_flatten_op.py

@@ -27,7 +27,7 @@ from paddle.fluid.core import AnalysisConfig, PassVersionChecker
 class TRTFlattenTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, 64, 64], dtype="float32"
             )
             flatten_out = self.append_flatten(data)
@@ -56,7 +56,7 @@ class TRTFlattenTest(InferencePassTest):
 class TRTFlattenDynamicTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, 64, 64], dtype="float32"
             )
             flatten_out = self.append_flatten(data)

python/paddle/fluid/tests/unittests/ir/inference/test_trt_gather_nd_op.py

@@ -27,8 +27,12 @@ from paddle.fluid.core import AnalysisConfig, PassVersionChecker
 class TRTGatherNdTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[-1, 3, 4], dtype="float32")
-            index = fluid.data(name="index", shape=[-1, 2, 2], dtype="int32")
+            data = paddle.static.data(
+                name="data", shape=[-1, 3, 4], dtype="float32"
+            )
+            index = paddle.static.data(
+                name="index", shape=[-1, 2, 2], dtype="int32"
+            )
             gather_nd = paddle.gather_nd(data, index)
             out = nn.batch_norm(gather_nd, is_test=True)
 
@@ -62,10 +66,12 @@ class TRTGatherNdTest(InferencePassTest):
 class TRTGatherNdFp16Test(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 1280, 192], dtype="float32"
             )
-            index = fluid.data(name="index", shape=[-1, 1028, 2], dtype="int32")
+            index = paddle.static.data(
+                name="index", shape=[-1, 1028, 2], dtype="int32"
+            )
             gather_nd = paddle.gather_nd(data, index)
             out = nn.batch_norm(gather_nd, is_test=True)
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_gather_op.py

@@ -27,8 +27,12 @@ class TRTGatherTest1(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name='data', shape=[-1, 128], dtype='float32')
-            index = fluid.data(name='index', shape=[-1, 1], dtype='int32')
+            data = paddle.static.data(
+                name='data', shape=[-1, 128], dtype='float32'
+            )
+            index = paddle.static.data(
+                name='index', shape=[-1, 1], dtype='int32'
+            )
             scale_out = paddle.gather(data, index=index)
             out = paddle.nn.functional.softmax(scale_out)
 
@@ -66,8 +70,10 @@ class TRTGatherTest2(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name='data', shape=[16, 64], dtype='float32')
-            index = fluid.data(name='index', shape=[2], dtype='int32')
+            data = paddle.static.data(
+                name='data', shape=[16, 64], dtype='float32'
+            )
+            index = paddle.static.data(name='index', shape=[2], dtype='int32')
             scale_out = paddle.gather(data, index=index)
             out = paddle.nn.functional.softmax(scale_out)
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_inspector.py

@@ -29,7 +29,9 @@ class TensorRTInspectorTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[1, 16, 16], dtype="float32")
+            data = paddle.static.data(
+                name="data", shape=[1, 16, 16], dtype="float32"
+            )
             matmul_out = paddle.matmul(
                 x=data,
                 y=data,

python/paddle/fluid/tests/unittests/ir/inference/test_trt_instance_norm_op.py

@@ -20,6 +20,7 @@ import unittest
 import numpy as np
 from inference_pass_test import InferencePassTest
 
+import paddle
 import paddle.fluid as fluid
 import paddle.fluid.core as core
 import paddle.static.nn as nn
@@ -43,7 +44,7 @@ class TRTInstanceNormTest(InferencePassTest):
 
         with fluid.program_guard(self.main_program, self.startup_program):
             shape = [-1, self.channel, self.height, self.width]
-            data = fluid.data(name='in', shape=shape, dtype='float32')
+            data = paddle.static.data(name='in', shape=shape, dtype='float32')
             instance_norm_out = nn.instance_norm(data)
             out = nn.batch_norm(instance_norm_out, is_test=True)
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_matmul.py

@@ -28,7 +28,9 @@ class TensorRTMatMulDims2Test(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[24, 24], dtype="float32")
+            data = paddle.static.data(
+                name="data", shape=[24, 24], dtype="float32"
+            )
             matmul_out = paddle.matmul(
                 x=data,
                 y=data,
@@ -65,7 +67,7 @@ class TensorRTMatMulTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, 24, 24], dtype="float32"
             )
             matmul_out = paddle.matmul(
@@ -126,10 +128,12 @@ class TensorRTMatMulBroadcastTest(InferencePassTest):
         self.set_params()
         place = fluid.CPUPlace()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data_x = fluid.data(
+            data_x = paddle.static.data(
                 name="data_x", shape=[-1, 6, 24], dtype="float32"
             )
-            data_y = fluid.data(name="data_y", shape=[24, 16], dtype="float32")
+            data_y = paddle.static.data(
+                name="data_y", shape=[24, 16], dtype="float32"
+            )
             matmul_out = paddle.matmul(
                 x=data_x,
                 y=data_y,

python/paddle/fluid/tests/unittests/ir/inference/test_trt_matmul_quant_dequant.py

@@ -29,10 +29,12 @@ class TensorRTMatMulQuantDequantDims3Test(QuantDequantTest):
         self.set_params()
 
         def network():
-            self.data = fluid.data(
+            self.data = paddle.static.data(
                 name='data', shape=[1, 28, 28], dtype='float32'
             )
-            self.label = fluid.data(name='label', shape=[1, 1], dtype='int64')
+            self.label = paddle.static.data(
+                name='label', shape=[1, 1], dtype='int64'
+            )
             matmul_out = paddle.matmul(
                 x=self.data,
                 y=self.data,
@@ -129,10 +131,12 @@ class TensorRTMatMulQuantDequantDims4Test(QuantDequantTest):
         self.set_params()
 
         def network():
-            self.data = fluid.data(
+            self.data = paddle.static.data(
                 name='data', shape=[1, 28, 28], dtype='float32'
             )
-            self.label = fluid.data(name='label', shape=[1, 1], dtype='int64')
+            self.label = paddle.static.data(
+                name='label', shape=[1, 1], dtype='int64'
+            )
             reshape_out = paddle.reshape(self.data, shape=[1, 4, 14, 14])
             matmul_out = paddle.matmul(
                 x=reshape_out,
@@ -231,10 +235,12 @@ class TensorRTMatMulQuantDequantDims3DynamicTest(QuantDequantTest):
         self.set_params()
 
         def network():
-            self.data = fluid.data(
+            self.data = paddle.static.data(
                 name='data', shape=[-1, 28, 28], dtype='float32'
             )
-            self.label = fluid.data(name='label', shape=[1, 1], dtype='int64')
+            self.label = paddle.static.data(
+                name='label', shape=[1, 1], dtype='int64'
+            )
             matmul_out = paddle.matmul(
                 x=self.data,
                 y=self.data,

python/paddle/fluid/tests/unittests/ir/inference/test_trt_multiclass_nms3_op.py

@@ -218,10 +218,10 @@ class TensorRTMultiClassNMS3Test(InferencePassTest):
 
     def build(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            boxes = fluid.data(
+            boxes = paddle.static.data(
                 name='bboxes', shape=[-1, self.num_boxes, 4], dtype='float32'
             )
-            scores = fluid.data(
+            scores = paddle.static.data(
                 name='scores',
                 shape=[-1, self.num_classes, self.num_boxes],
                 dtype='float32',

python/paddle/fluid/tests/unittests/ir/inference/test_trt_nearest_interp_op.py

@@ -43,7 +43,7 @@ class TRTNearestInterpTest(InferencePassTest):
                     self.origin_shape[1],
                     self.channels,
                 ]
-            data = fluid.data(name='data', shape=shape, dtype='float32')
+            data = paddle.static.data(name='data', shape=shape, dtype='float32')
             resize_out = self.append_nearest_interp(data)
             out = nn.batch_norm(resize_out, is_test=True)
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_nearest_interp_v2_op.py

@@ -17,6 +17,7 @@ import unittest
 import numpy as np
 from inference_pass_test import InferencePassTest
 
+import paddle
 import paddle.fluid.core as core
 import paddle.nn.functional as F
 import paddle.static.nn as nn
@@ -43,7 +44,7 @@ class TRTNearestInterpTest(InferencePassTest):
                     self.origin_shape[1],
                     self.channels,
                 ]
-            data = fluid.data(name='data', shape=shape, dtype='float32')
+            data = paddle.static.data(name='data', shape=shape, dtype='float32')
             resize_out = self.append_nearest_interp(data)
             out = nn.batch_norm(resize_out, is_test=True)
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_pad_op.py

@@ -27,7 +27,7 @@ from paddle.fluid.core import AnalysisConfig
 class PadOpTRTTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[1, 3, 128, 128], dtype="float32"
             )
             pad_out = paddle.nn.functional.pad(

python/paddle/fluid/tests/unittests/ir/inference/test_trt_pool3d_op.py

@@ -58,7 +58,7 @@ class TensorRTPool3dTest(InferencePassTest):
         )
 
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name='data',
                 shape=[-1, self.channel, self.depth, self.height, self.width],
                 dtype='float32',
@@ -190,7 +190,7 @@ class TensorRTAdaptiveAvgPool3DTest(InferencePassTest):
         )
 
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name='data',
                 shape=[-1, self.channel, self.depth, self.height, self.width],
                 dtype='float32',
@@ -290,7 +290,7 @@ class TensorRTAdaptiveMaxPool3DTest(InferencePassTest):
         )
 
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name='data',
                 shape=[-1, self.channel, self.depth, self.height, self.width],
                 dtype='float32',

python/paddle/fluid/tests/unittests/ir/inference/test_trt_pool_op.py

@@ -59,7 +59,7 @@ class TensorRTPoolTest(InferencePassTest):
         )
 
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name='data',
                 shape=[-1, self.channel, self.height, self.width],
                 dtype='float32',

python/paddle/fluid/tests/unittests/ir/inference/test_trt_reduce_sum_op.py

@@ -27,7 +27,7 @@ from paddle.fluid.core import AnalysisConfig, PassVersionChecker
 class TRTReduceSumTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 3, 10, 192], dtype="float32"
             )
             reduce_sum = paddle.sum(data, axis=[2, -1], keepdim=True)
@@ -60,7 +60,7 @@ class TRTReduceSumTest(InferencePassTest):
 class TRTReduceSumAllTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 3, 10, 192], dtype="float32"
             )
             reduce_sum = paddle.sum(data, keepdim=True)

python/paddle/fluid/tests/unittests/ir/inference/test_trt_reshape_op.py

@@ -36,7 +36,7 @@ class TRTReshapeTest(InferencePassTest):
             self.input_shape[2],
         ]
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name='data', shape=self.data_shape, dtype='float32'
             )
             reshape_out = self.append_reshape(data, self.reshape)
@@ -74,7 +74,7 @@ class TRTReshapeTest1(TRTReshapeTest):
             self.input_shape[2],
         ]
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name='data', shape=self.data_shape, dtype='float32'
             )
             reshape_out = self.append_reshape(data, self.reshape)
@@ -101,7 +101,7 @@ class TRTReshapeTest2(TRTReshapeTest):
             self.input_shape[2],
         ]
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name='data', shape=self.data_shape, dtype='float32'
             )
             reshape_out = paddle.reshape(x=data, shape=self.reshape)
@@ -128,7 +128,7 @@ class TRTReshapeTest3(TRTReshapeTest):
             self.input_shape[2],
         ]
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name='data', shape=self.data_shape, dtype='float32'
             )
             bn_out = nn.batch_norm(data, is_test=True)

python/paddle/fluid/tests/unittests/ir/inference/test_trt_scale_op.py

@@ -27,7 +27,9 @@ from paddle.fluid.core import AnalysisConfig, PassVersionChecker
 class TRTScaleTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[-1, 512], dtype="float32")
+            data = paddle.static.data(
+                name="data", shape=[-1, 512], dtype="float32"
+            )
             scale_out = self.append_scale(data)
             out = nn.batch_norm(scale_out, is_test=True)
 
@@ -57,7 +59,7 @@ class TRTScaleTest(InferencePassTest):
 class TRTScaleShape2Test(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 512, 512], dtype="float32"
             )
             scale_out = self.append_scale(data)

python/paddle/fluid/tests/unittests/ir/inference/test_trt_shuffle_channel_detect_pass.py

@@ -26,7 +26,7 @@ from paddle.fluid.core import AnalysisConfig, PassVersionChecker
 class ShuffleChannelFuseTRTPassTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, 64, 64], dtype="float32"
             )
             reshape1 = paddle.reshape(x=data, shape=[-1, 2, 3, 64, 64])

python/paddle/fluid/tests/unittests/ir/inference/test_trt_slice_dynamic_plugin.py

@@ -46,7 +46,9 @@ class SlicePluginTRTDynamicTest(InferencePassTest):
         self.setUpSliceParams()
         self.setUpTensorRTParams()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[3, 3, 3, 3], dtype="float32")
+            data = paddle.static.data(
+                name="data", shape=[3, 3, 3, 3], dtype="float32"
+            )
             axes = self.params_axes
             starts = self.params_starts
             ends = self.params_ends

python/paddle/fluid/tests/unittests/ir/inference/test_trt_slice_plugin.py

@@ -41,7 +41,9 @@ class SlicePluginTRTTest(InferencePassTest):
         self.setUpSliceParams()
         self.setUpTensorRTParams()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[3, 3, 3, 3], dtype="float32")
+            data = paddle.static.data(
+                name="data", shape=[3, 3, 3, 3], dtype="float32"
+            )
             axes = self.params_axes
             starts = self.params_starts
             ends = self.params_ends
@@ -110,7 +112,9 @@ class SlicePluginTRTTestInt32(SlicePluginTRTTest):
         self.setUpSliceParams()
         self.setUpTensorRTParams()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[3, 3, 3, 3], dtype="int32")
+            data = paddle.static.data(
+                name="data", shape=[3, 3, 3, 3], dtype="int32"
+            )
             axes = self.params_axes
             starts = self.params_starts
             ends = self.params_ends
@@ -135,7 +139,9 @@ class StaticSlicePluginTRTTestInt32(SlicePluginTRTTest):
         self.setUpSliceParams()
         self.setUpTensorRTParams()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[3, 3, 3, 3], dtype="int32")
+            data = paddle.static.data(
+                name="data", shape=[3, 3, 3, 3], dtype="int32"
+            )
             axes = self.params_axes
             starts = self.params_starts
             ends = self.params_ends

python/paddle/fluid/tests/unittests/ir/inference/test_trt_subgraph_pass.py

@@ -28,7 +28,7 @@ from paddle.fluid.core import AnalysisConfig, PassVersionChecker
 class TensorRTSubgraphPassFcTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, 64, 64], dtype="float32"
             )
             fc_out = paddle.static.nn.fc(x=[data], activation=None, size=1000)
@@ -55,10 +55,10 @@ class TensorRTSubgraphPassFcTest(InferencePassTest):
 class TensorRTSubgraphPassConcatTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data1 = fluid.data(
+            data1 = paddle.static.data(
                 name="data1", shape=[-1, 3, 64, 64], dtype="float32"
             )
-            data2 = fluid.data(
+            data2 = paddle.static.data(
                 name="data2", shape=[-1, 3, 64, 64], dtype="float32"
             )
             concat_out = paddle.concat([data1, data2], axis=2)
@@ -85,7 +85,7 @@ class TensorRTSubgraphPassConcatTest(InferencePassTest):
 class TensorRTSubgraphPassSplitTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 3, 64, 64], dtype="float32"
             )
             split_out = paddle.split(data, axis=-1, num_or_sections=2)
@@ -111,7 +111,7 @@ class TensorRTSubgraphPassSplitTest(InferencePassTest):
 class TensorRTSubgraphPassSplitSerializeTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 3, 64, 64], dtype="float32"
             )
             split_out = paddle.split(data, axis=-1, num_or_sections=2)
@@ -139,7 +139,7 @@ class TensorRTSubgraphPassSplitSerializeTest(InferencePassTest):
 class TensorRTSubgraphPassDynamicSplitFp16SerializeTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 3, 64, 64], dtype="float32"
             )
             split_out = paddle.split(data, axis=-1, num_or_sections=2)
@@ -175,7 +175,7 @@ class TensorRTSubgraphPassDynamicSplitFp16SerializeTest(InferencePassTest):
 class TensorRTSubgraphPassInstanceNormTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 3, 64, 64], dtype="float32"
             )
             param_attr = fluid.ParamAttr(
@@ -212,7 +212,7 @@ class TensorRTSubgraphPassInstanceNormTest(InferencePassTest):
 class TensorRTSubgraphPassTransposeTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, 64, 64], dtype="float32"
             )
             transpose_out = self.append_transpose(data)
@@ -242,7 +242,7 @@ class TensorRTSubgraphPassLayerNormTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 3, 64, 64], dtype="float32"
             )
             out = paddle.static.nn.layer_norm(
@@ -273,7 +273,7 @@ class TensorRTSubgraphPassLayerNormDynamicTest(InferencePassTest):
     def setUp(self):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 3, 64, 64], dtype="float32"
             )
             out = paddle.static.nn.layer_norm(
@@ -359,10 +359,10 @@ class TensorRTSubgraphPassLayerNormBeginNormAxis3Test(
 class TensorRTSubgraphPassElementwiseTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data1 = fluid.data(
+            data1 = paddle.static.data(
                 name="data1", shape=[-1, 3, 64, 64], dtype="float32"
             )
-            data2 = fluid.data(
+            data2 = paddle.static.data(
                 name="data2", shape=[-1, 3, 64, 64], dtype="float32"
             )
             eltwise_out = self.append_eltwise(data1, data2)
@@ -414,10 +414,12 @@ class TensorRTSubgraphPassElementwiseSerializeTest(
 class TensorRTSubgraphPassElementwiseBroadcastDynamicTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data1 = fluid.data(
+            data1 = paddle.static.data(
                 name="data1", shape=[-1, 3, 64, 64], dtype="float32"
             )
-            data2 = fluid.data(name="data2", shape=[64, 64], dtype="float32")
+            data2 = paddle.static.data(
+                name="data2", shape=[64, 64], dtype="float32"
+            )
             eltwise_out = self.append_eltwise(data1, data2)
             out = nn.batch_norm(eltwise_out, is_test=True)
         self.feeds = {

python/paddle/fluid/tests/unittests/ir/inference/test_trt_tile_op.py

@@ -26,7 +26,7 @@ from paddle.fluid.core import AnalysisConfig, PassVersionChecker
 class TRTTileTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[4, 3, 224, 256], dtype="float32"
             )
             tile_out = paddle.tile(x=data, repeat_times=[1, 1, 1, 1])
@@ -53,7 +53,9 @@ class TRTTileTest(InferencePassTest):
 class TRTTileExpandTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[1, 1, 1, 1], dtype="float32")
+            data = paddle.static.data(
+                name="data", shape=[1, 1, 1, 1], dtype="float32"
+            )
             tile_out = paddle.tile(x=data, repeat_times=[1, 4, 1080, 1920])
             out = paddle.static.nn.batch_norm(tile_out, is_test=True)
 
@@ -78,7 +80,9 @@ class TRTTileExpandTest(InferencePassTest):
 class TRTTileExpandStaticTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[1, 1, 1, 1], dtype="float32")
+            data = paddle.static.data(
+                name="data", shape=[1, 1, 1, 1], dtype="float32"
+            )
             tile_out = paddle.tile(x=data, repeat_times=[1, 4, 1080, 1920])
             out = paddle.static.nn.batch_norm(tile_out, is_test=True)
 
@@ -103,7 +107,9 @@ class TRTTileExpandStaticTest(InferencePassTest):
 class TRTTileExpandHalfTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(name="data", shape=[1, 1, 1, 1], dtype="float32")
+            data = paddle.static.data(
+                name="data", shape=[1, 1, 1, 1], dtype="float32"
+            )
             tile_out = paddle.tile(x=data, repeat_times=[1, 4, 1080, 1920])
             out = paddle.static.nn.batch_norm(tile_out, is_test=True)
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_transpose_flatten_concat_fuse_pass.py

@@ -26,10 +26,10 @@ from paddle.fluid.core import AnalysisConfig
 class TransposeFlattenConcatFusePassTRTTest(InferencePassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data1 = fluid.data(
+            data1 = paddle.static.data(
                 name="data1", shape=[8, 32, 128], dtype="float32"
             )
-            data2 = fluid.data(
+            data2 = paddle.static.data(
                 name="data2", shape=[8, 32, 128], dtype="float32"
             )
 

python/paddle/fluid/tests/unittests/ir/inference/test_trt_tuned_dynamic_shape.py

@@ -31,7 +31,7 @@ class TRTTunedDynamicShapeTest(unittest.TestCase):
         main_program = fluid.Program()
         startup_program = fluid.Program()
         with fluid.program_guard(main_program, startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[-1, 6, 64, 64], dtype="float32"
             )
             conv_out = paddle.static.nn.conv2d(

python/paddle/fluid/tests/unittests/ir/inference/test_trt_yolo_box_op.py

@@ -27,8 +27,10 @@ class TRTYoloBoxTest(InferencePassTest):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
             image_shape = [self.bs, self.channel, self.height, self.width]
-            image = fluid.data(name='image', shape=image_shape, dtype='float32')
-            image_size = fluid.data(
+            image = paddle.static.data(
+                name='image', shape=image_shape, dtype='float32'
+            )
+            image_size = paddle.static.data(
                 name='image_size', shape=[self.bs, 2], dtype='int32'
             )
             boxes, scores = self.append_yolobox(image, image_size)
@@ -79,8 +81,10 @@ class TRTYoloBoxFP16Test(InferencePassTest):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
             image_shape = [self.bs, self.channel, self.height, self.width]
-            image = fluid.data(name='image', shape=image_shape, dtype='float32')
-            image_size = fluid.data(
+            image = paddle.static.data(
+                name='image', shape=image_shape, dtype='float32'
+            )
+            image_size = paddle.static.data(
                 name='image_size', shape=[self.bs, 2], dtype='int32'
             )
             boxes, scores = self.append_yolobox(image, image_size)
@@ -129,8 +133,10 @@ class TRTYoloBoxIoUAwareTest(InferencePassTest):
         self.set_params()
         with fluid.program_guard(self.main_program, self.startup_program):
             image_shape = [self.bs, self.channel, self.height, self.width]
-            image = fluid.data(name='image', shape=image_shape, dtype='float32')
-            image_size = fluid.data(
+            image = paddle.static.data(
+                name='image', shape=image_shape, dtype='float32'
+            )
+            image_size = paddle.static.data(
                 name='image_size', shape=[self.bs, 2], dtype='int32'
             )
             boxes, scores = self.append_yolobox(image, image_size)

python/paddle/fluid/tests/unittests/ir/test_ir_fc_fuse_pass.py

@@ -25,7 +25,7 @@ import paddle.fluid.core as core
 class FCFusePassTest(PassTest):
     def setUp(self):
         with fluid.program_guard(self.main_program, self.startup_program):
-            data = fluid.data(
+            data = paddle.static.data(
                 name="data", shape=[32, 128], dtype="float32", lod_level=0
             )
             tmp_0 = paddle.static.nn.fc(

python/paddle/fluid/tests/unittests/ir/test_ir_fusion_group_pass.py

@@ -27,7 +27,7 @@ class FusionGroupPassTest(PassTest):
         with fluid.program_guard(self.main_program, self.startup_program):
             self.feed_vars = self._prepare_feed_vars([32, 128], dtype, 2)
             self.feed_vars.append(
-                fluid.data(name="data2", shape=[128, 128], dtype=dtype)
+                paddle.static.data(name="data2", shape=[128, 128], dtype=dtype)
             )
 
             # subgraph with only 1 op node
@@ -51,7 +51,9 @@ class FusionGroupPassTest(PassTest):
     def _prepare_feed_vars(self, shape, dtype, num_data, stop_gradient=True):
         feed_vars = []
         for i in range(num_data):
-            var = fluid.data(name=("data" + str(i)), shape=shape, dtype=dtype)
+            var = paddle.static.data(
+                name=("data" + str(i)), shape=shape, dtype=dtype
+            )
             var.stop_gradient = stop_gradient
             feed_vars.append(var)
         return feed_vars
@@ -108,7 +110,7 @@ class FusionGroupPassInplaceTest(FusionGroupPassTest):
         with fluid.program_guard(self.main_program, self.startup_program):
             self.feed_vars = self._prepare_feed_vars([32, 128], dtype, 3)
             self.feed_vars.append(
-                fluid.data(name="data3", shape=[128, 32], dtype=dtype)
+                paddle.static.data(name="data3", shape=[128, 32], dtype=dtype)
             )
 
             # subgraph with 3 op node
@@ -134,7 +136,7 @@ class FusionGroupPassTestCastAndFP16(FusionGroupPassTest):
         with fluid.program_guard(self.main_program, self.startup_program):
             self.feed_vars = self._prepare_feed_vars([32, 128], dtype, 2)
             self.feed_vars.append(
-                fluid.data(name="data2", shape=[128, 128], dtype=dtype)
+                paddle.static.data(name="data2", shape=[128, 128], dtype=dtype)
             )
 
             # subgraph with 2 op nodes
@@ -165,7 +167,7 @@ class FusionGroupPassSumTest(FusionGroupPassTest):
         with fluid.program_guard(self.main_program, self.startup_program):
             self.feed_vars = self._prepare_feed_vars([32, 128], dtype, 3)
             self.feed_vars.append(
-                fluid.data(name="data3", shape=[128, 128], dtype=dtype)
+                paddle.static.data(name="data3", shape=[128, 128], dtype=dtype)
             )
 
             # subgraph with 2 op nodes

python/paddle/fluid/tests/unittests/ir/test_ir_skip_layernorm_pass.py

@@ -25,10 +25,10 @@ class SkipLayerNormFusePassTest(PassTest):
     def setUp(self):
         paddle.enable_static()
         with fluid.program_guard(self.main_program, self.startup_program):
-            x = fluid.data(
+            x = paddle.static.data(
                 name="x", shape=[128, 768], dtype="float32", lod_level=0
             )
-            y = fluid.data(
+            y = paddle.static.data(
                 name="y", shape=[128, 768], dtype="float32", lod_level=0
             )
             elementwise_out = paddle.add(x=x, y=y)

python/paddle/fluid/tests/unittests/mlu/test_batch_norm_op_mlu.py

@@ -803,7 +803,7 @@ class TestDygraphBatchNormTrainableStats(unittest.TestCase):
                         is_test=is_test,
                         trainable_statistics=trainable_statistics,
                     )
-                    x = fluid.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
+                    x = paddle.static.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
                     y = bn(x)
                     exe.run(fluid.default_startup_program())
                     r = exe.run(feed={'x': x_np}, fetch_list=[y])[0]
@@ -820,7 +820,7 @@ class TestDygraphBatchNormOpenReserveSpace(unittest.TestCase):
         with program_guard(Program(), Program()):
             paddle.enable_static()
             x = np.random.random(size=(3, 10, 3, 7)).astype('float32')
-            x = fluid.data(name='x', shape=x.shape, dtype=x.dtype)
+            x = paddle.static.data(name='x', shape=x.shape, dtype=x.dtype)
             # Set this FLAG, the BatchNorm API will pass "reserve_space" argument into batch_norm op.
             os.environ['FLAGS_cudnn_batchnorm_spatial_persistent'] = '1'
             batch_norm = paddle.nn.BatchNorm(7, data_layout="NHWC")

python/paddle/fluid/tests/unittests/mlu/test_batch_norm_op_mlu_v2.py

@@ -157,7 +157,7 @@ class TestBatchNorm(unittest.TestCase):
                         is_test=is_test,
                         trainable_statistics=trainable_statistics,
                     )
-                    x = fluid.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
+                    x = paddle.static.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
                     y = bn(x)
                     exe.run(fluid.default_startup_program())
                     r = exe.run(feed={'x': x_np}, fetch_list=[y])[0]
@@ -166,7 +166,7 @@ class TestBatchNorm(unittest.TestCase):
             def compute_v2(x_np):
                 with program_guard(Program(), Program()):
                     bn = paddle.nn.BatchNorm2D(shape[1])
-                    x = fluid.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
+                    x = paddle.static.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
                     y = bn(x)
                     exe.run(fluid.default_startup_program())
                     r = exe.run(feed={'x': x_np}, fetch_list=[y])[0]

python/paddle/fluid/tests/unittests/mlu/test_bce_loss_mlu.py

@@ -30,14 +30,14 @@ def test_static_layer(
     prog = paddle.static.Program()
     startup_prog = paddle.static.Program()
     with paddle.static.program_guard(prog, startup_prog):
-        input = paddle.fluid.data(
+        input = paddle.static.data(
             name='input', shape=input_np.shape, dtype='float32'
         )
-        label = paddle.fluid.data(
+        label = paddle.static.data(
             name='label', shape=label_np.shape, dtype='float32'
         )
         if weight_np is not None:
-            weight = paddle.fluid.data(
+            weight = paddle.static.data(
                 name='weight', shape=weight_np.shape, dtype='float32'
             )
             bce_loss = paddle.nn.loss.BCELoss(
@@ -63,14 +63,14 @@ def test_static_functional(
     prog = paddle.static.Program()
     startup_prog = paddle.static.Program()
     with paddle.static.program_guard(prog, startup_prog):
-        input = paddle.fluid.data(
+        input = paddle.static.data(
             name='input', shape=input_np.shape, dtype='float32'
         )
-        label = paddle.fluid.data(
+        label = paddle.static.data(
             name='label', shape=label_np.shape, dtype='float32'
         )
         if weight_np is not None:
-            weight = paddle.fluid.data(
+            weight = paddle.static.data(
                 name='weight', shape=weight_np.shape, dtype='float32'
             )
             res = paddle.nn.functional.binary_cross_entropy(

python/paddle/fluid/tests/unittests/mlu/test_bce_with_logits_loss_mlu.py

@@ -41,10 +41,10 @@ def test_static(
     prog = paddle.static.Program()
     startup_prog = paddle.static.Program()
     with paddle.static.program_guard(prog, startup_prog):
-        logit = paddle.fluid.data(
+        logit = paddle.static.data(
             name='logit', shape=logit_np.shape, dtype='float32'
         )
-        label = paddle.fluid.data(
+        label = paddle.static.data(
             name='label', shape=label_np.shape, dtype='float32'
         )
         feed_dict = {"logit": logit_np, "label": label_np}
@@ -52,12 +52,12 @@ def test_static(
         pos_weight = None
         weight = None
         if pos_weight_np is not None:
-            pos_weight = paddle.fluid.data(
+            pos_weight = paddle.static.data(
                 name='pos_weight', shape=pos_weight_np.shape, dtype='float32'
             )
             feed_dict["pos_weight"] = pos_weight_np
         if weight_np is not None:
-            weight = paddle.fluid.data(
+            weight = paddle.static.data(
                 name='weight', shape=weight_np.shape, dtype='float32'
             )
             feed_dict["weight"] = weight_np

python/paddle/fluid/tests/unittests/mlu/test_dropout_op_mlu.py

@@ -224,7 +224,7 @@ class TestDropoutAPI(unittest.TestCase):
 
     def check_static_result(self, place):
         with fluid.program_guard(fluid.Program(), fluid.Program()):
-            input = fluid.data(name="input", shape=[40, 40], dtype="float32")
+            input = paddle.static.data(name="input", shape=[40, 40], dtype="float32")
             res1 = paddle.nn.functional.dropout(
                 x=input, p=0.0, training=False, mode='upscale_in_train'
             )

python/paddle/fluid/tests/unittests/mlu/test_elementwise_add_op_mlu.py

@@ -402,8 +402,8 @@ class TestAddApi(unittest.TestCase):
 
     def test_name(self):
         with fluid.program_guard(fluid.Program()):
-            x = fluid.data(name="x", shape=[2, 3], dtype="float32")
-            y = fluid.data(name='y', shape=[2, 3], dtype='float32')
+            x = paddle.static.data(name="x", shape=[2, 3], dtype="float32")
+            y = paddle.static.data(name='y', shape=[2, 3], dtype='float32')
 
             y_1 = self._executed_api(x, y, name='add_res')
             self.assertEqual(('add_res' in y_1.name), True)
@@ -417,8 +417,8 @@ class TestAddApi(unittest.TestCase):
                     "y": np.array([1, 5, 2]).astype('float32'),
                 }
 
-            x = fluid.data(name="x", shape=[3], dtype='float32')
-            y = fluid.data(name="y", shape=[3], dtype='float32')
+            x = paddle.static.data(name="x", shape=[3], dtype='float32')
+            y = paddle.static.data(name="y", shape=[3], dtype='float32')
             z = self._executed_api(x, y)
 
             place = fluid.MLUPlace(0)

python/paddle/fluid/tests/unittests/mlu/test_fill_constant_op_mlu.py

@@ -271,10 +271,10 @@ class TestFillConstantAPI(unittest.TestCase):
         positive_2_int32 = paddle.tensor.fill_constant([1], "int32", 2)
         positive_2_int64 = paddle.tensor.fill_constant([1], "int64", 2)
 
-        shape_tensor_int32 = fluid.data(
+        shape_tensor_int32 = paddle.static.data(
             name="shape_tensor_int32", shape=[2], dtype="int32"
         )
-        shape_tensor_int64 = fluid.data(
+        shape_tensor_int64 = paddle.static.data(
             name="shape_tensor_int64", shape=[2], dtype="int64"
         )
 
@@ -446,7 +446,7 @@ class TestFillConstantOpError(unittest.TestCase):
 
             # The shape dtype of fill_constant_op must be int32 or int64.
             def test_shape_tensor_dtype():
-                shape = fluid.data(
+                shape = paddle.static.data(
                     name="shape_tensor", shape=[2], dtype="float32"
                 )
                 paddle.tensor.fill_constant(
@@ -456,7 +456,7 @@ class TestFillConstantOpError(unittest.TestCase):
             self.assertRaises(TypeError, test_shape_tensor_dtype)
 
             def test_shape_tensor_list_dtype():
-                shape = fluid.data(
+                shape = paddle.static.data(
                     name="shape_tensor_list", shape=[1], dtype="bool"
                 )
                 paddle.tensor.fill_constant(

python/paddle/fluid/tests/unittests/mlu/test_gather_op_mlu.py

@@ -129,10 +129,10 @@ class TestGathertError(unittest.TestCase):
         ):
 
             shape = [8, 9, 6]
-            x = paddle.fluid.data(shape=shape, dtype='int8', name='x')
-            axis = paddle.fluid.data(shape=[1], dtype='float32', name='axis')
-            index = paddle.fluid.data(shape=shape, dtype='int32', name='index')
-            index_float = paddle.fluid.data(
+            x = paddle.static.data(shape=shape, dtype='int8', name='x')
+            axis = paddle.static.data(shape=[1], dtype='float32', name='axis')
+            index = paddle.static.data(shape=shape, dtype='int32', name='index')
+            index_float = paddle.static.data(
                 shape=shape, dtype='float32', name='index_float'
             )
 
@@ -160,9 +160,9 @@ class TestGathertError(unittest.TestCase):
         with fluid.program_guard(fluid.Program(), fluid.Program()):
 
             shape = [8, 9, 6]
-            x = fluid.data(shape=shape, dtype='int8', name='x')
-            index = fluid.data(shape=shape, dtype='int32', name='mask')
-            index_float = fluid.data(
+            x = paddle.static.data(shape=shape, dtype='int8', name='x')
+            index = paddle.static.data(shape=shape, dtype='int32', name='mask')
+            index_float = paddle.static.data(
                 shape=shape, dtype='float32', name='index_float'
             )
 

python/paddle/fluid/tests/unittests/mlu/test_hard_sigmoid_op_mlu.py

@@ -161,7 +161,7 @@ class TestHardsigmoidAPI(unittest.TestCase):
     def test_fluid_api(self):
         paddle.enable_static()
         with fluid.program_guard(fluid.Program()):
-            x = fluid.data('X', self.x_np.shape, self.x_np.dtype)
+            x = paddle.static.data('X', self.x_np.shape, self.x_np.dtype)
             out = paddle.nn.functional.hardsigmoid(x)
             exe = fluid.Executor(self.place)
             res = exe.run(feed={'X': self.x_np}, fetch_list=[out])
@@ -179,12 +179,12 @@ class TestHardsigmoidAPI(unittest.TestCase):
             # The input type must be Variable.
             self.assertRaises(TypeError, F.hardsigmoid, 1)
             # The input dtype must be float16, float32, float64.
-            x_int32 = paddle.fluid.data(
+            x_int32 = paddle.static.data(
                 name='x_int32', shape=[12, 10], dtype='int32'
             )
             self.assertRaises(TypeError, F.hardsigmoid, x_int32)
             # support the input dtype is float16
-            x_fp16 = paddle.fluid.data(
+            x_fp16 = paddle.static.data(
                 name='x_fp16', shape=[12, 10], dtype='float16'
             )
             F.hardsigmoid(x_fp16)

python/paddle/fluid/tests/unittests/mlu/test_log_softmax_op_mlu.py

@@ -140,7 +140,7 @@ class TestNNLogSoftmaxAPI(unittest.TestCase):
         paddle.enable_static()
         # test static api
         with paddle.static.program_guard(paddle.static.Program()):
-            x = paddle.fluid.data(name='x', shape=self.x_shape)
+            x = paddle.static.data(name='x', shape=self.x_shape)
             y = logsoftmax(x)
             exe = paddle.static.Executor(self.place)
             out = exe.run(feed={'x': self.x}, fetch_list=[y])
@@ -174,7 +174,7 @@ class TestNNFunctionalLogSoftmaxAPI(unittest.TestCase):
             x = x.astype(dtype)
         ref_out = np.apply_along_axis(ref_log_softmax, axis, x)
         with paddle.static.program_guard(paddle.static.Program()):
-            x = paddle.fluid.data(name='x', shape=self.x_shape)
+            x = paddle.static.data(name='x', shape=self.x_shape)
             y = F.log_softmax(x, axis, dtype)
             exe = paddle.static.Executor(self.place)
             out = exe.run(feed={'x': self.x}, fetch_list=[y])
@@ -194,10 +194,10 @@ class TestNNFunctionalLogSoftmaxAPI(unittest.TestCase):
     def test_errors(self):
         paddle.enable_static()
         with paddle.static.program_guard(paddle.static.Program()):
-            x = paddle.fluid.data(name='X1', shape=[100], dtype='int32')
+            x = paddle.static.data(name='X1', shape=[100], dtype='int32')
             self.assertRaises(TypeError, F.log_softmax, x)
 
-            x = paddle.fluid.data(name='X2', shape=[100], dtype='float32')
+            x = paddle.static.data(name='X2', shape=[100], dtype='float32')
             self.assertRaises(TypeError, F.log_softmax, x, dtype='int32')
         paddle.disable_static()
 

python/paddle/fluid/tests/unittests/mlu/test_masked_select_op_mlu.py

@@ -107,8 +107,8 @@ class TestMaskedSelectAPI(unittest.TestCase):
 
     def test_static_mode(self):
         shape = [8, 9, 6]
-        x = paddle.fluid.data(shape=shape, dtype='float32', name='x')
-        mask = paddle.fluid.data(shape=shape, dtype='bool', name='mask')
+        x = paddle.static.data(shape=shape, dtype='float32', name='x')
+        mask = paddle.static.data(shape=shape, dtype='bool', name='mask')
         np_x = np.random.random(shape).astype('float32')
         np_mask = np.array(np.random.randint(2, size=shape, dtype=bool))
 
@@ -132,9 +132,9 @@ class TestMaskedSelectError(unittest.TestCase):
         ):
 
             shape = [8, 9, 6]
-            x = paddle.fluid.data(shape=shape, dtype='float32', name='x')
-            mask = paddle.fluid.data(shape=shape, dtype='bool', name='mask')
-            mask_float = paddle.fluid.data(
+            x = paddle.static.data(shape=shape, dtype='float32', name='x')
+            mask = paddle.static.data(shape=shape, dtype='bool', name='mask')
+            mask_float = paddle.static.data(
                 shape=shape, dtype='float32', name='mask_float'
             )
             np_x = np.random.random(shape).astype('float32')

python/paddle/fluid/tests/unittests/mlu/test_matmul_v2_op_mlu.py

@@ -350,8 +350,8 @@ class TestMatMulV2API(unittest.TestCase):
 
     def check_static_result(self, place):
         with fluid.program_guard(fluid.Program(), fluid.Program()):
-            input_x = fluid.data(name="input_x", shape=[4, 3], dtype="float32")
-            input_y = fluid.data(name="input_y", shape=[3, 4], dtype="float32")
+            input_x = paddle.static.data(name="input_x", shape=[4, 3], dtype="float32")
+            input_y = paddle.static.data(name="input_y", shape=[3, 4], dtype="float32")
 
             result = paddle.matmul(input_x, input_y)
 

python/paddle/fluid/tests/unittests/mlu/test_meshgrid_op_mlu.py

@@ -68,8 +68,8 @@ class TestMeshgridOp2(TestMeshgridOp):
 
 class TestMeshgridOp3(unittest.TestCase):
     def test_api(self):
-        x = fluid.data(shape=[100], dtype='int32', name='x')
-        y = fluid.data(shape=[200], dtype='int32', name='y')
+        x = paddle.static.data(shape=[100], dtype='int32', name='x')
+        y = paddle.static.data(shape=[200], dtype='int32', name='y')
 
         input_1 = np.random.randint(
             0,
@@ -104,8 +104,8 @@ class TestMeshgridOp3(unittest.TestCase):
 
 class TestMeshgridOp4(unittest.TestCase):
     def test_list_input(self):
-        x = fluid.data(shape=[100], dtype='int32', name='x')
-        y = fluid.data(shape=[200], dtype='int32', name='y')
+        x = paddle.static.data(shape=[100], dtype='int32', name='x')
+        y = paddle.static.data(shape=[200], dtype='int32', name='y')
 
         input_1 = np.random.randint(
             0,
@@ -141,8 +141,8 @@ class TestMeshgridOp4(unittest.TestCase):
 
 class TestMeshgridOp5(unittest.TestCase):
     def test_tuple_input(self):
-        x = fluid.data(shape=[100], dtype='int32', name='x')
-        y = fluid.data(shape=[200], dtype='int32', name='y')
+        x = paddle.static.data(shape=[100], dtype='int32', name='x')
+        y = paddle.static.data(shape=[200], dtype='int32', name='y')
 
         input_1 = np.random.randint(
             0,

python/paddle/fluid/tests/unittests/mlu/test_scatter_op_mlu.py

@@ -127,9 +127,9 @@ class TestScatterAPI(unittest.TestCase):
 
     def check_static_result(self, place):
         with fluid.program_guard(fluid.Program(), fluid.Program()):
-            input = fluid.data(name="input", shape=[3, 2], dtype="float32")
-            index = fluid.data(name="index", shape=[4], dtype="int64")
-            updates = fluid.data(name="updates", shape=[4, 2], dtype="float32")
+            input = paddle.static.data(name="input", shape=[3, 2], dtype="float32")
+            index = paddle.static.data(name="index", shape=[4], dtype="int64")
+            updates = paddle.static.data(name="updates", shape=[4, 2], dtype="float32")
             result = self.scatter(input, index, updates, False)
 
             input_data = np.array([[1, 1], [2, 2], [3, 3]]).astype(np.float32)

python/paddle/fluid/tests/unittests/mlu/test_size_op_mlu.py

@@ -67,8 +67,8 @@ class TestSizeAPI(unittest.TestCase):
         with fluid.program_guard(main_program, startup_program):
             shape1 = [2, 1, 4, 5]
             shape2 = [1, 4, 5]
-            x_1 = paddle.fluid.data(shape=shape1, dtype='int32', name='x_1')
-            x_2 = paddle.fluid.data(shape=shape2, dtype='int32', name='x_2')
+            x_1 = paddle.static.data(shape=shape1, dtype='int32', name='x_1')
+            x_2 = paddle.static.data(shape=shape2, dtype='int32', name='x_2')
             input_1 = np.random.random(shape1).astype("int32")
             input_2 = np.random.random(shape2).astype("int32")
             out_1 = paddle.numel(x_1)

python/paddle/fluid/tests/unittests/mlu/test_softmax_op_mlu.py

@@ -132,7 +132,7 @@ class TestSoftmaxAPI(unittest.TestCase):
 
     def test_static_check(self):
         with paddle.static.program_guard(paddle.static.Program()):
-            x = paddle.fluid.data('X', self.x_np.shape, 'float32')
+            x = paddle.static.data('X', self.x_np.shape, 'float32')
             out1 = self.softmax(x)
             m = paddle.nn.Softmax()
             out2 = m(x)
@@ -173,12 +173,12 @@ class TestSoftmaxAPI(unittest.TestCase):
             # The input type must be Variable.
             self.assertRaises(TypeError, self.softmax, 1)
             # The input dtype must be float16, float32
-            x_int32 = paddle.fluid.data(
+            x_int32 = paddle.static.data(
                 name='x_int32', shape=[2, 3], dtype='int32'
             )
             self.assertRaises(TypeError, self.softmax, x_int32)
             # support the input dtype is float16
-            x_fp16 = paddle.fluid.data(
+            x_fp16 = paddle.static.data(
                 name='x_fp16', shape=[2, 3], dtype='float16'
             )
             self.softmax(x_fp16)

python/paddle/fluid/tests/unittests/mlu/test_transpose_op_mlu.py

@@ -256,7 +256,7 @@ class TestTransposeApi(unittest.TestCase):
 class TestTAPI(unittest.TestCase):
     def test_out(self):
         with fluid.program_guard(fluid.Program()):
-            data = fluid.data(shape=[10], dtype="float32", name="data")
+            data = paddle.static.data(shape=[10], dtype="float32", name="data")
             data_t = paddle.t(data)
             place = fluid.MLUPlace(0)
             exe = fluid.Executor(place)
@@ -266,7 +266,7 @@ class TestTAPI(unittest.TestCase):
         self.assertEqual((result == expected_result).all(), True)
 
         with fluid.program_guard(fluid.Program()):
-            data = fluid.data(shape=[10, 5], dtype="float32", name="data")
+            data = paddle.static.data(shape=[10, 5], dtype="float32", name="data")
             data_t = paddle.t(data)
             place = fluid.MLUPlace(0)
             exe = fluid.Executor(place)
@@ -276,7 +276,7 @@ class TestTAPI(unittest.TestCase):
         self.assertEqual((result == expected_result).all(), True)
 
         with fluid.program_guard(fluid.Program()):
-            data = fluid.data(shape=[1, 5], dtype="float32", name="data")
+            data = paddle.static.data(shape=[1, 5], dtype="float32", name="data")
             data_t = paddle.t(data)
             place = fluid.MLUPlace(0)
             exe = fluid.Executor(place)
@@ -311,7 +311,7 @@ class TestTAPI(unittest.TestCase):
 
     def test_errors(self):
         with fluid.program_guard(fluid.Program()):
-            x = fluid.data(name='x', shape=[10, 5, 3], dtype='float32')
+            x = paddle.static.data(name='x', shape=[10, 5, 3], dtype='float32')
 
             def test_x_dimension_check():
                 paddle.t(x)

python/paddle/fluid/tests/unittests/mlu/test_tril_triu_op_mlu.py

@@ -81,7 +81,7 @@ def case_generator(op_type, Xshape, diagonal, expected):
         def test_failure(self):
             paddle.enable_static()
 
-            data = fluid.data(shape=Xshape, dtype='float64', name=cls_name)
+            data = paddle.static.data(shape=Xshape, dtype='float64', name=cls_name)
             with self.assertRaisesRegex(
                 eval(expected.split(':')[-1]), errmsg[expected]
             ):
@@ -146,7 +146,7 @@ class TestTrilTriuOpAPI(unittest.TestCase):
             startup_prog = Program()
             with program_guard(prog, startup_prog):
                 data = np.random.random([1, 9, 9, 4]).astype(dtype)
-                x = fluid.data(shape=[1, 9, -1, 4], dtype=dtype, name='x')
+                x = paddle.static.data(shape=[1, 9, -1, 4], dtype=dtype, name='x')
                 tril_out, triu_out = tensor.tril(x), tensor.triu(x)
 
                 place = fluid.MLUPlace(0)
@@ -183,7 +183,7 @@ class TestTrilTriuOpAPI(unittest.TestCase):
             startup_prog = Program()
             with program_guard(prog, startup_prog):
                 data = np.random.random([1, 9, 9, 4]).astype(dtype)
-                x = fluid.data(shape=[1, 9, -1, 4], dtype=dtype, name='x')
+                x = paddle.static.data(shape=[1, 9, -1, 4], dtype=dtype, name='x')
                 triu_out = paddle.triu(x)
 
                 place = fluid.MLUPlace(0)

python/paddle/fluid/tests/unittests/npu/test_batch_norm_op_npu.py

@@ -588,7 +588,7 @@ class TestDygraphBatchNormTrainableStats(unittest.TestCase):
                         is_test=is_test,
                         trainable_statistics=trainable_statistics,
                     )
-                    x = fluid.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
+                    x = paddle.static.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
                     y = bn(x)
                     exe.run(fluid.default_startup_program())
                     r = exe.run(feed={'x': x_np}, fetch_list=[y])[0]

python/paddle/fluid/tests/unittests/npu/test_bce_loss_npu.py

@@ -30,14 +30,14 @@ def test_static_layer(
     prog = paddle.static.Program()
     startup_prog = paddle.static.Program()
     with paddle.static.program_guard(prog, startup_prog):
-        input = paddle.fluid.data(
+        input = paddle.static.data(
             name='input', shape=input_np.shape, dtype='float32'
         )
-        label = paddle.fluid.data(
+        label = paddle.static.data(
             name='label', shape=label_np.shape, dtype='float32'
         )
         if weight_np is not None:
-            weight = paddle.fluid.data(
+            weight = paddle.static.data(
                 name='weight', shape=weight_np.shape, dtype='float32'
             )
             bce_loss = paddle.nn.loss.BCELoss(
@@ -63,14 +63,14 @@ def test_static_functional(
     prog = paddle.static.Program()
     startup_prog = paddle.static.Program()
     with paddle.static.program_guard(prog, startup_prog):
-        input = paddle.fluid.data(
+        input = paddle.static.data(
             name='input', shape=input_np.shape, dtype='float32'
         )
-        label = paddle.fluid.data(
+        label = paddle.static.data(
             name='label', shape=label_np.shape, dtype='float32'
         )
         if weight_np is not None:
-            weight = paddle.fluid.data(
+            weight = paddle.static.data(
                 name='weight', shape=weight_np.shape, dtype='float32'
             )
             res = paddle.nn.functional.binary_cross_entropy(

python/paddle/fluid/tests/unittests/npu/test_clip_op_npu.py

@@ -137,9 +137,9 @@ class TestClipAPI(unittest.TestCase):
         paddle.enable_static()
         data_shape = [1, 9, 9, 4]
         data = np.random.random(data_shape).astype('float32')
-        images = fluid.data(name='image', shape=data_shape, dtype='float32')
-        min = fluid.data(name='min', shape=[1], dtype='float32')
-        max = fluid.data(name='max', shape=[1], dtype='float32')
+        images = paddle.static.data(name='image', shape=data_shape, dtype='float32')
+        min = paddle.static.data(name='min', shape=[1], dtype='float32')
+        max = paddle.static.data(name='max', shape=[1], dtype='float32')
 
         place = (
             fluid.NPUPlace(0)
@@ -203,8 +203,8 @@ class TestClipAPI(unittest.TestCase):
 
     def test_errors(self):
         paddle.enable_static()
-        x1 = fluid.data(name='x1', shape=[1], dtype="int16")
-        x2 = fluid.data(name='x2', shape=[1], dtype="int8")
+        x1 = paddle.static.data(name='x1', shape=[1], dtype="int16")
+        x2 = paddle.static.data(name='x2', shape=[1], dtype="int8")
         self.assertRaises(TypeError, paddle.clip, x=x1, min=0.2, max=0.8)
         self.assertRaises(TypeError, paddle.clip, x=x2, min=0.2, max=0.8)
         paddle.disable_static()

python/paddle/fluid/tests/unittests/npu/test_dropout_op_npu.py

@@ -215,7 +215,7 @@ class TestDropoutAPI(unittest.TestCase):
 
     def check_static_result(self, place):
         with fluid.program_guard(fluid.Program(), fluid.Program()):
-            input = fluid.data(name="input", shape=[40, 40], dtype="float32")
+            input = paddle.static.data(name="input", shape=[40, 40], dtype="float32")
             res1 = paddle.nn.functional.dropout(
                 x=input, p=0.0, training=False, mode='upscale_in_train'
             )

python/paddle/fluid/tests/unittests/npu/test_elementwise_add_op_npu.py

@@ -510,8 +510,8 @@ class TestAddApi(unittest.TestCase):
 
     def test_name(self):
         with fluid.program_guard(fluid.Program()):
-            x = fluid.data(name="x", shape=[2, 3], dtype="float32")
-            y = fluid.data(name='y', shape=[2, 3], dtype='float32')
+            x = paddle.static.data(name="x", shape=[2, 3], dtype="float32")
+            y = paddle.static.data(name='y', shape=[2, 3], dtype='float32')
 
             y_1 = self._executed_api(x, y, name='add_res')
             self.assertEqual(('add_res' in y_1.name), True)
@@ -525,8 +525,8 @@ class TestAddApi(unittest.TestCase):
                     "y": np.array([1, 5, 2]).astype('float32'),
                 }
 
-            x = fluid.data(name="x", shape=[3], dtype='float32')
-            y = fluid.data(name="y", shape=[3], dtype='float32')
+            x = paddle.static.data(name="x", shape=[3], dtype='float32')
+            y = paddle.static.data(name="y", shape=[3], dtype='float32')
             z = self._executed_api(x, y)
 
             place = fluid.NPUPlace(0)

python/paddle/fluid/tests/unittests/npu/test_elementwise_mod_op_npu.py

@@ -144,8 +144,8 @@ class TestRemainderOp(unittest.TestCase):
     def test_name(self):
         paddle.set_device('npu:0')
         with fluid.program_guard(fluid.Program()):
-            x = fluid.data(name="x", shape=[2, 3], dtype="int64")
-            y = fluid.data(name='y', shape=[2, 3], dtype='int64')
+            x = paddle.static.data(name="x", shape=[2, 3], dtype="int64")
+            y = paddle.static.data(name='y', shape=[2, 3], dtype='int64')
             y_1 = paddle.remainder(x, y, name='div_res')
             self.assertEqual(('div_res' in y_1.name), True)
 

python/paddle/fluid/tests/unittests/npu/test_gather_op_npu.py

@@ -101,8 +101,8 @@ class API_TestGather(unittest.TestCase):
         with paddle.static.program_guard(
             paddle.static.Program(), paddle.static.Program()
         ):
-            x = paddle.fluid.data('x', shape=[-1, 2], dtype='float32')
-            index = paddle.fluid.data('index', shape=[-1, 1], dtype='int32')
+            x = paddle.static.data('x', shape=[-1, 2], dtype='float32')
+            index = paddle.static.data('index', shape=[-1, 1], dtype='int32')
             out = paddle.gather(x, index)
             place = paddle.NPUPlace(0)
             exe = paddle.static.Executor(place)

python/paddle/fluid/tests/unittests/npu/test_group_norm_op_npu.py

@@ -216,7 +216,7 @@ class TestGroupNormOpFP16_With_NHWC(TestGroupNormOp):
 class TestGroupNormException(unittest.TestCase):
     # data_layout is not NHWC or NCHW
     def test_exception(self):
-        data = fluid.data(name='data', shape=[None, 3, 3, 4], dtype="float64")
+        data = paddle.static.data(name='data', shape=[None, 3, 3, 4], dtype="float64")
 
         def attr_data_format():
             out = paddle.static.nn.group_norm(

python/paddle/fluid/tests/unittests/npu/test_hard_sigmoid_op_npu.py

@@ -122,7 +122,7 @@ class TestHardsigmoidAPI(unittest.TestCase):
 
     def test_fluid_api(self):
         with fluid.program_guard(fluid.Program()):
-            x = fluid.data('X', self.x_np.shape, self.x_np.dtype)
+            x = paddle.static.data('X', self.x_np.shape, self.x_np.dtype)
             out = paddle.nn.functional.hardsigmoid(x)
             exe = fluid.Executor(self.place)
             res = exe.run(feed={'X': self.x_np}, fetch_list=[out])
@@ -140,12 +140,12 @@ class TestHardsigmoidAPI(unittest.TestCase):
             # The input type must be Variable.
             self.assertRaises(TypeError, F.hardsigmoid, 1)
             # The input dtype must be float16, float32, float64.
-            x_int32 = paddle.fluid.data(
+            x_int32 = paddle.static.data(
                 name='x_int32', shape=[12, 10], dtype='int32'
             )
             self.assertRaises(TypeError, F.hardsigmoid, x_int32)
             # support the input dtype is float16
-            x_fp16 = paddle.fluid.data(
+            x_fp16 = paddle.static.data(
                 name='x_fp16', shape=[12, 10], dtype='float16'
             )
             F.hardsigmoid(x_fp16)

python/paddle/fluid/tests/unittests/npu/test_index_sample_op_npu.py

@@ -160,8 +160,8 @@ class TestIndexSampleShape(unittest.TestCase):
             low=0, high=x_shape[1], size=index_shape
         ).astype(index_type)
 
-        x = fluid.data(name='x', shape=[-1, 5], dtype='float32')
-        index = fluid.data(name='index', shape=[-1, 3], dtype='int32')
+        x = paddle.static.data(name='x', shape=[-1, 5], dtype='float32')
+        index = paddle.static.data(name='index', shape=[-1, 3], dtype='int32')
         output = paddle.index_sample(x=x, index=index)
 
         place = fluid.NPUPlace(0)

python/paddle/fluid/tests/unittests/npu/test_instance_norm_op_npu.py

@@ -61,7 +61,7 @@ class TestInstanceNorm(unittest.TestCase):
             def compute_v1(x_np):
                 with program_guard(Program(), Program()):
                     ins = paddle.nn.InstanceNorm(shape[1])
-                    x = fluid.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
+                    x = paddle.static.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
                     y = ins(x)
                     exe.run(fluid.default_startup_program())
                     r = exe.run(feed={'x': x_np}, fetch_list=[y])[0]
@@ -70,7 +70,7 @@ class TestInstanceNorm(unittest.TestCase):
             def compute_v2(x_np):
                 with program_guard(Program(), Program()):
                     ins = paddle.nn.InstanceNorm2D(shape[1])
-                    x = fluid.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
+                    x = paddle.static.data(name='x', shape=x_np.shape, dtype=x_np.dtype)
                     y = ins(x)
                     exe.run(fluid.default_startup_program())
                     r = exe.run(feed={'x': x_np}, fetch_list=[y])[0]

python/paddle/fluid/tests/unittests/npu/test_kldiv_loss_op_npu.py

@@ -137,8 +137,8 @@ class TestKLDivLossDygraph(unittest.TestCase):
         self.run_kl_loss('none')
 
     def test_kl_loss_static_api(self):
-        input = paddle.fluid.data(name='input', shape=[5, 20])
-        label = paddle.fluid.data(name='label', shape=[5, 20])
+        input = paddle.static.data(name='input', shape=[5, 20])
+        label = paddle.static.data(name='label', shape=[5, 20])
 
         pred_loss = paddle.nn.functional.kl_div(input, label)