add full op API (#23112)

python/paddle/__init__.py

@@ -52,7 +52,7 @@ import paddle.nn
 # from .tensor.creation import zeros_like   #DEFINE_ALIAS
 # from .tensor.creation import arrange   #DEFINE_ALIAS
 # from .tensor.creation import eye   #DEFINE_ALIAS
-# from .tensor.creation import full   #DEFINE_ALIAS
+from .tensor.creation import full  #DEFINE_ALIAS
 # from .tensor.creation import linspace   #DEFINE_ALIAS
 # from .tensor.creation import full_like   #DEFINE_ALIAS
 # from .tensor.creation import triu   #DEFINE_ALIAS

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

@@ -0,0 +1,139 @@
+#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import unittest
+import numpy as np
+from op_test import OpTest
+
+import paddle.fluid.core as core
+from paddle.fluid.op import Operator
+import paddle.fluid as fluid
+import paddle.tensor as tensor
+from paddle.fluid import compiler, Program, program_guard
+
+
+# Test python API
+class TestFullAPI(unittest.TestCase):
+    def test_api(self):
+        positive_2_int32 = fluid.layers.fill_constant([1], "int32", 2)
+
+        positive_2_int64 = fluid.layers.fill_constant([1], "int64", 2)
+        shape_tensor_int32 = fluid.data(
+            name="shape_tensor_int32", shape=[2], dtype="int32")
+
+        shape_tensor_int64 = fluid.data(
+            name="shape_tensor_int64", shape=[2], dtype="int64")
+
+        out_1 = tensor.full(
+            shape=[1, 2], dtype="float32", fill_value=1.1, device='gpu')
+
+        out_2 = tensor.full(
+            shape=[1, positive_2_int32],
+            dtype="float32",
+            fill_value=1.1,
+            device='cpu')
+
+        out_3 = tensor.full(
+            shape=[1, positive_2_int64],
+            dtype="float32",
+            fill_value=1.1,
+            device='gpu')
+
+        out_4 = tensor.full(
+            shape=shape_tensor_int32,
+            dtype="float32",
+            fill_value=1.2,
+            out=out_3)
+
+        out_5 = tensor.full(
+            shape=shape_tensor_int64,
+            dtype="float32",
+            fill_value=1.1,
+            device='gpu',
+            stop_gradient=False)
+
+        out_6 = tensor.full(
+            shape=shape_tensor_int64, dtype=np.float32, fill_value=1.1)
+
+        exe = fluid.Executor(place=fluid.CPUPlace())
+        res_1, res_2, res_3, res_4, res_5, res_6 = exe.run(
+            fluid.default_main_program(),
+            feed={
+                "shape_tensor_int32": np.array([1, 2]).astype("int32"),
+                "shape_tensor_int64": np.array([1, 2]).astype("int64"),
+            },
+            fetch_list=[out_1, out_2, out_3, out_4, out_5, out_6])
+
+        assert np.array_equal(res_1, np.full([1, 2], 1.1, dtype="float32"))
+        assert np.array_equal(res_2, np.full([1, 2], 1.1, dtype="float32"))
+        assert np.array_equal(res_3, np.full([1, 2], 1.2, dtype="float32"))
+        assert np.array_equal(res_4, np.full([1, 2], 1.2, dtype="float32"))
+        assert np.array_equal(res_5, np.full([1, 2], 1.1, dtype="float32"))
+        assert np.array_equal(res_6, np.full([1, 2], 1.1, dtype="float32"))
+
+
+class TestFullOpError(unittest.TestCase):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            #for ci coverage
+            x1 = fluid.layers.data(name='x1', shape=[1], dtype="int16")
+            self.assertRaises(
+                ValueError, tensor.full, shape=[1], fill_value=5, dtype='uint4')
+            self.assertRaises(
+                TypeError,
+                tensor.full,
+                shape=[1],
+                fill_value=5,
+                dtype='int16',
+                out=x1)
+
+            # The argument dtype of full must be one of bool, float16,
+            #float32, float64, int32 or int64
+            x2 = fluid.layers.data(name='x2', shape=[1], dtype="int32")
+
+            self.assertRaises(
+                TypeError, tensor.full, shape=[1], fill_value=5, dtype='uint8')
+
+            # The argument shape's type of full_op  must be list, tuple or Variable.
+            def test_shape_type():
+                tensor.full(shape=1, dtype="float32", fill_value=1)
+
+            self.assertRaises(TypeError, test_shape_type)
+
+            # The argument shape's size of full_op must not be 0.
+            def test_shape_size():
+                tensor.full(shape=[], dtype="float32", fill_value=1)
+
+            self.assertRaises(AssertionError, test_shape_size)
+
+            # The shape dtype of full op must be int32 or int64.
+            def test_shape_tensor_dtype():
+                shape = fluid.data(
+                    name="shape_tensor", shape=[2], dtype="float32")
+                tensor.full(shape=shape, dtype="float32", fill_value=1)
+
+            self.assertRaises(TypeError, test_shape_tensor_dtype)
+
+            def test_shape_tensor_list_dtype():
+                shape = fluid.data(
+                    name="shape_tensor_list", shape=[1], dtype="bool")
+                tensor.full(shape=[shape, 2], dtype="float32", fill_value=1)
+
+            self.assertRaises(TypeError, test_shape_tensor_list_dtype)
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/tensor/__init__.py

@@ -29,7 +29,7 @@
 # from .creation import zeros_like   #DEFINE_ALIAS
 # from .creation import arrange   #DEFINE_ALIAS
 # from .creation import eye   #DEFINE_ALIAS
-# from .creation import full   #DEFINE_ALIAS
+from .creation import full  #DEFINE_ALIAS
 # from .creation import linspace   #DEFINE_ALIAS
 # from .creation import full_like   #DEFINE_ALIAS
 # from .creation import triu   #DEFINE_ALIAS

python/paddle/tensor/creation.py

@@ -13,24 +13,103 @@
 # limitations under the License.
 
 # TODO: define functions to get create a tensor  
-# __all__ = ['create_tensor', 
-#            'create_lod_tensor', 
-#            'create_random_int_lodtensor',
-#            'crop_tensor', 
-#            'diag', 'eye', 
-#            'fill_constant', 
-#            'get_tensor_from_selected_rows', 
-#            'linspace', 
-#            'ones', 
-#            'ones_like', 
-#            'range', 
-#            'zeros', 
-#            'zeros_like', 
-#            'arrange',
-#            'eye',
-#            'full',
-#            'linspace',
-#            'full_like',
-#            'triu',
-#            'tril',
-#            'meshgrid']
+
+from __future__ import print_function
+from ..fluid.framework import Variable
+from ..fluid.initializer import Constant
+from ..fluid.layer_helper import LayerHelper
+from ..fluid.data_feeder import check_variable_and_dtype, check_type, check_dtype, convert_dtype
+from ..fluid.framework import convert_np_dtype_to_dtype_, in_dygraph_mode, _varbase_creator, device_guard
+from ..fluid.layers import fill_constant
+
+__all__ = [
+    'create_tensor',
+    #            'create_lod_tensor', 
+    #            'create_random_int_lodtensor',
+    #            'crop_tensor', 
+    #            'diag', 'eye', 
+    #            'fill_constant', 
+    #            'get_tensor_from_selected_rows', 
+    #            'linspace', 
+    #            'ones', 
+    #            'ones_like', 
+    #            'range', 
+    #            'zeros', 
+    #            'zeros_like', 
+    #            'arrange',
+    #            'eye',
+    'full',
+    #            'linspace',
+    #            'full_like',
+    #            'triu',
+    #            'tril',
+    #            'meshgrid'
+]
+
+
+def full(shape,
+         fill_value,
+         out=None,
+         dtype=None,
+         device=None,
+         stop_gradient=True,
+         name=None):
+    """
+    This function return a Tensor with the `fill_value` which size is same as `shape`
+    
+    Args:
+        shape(list|tuple|Variable): Shape of the Tensor to be created.
+                The data type is ``int32`` or ``int64`` . If ``shape`` is a list or tuple,
+                the elements of it should be integers or Tensors with shape [1].
+                If ``shape`` is an Variable, it should be an 1-D Tensor .
+        value(float): The constant value used to initialize the Tensor to be created.
+        out(Variable, optional): Optional output which can be any created 
+            Variable that meets the requirements to store the result of operation.
+            if out is None, a new Varibale will be create to store the result.
+        dtype(np.dtype|core.VarDesc.VarType|str, optional): Data type of the output tensor
+            which can be float16, float32, float64, int32, int64, if dytpe is `None`, the data
+            type of created tensor is `float32`
+        device(str, optional): This parameter specifies that the Tensor is created 
+            on the GPU or CPU.
+        stop_gradient(bool, optional): Indicating if we stop gradient from current(out) Variable,
+            default value is True.
+        name(str, optional): The default value is None.  Normally there is no need for user to set this
+            property.  For more information, please refer to :ref:`api_guide_Name`.
+    
+    Examples:
+        .. code-block:: python
+
+          import paddle.tensor as tensor
+          import paddle.fluid as fluid
+
+          data1 = tensor.full(shape=[2,1], full_value=0, dtype='int64') # data1=[[0],[0]]
+          data2 = tensor.full(shape=[2,1], full_value=5, dtype='int64', device='gpu') # data2=[[5],[5]]
+
+          # attr shape is a list which contains Variable Tensor.
+          positive_2 = fluid.layers.fill_constant([1], "int32", 2)
+          data3 = tensor.full(shape=[1, positive_2], dtype='float32', full_value=1.5) # data3=[1.5, 1.5]
+
+          # attr shape is an Variable Tensor.
+          shape = fluid.layers.fill_constant([1,2], "int32", 2) # shape=[2,2]
+          data4 = tensor.full(shape=shape, dtype='bool', full_value=True) # data4=[[True,True],[True,True]]
+    """
+
+    helper = LayerHelper("full", **locals())
+
+    if dtype is None:
+        dtype = 'float32'
+
+    check_dtype(dtype, 'create data type',
+                ['bool', 'float16', 'float32', 'float64', 'int32', 'int64'],
+                'full')
+    check_type(shape, 'shape', (Variable, list, tuple), 'full')
+
+    if out is None:
+        out = helper.create_variable_for_type_inference(dtype=dtype)
+
+    out.stop_gradient = stop_gradient
+
+    with device_guard(device):
+        out = fill_constant(shape=shape, dtype=dtype, value=fill_value, out=out)
+
+    return out

python/setup.py.in

@@ -113,6 +113,7 @@ packages=['paddle',
           'paddle.reader',
           'paddle.distributed',
           'paddle.fluid',
+          'paddle.tensor',
           'paddle.fluid.dygraph',
           'paddle.fluid.dygraph.dygraph_to_static',
           'paddle.fluid.proto',