提交 f1823141 编写于 作者: Z zhouwei25 提交者: liuwei1031

fix English Doc of API:layers.array_read/array_write/array_length (#20345)

* fix English Doc of API:layers.py_func/sum, test=document_fix

* fix English Doc of API:layers.array_read/array_write/array_length,test=develop test=document_fix
上级 9f4a32fb
......@@ -347,7 +347,7 @@ paddle.fluid.layers.Switch.__init__ (ArgSpec(args=['self', 'name'], varargs=None
paddle.fluid.layers.Switch.case (ArgSpec(args=['self', 'condition'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.layers.Switch.default (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.layers.increment (ArgSpec(args=['x', 'value', 'in_place'], varargs=None, keywords=None, defaults=(1.0, True)), ('document', 'f88b5787bb80ae6b8bf513a70dabbdc1'))
paddle.fluid.layers.array_write (ArgSpec(args=['x', 'i', 'array'], varargs=None, keywords=None, defaults=(None,)), ('document', '3f913b5069ad40bd85d89b33e4aa5939'))
paddle.fluid.layers.array_write (ArgSpec(args=['x', 'i', 'array'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd357f71a280bf06aab4c79de9bd4facf'))
paddle.fluid.layers.create_array (ArgSpec(args=['dtype'], varargs=None, keywords=None, defaults=None), ('document', '556de793fdf24d515f3fc91260e2c048'))
paddle.fluid.layers.less_than (ArgSpec(args=['x', 'y', 'force_cpu', 'cond'], varargs=None, keywords=None, defaults=(None, None)), ('document', '04af32422c3a3d8f6040aeb406c82768'))
paddle.fluid.layers.less_equal (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '04e5623dd39b4437b9b08e0ce11071ca'))
......@@ -355,8 +355,8 @@ paddle.fluid.layers.greater_than (ArgSpec(args=['x', 'y', 'cond'], varargs=None,
paddle.fluid.layers.greater_equal (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '44bdacd11299d72c0a52d2181e7ae6ca'))
paddle.fluid.layers.equal (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '788aa651e8b9fec79d16931ef3a33e90'))
paddle.fluid.layers.not_equal (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '8b76aaac4ba7cf9111750b9c2c9418cb'))
paddle.fluid.layers.array_read (ArgSpec(args=['array', 'i'], varargs=None, keywords=None, defaults=None), ('document', 'caf0d94349cdc28e1bda3b8a19411ac0'))
paddle.fluid.layers.array_length (ArgSpec(args=['array'], varargs=None, keywords=None, defaults=None), ('document', '6f24a9b872027634ad758ea2826c9727'))
paddle.fluid.layers.array_read (ArgSpec(args=['array', 'i'], varargs=None, keywords=None, defaults=None), ('document', 'b75c821cc1d22355c3c17e7bdf509510'))
paddle.fluid.layers.array_length (ArgSpec(args=['array'], varargs=None, keywords=None, defaults=None), ('document', 'c90d305395eb44e6dc772fab24ff2ef5'))
paddle.fluid.layers.IfElse ('paddle.fluid.layers.control_flow.IfElse', ('document', '720054043e55273224682fdb6b9ad13b'))
paddle.fluid.layers.IfElse.__init__ (ArgSpec(args=['self', 'cond', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.layers.IfElse.false_block (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
......
......@@ -1057,31 +1057,53 @@ def increment(x, value=1.0, in_place=True):
def array_write(x, i, array=None):
"""
This function writes the given input variable to the specified position
indicating by the arrary index to an output LOD_TENSOR_ARRAY. If the
output LOD_TENSOR_ARRAY is not given(None), a new one will be created and
returned.
This OP writes the input ``x`` into the i-th position of the ``array``
:ref:`api_fluid_LoDTensorArray` and returns the modified array.
If ``array`` is none, a new LoDTensorArray will be created and returned.
This OP is often used together with :ref:`api_fluid_layers_array_read` OP.
Args:
x (Variable|list): The input tensor from which the data will be read.
i (Variable|list): The index of the output LOD_TENSOR_ARRAY, pointing to
the position to which the input tensor will be
written.
array (Variable|list): The output LOD_TENSOR_ARRAY to which the input
tensor will be written. If this parameter is
NONE, a new LOD_TENSOR_ARRAY will be created and
returned.
x (Variable): The input data to be written into array. It's multi-dimensional
Tensor or LoDTensor. Data type: float32, float64, int32, int64.
i (Variable): 1-D Tensor with shape [1], which represents the position into which
``x`` is written. Data type: int64.
array (LoDTensorArray, optional): The LoDTensorArray into which ``x`` is written.
The default value is None, when a new LoDTensorArray will be created and returned
as a result.
Returns:
Variable: The output LOD_TENSOR_ARRAY where the input tensor is written.
Variable: The input ``array`` after ``x`` is written into.
Examples:
.. code-block:: python
import paddle.fluid as fluid
tmp = fluid.layers.zeros(shape=[10], dtype='int32')
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=10)
arr = fluid.layers.array_write(tmp, i=i)
import paddle.fluid as fluid
tmp = fluid.layers.fill_constant(shape=[3, 2], dtype='int64', value=5)
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=10)
# Write tmp into the position of arr with subscript 10 and return arr.
arr = fluid.layers.array_write(tmp, i=i)
# Now, arr is a LoDTensorArray with length 11. We can use array_read OP to read
# the data at subscript 10 and print it out.
item = fluid.layers.array_read(arr, i=i)
input = fluid.layers.Print(item, message="The content of i-th LoDTensor:")
main_program = fluid.default_main_program()
exe = fluid.Executor(fluid.CPUPlace())
exe.run(main_program)
# The printed result is:
# 1570533133 The content of i-th LoDTensor: The place is:CPUPlace
# Tensor[array_read_0.tmp_0]
# shape: [3,2,]
# dtype: l
# data: 5,5,5,5,5,5,
# the output is 2-D Tensor with shape [3,2], which is tmp above.
# dtype is the corresponding C++ data type, which may vary in different environments.
# Eg: if the data type of tensor is int64, then the corresponding C++ data type is int64_t,
# so the dtype value is typeid(int64_t).Name(), which is 'x' on MacOS, 'l' on Linux,
# and '__int64' on Windows. They both represent 64-bit integer variables.
"""
helper = LayerHelper('array_write', **locals())
if array is None:
......@@ -1365,37 +1387,64 @@ def not_equal(x, y, cond=None):
def array_read(array, i):
"""
This function performs the operation to read the data in as an
LOD_TENSOR_ARRAY.
.. code-block:: text
Given:
array = [0.6, 0.1, 0.3, 0.1]
And:
i = 2
Then:
output = 0.3
This OP is used to read data at the specified position from the input array
:ref:`api_fluid_LoDTensorArray` . ``array`` is the input array and ``i``
is the specified read position. This OP is often used together with
:ref:`api_fluid_layers_array_write` OP.
Case 1:
::
Input:
The shape of first three tensors are [1], and that of the last one is [1,2]:
array = ([0.6], [0.1], [0.3], [0.4, 0.2])
And:
i = [3]
Output:
output = [0.4, 0.2]
Args:
array (Variable|list): The input tensor that store data to be read.
i (Variable|list): The index of the data to be read from input array.
array (LoDTensorArray): The input LoDTensorArray.
i (Variable): 1-D Tensor, whose shape is [1] and dtype is int64. It represents the
specified read position of ``array``.
Returns:
Variable: The tensor type variable that has the data written to it.
Variable: The LoDTensor or Tensor that is read at the specified position of ``array``.
Examples:
.. code-block:: python
import paddle.fluid as fluid
array = fluid.layers.create_array(dtype='float32')
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=10)
item = fluid.layers.array_read(array, i)
# First we're going to create a LoDTensorArray, then we're going to write the Tensor into
# the specified position, and finally we're going to read the Tensor at that position.
import paddle.fluid as fluid
arr = fluid.layers.create_array(dtype='float32')
tmp = fluid.layers.fill_constant(shape=[3, 2], dtype='int64', value=5)
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=10)
# tmp is the Tensor with shape [3,2], and if we write it into the position with subscript 10
# of the empty-array: arr, then the length of arr becomes 11.
arr = fluid.layers.array_write(tmp, i, array=arr)
# Read the data of the position with subscript 10.
item = fluid.layers.array_read(arr, i)
# You can print out the data via executor.
input = fluid.layers.Print(item, message="The LoDTensor of the i-th position:")
main_program = fluid.default_main_program()
exe = fluid.Executor(fluid.CPUPlace())
exe.run(main_program)
# The printed result is:
# 1569588169 The LoDTensor of the i-th position: The place is:CPUPlace
# Tensor[array_read_0.tmp_0]
# shape: [3,2,]
# dtype: l
# data: 5,5,5,5,5,5,
# the output is 2-D Tensor with shape [3,2].
# dtype is the corresponding C++ data type, which may vary in different environments.
# Eg: if the data type of tensor is int64, then the corresponding C++ data type is int64_t,
# so the dtype value is typeid(int64_t).Name(), which is 'x' on MacOS, 'l' on Linux,
# and '__int64' on Windows. They both represent 64-bit integer variables.
"""
helper = LayerHelper('array_read', **locals())
if not isinstance(
......@@ -1450,29 +1499,48 @@ def shrink_memory(x, i, table):
def array_length(array):
"""
**Get the Length of Input LoDTensorArray**
This function performs the operation to find the length of the input
LOD_TENSOR_ARRAY.
Related API: array_read, array_write, While.
This OP is used to get the length of the input array :ref:`api_fluid_LoDTensorArray` .
It can be used together with :ref:`api_fluid_layers_array_read` , :ref:`api_fluid_layers_array_write` ,
:ref:`api_fluid_layers_While` OP to traverse, read and wirte LoDTensorArray.
Args:
array (LOD_TENSOR_ARRAY): The input array that will be used
to compute the length.
array (LoDTensorArray): The input array that will be used to compute the length.
Returns:
Variable: The length of the input LoDTensorArray.
Variable: 1-D Tensor with shape [1], which is the length of array. Datatype: int64.
Examples:
.. code-block:: python
import paddle.fluid as fluid
tmp = fluid.layers.zeros(shape=[10], dtype='int32')
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=10)
arr = fluid.layers.array_write(tmp, i=i)
arr_len = fluid.layers.array_length(arr)
import paddle.fluid as fluid
tmp = fluid.layers.zeros(shape=[10], dtype='int32')
i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=10)
# tmp is 1-D Tensor with shape [10]. We write tmp into arr on subscript 10,
# then the length of arr becomes 11.
arr = fluid.layers.array_write(tmp, i=i)
# return the length of arr
arr_len = fluid.layers.array_length(arr)
# You can use executor to print out the length of LoDTensorArray.
input = fluid.layers.Print(arr_len, message="The length of LoDTensorArray:")
main_program = fluid.default_main_program()
exe = fluid.Executor(fluid.CPUPlace())
exe.run(main_program)
# The printed result is:
# 1569576542 The length of LoDTensorArray: The place is:CPUPlace
# Tensor[array_length_0.tmp_0]
# shape: [1,]
# dtype: l
# data: 11,
# 1-D Tensor with shape [1], whose value is 11. It means that the length of LoDTensorArray
# is 11.
# dtype is the corresponding C++ data type, which may vary in different environments.
# Eg: if the data type of tensor is int64, then the corresponding C++ data type is int64_t,
# so the dtype value is typeid(int64_t).Name(), which is 'x' on MacOS, 'l' on Linux,
# and '__int64' on Windows. They both represent 64-bit integer variables.
"""
helper = LayerHelper('array_length', **locals())
tmp = helper.create_variable_for_type_inference(dtype='int64')
......
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