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Migrate 4 APIs about array to paddle.tensor.* (#29565)

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4 APIs: array_length, array_read, array_write, create_array
revert-31562-mean
liym27 4 years ago committed by GitHub
parent 1cbb282d77
commit 0cc42e34c6
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GPG Key ID: 4AEE18F83AFDEB23
4 changed files with 221 additions and 11 deletions
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44
python/paddle/fluid/tests/unittests/test_array_read_write_op.py
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@ -15,6 +15,8 @@
from __future__ import print_function
import unittest
import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
import paddle.fluid.layers as layers
@ -127,17 +129,53 @@ class TestArrayReadWrite(unittest.TestCase):
class TestArrayReadWriteOpError(unittest.TestCase):
def test_errors(self):
def _test_errors(self, use_fluid_api=True):
if use_fluid_api:
with program_guard(Program(), Program()):
#for ci coverage
x1 = numpy.random.randn(2, 4).astype('int32')
x2 = fluid.layers.fill_constant(shape=[1], dtype='int32', value=1)
x2 = fluid.layers.fill_constant(
shape=[1], dtype='int32', value=1)
x3 = numpy.random.randn(2, 4).astype('int32')
self.assertRaises(
TypeError, fluid.layers.array_read, array=x1, i=x2)
self.assertRaises(
TypeError, fluid.layers.array_write, array=x1, i=x2, out=x3)
else:
with program_guard(Program(), Program()):
x1 = numpy.random.randn(2, 4).astype('int32')
x2 = paddle.ones(shape=[1], dtype='int32')
x3 = numpy.random.randn(2, 4).astype('int32')
self.assertRaises(
TypeError, paddle.tensor.array_read, array=x1, i=x2)
self.assertRaises(
TypeError,
paddle.tensor.array_write,
array=x1,
i=x2,
out=x3)
def test_fluid_api(self):
self._test_errors(use_fluid_api=True)
def test_paddle_api(self):
self._test_errors(use_fluid_api=False)
class TestArrayReadWriteApi(unittest.TestCase):
def test_api(self):
paddle.disable_static()
arr = paddle.tensor.create_array(dtype="float32")
x = paddle.full(shape=[1, 3], fill_value=5, dtype="float32")
i = paddle.zeros(shape=[1], dtype="int32")
arr = paddle.tensor.array_write(x, i, array=arr)
item = paddle.tensor.array_read(arr, i)
self.assertTrue(numpy.allclose(x.numpy(), item.numpy()))
paddle.enable_static()
if __name__ == '__main__':

17
python/paddle/fluid/tests/unittests/test_lod_array_length_op.py
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@ -15,6 +15,8 @@
from __future__ import print_function
import unittest
import paddle
import paddle.fluid.layers as layers
from paddle.fluid.executor import Executor
import paddle.fluid.core as core
@ -44,5 +46,20 @@ class TestLoDArrayLengthOpError(unittest.TestCase):
self.assertRaises(TypeError, fluid.layers.array_length, array=x1)
class TestArrayLengthApi(unittest.TestCase):
def test_api(self):
paddle.disable_static()
arr = paddle.tensor.create_array(dtype='float32')
x = paddle.full(shape=[3, 3], fill_value=5, dtype="float32")
i = paddle.zeros(shape=[1], dtype="int32")
arr = paddle.tensor.array_write(x, i, array=arr)
arr_len = paddle.tensor.array_length(arr)
self.assertEqual(arr_len, 1)
paddle.enable_static()
if __name__ == '__main__':
unittest.main()

5
python/paddle/tensor/__init__.py
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@ -203,3 +203,8 @@ from .stat import median #DEFINE_ALIAS
# from .tensor import LoDTensor #DEFINE_ALIAS
# from .tensor import LoDTensorArray #DEFINE_ALIAS
from .to_string import set_printoptions #DEFINE_ALIAS
from .array import array_length #DEFINE_ALIAS
from .array import array_read #DEFINE_ALIAS
from .array import array_write #DEFINE_ALIAS
from .array import create_array #DEFINE_ALIAS

150
python/paddle/tensor/array.py
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@ -0,0 +1,150 @@
# Copyright (c) 2020 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.
# Define functions about array.
from ..fluid import layers
def array_length(array):
"""
This OP is used to get the length of the input array.
Args:
array (list|Tensor): The input array that will be used to compute the length. In dynamic mode, ``array`` is a Python list. But in static mode, array is a Tensor whose VarType is LOD_TENSOR_ARRAY.
Returns:
Tensor: 1-D Tensor with shape [1], which is the length of array.
Examples:
.. code-block:: python
import paddle
arr = paddle.tensor.create_array(dtype='float32')
x = paddle.full(shape=[3, 3], fill_value=5, dtype="float32")
i = paddle.zeros(shape=[1], dtype="int32")
arr = paddle.tensor.array_write(x, i, array=arr)
arr_len = paddle.tensor.array_length(arr)
print(arr_len) # 1
"""
return layers.array_length(array)
def array_read(array, i):
"""
This OP is used to read data at the specified position from the input array.
Case:
.. code-block:: text
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 (list|Tensor): The input array. In dynamic mode, ``array`` is a Python list. But in static mode, array is a Tensor whose ``VarType`` is ``LOD_TENSOR_ARRAY``.
i (Tensor): 1-D Tensor, whose shape is [1] and dtype is int64. It represents the
specified read position of ``array``.
Returns:
Tensor: A Tensor that is read at the specified position of ``array``.
Examples:
.. code-block:: python
import paddle
arr = paddle.tensor.create_array(dtype="float32")
x = paddle.full(shape=[1, 3], fill_value=5, dtype="float32")
i = paddle.zeros(shape=[1], dtype="int32")
arr = paddle.tensor.array_write(x, i, array=arr)
item = paddle.tensor.array_read(arr, i)
print(item) # [[5., 5., 5.]]
"""
return layers.array_read(array, i)
def array_write(x, i, array=None):
"""
This OP writes the input ``x`` into the i-th position of the ``array`` returns the modified array.
If ``array`` is none, a new array will be created and returned.
Args:
x (Tensor): The input data to be written into array. It's multi-dimensional
Tensor or LoDTensor. Data type: float32, float64, int32, int64 and bool.
i (Tensor): 1-D Tensor with shape [1], which represents the position into which
``x`` is written.
array (list|Tensor, optional): The array into which ``x`` is written. The default value is None,
when a new array will be created and returned as a result. In dynamic mode, ``array`` is a Python list.
But in static mode, array is a Tensor whose ``VarType`` is ``LOD_TENSOR_ARRAY``.
Returns:
list|Tensor: The input ``array`` after ``x`` is written into.
Examples:
.. code-block:: python
import paddle
arr = paddle.tensor.create_array(dtype="float32")
x = paddle.full(shape=[1, 3], fill_value=5, dtype="float32")
i = paddle.zeros(shape=[1], dtype="int32")
arr = paddle.tensor.array_write(x, i, array=arr)
item = paddle.tensor.array_read(arr, i)
print(item) # [[5., 5., 5.]]
"""
return layers.array_write(x, i, array)
def create_array(dtype):
"""
This OP creates an array. It is used as the input of :ref:`api_paddle_tensor_array_array_read` and
:ref:`api_paddle_tensor_array_array_write`.
Args:
dtype (str): The data type of the elements in the array. Support data type: float32, float64, int32, int64 and bool.
Returns:
list|Tensor: An empty array. In dynamic mode, ``array`` is a Python list. But in static mode, array is a Tensor
whose ``VarType`` is ``LOD_TENSOR_ARRAY``.
Examples:
.. code-block:: python
import paddle
arr = paddle.tensor.create_array(dtype="float32")
x = paddle.full(shape=[1, 3], fill_value=5, dtype="float32")
i = paddle.zeros(shape=[1], dtype="int32")
arr = paddle.tensor.array_write(x, i, array=arr)
item = paddle.tensor.array_read(arr, i)
print(item) # [[5., 5., 5.]]
"""
return layers.create_array(dtype)
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