Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fixed get_tensor method for EagerTensor #39414

Merged
merged 3 commits into from
Feb 14, 2022
Merged

Fixed get_tensor method for EagerTensor #39414

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
280e080
Enabled Eager OpTest #1
jim19930609 Feb 9, 2022
9a3e34e
Enabled Eager OpTest #1
jim19930609 Feb 9, 2022
8b2d55c
Fixed get_tensor method for EagerTensor
jim19930609 Feb 10, 2022
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion paddle/fluid/pybind/eager_utils.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -509,7 +509,7 @@ PyObject* ToPyObject(const paddle::framework::proto::VarType& type) {
}

PyObject* ToPyObject(const paddle::framework::LoDTensor* value) {
auto obj = ::pybind11::cast(value, py::return_value_policy::copy);
auto obj = ::pybind11::cast(value, py::return_value_policy::reference);
obj.inc_ref();
return obj.ptr();
}
Expand Down
155 changes: 75 additions & 80 deletions python/paddle/fluid/tests/unittests/test_where_op.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,19 +1,18 @@
#Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Copyright (c) 2022 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
import paddle
Expand All @@ -24,38 +23,39 @@
from paddle.fluid import compiler, Program, program_guard
from paddle.fluid.op import Operator
from paddle.fluid.backward import append_backward
from paddle.fluid.framework import _test_eager_guard


class TestWhereOp(OpTest):
def setUp(self):
self.op_type = "where"
self.op_type = 'where'
self.init_config()
self.inputs = {'Condition': self.cond, 'X': self.x, 'Y': self.y}
self.outputs = {'Out': np.where(self.cond, self.x, self.y)}

def test_check_output(self):
self.check_output()
self.check_output(check_eager=True)

def test_check_grad(self):
self.check_grad(['X', 'Y'], 'Out')
self.check_grad(['X', 'Y'], 'Out', check_eager=True)

def init_config(self):
self.x = np.random.uniform(-3, 5, (100)).astype("float64")
self.y = np.random.uniform(-3, 5, (100)).astype("float64")
self.cond = np.zeros((100)).astype("bool")
self.x = np.random.uniform((-3), 5, 100).astype('float64')
self.y = np.random.uniform((-3), 5, 100).astype('float64')
self.cond = np.zeros(100).astype('bool')


class TestWhereOp2(TestWhereOp):
def init_config(self):
self.x = np.random.uniform(-5, 5, (60, 2)).astype("float64")
self.y = np.random.uniform(-5, 5, (60, 2)).astype("float64")
self.cond = np.ones((60, 2)).astype("bool")
self.x = np.random.uniform((-5), 5, (60, 2)).astype('float64')
self.y = np.random.uniform((-5), 5, (60, 2)).astype('float64')
self.cond = np.ones((60, 2)).astype('bool')


class TestWhereOp3(TestWhereOp):
def init_config(self):
self.x = np.random.uniform(-3, 5, (20, 2, 4)).astype("float64")
self.y = np.random.uniform(-3, 5, (20, 2, 4)).astype("float64")
self.x = np.random.uniform((-3), 5, (20, 2, 4)).astype('float64')
self.y = np.random.uniform((-3), 5, (20, 2, 4)).astype('float64')
self.cond = np.array(np.random.randint(2, size=(20, 2, 4)), dtype=bool)


Expand All @@ -66,15 +66,15 @@ def setUp(self):
def init_data(self):
self.shape = [10, 15]
self.cond = np.array(np.random.randint(2, size=self.shape), dtype=bool)
self.x = np.random.uniform(-2, 3, self.shape).astype(np.float32)
self.y = np.random.uniform(-2, 3, self.shape).astype(np.float32)
self.x = np.random.uniform((-2), 3, self.shape).astype(np.float32)
self.y = np.random.uniform((-2), 3, self.shape).astype(np.float32)
self.out = np.where(self.cond, self.x, self.y)

def ref_x_backward(self, dout):
return np.where(self.cond == True, dout, 0)
return np.where((self.cond == True), dout, 0)

def ref_y_backward(self, dout):
return np.where(self.cond == False, dout, 0)
return np.where((self.cond == False), dout, 0)

def test_api(self, use_cuda=False):
for x_stop_gradient in [False, True]:
Expand All @@ -90,17 +90,17 @@ def test_api(self, use_cuda=False):
y.stop_gradient = y_stop_gradient
result = paddle.where(cond, x, y)
append_backward(layers.mean(result))

for use_cuda in [False, True]:
if use_cuda and not fluid.core.is_compiled_with_cuda():
if (use_cuda and
(not fluid.core.is_compiled_with_cuda())):
break
place = fluid.CUDAPlace(
0) if use_cuda else fluid.CPUPlace()
place = (fluid.CUDAPlace(0)
if use_cuda else fluid.CPUPlace())
exe = fluid.Executor(place)
fetch_list = [result, result.grad_name]
if x_stop_gradient is False:
if (x_stop_gradient is False):
fetch_list.append(x.grad_name)
if y_stop_gradient is False:
if (y_stop_gradient is False):
fetch_list.append(y.grad_name)
out = exe.run(
fluid.default_main_program(),
Expand All @@ -109,13 +109,13 @@ def test_api(self, use_cuda=False):
'y': self.y},
fetch_list=fetch_list)
assert np.array_equal(out[0], self.out)
if x_stop_gradient is False:
if (x_stop_gradient is False):
assert np.array_equal(out[2],
self.ref_x_backward(out[1]))
if y.stop_gradient is False:
if (y.stop_gradient is False):
assert np.array_equal(
out[3], self.ref_y_backward(out[1]))
elif y.stop_gradient is False:
elif (y.stop_gradient is False):
assert np.array_equal(out[2],
self.ref_y_backward(out[1]))

Expand All @@ -124,54 +124,46 @@ def test_api_broadcast(self, use_cuda=False):
with fluid.program_guard(main_program):
x = fluid.layers.data(name='x', shape=[4, 1], dtype='float32')
y = fluid.layers.data(name='y', shape=[4, 2], dtype='float32')
x_i = np.array([[0.9383, 0.1983, 3.2, 1.2]]).astype("float32")
y_i = np.array([[1.0, 1.0, 1.0, 1.0],
[1.0, 1.0, 1.0, 1.0]]).astype("float32")
result = paddle.where(x > 1, x=x, y=y)

x_i = np.array([[0.9383, 0.1983, 3.2, 1.2]]).astype('float32')
y_i = np.array(
[[1.0, 1.0, 1.0, 1.0], [1.0, 1.0, 1.0, 1.0]]).astype('float32')
result = paddle.where((x > 1), x=x, y=y)
for use_cuda in [False, True]:
if use_cuda and not fluid.core.is_compiled_with_cuda():
if (use_cuda and (not fluid.core.is_compiled_with_cuda())):
return
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
place = (fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace())
exe = fluid.Executor(place)
out = exe.run(fluid.default_main_program(),
feed={'x': x_i,
'y': y_i},
fetch_list=[result])
assert np.array_equal(out[0], np.where(x_i > 1, x_i, y_i))
assert np.array_equal(out[0], np.where((x_i > 1), x_i, y_i))

def __test_where_with_broadcast_static(self, cond_shape, x_shape, y_shape):
paddle.enable_static()

main_program = Program()
with fluid.program_guard(main_program):
cond = fluid.layers.data(
name='cond', shape=cond_shape, dtype='bool')
x = fluid.layers.data(name='x', shape=x_shape, dtype='float32')
y = fluid.layers.data(name='y', shape=y_shape, dtype='float32')

cond_data_tmp = np.random.random(size=cond_shape).astype("float32")
cond_data = cond_data_tmp < 0.3
x_data = np.random.random(size=x_shape).astype("float32")
y_data = np.random.random(size=y_shape).astype("float32")

cond_data_tmp = np.random.random(size=cond_shape).astype('float32')
cond_data = (cond_data_tmp < 0.3)
x_data = np.random.random(size=x_shape).astype('float32')
y_data = np.random.random(size=y_shape).astype('float32')
result = paddle.where(condition=cond, x=x, y=y)

for use_cuda in [False, True]:
if use_cuda and not fluid.core.is_compiled_with_cuda():
if (use_cuda and (not fluid.core.is_compiled_with_cuda())):
return
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()

place = (fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace())
exe = fluid.Executor(place)
out = exe.run(
fluid.default_main_program(),
feed={'cond': cond_data,
'x': x_data,
'y': y_data},
fetch_list=[result])

expect = np.where(cond_data, x_data, y_data)

assert np.array_equal(out[0], expect)

def test_static_api_broadcast_1(self):
Expand All @@ -198,28 +190,24 @@ def test_static_api_broadcast_4(self):
b_shape = [2, 2, 4]
self.__test_where_with_broadcast_static(cond_shape, a_shape, b_shape)

# @Note Now, maybe not compatibility with old version
def test_static_api_broadcast_5(self):
cond_shape = [3, 2, 2, 4]
a_shape = [2, 2, 4]
b_shape = [2, 2, 4]
self.__test_where_with_broadcast_static(cond_shape, a_shape, b_shape)

# @Note Now, maybe not compatibility with old version
def test_static_api_broadcast_6(self):
cond_shape = [2, 2, 4]
a_shape = [2, 2, 1]
b_shape = [2, 2, 1]
self.__test_where_with_broadcast_static(cond_shape, a_shape, b_shape)

# @Note Now, maybe not compatibility with old version
def test_static_api_broadcast_7(self):
cond_shape = [2, 2, 4]
a_shape = [2, 1, 4]
b_shape = [2, 1, 4]
self.__test_where_with_broadcast_static(cond_shape, a_shape, b_shape)

# @Note Now, maybe not compatibility with old version
def test_static_api_broadcast_8(self):
cond_shape = [3, 2, 2, 4]
a_shape = [2, 2, 1]
Expand All @@ -230,9 +218,9 @@ def test_static_api_broadcast_8(self):
class TestWhereDygraphAPI(unittest.TestCase):
def test_api(self):
with fluid.dygraph.guard():
x_i = np.array([0.9383, 0.1983, 3.2, 1.2]).astype("float64")
y_i = np.array([1.0, 1.0, 1.0, 1.0]).astype("float64")
cond_i = np.array([False, False, True, True]).astype("bool")
x_i = np.array([0.9383, 0.1983, 3.2, 1.2]).astype('float64')
y_i = np.array([1.0, 1.0, 1.0, 1.0]).astype('float64')
cond_i = np.array([False, False, True, True]).astype('bool')
x = fluid.dygraph.to_variable(x_i)
y = fluid.dygraph.to_variable(y_i)
cond = fluid.dygraph.to_variable(cond_i)
Expand All @@ -242,15 +230,12 @@ def test_api(self):
def __test_where_with_broadcast_dygraph(self, cond_shape, a_shape, b_shape):
with fluid.dygraph.guard():
cond_tmp = paddle.rand(cond_shape)
cond = cond_tmp < 0.3
cond = (cond_tmp < 0.3)
a = paddle.rand(a_shape)
b = paddle.rand(b_shape)

result = paddle.where(cond, a, b)
result = result.numpy()

expect = np.where(cond, a, b)

self.assertTrue(np.array_equal(expect, result))

def test_dygraph_api_broadcast_1(self):
Expand All @@ -277,28 +262,24 @@ def test_dygraph_api_broadcast_4(self):
b_shape = [2, 2, 4]
self.__test_where_with_broadcast_dygraph(cond_shape, a_shape, b_shape)

# @Note Now, maybe not compatibility with old version
def test_dygraph_api_broadcast_5(self):
cond_shape = [3, 2, 2, 4]
a_shape = [2, 2, 4]
b_shape = [2, 2, 4]
self.__test_where_with_broadcast_dygraph(cond_shape, a_shape, b_shape)

# @Note Now, maybe not compatibility with old version
def test_dygraph_api_broadcast_6(self):
cond_shape = [2, 2, 4]
a_shape = [2, 2, 1]
b_shape = [2, 2, 1]
self.__test_where_with_broadcast_dygraph(cond_shape, a_shape, b_shape)

# @Note Now, maybe not compatibility with old version
def test_dygraph_api_broadcast_7(self):
cond_shape = [2, 2, 4]
a_shape = [2, 1, 4]
b_shape = [2, 1, 4]
self.__test_where_with_broadcast_dygraph(cond_shape, a_shape, b_shape)

# @Note Now, maybe not compatibility with old version
def test_dygraph_api_broadcast_8(self):
cond_shape = [3, 2, 2, 4]
a_shape = [2, 2, 1]
Expand All @@ -308,40 +289,50 @@ def test_dygraph_api_broadcast_8(self):
def test_where_condition(self):
data = np.array([[True, False], [False, True]])
with program_guard(Program(), Program()):
x = fluid.layers.data(name='x', shape=[-1, 2])
x = fluid.layers.data(name='x', shape=[(-1), 2])
y = paddle.where(x)
self.assertEqual(type(y), tuple)
self.assertEqual(len(y), 2)
z = fluid.layers.concat(list(y), axis=1)
exe = fluid.Executor(fluid.CPUPlace())

res, = exe.run(feed={'x': data},
fetch_list=[z.name],
return_numpy=False)
(res, ) = exe.run(feed={'x': data},
fetch_list=[z.name],
return_numpy=False)
expect_out = np.array([[0, 0], [1, 1]])
self.assertTrue(np.allclose(expect_out, np.array(res)))

data = np.array([True, True, False])
with program_guard(Program(), Program()):
x = fluid.layers.data(name='x', shape=[-1])
x = fluid.layers.data(name='x', shape=[(-1)])
y = paddle.where(x)
self.assertEqual(type(y), tuple)
self.assertEqual(len(y), 1)
z = fluid.layers.concat(list(y), axis=1)
exe = fluid.Executor(fluid.CPUPlace())
res, = exe.run(feed={'x': data},
fetch_list=[z.name],
return_numpy=False)
(res, ) = exe.run(feed={'x': data},
fetch_list=[z.name],
return_numpy=False)
expect_out = np.array([[0], [1]])
self.assertTrue(np.allclose(expect_out, np.array(res)))

def test_eager(self):
with _test_eager_guard():
self.test_api()
self.test_dygraph_api_broadcast_1()
self.test_dygraph_api_broadcast_2()
self.test_dygraph_api_broadcast_3()
self.test_dygraph_api_broadcast_4()
self.test_dygraph_api_broadcast_5()
self.test_dygraph_api_broadcast_6()
self.test_dygraph_api_broadcast_7()
self.test_dygraph_api_broadcast_8()


class TestWhereOpError(unittest.TestCase):
def test_errors(self):
with program_guard(Program(), Program()):
x_i = np.array([0.9383, 0.1983, 3.2, 1.2]).astype("float64")
y_i = np.array([1.0, 1.0, 1.0, 1.0]).astype("float64")
cond_i = np.array([False, False, True, True]).astype("bool")
x_i = np.array([0.9383, 0.1983, 3.2, 1.2]).astype('float64')
y_i = np.array([1.0, 1.0, 1.0, 1.0]).astype('float64')
cond_i = np.array([False, False, True, True]).astype('bool')

def test_Variable():
paddle.where(cond_i, x_i, y_i)
Expand All @@ -360,10 +351,14 @@ def test_value_error(self):
with fluid.dygraph.guard():
cond_shape = [2, 2, 4]
cond_tmp = paddle.rand(cond_shape)
cond = cond_tmp < 0.3
cond = (cond_tmp < 0.3)
a = paddle.rand(cond_shape)
self.assertRaises(ValueError, paddle.where, cond, a)

def test_eager(self):
with _test_eager_guard():
self.test_value_error()


if __name__ == '__main__':
if (__name__ == '__main__'):
unittest.main()
Loading