wehub-resource-sync
164 lines
5.1 KiB
Python
164 lines
5.1 KiB
Python
# Copyright (c) 2023 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 unittest
|
|
|
|
import numpy as np
|
|
from get_test_cover_info import (
|
|
XPUOpTestWrapper,
|
|
create_test_class,
|
|
get_xpu_op_support_types,
|
|
)
|
|
from op_test_xpu import XPUOpTest
|
|
|
|
import paddle
|
|
from paddle import base
|
|
|
|
paddle.enable_static()
|
|
|
|
|
|
class XPUTestIndexSampleOP(XPUOpTestWrapper):
|
|
def __init__(self):
|
|
self.op_name = 'index_sample'
|
|
self.use_dynamic_create_class = False
|
|
|
|
class TestIndexSampleOPBase(XPUOpTest):
|
|
def setUp(self):
|
|
self.place = paddle.XPUPlace(0)
|
|
self.init_dtype()
|
|
self.set_case()
|
|
|
|
def set_case(self):
|
|
self.op_type = 'index_sample'
|
|
self.config()
|
|
|
|
xnp = np.random.random(self.x_shape).astype(self.dtype)
|
|
indexnp = np.random.randint(
|
|
low=0, high=self.x_shape[1], size=self.index_shape
|
|
).astype(self.index_type)
|
|
self.inputs = {'X': xnp, 'Index': indexnp}
|
|
index_array = []
|
|
for i in range(self.index_shape[0]):
|
|
for j in indexnp[i]:
|
|
index_array.append(xnp[i, j])
|
|
index_array = np.array(index_array).astype(self.dtype)
|
|
out = np.reshape(index_array, self.index_shape)
|
|
self.outputs = {'Out': out}
|
|
|
|
def init_dtype(self):
|
|
self.dtype = self.in_type
|
|
|
|
def test_check_output(self):
|
|
self.check_output_with_place(self.place)
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad_with_place(self.place, ['X'], 'Out')
|
|
|
|
def config(self):
|
|
self.x_shape = (10, 20)
|
|
self.index_shape = (10, 10)
|
|
self.index_type = "int32"
|
|
|
|
class XPUTestIndexSample1(TestIndexSampleOPBase):
|
|
def config(self):
|
|
self.x_shape = (100, 1)
|
|
self.index_shape = (100, 1)
|
|
self.index_type = "int32"
|
|
|
|
class XPUTestIndexSample2(TestIndexSampleOPBase):
|
|
def config(self):
|
|
self.x_shape = (100, 1)
|
|
self.index_shape = (100, 1)
|
|
self.index_type = "int64"
|
|
|
|
class XPUTestIndexSample3(TestIndexSampleOPBase):
|
|
def config(self):
|
|
self.x_shape = (10, 100)
|
|
self.index_shape = (10, 10)
|
|
self.index_type = "int64"
|
|
|
|
class XPUTestIndexSample4(TestIndexSampleOPBase):
|
|
def config(self):
|
|
self.x_shape = (10, 100)
|
|
self.index_shape = (10, 10)
|
|
self.index_type = "int32"
|
|
|
|
class XPUTestIndexSample5(TestIndexSampleOPBase):
|
|
def config(self):
|
|
self.x_shape = (10, 128)
|
|
self.index_shape = (10, 64)
|
|
self.index_type = "int64"
|
|
|
|
class XPUTestIndexSample6(TestIndexSampleOPBase):
|
|
def config(self):
|
|
self.x_shape = (10, 128)
|
|
self.index_shape = (10, 64)
|
|
self.index_type = "int32"
|
|
|
|
|
|
class TestIndexSampleShape(unittest.TestCase):
|
|
def test_shape(self):
|
|
paddle.enable_static()
|
|
# create x value
|
|
x_shape = (2, 5)
|
|
x_np = np.random.random(x_shape).astype('float32')
|
|
|
|
# create index value
|
|
index_shape = (2, 3)
|
|
index_type = "int32"
|
|
index_np = np.random.randint(
|
|
low=0, high=x_shape[1], size=index_shape
|
|
).astype(index_type)
|
|
|
|
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 = base.XPUPlace(0)
|
|
exe = base.Executor(place=place)
|
|
exe.run(base.default_startup_program())
|
|
|
|
feed = {'x': x_np, 'index': index_np}
|
|
res = exe.run(feed=feed, fetch_list=[output])
|
|
|
|
|
|
class TestIndexSampleDynamic(unittest.TestCase):
|
|
def test_result(self):
|
|
with base.dygraph.guard():
|
|
x = paddle.to_tensor(
|
|
[
|
|
[1.0, 2.0, 3.0, 4.0],
|
|
[5.0, 6.0, 7.0, 8.0],
|
|
[9.0, 10.0, 11.0, 12.0],
|
|
],
|
|
dtype='float32',
|
|
)
|
|
index = paddle.to_tensor(
|
|
[[0, 1, 2], [1, 2, 3], [0, 0, 0]], dtype='int32'
|
|
)
|
|
out_z1 = paddle.index_sample(x, index)
|
|
|
|
except_output = np.array(
|
|
[[1.0, 2.0, 3.0], [6.0, 7.0, 8.0], [9.0, 9.0, 9.0]]
|
|
)
|
|
assert out_z1.numpy().all() == except_output.all()
|
|
|
|
|
|
support_types = get_xpu_op_support_types('index_sample')
|
|
for stype in support_types:
|
|
create_test_class(globals(), XPUTestIndexSampleOP, stype)
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|