wehub-resource-sync
430 lines
15 KiB
Python
430 lines
15 KiB
Python
# 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.
|
|
|
|
import unittest
|
|
|
|
import paddle
|
|
from paddle.base.framework import in_pir_mode
|
|
from paddle.sparse.binary import is_same_shape
|
|
|
|
|
|
class TestSparseIsSameShapeAPI(unittest.TestCase):
|
|
"""
|
|
test paddle.sparse.is_same_shape
|
|
"""
|
|
|
|
def setUp(self):
|
|
self.shapes = [[2, 5, 8], [3, 4]]
|
|
self.tensors = [
|
|
paddle.rand(self.shapes[0]),
|
|
paddle.rand(self.shapes[0]),
|
|
paddle.rand(self.shapes[1]),
|
|
]
|
|
self.sparse_dim = 2
|
|
|
|
def test_dense_dense(self):
|
|
self.assertTrue(is_same_shape(self.tensors[0], self.tensors[1]))
|
|
self.assertFalse(is_same_shape(self.tensors[0], self.tensors[2]))
|
|
self.assertFalse(is_same_shape(self.tensors[1], self.tensors[2]))
|
|
|
|
def test_dense_csr(self):
|
|
self.assertTrue(
|
|
is_same_shape(self.tensors[0], self.tensors[1].to_sparse_csr())
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(self.tensors[0], self.tensors[2].to_sparse_csr())
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(self.tensors[1], self.tensors[2].to_sparse_csr())
|
|
)
|
|
|
|
def test_dense_coo(self):
|
|
self.assertTrue(
|
|
is_same_shape(
|
|
self.tensors[0], self.tensors[1].to_sparse_coo(self.sparse_dim)
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[0], self.tensors[2].to_sparse_coo(self.sparse_dim)
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[1], self.tensors[2].to_sparse_coo(self.sparse_dim)
|
|
)
|
|
)
|
|
|
|
def test_csr_dense(self):
|
|
self.assertTrue(
|
|
is_same_shape(self.tensors[0].to_sparse_csr(), self.tensors[1])
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(self.tensors[0].to_sparse_csr(), self.tensors[2])
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(self.tensors[1].to_sparse_csr(), self.tensors[2])
|
|
)
|
|
|
|
def test_csr_csr(self):
|
|
self.assertTrue(
|
|
is_same_shape(
|
|
self.tensors[0].to_sparse_csr(), self.tensors[1].to_sparse_csr()
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[0].to_sparse_csr(), self.tensors[2].to_sparse_csr()
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[1].to_sparse_csr(), self.tensors[2].to_sparse_csr()
|
|
)
|
|
)
|
|
|
|
def test_csr_coo(self):
|
|
self.assertTrue(
|
|
is_same_shape(
|
|
self.tensors[0].to_sparse_csr(),
|
|
self.tensors[1].to_sparse_coo(self.sparse_dim),
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[0].to_sparse_csr(),
|
|
self.tensors[2].to_sparse_coo(self.sparse_dim),
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[1].to_sparse_csr(),
|
|
self.tensors[2].to_sparse_coo(self.sparse_dim),
|
|
)
|
|
)
|
|
|
|
def test_coo_dense(self):
|
|
self.assertTrue(
|
|
is_same_shape(
|
|
self.tensors[0].to_sparse_coo(self.sparse_dim), self.tensors[1]
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[0].to_sparse_coo(self.sparse_dim), self.tensors[2]
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[1].to_sparse_coo(self.sparse_dim), self.tensors[2]
|
|
)
|
|
)
|
|
|
|
def test_coo_csr(self):
|
|
self.assertTrue(
|
|
is_same_shape(
|
|
self.tensors[0].to_sparse_coo(self.sparse_dim),
|
|
self.tensors[1].to_sparse_csr(),
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[0].to_sparse_coo(self.sparse_dim),
|
|
self.tensors[2].to_sparse_csr(),
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[1].to_sparse_coo(self.sparse_dim),
|
|
self.tensors[2].to_sparse_csr(),
|
|
)
|
|
)
|
|
|
|
def test_coo_coo(self):
|
|
self.assertTrue(
|
|
is_same_shape(
|
|
self.tensors[0].to_sparse_coo(self.sparse_dim),
|
|
self.tensors[1].to_sparse_coo(self.sparse_dim),
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[0].to_sparse_coo(self.sparse_dim),
|
|
self.tensors[2].to_sparse_coo(self.sparse_dim),
|
|
)
|
|
)
|
|
self.assertFalse(
|
|
is_same_shape(
|
|
self.tensors[1].to_sparse_coo(self.sparse_dim),
|
|
self.tensors[2].to_sparse_coo(self.sparse_dim),
|
|
)
|
|
)
|
|
|
|
|
|
class TestSparseIsSameShapeStatic(unittest.TestCase):
|
|
'''
|
|
test paddle.sparse.is_same_shape in static graph in pir mode
|
|
only support sparse_coo_tensor in static graph
|
|
'''
|
|
|
|
def setUp(self):
|
|
self.shapes = [[2, 5, 8], [3, 4]]
|
|
self.tensors = [
|
|
paddle.rand(self.shapes[0]),
|
|
paddle.rand(self.shapes[0]),
|
|
paddle.rand(self.shapes[1]),
|
|
]
|
|
self.sparse_dim = 2
|
|
|
|
def test_dense_dense(self):
|
|
if in_pir_mode():
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(
|
|
paddle.static.Program(), paddle.static.Program()
|
|
):
|
|
x = paddle.static.data(
|
|
name='x', shape=self.shapes[0], dtype='float32'
|
|
)
|
|
y = paddle.static.data(
|
|
name='y', shape=self.shapes[0], dtype='float32'
|
|
)
|
|
z = paddle.static.data(
|
|
name='z', shape=self.shapes[1], dtype='float32'
|
|
)
|
|
out1 = paddle.sparse.is_same_shape(x, y)
|
|
out2 = paddle.sparse.is_same_shape(z, x)
|
|
out3 = paddle.sparse.is_same_shape(y, z)
|
|
exe = paddle.static.Executor()
|
|
fetch = exe.run(
|
|
feed={
|
|
'x': self.tensors[0].numpy(),
|
|
'y': self.tensors[1].numpy(),
|
|
'z': self.tensors[2].numpy(),
|
|
},
|
|
fetch_list=[out1, out2, out3],
|
|
return_numpy=True,
|
|
)
|
|
self.assertTrue(fetch[0])
|
|
self.assertFalse(fetch[1])
|
|
self.assertFalse(fetch[2])
|
|
paddle.disable_static()
|
|
|
|
def test_dense_coo(self):
|
|
if in_pir_mode():
|
|
x_indices_data, x_values_data = (
|
|
self.tensors[0]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.indices(),
|
|
self.tensors[0]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.values(),
|
|
)
|
|
y_indices_data, y_values_data = (
|
|
self.tensors[1]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.indices(),
|
|
self.tensors[1]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.values(),
|
|
)
|
|
z_indices_data, z_values_data = (
|
|
self.tensors[2]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.indices(),
|
|
self.tensors[2]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.values(),
|
|
)
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(
|
|
paddle.static.Program(), paddle.static.Program()
|
|
):
|
|
x = paddle.static.data(
|
|
name='x', shape=self.shapes[0], dtype='float32'
|
|
)
|
|
y = paddle.static.data(
|
|
name='y', shape=self.shapes[0], dtype='float32'
|
|
)
|
|
z = paddle.static.data(
|
|
name='z', shape=self.shapes[1], dtype='float32'
|
|
)
|
|
x_indices = paddle.static.data(
|
|
name='x_indices', shape=x_indices_data.shape, dtype='int64'
|
|
)
|
|
x_values = paddle.static.data(
|
|
name='x_values', shape=x_values_data.shape, dtype='float32'
|
|
)
|
|
y_indices = paddle.static.data(
|
|
name='y_indices', shape=y_indices_data.shape, dtype='int64'
|
|
)
|
|
y_values = paddle.static.data(
|
|
name='y_values', shape=y_values_data.shape, dtype='float32'
|
|
)
|
|
z_indices = paddle.static.data(
|
|
name='z_indices', shape=z_indices_data.shape, dtype='int64'
|
|
)
|
|
z_values = paddle.static.data(
|
|
name='z_values', shape=z_values_data.shape, dtype='float32'
|
|
)
|
|
x_coo = paddle.sparse.sparse_coo_tensor(
|
|
x_indices,
|
|
x_values,
|
|
shape=self.shapes[0],
|
|
dtype='float32',
|
|
)
|
|
y_coo = paddle.sparse.sparse_coo_tensor(
|
|
y_indices,
|
|
y_values,
|
|
shape=self.shapes[0],
|
|
dtype='float32',
|
|
)
|
|
z_coo = paddle.sparse.sparse_coo_tensor(
|
|
z_indices,
|
|
z_values,
|
|
shape=self.shapes[1],
|
|
dtype='float32',
|
|
)
|
|
out1 = paddle.sparse.is_same_shape(x, y_coo)
|
|
out2 = paddle.sparse.is_same_shape(z, x_coo)
|
|
out3 = paddle.sparse.is_same_shape(y, z_coo)
|
|
out4 = paddle.sparse.is_same_shape(x_coo, y)
|
|
out5 = paddle.sparse.is_same_shape(z_coo, x)
|
|
out6 = paddle.sparse.is_same_shape(y_coo, z)
|
|
exe = paddle.static.Executor()
|
|
fetch = exe.run(
|
|
feed={
|
|
'x': self.tensors[0].numpy(),
|
|
'y': self.tensors[1].numpy(),
|
|
'z': self.tensors[2].numpy(),
|
|
'x_indices': x_indices_data.numpy(),
|
|
'x_values': x_values_data.numpy(),
|
|
'y_indices': y_indices_data.numpy(),
|
|
'y_values': y_values_data.numpy(),
|
|
'z_indices': z_indices_data.numpy(),
|
|
'z_values': z_values_data.numpy(),
|
|
},
|
|
fetch_list=[out1, out2, out3, out4, out5, out6],
|
|
return_numpy=True,
|
|
)
|
|
self.assertTrue(fetch[0])
|
|
self.assertFalse(fetch[1])
|
|
self.assertFalse(fetch[2])
|
|
self.assertTrue(fetch[3])
|
|
self.assertFalse(fetch[4])
|
|
self.assertFalse(fetch[5])
|
|
paddle.disable_static()
|
|
|
|
def test_coo_coo(self):
|
|
if in_pir_mode():
|
|
x_indices_data, x_values_data = (
|
|
self.tensors[0]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.indices(),
|
|
self.tensors[0]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.values(),
|
|
)
|
|
y_indices_data, y_values_data = (
|
|
self.tensors[1]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.indices(),
|
|
self.tensors[1]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.values(),
|
|
)
|
|
z_indices_data, z_values_data = (
|
|
self.tensors[2]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.indices(),
|
|
self.tensors[2]
|
|
.detach()
|
|
.to_sparse_coo(self.sparse_dim)
|
|
.values(),
|
|
)
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(
|
|
paddle.static.Program(), paddle.static.Program()
|
|
):
|
|
x_indices = paddle.static.data(
|
|
name='x_indices', shape=x_indices_data.shape, dtype='int64'
|
|
)
|
|
x_values = paddle.static.data(
|
|
name='x_values', shape=x_values_data.shape, dtype='float32'
|
|
)
|
|
y_indices = paddle.static.data(
|
|
name='y_indices', shape=y_indices_data.shape, dtype='int64'
|
|
)
|
|
y_values = paddle.static.data(
|
|
name='y_values', shape=y_values_data.shape, dtype='float32'
|
|
)
|
|
z_indices = paddle.static.data(
|
|
name='z_indices', shape=z_indices_data.shape, dtype='int64'
|
|
)
|
|
z_values = paddle.static.data(
|
|
name='z_values', shape=z_values_data.shape, dtype='float32'
|
|
)
|
|
x_coo = paddle.sparse.sparse_coo_tensor(
|
|
x_indices,
|
|
x_values,
|
|
shape=self.shapes[0],
|
|
dtype='float32',
|
|
)
|
|
y_coo = paddle.sparse.sparse_coo_tensor(
|
|
y_indices,
|
|
y_values,
|
|
shape=self.shapes[0],
|
|
dtype='float32',
|
|
)
|
|
z_coo = paddle.sparse.sparse_coo_tensor(
|
|
z_indices,
|
|
z_values,
|
|
shape=self.shapes[1],
|
|
dtype='float32',
|
|
)
|
|
out1 = paddle.sparse.is_same_shape(x_coo, y_coo)
|
|
out2 = paddle.sparse.is_same_shape(z_coo, x_coo)
|
|
out3 = paddle.sparse.is_same_shape(y_coo, z_coo)
|
|
exe = paddle.static.Executor()
|
|
fetch = exe.run(
|
|
feed={
|
|
'x_indices': x_indices_data.numpy(),
|
|
'x_values': x_values_data.numpy(),
|
|
'y_indices': y_indices_data.numpy(),
|
|
'y_values': y_values_data.numpy(),
|
|
'z_indices': z_indices_data.numpy(),
|
|
'z_values': z_values_data.numpy(),
|
|
},
|
|
fetch_list=[out1, out2, out3],
|
|
return_numpy=True,
|
|
)
|
|
self.assertTrue(fetch[0])
|
|
self.assertFalse(fetch[1])
|
|
self.assertFalse(fetch[2])
|
|
paddle.disable_static()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|