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# Copyright 2016 The TensorFlow 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 absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.contrib.solvers.python.ops import lanczos
from tensorflow.contrib.solvers.python.ops import util
from tensorflow.python.framework import constant_op
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.platform import test as test_lib
def _add_test(test, test_name, fn):
test_name = "_".join(["test", test_name])
if hasattr(test, test_name):
raise RuntimeError("Test %s defined more than once" % test_name)
setattr(test, test_name, fn)
class LanczosBidiagTest(test_lib.TestCase):
pass # Filled in below.
def _get_lanczos_tests(dtype_, use_static_shape_, shape_, orthogonalize_,
steps_):
def test_lanczos_bidiag(self):
np.random.seed(1)
a_np = np.random.uniform(
low=-1.0, high=1.0, size=np.prod(shape_)).reshape(shape_).astype(dtype_)
tol = 1e-12 if dtype_ == np.float64 else 1e-5
with self.cached_session() as sess:
if use_static_shape_:
a = constant_op.constant(a_np)
else:
a = array_ops.placeholder(dtype_)
operator = util.create_operator(a)
lbd = lanczos.lanczos_bidiag(
operator, steps_, orthogonalize=orthogonalize_)
# The computed factorization should satisfy the equations
# A * V = U * B
# A' * U[:, :-1] = V * B[:-1, :]'
av = math_ops.matmul(a, lbd.v)
ub = lanczos.bidiag_matmul(lbd.u, lbd.alpha, lbd.beta, adjoint_b=False)
atu = math_ops.matmul(a, lbd.u[:, :-1], adjoint_a=True)
vbt = lanczos.bidiag_matmul(lbd.v, lbd.alpha, lbd.beta, adjoint_b=True)
if use_static_shape_:
av_val, ub_val, atu_val, vbt_val = sess.run([av, ub, atu, vbt])
else:
av_val, ub_val, atu_val, vbt_val = sess.run([av, ub, atu, vbt],
feed_dict={a: a_np})
self.assertAllClose(av_val, ub_val, atol=tol, rtol=tol)
self.assertAllClose(atu_val, vbt_val, atol=tol, rtol=tol)
return [test_lanczos_bidiag]
if __name__ == "__main__":
for dtype in np.float32, np.float64:
for shape in [[4, 4], [7, 4], [5, 8]]:
for orthogonalize in True, False:
for steps in range(1, min(shape) + 1):
for use_static_shape in True, False:
arg_string = "%s_%s_%s_%s_staticshape_%s" % (
dtype.__name__, "_".join(map(str, shape)), orthogonalize, steps,
use_static_shape)
for test_fn in _get_lanczos_tests(dtype, use_static_shape, shape,
orthogonalize, steps):
name = "_".join(["Lanczos", test_fn.__name__, arg_string])
_add_test(LanczosBidiagTest, name, test_fn)
test_lib.main()
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