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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 util
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
class UtilTest(test.TestCase):
def _testCreateOperator(self, use_static_shape_):
for dtype in np.float32, np.float64:
a_np = np.array([[1., 2.], [3., 4.], [5., 6.]], dtype=dtype)
x_np = np.array([[2.], [-3.]], dtype=dtype)
y_np = np.array([[2], [-3.], [5.]], dtype=dtype)
with self.test_session() as sess:
if use_static_shape_:
a = constant_op.constant(a_np, dtype=dtype)
x = constant_op.constant(x_np, dtype=dtype)
y = constant_op.constant(y_np, dtype=dtype)
else:
a = array_ops.placeholder(dtype)
x = array_ops.placeholder(dtype)
y = array_ops.placeholder(dtype)
op = util.create_operator(a)
ax = op.apply(x)
aty = op.apply_adjoint(y)
op_shape = ops.convert_to_tensor(op.shape)
if use_static_shape_:
op_shape_val, ax_val, aty_val = sess.run([op_shape, ax, aty])
else:
op_shape_val, ax_val, aty_val = sess.run(
[op_shape, ax, aty], feed_dict={a: a_np,
x: x_np,
y: y_np})
self.assertAllEqual(op_shape_val, [3, 2])
self.assertAllClose(ax_val, np.dot(a_np, x_np))
self.assertAllClose(aty_val, np.dot(a_np.T, y_np))
def testCreateOperator(self):
self._testCreateOperator(True)
def testCreateOperatorUnknownShape(self):
self._testCreateOperator(False)
def testL2Norm(self):
with self.test_session():
x_np = np.array([[2], [-3.], [5.]])
x_norm_np = np.linalg.norm(x_np)
x_normalized_np = x_np / x_norm_np
x = constant_op.constant(x_np)
l2norm = util.l2norm(x)
l2norm_squared = util.l2norm_squared(x)
x_normalized, x_norm = util.l2normalize(x)
self.assertAllClose(l2norm.eval(), x_norm_np)
self.assertAllClose(l2norm_squared.eval(), np.square(x_norm_np))
self.assertAllClose(x_norm.eval(), x_norm_np)
self.assertAllClose(x_normalized.eval(), x_normalized_np)
if __name__ == '__main__':
test.main()
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