1# Copyright 2015 The TensorFlow Authors. All Rights Reserved. 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================== 15"""Tests for tensorflow.ops.tf.norm.""" 16 17import numpy as np 18 19from tensorflow.python.framework import constant_op 20from tensorflow.python.framework import test_util 21from tensorflow.python.ops import array_ops 22from tensorflow.python.ops import linalg_ops 23from tensorflow.python.platform import test as test_lib 24 25 26def _AddTest(test, test_name, fn): 27 test_name = "_".join(["test", test_name]) 28 if hasattr(test, test_name): 29 raise RuntimeError("Test %s defined more than once" % test_name) 30 setattr(test, test_name, fn) 31 32 33class NormOpTest(test_lib.TestCase): 34 35 @test_util.run_v1_only("b/120545219") 36 def testBadOrder(self): 37 matrix = [[0., 1.], [2., 3.]] 38 for ord_ in "fro", -7, -1.1, 0: 39 with self.assertRaisesRegex(ValueError, 40 "'ord' must be a supported vector norm"): 41 linalg_ops.norm(matrix, ord=ord_) 42 43 for ord_ in "fro", -7, -1.1, 0: 44 with self.assertRaisesRegex(ValueError, 45 "'ord' must be a supported vector norm"): 46 linalg_ops.norm(matrix, ord=ord_, axis=-1) 47 48 for ord_ in "foo", -7, -1.1, 1.1: 49 with self.assertRaisesRegex(ValueError, 50 "'ord' must be a supported matrix norm"): 51 linalg_ops.norm(matrix, ord=ord_, axis=[-2, -1]) 52 53 @test_util.run_v1_only("b/120545219") 54 def testInvalidAxis(self): 55 matrix = [[0., 1.], [2., 3.]] 56 for axis_ in [], [1, 2, 3], [[1]], [[1], [2]], [3.1415], [1, 1]: 57 error_prefix = ("'axis' must be None, an integer, or a tuple of 2 unique " 58 "integers") 59 with self.assertRaisesRegex(ValueError, error_prefix): 60 linalg_ops.norm(matrix, axis=axis_) 61 62 63def _GetNormOpTest(dtype_, shape_, ord_, axis_, keep_dims_, use_static_shape_): 64 65 def _CompareNorm(self, matrix): 66 np_norm = np.linalg.norm(matrix, ord=ord_, axis=axis_, keepdims=keep_dims_) 67 with self.cached_session() as sess: 68 if use_static_shape_: 69 tf_matrix = constant_op.constant(matrix) 70 tf_norm = linalg_ops.norm( 71 tf_matrix, ord=ord_, axis=axis_, keepdims=keep_dims_) 72 tf_norm_val = self.evaluate(tf_norm) 73 else: 74 tf_matrix = array_ops.placeholder(dtype_) 75 tf_norm = linalg_ops.norm( 76 tf_matrix, ord=ord_, axis=axis_, keepdims=keep_dims_) 77 tf_norm_val = sess.run(tf_norm, feed_dict={tf_matrix: matrix}) 78 self.assertAllClose(np_norm, tf_norm_val, rtol=1e-5, atol=1e-5) 79 80 @test_util.run_v1_only("b/120545219") 81 def Test(self): 82 is_matrix_norm = (isinstance(axis_, tuple) or 83 isinstance(axis_, list)) and len(axis_) == 2 84 is_fancy_p_norm = np.isreal(ord_) and np.floor(ord_) != ord_ 85 if ((not is_matrix_norm and ord_ == "fro") or 86 (is_matrix_norm and is_fancy_p_norm)): 87 self.skipTest("Not supported by neither numpy.linalg.norm nor tf.norm") 88 if ord_ == "euclidean" or (axis_ is None and len(shape) > 2): 89 self.skipTest("Not supported by numpy.linalg.norm") 90 matrix = np.random.randn(*shape_).astype(dtype_) 91 if dtype_ in (np.complex64, np.complex128): 92 matrix += 1j * np.random.randn(*shape_).astype(dtype_) 93 _CompareNorm(self, matrix) 94 95 return Test 96 97# pylint: disable=redefined-builtin 98if __name__ == "__main__": 99 for use_static_shape in False, True: 100 for dtype in np.float32, np.float64, np.complex64, np.complex128: 101 for rows in 2, 5: 102 for cols in 2, 5: 103 for batch in [], [2], [2, 3]: 104 shape = batch + [rows, cols] 105 for ord in "euclidean", "fro", 0.5, 1, 2, np.inf: 106 for axis in [ 107 None, (-2, -1), (-1, -2), -len(shape), 0, len(shape) - 1 108 ]: 109 for keep_dims in False, True: 110 name = "%s_%s_ord_%s_axis_%s_%s_%s" % ( 111 dtype.__name__, "_".join(map(str, shape)), ord, axis, 112 keep_dims, use_static_shape) 113 _AddTest(NormOpTest, "Norm_" + name, 114 _GetNormOpTest(dtype, shape, ord, axis, keep_dims, 115 use_static_shape)) 116 117 test_lib.main() 118