| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| D | test_util.py | 44 rtol=1e-2, atol=0.): argument
101 rtol=rtol, atol=atol)
106 rtol=1e-2, atol=0.): argument
150 self.assertAllClose(mean_, sample_mean_, rtol=rtol, atol=atol)
151 self.assertAllClose(variance_, sample_variance_, rtol=rtol, atol=atol)
152 self.assertAllClose(stddev_, sample_stddev_, rtol=rtol, atol=atol)
205 atol=0.): argument
321 rtol=rtol, atol=atol)
330 atol=0.1, argument
386 self.assertAllClose(mean_, sample_mean_, rtol=rtol, atol=atol)
[all …]
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| D | deterministic.py | 48 atol=None, argument
90 with ops.name_scope(name, values=[loc, atol, rtol]):
111 self._atol = self._get_tol(atol)
115 self._slack = self.atol
117 self._slack = self.atol + self.rtol * math_ops.abs(self.loc)
137 def atol(self): member in _BaseDeterministic
208 atol=None, argument
245 atol=atol,
313 atol=None, argument
353 atol=atol,
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| /external/tensorflow/tensorflow/core/framework/ |
| D | tensor_testutil.cc | 23 bool IsClose(const T& x, const T& y, double atol, double rtol) { in IsClose() argument
25 return x == y || std::abs(x - y) < atol + rtol * std::abs(x); in IsClose()
29 void ExpectClose(const Tensor& x, const Tensor& y, double atol, double rtol) { in ExpectClose() argument
33 if (!IsClose(Tx(i), Ty(i), atol, rtol)) { in ExpectClose()
36 LOG(ERROR) << "atol = " << atol << " rtol = " << rtol in ExpectClose()
37 << " tol = " << atol + rtol * std::abs(Tx(i)); in ExpectClose()
44 void ExpectClose(const Tensor& x, const Tensor& y, double atol, double rtol) { in ExpectClose() argument
48 ExpectClose<float>(x, y, atol, rtol); in ExpectClose()
51 ExpectClose<double>(x, y, atol, rtol); in ExpectClose()
54 ExpectClose<complex64>(x, y, atol, rtol); in ExpectClose()
[all …]
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | linalg_ops_test.py | 54 for np_type, atol in [(np.float32, 0.05), (np.float64, 1e-5)]:
65 rhs, math_ops.matmul(array, x).eval(), atol=atol)
75 for np_dtype, atol in [(np.float32, 0.05), (np.float64, 1e-5),
85 self.assertAllClose(logdet_np, logdet_tf.eval(), atol=atol)
88 for np_dtype, atol in [(np.float32, 0.05), (np.float64, 1e-5),
94 self.assertAllClose(logdet_np, logdet_tf.eval(), atol=atol)
104 for np_dtype, atol in [(np.float32, 0.05), (np.float64, 1e-5),
110 self.assertAllClose(log_abs_det_np, log_abs_det_tf.eval(), atol=atol)
111 self.assertAllClose(sign_np, sign_tf.eval(), atol=atol)
114 for np_dtype, atol in [(np.float32, 0.05), (np.float64, 1e-5),
[all …]
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| D | reduction_ops_test.py | 151 def _compareGradient(self, x, reduction_axes, rtol=1e-8, atol=1e-8): argument
154 self._compareGradient(x, reduction_axes[0], rtol=rtol, atol=atol)
160 self.assertAllClose(jacob_t, jacob_n, rtol=rtol, atol=atol)
162 def _compareGradientAxes(self, x, rtol=1e-8, atol=1e-8): argument
163 self._compareGradient(x, None, rtol=rtol, atol=atol)
164 self._compareGradient(x, [], rtol=rtol, atol=atol)
165 self._compareGradient(x, 0, rtol=rtol, atol=atol)
166 self._compareGradient(x, [1], rtol=rtol, atol=atol)
167 self._compareGradient(x, [2], rtol=rtol, atol=atol)
168 self._compareGradient(x, [1, 2], rtol=rtol, atol=atol)
[all …]
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| D | self_adjoint_eig_op_test.py | 106 self.assertAllClose(x, y, atol=tol)
118 self.assertAllClose(x_ei, y_ei, atol=tol, rtol=tol)
134 atol = 1e-4
136 atol = 1e-12
147 self.assertAllClose(a_ev.eval(), a, atol=atol)
151 tf_e.eval(), tf_v.eval(), atol)
155 np.sort(np_e, -1), np.sort(tf_e.eval(), -1), atol=atol)
219 self.assertAllClose(theoretical, numerical, atol=tol, rtol=tol)
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| /external/tensorflow/tensorflow/python/ops/distributions/ |
| D | bijector_test_util.py | 149 inverse_forward_x_v, uniform_x_samps_v, atol=1e-5, rtol=1e-3)
151 forward_inverse_y_v, uniform_y_samps_v, atol=1e-5, rtol=1e-3)
154 upper_x - lower_x, change_measure_dy_dx_v, atol=0, rtol=rtol)
158 dy_dx_v, np.divide(1., dx_dy_v), atol=1e-5, rtol=1e-3)
161 def assert_bijective_and_finite(bijector, x, y, atol=0, rtol=1e-5, sess=None): argument
217 np.testing.assert_allclose(x_from_x, x, atol=atol, rtol=rtol)
218 np.testing.assert_allclose(y_from_y, y, atol=atol, rtol=rtol)
219 np.testing.assert_allclose(-ildj_f_x, fldj_x, atol=atol, rtol=rtol)
220 np.testing.assert_allclose(-ildj_y, fldj_g_y, atol=atol, rtol=rtol)
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| /external/tensorflow/tensorflow/contrib/linear_optimizer/python/kernel_tests/ |
| D | sdca_ops_test.py | 231 self.assertAllClose(0.411608, unregularized_loss.eval(), atol=0.05)
232 self.assertAllClose(0.525457, loss.eval(), atol=0.01)
236 0.01, lr.approximate_duality_gap().eval(), rtol=1e-2, atol=1e-2)
294 self.assertAllClose(0.411608, unregularized_loss.eval(), atol=0.05)
295 self.assertAllClose(0.525457, loss.eval(), atol=0.01)
339 self.assertAllClose(0.40244, unregularized_loss.eval(), atol=0.01)
340 self.assertAllClose(0.40244, loss.eval(), atol=0.01)
344 0.01, lr.approximate_duality_gap().eval(), rtol=1e-2, atol=1e-2)
393 self.assertAllClose(0.411608, unregularized_loss.eval(), atol=0.05)
394 self.assertAllClose(0.525457, loss.eval(), atol=0.01)
[all …]
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| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| D | special_math_test.py | 92 self.assertAllClose(expected_x, x.eval(), atol=0.)
107 self.assertAllClose(expected_x_, x_, atol=0.)
137 _error32 = ErrorSpec(rtol=1e-4, atol=0.)
138 _error64 = ErrorSpec(rtol=1e-6, atol=0.)
171 atol=error_spec.atol)
198 atol=error_spec.atol)
211 _error32 = ErrorSpec(rtol=1e-4, atol=0.)
212 _error64 = ErrorSpec(rtol=1e-4, atol=0.)
226 _error32 = ErrorSpec(rtol=0.1, atol=1e-7)
227 _error64 = ErrorSpec(rtol=0.1, atol=1e-7)
[all …]
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| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| D | mvn_diag_plus_low_rank_test.py | 315 atol=0., rtol=0.02)
317 atol=0., rtol=1e-6)
320 atol=0., rtol=0.02)
322 atol=0., rtol=1e-6)
325 atol=0., rtol=0.02)
327 atol=0., rtol=1e-6)
330 atol=0., rtol=0.02)
332 atol=0., rtol=1e-6)
335 atol=0., rtol=1e-6)
338 atol=0., rtol=0.02)
[all …]
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| D | vector_student_t_test.py | 95 rtol=0., atol=1e-5)
98 rtol=0., atol=1e-5)
124 rtol=0., atol=1e-5)
127 rtol=0., atol=1e-5)
157 rtol=0., atol=1e-5)
160 rtol=0., atol=1e-5)
188 rtol=0., atol=1e-5)
191 rtol=0., atol=1e-5)
223 rtol=0., atol=1e-5)
226 rtol=0., atol=1e-5)
[all …]
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| D | mvn_tril_test.py | 84 self.assertAllClose(expected_log_pdf, log_pdf.eval(), atol=0., rtol=0.02)
85 self.assertAllClose(expected_pdf, pdf.eval(), atol=0., rtol=0.03)
151 self.assertAllClose(sample_values.mean(axis=0), mu, atol=1e-2)
152 self.assertAllClose(np.cov(sample_values, rowvar=0), sigma, atol=0.06)
178 x.reshape(10 * 11 * 12, 2).mean(axis=0), mu[1, 1], atol=0.05)
201 sample_values[:, 1, 1, :].mean(axis=0), mu[1, 1, :], atol=0.05)
205 atol=1e-1)
383 atol=0., rtol=0.03)
385 atol=0., rtol=1e-6)
388 atol=0., rtol=0.03)
[all …]
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| D | moving_stats_test.py | 62 self.assertAllClose(true_mean, ema_, rtol=0.005, atol=0.015)
63 self.assertAllClose(true_stddev**2., emv_, rtol=0.06, atol=0.)
80 self.assertAllClose(true_mean, ema_, rtol=0.005, atol=0.015)
81 self.assertAllClose(true_stddev**2., emv_, rtol=0.1, atol=0.)
103 self.assertAllClose(true_mean, ema_, rtol=0.005, atol=0.015)
104 self.assertAllClose(true_stddev**2., emv_, rtol=0.06, atol=0.)
126 self.assertAllClose(expected_, log_mean_exp_, rtol=1e-6, atol=1e-9)
|
| /external/tensorflow/tensorflow/compiler/tests/ |
| D | cholesky_op_test.py | 37 def _verifyCholeskyBase(self, sess, placeholder, x, chol, verification, atol): argument
39 self.assertAllClose(x, verification_np, atol=atol)
47 self.assertAllClose(chol_matrix, np.tril(chol_matrix), atol=atol)
50 def _verifyCholesky(self, x, atol=1e-6): argument
58 self._verifyCholeskyBase(sess, placeholder, x, chol, verification, atol)
79 self._verifyCholesky(matrices, atol=1e-4)
105 self._verifyCholesky(data, atol=1e-4)
122 self._verifyCholesky(matrix, atol=1e-4)
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| D | matrix_triangular_solve_op_test.py | 42 atol): argument
45 self.assertAllClose(b, verification_np, atol=atol)
47 def _VerifyTriangularSolve(self, a, b, lower, adjoint, atol): argument
59 verification, atol)
61 def _VerifyTriangularSolveCombo(self, a, b, atol=1e-4): argument
65 a if lower else transp(a), b, lower, adjoint, atol)
98 a.astype(dtype), b.astype(dtype), atol=1e-3)
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ |
| D | reshape_test.py | 72 self.assertAllClose(expected_y, y_, rtol=1e-6, atol=0)
73 self.assertAllClose(expected_x, x_, rtol=1e-6, atol=0)
74 self.assertAllClose(0., fldj_, rtol=1e-6, atol=0)
75 self.assertAllClose(0., ildj_, rtol=1e-6, atol=0)
123 self.assertAllClose(expected_y, y_, rtol=1e-6, atol=0)
124 self.assertAllClose(expected_x, x_, rtol=1e-6, atol=0)
125 self.assertAllClose(expected_y_scalar, y_scalar_, rtol=1e-6, atol=0)
126 self.assertAllClose(expected_x_scalar, x_scalar_, rtol=1e-6, atol=0)
227 self.assertAllClose(expected_y, y_, rtol=1e-6, atol=0)
228 self.assertAllClose(expected_x, x_, rtol=1e-6, atol=0)
[all …]
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| D | sigmoid_test.py | 39 self.assertAllClose(y, Sigmoid().forward(x).eval(), atol=0., rtol=1e-2)
40 self.assertAllClose(x, Sigmoid().inverse(y).eval(), atol=0., rtol=1e-4)
42 atol=0., rtol=1e-6)
44 atol=0., rtol=1e-4)
55 assert_bijective_and_finite(Sigmoid(), x, y, atol=0., rtol=1e-4)
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/python/utils/ |
| D | losses_test.py | 61 self.assertAllClose(np.exp(np.ones([2, 1])), pos_loss[:2], atol=1e-4)
62 self.assertAllClose(np.exp(-np.ones([2, 1])), neg_loss[:2], atol=1e-4)
67 self.assertAllClose(np.exp(-np.ones([4, 1])), pos_loss[6:10], atol=1e-4)
68 self.assertAllClose(np.exp(np.ones([4, 1])), neg_loss[6:10], atol=1e-4)
75 pos_loss[2:6], atol=1e-4)
78 neg_loss[2:6], atol=1e-4)
93 np.square(labels[:5] - predictions[:5]), loss[:5], atol=1e-4)
|
| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| D | factorization_ops_test.py | 208 self.assertAllClose(row_factors[0], self._row_factors_0, atol=1e-3)
209 self.assertAllClose(row_factors[1], self._row_factors_1, atol=1e-3)
232 atol=1e-3)
236 atol=1e-3)
280 self.assertAllClose(col_factors[0], self._col_factors_0, atol=1e-3)
281 self.assertAllClose(col_factors[1], self._col_factors_1, atol=1e-3)
282 self.assertAllClose(col_factors[2], self._col_factors_2, atol=1e-3)
307 atol=1e-3)
312 atol=1e-3)
383 self.assertAllClose(row_factors[0], self._row_factors_0, atol=1e-3)
[all …]
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| /external/tensorflow/tensorflow/python/framework/ |
| D | test_util.py | 1069 def _assertArrayLikeAllClose(self, a, b, rtol=1e-6, atol=1e-6, msg=None): argument
1074 if not np.allclose(a, b, rtol=rtol, atol=atol):
1084 np.abs(a - b) > atol + rtol * np.abs(b),
1096 print("not close tol = ", atol + rtol * np.abs(y))
1102 a, b, rtol=rtol, atol=atol, err_msg=msg, equal_nan=True)
1108 atol=1e-6, argument
1133 a[k], b[k], rtol=rtol, atol=atol, path=path, msg=msg)
1145 atol=atol,
1156 a_ele, b_ele, rtol=rtol, atol=atol, path=path, msg=msg)
1165 atol=atol,
[all …]
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| /external/tensorflow/tensorflow/contrib/bayesflow/python/kernel_tests/ |
| D | csiszar_divergence_test.py | 512 rtol=0.08, atol=0.)
515 rtol=0.02, atol=0.)
546 rtol=0.07, atol=0.)
549 rtol=0.02, atol=0.)
581 rtol=0.02, atol=0.)
584 rtol=0.08, atol=0.)
619 rtol=0.06, atol=0.)
622 rtol=0.05, atol=0.)
702 rtol=0.02, atol=0.)
705 rtol=0.08, atol=0.)
[all …]
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| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| D | external_optimizer_test.py | 58 def assertAllClose(self, array1, array2, rtol=1e-5, atol=1e-5): argument
66 super(TestCase, self).assertAllClose(array1, array2, rtol=rtol, atol=atol)
161 atol=1e-5, argument
171 self.assertAllClose(np.ones(dimension), sess.run(x), rtol=rtol, atol=atol)
187 method='Nelder-Mead', options={}, rtol=1e-4, atol=1e-4)
195 atol=1e-3)
203 atol=1e-1)
213 atol=1e-1,
218 method='SLSQP', options={}, rtol=1e-3, atol=1e-3)
222 method='CG', options={'gtol': 1e-03}, rtol=1e-3, atol=1e-3)
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| /external/tensorflow/tensorflow/contrib/metrics/python/kernel_tests/ |
| D | histogram_ops_test.py | 78 atol=0.05,
88 atol=0.05,
103 atol=0.05,
116 atol=0.05,
127 atol=0.005,
136 atol=0.05, argument
182 np.testing.assert_allclose(desired_auc, auc_eval, atol=atol, err_msg=msg)
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| /external/tensorflow/tensorflow/contrib/estimator/python/estimator/ |
| D | multi_head_test.py | 65 }, rtol=tol, atol=tol)
328 self.assertAllClose(expected_loss, loss, rtol=tol, atol=tol)
330 self.assertAllClose(expected_metrics, metrics, rtol=tol, atol=tol)
334 atol=tol)
351 self.assertAllClose(17.5, loss.eval(), rtol=tol, atol=tol)
389 [[10.], [7.5]], unreduced_losses['head1'].eval(), rtol=tol, atol=tol)
395 [[40.], [20.]], unreduced_losses['head2'].eval(), rtol=tol, atol=tol)
397 self.assertAllClose(165, training_loss.eval(), rtol=tol, atol=tol)
400 [[1.], [2.]], weights['head1'].eval(), rtol=tol, atol=tol)
402 [[4.], [6.]], weights['head2'].eval(), rtol=tol, atol=tol)
[all …]
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| /external/ltp/testcases/kernel/fs/mongo/ |
| D | reiser_fract_tree.c | 478 bytes_to_consume = atol(argv[1]); in main()
479 max_file_size = atol(argv[3]); in main()
480 median_file_size = atol(argv[2]); in main()
489 stats = atol(argv[10]); in main()
490 median_dir_branching = atol(argv[6]); in main()
491 max_dir_branching = atol(argv[7]); in main()
492 median_dir_nr_files = atol(argv[4]); in main()
493 max_dir_nr_files = atol(argv[5]); in main()
|