| /device/linaro/bootloader/edk2/BaseTools/Source/C/VfrCompile/Pccts/h/ |
| int.h | 35 #define zzcr_attr(a,tok,t) *(a) = atol(t);
|
| /device/linaro/bootloader/edk2/EdkCompatibilityPkg/Other/Maintained/Tools/Pccts/h/ |
| int.h | 35 #define zzcr_attr(a,tok,t) *(a) = atol(t);
|
| /external/tensorflow/tensorflow/core/framework/ |
| tensor_testutil.cc | 23 void ExpectClose(const Tensor& x, const Tensor& y, double atol, double rtol) {
38 (atol < 0) ? kDefaultTol : static_cast<RealType>(atol);
53 void ExpectClose(const Tensor& x, const Tensor& y, double atol, double rtol) {
57 ExpectClose<Eigen::half>(x, y, atol, rtol);
60 ExpectClose<float>(x, y, atol, rtol);
63 ExpectClose<double>(x, y, atol, rtol);
66 ExpectClose<complex64>(x, y, atol, rtol);
69 ExpectClose<complex128>(x, y, atol, rtol);
|
| /external/compiler-rt/test/asan/TestCases/ |
| atol_strict.c | 1 // Test strict_string_checks option in atol function
21 long r = atol(array);
28 long r = atol(array + 9);
37 long r = atol(array);
|
| /external/toybox/toys/other/ |
| usleep.c | 21 long delay = atol(*toys.optargs);
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| test_util.py | 45 rtol=1e-2, atol=0.):
75 atol: Python `float`-type indicating the admissible absolute error between
102 rtol=rtol, atol=atol)
107 rtol=1e-2, atol=0.):
126 atol: Python `float`-type indicating the admissible absolute error between
151 self.assertAllClose(mean_, sample_mean_, rtol=rtol, atol=atol)
152 self.assertAllClose(variance_, sample_variance_, rtol=rtol, atol=atol)
[all...] |
| deterministic.py | 57 atol=None,
65 The `atol` and `rtol` parameters allow for some slack in `pmf`, `cdf`
70 = 1, if Abs(x - loc) <= atol + rtol * Abs(loc),
77 atol: Non-negative `Tensor` of same `dtype` as `loc` and broadcastable
99 with ops.name_scope(name, values=[loc, atol, rtol]) as name:
120 self._atol = self._get_tol(atol)
124 self._slack = self.atol
126 self._slack = self.atol + self.rtol * math_ops.abs(self.loc)
146 def atol(self): member in class:_BaseDeterministic
231 atol=None
[all...] |
| /external/ltp/testcases/kernel/fs/mongo/ |
| summ.c | 20 n = atol(str);
|
| reiser_fract_tree.c | 478 bytes_to_consume = atol(argv[1]);
479 max_file_size = atol(argv[3]);
480 median_file_size = atol(argv[2]);
489 stats = atol(argv[10]);
490 median_dir_branching = atol(argv[6]);
491 max_dir_branching = atol(argv[7]);
492 median_dir_nr_files = atol(argv[4]);
493 max_dir_nr_files = atol(argv[5]);
|
| /external/tensorflow/tensorflow/contrib/boosted_trees/python/utils/ |
| 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/distributions/python/kernel_tests/bijectors/ |
| sigmoid_test.py | 40 self.assertAllClose(y, bijector.forward(x).eval(), atol=0., rtol=1e-2)
41 self.assertAllClose(x, bijector.inverse(y).eval(), atol=0., rtol=1e-4)
43 y, event_ndims=0).eval(), atol=0., rtol=1e-6)
45 x, event_ndims=0).eval(), atol=0., rtol=1e-4)
57 Sigmoid(), x, y, event_ndims=0, atol=0., rtol=1e-4)
|
| permute_test.py | 61 self.assertAllClose(expected_y, y_, rtol=1e-6, atol=0)
62 self.assertAllClose(expected_x, x_, rtol=1e-6, atol=0)
63 self.assertAllClose(0., fldj, rtol=1e-6, atol=0)
64 self.assertAllClose(0., ildj, rtol=1e-6, atol=0)
83 bijector, x, y, event_ndims=1, rtol=1e-6, atol=0)
|
| reshape_test.py | 69 self.assertAllClose(expected_y, y_, rtol=1e-6, atol=0)
70 self.assertAllClose(expected_x, x_, rtol=1e-6, atol=0)
71 self.assertAllClose(0., fldj_, rtol=1e-6, atol=0)
72 self.assertAllClose(0., ildj_, rtol=1e-6, atol=0)
120 self.assertAllClose(expected_y, y_, rtol=1e-6, atol=0)
121 self.assertAllClose(expected_x, x_, rtol=1e-6, atol=0)
122 self.assertAllClose(expected_y_scalar, y_scalar_, rtol=1e-6, atol=0)
123 self.assertAllClose(expected_x_scalar, x_scalar_, rtol=1e-6, atol=0)
224 self.assertAllClose(expected_y, y_, rtol=1e-6, atol=0)
225 self.assertAllClose(expected_x, x_, rtol=1e-6, atol=0
[all...] |
| /external/tensorflow/tensorflow/python/kernel_tests/signal/ |
| dct_ops_test.py | 106 def _compare(self, signals, norm, dct_type, atol=5e-4, rtol=5e-4):
110 self.assertAllClose(np_dct, tf_dct, atol=atol, rtol=rtol)
113 self.assertAllClose(np_idct, tf_idct, atol=atol, rtol=rtol)
116 self.assertAllClose(scipy_dct, tf_dct, atol=atol, rtol=rtol)
118 self.assertAllClose(scipy_idct, tf_idct, atol=atol, rtol=rtol)
131 self.assertAllClose(signals, tf_idct_dct, atol=atol, rtol=rtol
[all...] |
| /external/tensorflow/tensorflow/python/ops/distributions/ |
| bijector_test_util.py | 151 inverse_forward_x_v, uniform_x_samps_v, atol=1e-5, rtol=1e-3)
153 forward_inverse_y_v, uniform_y_samps_v, atol=1e-5, rtol=1e-3)
156 upper_x - lower_x, change_measure_dy_dx_v, atol=0, rtol=rtol)
160 dy_dx_v, np.divide(1., dx_dy_v), atol=1e-5, rtol=1e-3)
164 bijector, x, y, event_ndims, atol=0, rtol=1e-5, sess=None):
176 atol: Absolute tolerance.
222 np.testing.assert_allclose(x_from_x, x, atol=atol, rtol=rtol)
223 np.testing.assert_allclose(y_from_y, y, atol=atol, rtol=rtol
[all...] |
| /external/libmtp/examples/ |
| newfolder.c | 45 newid = LIBMTP_Create_Folder(device, argv[1], atol(argv[2]), atol(argv[3]));
|
| /external/perfetto/tools/busy_threads/ |
| busy_threads.cc | 62 num_threads = atol(optarg);
65 period_us = atol(optarg);
68 duty_cycle = atol(optarg);
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| linalg_ops_test.py | 59 for np_type, atol in [(np.float32, 0.05), (np.float64, 1e-5)]:
70 rhs, math_ops.matmul(array, x).eval(), atol=atol)
81 for np_dtype, atol in [(np.float32, 0.05), (np.float64, 1e-5),
91 self.assertAllClose(logdet_np, self.evaluate(logdet_tf), atol=atol)
94 for np_dtype, atol in [(np.float32, 0.05), (np.float64, 1e-5),
100 self.assertAllClose(logdet_np, self.evaluate(logdet_tf), atol=atol)
111 for np_dtype, atol in [(np.float32, 0.05), (np.float64, 1e-5)
[all...] |
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| 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...] |
| /external/tensorflow/tensorflow/compiler/tests/ |
| cholesky_op_test.py | 42 def _verifyCholeskyBase(self, sess, placeholder, x, chol, verification, atol):
44 self.assertAllClose(x, verification_np, atol=atol)
52 self.assertAllClose(chol_matrix, np.tril(chol_matrix), atol=atol)
55 def _verifyCholesky(self, x, atol=1e-6):
63 self._verifyCholeskyBase(sess, placeholder, x, chol, verification, atol)
84 self._verifyCholesky(matrices, atol=1e-4)
109 self._verifyCholesky(data, atol=1e-4)
126 self._verifyCholesky(matrix, atol=1e-4
[all...] |
| /external/strace/tests/ |
| qual_inject-retval.c | 59 if (atol(argv[1]) != rval)
|
| /external/strace/tests-m32/ |
| qual_inject-retval.c | 59 if (atol(argv[1]) != rval)
|
| /external/strace/tests-mx32/ |
| qual_inject-retval.c | 59 if (atol(argv[1]) != rval)
|
| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| special_math_test.py | 82 ErrorSpec = collections.namedtuple("ErrorSpec", ["rtol", "atol"])
105 self.assertAllClose(expected_x, self.evaluate(x), atol=0.)
121 self.assertAllClose(expected_x_, x_, atol=0.)
156 _error32 = ErrorSpec(rtol=1e-4, atol=0.)
157 _error64 = ErrorSpec(rtol=1e-6, atol=0.)
189 atol=error_spec.atol)
215 atol=error_spec.atol)
230 _error32 = ErrorSpec(rtol=1e-4, atol=0.
[all...] |
| /external/tensorflow/tensorflow/contrib/linear_optimizer/python/kernel_tests/ |
| sdca_ops_test.py | 276 self.assertAllClose(0.411608, unregularized_loss.eval(), atol=0.05)
277 self.assertAllClose(0.525457, loss.eval(), atol=0.01)
281 0.01, lr.approximate_duality_gap().eval(), rtol=1e-2, atol=1e-2)
324 self.assertAllClose(0.411608, unregularized_loss.eval(), atol=0.05)
325 self.assertAllClose(0.525457, loss.eval(), atol=0.01)
329 0.01, lr.approximate_duality_gap().eval(), rtol=1e-2, atol=1e-2)
386 self.assertAllClose(0.512591, unregularized_loss.eval(), atol=0.05)
387 self.assertAllClose(0.593014, loss.eval(), atol=0.01)
391 0.01, lr.approximate_duality_gap().eval(), rtol=1e-2, atol=1e-2)
511 self.assertAllClose(0.411608, unregularized_loss.eval(), atol=0.02
[all...] |
