| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| uniform_test.py | 159 sample_values = samples.eval()
160 self.assertEqual(sample_values.shape, (100000, 2))
162 sample_values[::, 0].mean(), (b_v + a1_v) / 2, atol=1e-2)
164 sample_values[::, 1].mean(), (b_v + a2_v) / 2, atol=1e-2)
166 np.any(sample_values[::, 0] < a1_v) or np.any(sample_values >= b_v))
168 np.any(sample_values[::, 1] < a2_v) or np.any(sample_values >= b_v))
186 sample_values = samples.eval()
189 np.any(sample_values[:, 0, 0] < a_v[0]) o
[all...] |
| exponential_test.py | 122 sample_values = samples.eval()
123 self.assertEqual(sample_values.shape, (100000, 2))
124 self.assertFalse(np.any(sample_values < 0.0))
130 sample_values[:, i], stats.expon(scale=1.0 / lam_v[i]).cdf)[0],
145 sample_values = samples.eval()
147 self.assertFalse(np.any(sample_values < 0.0))
153 sample_values[:, 0, i],
158 sample_values[:, 1, i],
|
| gamma_test.py | 226 sample_values = samples.eval()
228 self.assertEqual(sample_values.shape, (n,))
229 self.assertTrue(self._kstest(alpha_v, beta_v, sample_values))
233 sample_values.mean(),
238 sample_values.var(),
251 sample_values = samples.eval()
253 self.assertEqual(sample_values.shape, (n,))
254 self.assertTrue(self._kstest(alpha_v, beta_v, sample_values))
258 sample_values.mean(),
263 sample_values.var()
[all...] |
| beta_test.py | 266 sample_values = samples.eval()
267 self.assertEqual(sample_values.shape, (100000,))
268 self.assertFalse(np.any(sample_values < 0.0))
274 sample_values,
279 sample_values.mean(axis=0), stats.beta.mean(a, b), atol=1e-2)
281 np.cov(sample_values, rowvar=0), stats.beta.var(a, b), atol=1e-1)
311 sample_values = samples.eval()
312 self.assertEqual(sample_values.shape, (100000, 3, 2, 2))
313 self.assertFalse(np.any(sample_values < 0.0))
317 sample_values[:, 1, :].mean(axis=0)
[all...] |
| laplace_test.py | 238 sample_values = samples.eval()
240 self.assertEqual(sample_values.shape, (n,))
244 sample_values.mean(),
250 sample_values.var(),
254 self.assertTrue(self._kstest(loc_v, scale_v, sample_values))
263 sample_values = samples.eval()
265 self.assertEqual(sample_values.shape, (n, 10, 100))
272 sample_values.mean(axis=0),
278 sample_values.var(axis=0),
286 s = sample_values[:, bi, ai
[all...] |
| student_t_test.py | 170 sample_values = samples.eval()
172 self.assertEqual(sample_values.shape, (n_val,))
173 self.assertAllClose(sample_values.mean(), mu_v, rtol=1e-2, atol=0)
175 sample_values.var(),
179 self._checkKLApprox(df_v, mu_v, sigma_v, sample_values)
208 sample_values = samples.eval()
210 self.assertEqual(sample_values.shape, (n_val, 4))
211 self.assertTrue(np.all(np.logical_not(np.isnan(sample_values))))
226 sample_values = samples.eval()
229 sample_values[:, 0, 0].mean(), mu_v[0], rtol=1e-2, atol=0
[all...] |
| normal_test.py | 388 sample_values = samples.eval()
393 self.assertEqual(sample_values.shape, (100000,))
394 self.assertAllClose(sample_values.mean(), mu_v, atol=1e-1)
395 self.assertAllClose(sample_values.std(), sigma_v, atol=1e-1)
401 self.assertAllEqual(expected_samples_shape, sample_values.shape)
407 self.assertAllEqual(expected_samples_shape, sample_values.shape)
420 sample_values = samples.eval()
426 self.assertAllClose(sample_values[:, 0, 0].mean(), mu_v[0], atol=1e-1)
427 self.assertAllClose(sample_values[:, 0, 0].std(), sigma_v[0], atol=1e-1)
428 self.assertAllClose(sample_values[:, 0, 1].mean(), mu_v[1], atol=1e-1
[all...] |
| bernoulli_test.py | 245 sample_values = samples.eval()
246 self.assertTrue(np.all(sample_values >= 0))
247 self.assertTrue(np.all(sample_values <= 1))
251 self.assertAllClose(p, np.mean(sample_values, axis=0), atol=1e-2)
252 self.assertEqual(set([0, 1]), set(sample_values.flatten()))
|
| dirichlet_test.py | 248 sample_values = samples.eval()
249 self.assertEqual(sample_values.shape, (100000, 2))
250 self.assertTrue(np.all(sample_values > 0.0))
256 sample_values[:, 0],
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| categorical_test.py | 341 sample_values = samples.eval()
342 self.assertFalse(np.any(sample_values < 0))
343 self.assertFalse(np.any(sample_values > 1))
346 sample_values == 0, axis=0), atol=1e-2)
349 sample_values == 1, axis=0), atol=1e-2)
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| geometric_test.py | 178 sample_values = samples.eval()
179 self.assertFalse(np.any(sample_values < 0.0))
181 self.assertAllClose(sample_values[:, i].mean(),
184 self.assertAllClose(sample_values[:, i].var(),
200 sample_values = samples.eval()
202 self.assertFalse(np.any(sample_values < 0.0))
204 self.assertAllClose(sample_values[:, 0, i].mean(),
207 self.assertAllClose(sample_values[:, 0, i].var(),
210 self.assertAllClose(sample_values[:, 1, i].mean(),
213 self.assertAllClose(sample_values[:, 1, i].var()
[all...] |
| poisson_test.py | 189 sample_values = samples.eval()
191 self.assertEqual(sample_values.shape, (n,))
193 sample_values.mean(), stats.poisson.mean(lam_v), rtol=.01)
195 sample_values.var(), stats.poisson.var(lam_v), rtol=.01)
205 sample_values = samples.eval()
207 self.assertEqual(sample_values.shape, (n, 1, 50))
209 sample_values.mean(axis=0),
223 sample_values = samples.eval()
225 self.assertEqual(sample_values.shape, (n, 1, 10))
228 sample_values.var(axis=0), stats.poisson.var(lam_v), rtol=.03, atol=0
[all...] |
| relaxed_bernoulli_test.py | 149 sample_values = samples.eval()
150 self.assertTrue(np.all(sample_values >= 0))
151 self.assertTrue(np.all(sample_values <= 1))
153 frac_ones_like = np.sum(sample_values >= 0.5, axis=0)/n
|
| inverse_gamma_test.py | 207 sample_values = samples.eval()
209 self.assertEqual(sample_values.shape, (n,))
211 sample_values.mean(),
216 sample_values.var(),
219 self.assertTrue(self._kstest(alpha_v, beta_v, sample_values))
228 sample_values = samples.eval()
230 self.assertEqual(sample_values.shape, (n, 10, 100))
235 sample_values.mean(axis=0),
240 sample_values.var(axis=0),
247 s = sample_values[:, bi, ai
[all...] |
| kumaraswamy_test.py | 300 sample_values = samples.eval()
301 self.assertEqual(sample_values.shape, (100000,))
302 self.assertFalse(np.any(sample_values < 0.0))
308 sample_values,
313 self.assertAllClose(sample_values.mean(axis=0), expected_mean, atol=1e-2)
317 np.cov(sample_values, rowvar=0), expected_variance, atol=1e-1)
345 sample_values = samples.eval()
346 self.assertEqual(sample_values.shape, (100000, 3, 2, 2))
347 self.assertFalse(np.any(sample_values < 0.0))
351 sample_values[:, 1, :].mean(axis=0)
[all...] |
| cauchy_test.py | 358 sample_values = samples.eval()
360 self.assertEqual(sample_values.shape, (100000,))
361 self.assertAllClose(np.median(sample_values), loc_v, atol=1e-1)
367 self.assertAllEqual(expected_shape, sample_values.shape)
373 self.assertAllEqual(expected_shape, sample_values.shape)
384 sample_values = samples.eval()
387 np.median(sample_values[:, 0, 0]), loc_v[0], atol=1e-1)
389 np.median(sample_values[:, 0, 1]), loc_v[1], atol=1e-1)
394 self.assertAllEqual(expected_shape, sample_values.shape)
399 self.assertAllEqual(expected_shape, sample_values.shape
[all...] |
| mvn_tril_test.py | 149 sample_values = samples.eval()
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)
197 sample_values = samples.eval()
201 sample_values[:, 1, 1, :].mean(axis=0), mu[1, 1, :], atol=0.05)
203 np.cov(sample_values[:, 1, 1, :], rowvar=0),
|
| mixture_test.py | 521 sample_values, cat_sample_values, dist_sample_values = sess.run(
523 self.assertEqual((4,), sample_values.shape)
533 self.assertAllClose(which_dist_samples, sample_values[which_c])
581 sample_values, cat_sample_values, dist_sample_values = sess.run(
583 self.assertEqual((4, 2), sample_values.shape)
592 self.assertAllClose(which_dist_samples, sample_values[which_c, :])
606 sample_values, cat_sample_values, dist_sample_values = sess.run(
608 self.assertEqual((4, 2, 3), sample_values.shape)
620 sample_values[which_c_s, which_c_b0, which_c_b1])
650 sample_values, cat_sample_values, dist_sample_values = sess.run
[all...] |
| onehot_categorical_test.py | 147 sample_values = samples.eval()
148 self.assertAllEqual([n, 1, 2, 2], sample_values.shape)
149 self.assertFalse(np.any(sample_values < 0))
150 self.assertFalse(np.any(sample_values > 1))
|
