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/external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/
Ddistribution_util_test.py25 from tensorflow.contrib.distributions.python.ops import distribution_util
113 scale = distribution_util.make_tril_scale(**scale_args)
116 scale = distribution_util.make_tril_scale(**scale_args)
147 scale = distribution_util.make_tril_scale(scale_tril=[[1., 1], [1., 1.]])
153 scale = distribution_util.make_tril_scale(
160 scale = distribution_util.make_tril_scale(
182 scale = distribution_util.make_diag_scale(**scale_args)
185 scale = distribution_util.make_diag_scale(**scale_args)
209 scale = distribution_util.make_diag_scale(
216 scale = distribution_util.make_diag_scale(
[all …]
/external/tensorflow/tensorflow/contrib/distributions/python/ops/
Dconditional_distribution.py22 from tensorflow.python.ops.distributions import util as distribution_util unknown
32 @distribution_util.AppendDocstring(kwargs_dict={
39 @distribution_util.AppendDocstring(kwargs_dict={
45 @distribution_util.AppendDocstring(kwargs_dict={
51 @distribution_util.AppendDocstring(kwargs_dict={
57 @distribution_util.AppendDocstring(kwargs_dict={
63 @distribution_util.AppendDocstring(kwargs_dict={
70 @distribution_util.AppendDocstring(kwargs_dict={
Dconditional_transformed_distribution.py26 from tensorflow.python.ops.distributions import util as distribution_util unknown
52 @distribution_util.AppendDocstring(kwargs_dict=_condition_kwargs_dict)
57 distribution_util.pick_vector(self._needs_rotation, self._empty, [n]),
60 distribution_util.pick_vector(self._needs_rotation, [n], self._empty))
101 @distribution_util.AppendDocstring(kwargs_dict=_condition_kwargs_dict)
128 @distribution_util.AppendDocstring(kwargs_dict=_condition_kwargs_dict)
152 @distribution_util.AppendDocstring(kwargs_dict=_condition_kwargs_dict)
165 @distribution_util.AppendDocstring(kwargs_dict=_condition_kwargs_dict)
178 @distribution_util.AppendDocstring(kwargs_dict=_condition_kwargs_dict)
192 @distribution_util.AppendDocstring(kwargs_dict=_condition_kwargs_dict)
[all …]
Dpoisson.py30 from tensorflow.python.ops.distributions import util as distribution_util unknown
156 @distribution_util.AppendDocstring(_poisson_sample_note)
160 @distribution_util.AppendDocstring(_poisson_sample_note)
164 @distribution_util.AppendDocstring(_poisson_sample_note)
167 x = distribution_util.embed_check_nonnegative_integer_form(x)
175 x = distribution_util.embed_check_nonnegative_integer_form(x)
184 @distribution_util.AppendDocstring(
Dvector_laplace_linear_operator.py24 from tensorflow.contrib.distributions.python.ops import distribution_util
214 batch_shape, event_shape = distribution_util.shapes_from_loc_and_scale(
239 @distribution_util.AppendDocstring(_mvn_sample_note)
243 @distribution_util.AppendDocstring(_mvn_sample_note)
275 if distribution_util.is_diagonal_scale(self.scale):
281 if distribution_util.is_diagonal_scale(self.scale):
292 if distribution_util.is_diagonal_scale(self.scale):
Dvector_exponential_linear_operator.py22 from tensorflow.contrib.distributions.python.ops import distribution_util
198 batch_shape, event_shape = distribution_util.shapes_from_loc_and_scale(
222 @distribution_util.AppendDocstring(_mvn_sample_note)
226 @distribution_util.AppendDocstring(_mvn_sample_note)
251 if distribution_util.is_diagonal_scale(self.scale):
257 if distribution_util.is_diagonal_scale(self.scale):
268 if distribution_util.is_diagonal_scale(self.scale):
Dnegative_binomial.py29 from tensorflow.python.ops.distributions import util as distribution_util unknown
104 self._logits, self._probs = distribution_util.get_logits_and_probs(
164 seed=distribution_util.gen_new_seed(seed, "negative_binom"))
168 x = distribution_util.embed_check_nonnegative_integer_form(x)
178 x = distribution_util.embed_check_nonnegative_integer_form(x)
184 x = distribution_util.embed_check_nonnegative_integer_form(x)
Dbinomial.py29 from tensorflow.python.ops.distributions import util as distribution_util unknown
188 self._logits, self._probs = distribution_util.get_logits_and_probs(
235 @distribution_util.AppendDocstring(_binomial_sample_note)
239 @distribution_util.AppendDocstring(_binomial_sample_note)
272 @distribution_util.AppendDocstring(
287 distribution_util.assert_integer_form(
296 counts = distribution_util.embed_check_nonnegative_integer_form(counts)
Dmvn_linear_operator.py21 from tensorflow.contrib.distributions.python.ops import distribution_util
193 batch_shape, event_shape = distribution_util.shapes_from_loc_and_scale(
218 @distribution_util.AppendDocstring(_mvn_sample_note)
222 @distribution_util.AppendDocstring(_mvn_sample_note)
246 if distribution_util.is_diagonal_scale(self.scale):
252 if distribution_util.is_diagonal_scale(self.scale):
263 if distribution_util.is_diagonal_scale(self.scale):
Dquantized_distribution.py29 from tensorflow.python.ops.distributions import util as distribution_util unknown
378 @distribution_util.AppendDocstring(_log_prob_note)
417 @distribution_util.AppendDocstring(_prob_note)
447 @distribution_util.AppendDocstring(_log_cdf_note)
479 @distribution_util.AppendDocstring(_cdf_note)
513 @distribution_util.AppendDocstring(_log_sf_note)
546 @distribution_util.AppendDocstring(_sf_note)
585 dependencies = [distribution_util.assert_integer_form(
Dvector_sinh_arcsinh_diag.py22 from tensorflow.contrib.distributions.python.ops import distribution_util
198 scale_linop = distribution_util.make_diag_scale(
204 batch_shape, event_shape = distribution_util.shapes_from_loc_and_scale(
216 asserts = distribution_util.maybe_check_scalar_distribution(
Dinverse_gamma.py34 from tensorflow.python.ops.distributions import util as distribution_util unknown
192 @distribution_util.AppendDocstring(
227 @distribution_util.AppendDocstring(
247 @distribution_util.AppendDocstring(
269 @distribution_util.AppendDocstring(
Dgeometric.py33 from tensorflow.python.ops.distributions import util as distribution_util unknown
99 self._logits, self._probs = distribution_util.get_logits_and_probs(
157 x = distribution_util.embed_check_nonnegative_integer_form(x)
170 x = distribution_util.embed_check_nonnegative_integer_form(x)
Dvector_student_t.py22 from tensorflow.contrib.distributions.python.ops import distribution_util
222 distribution_util.shapes_from_loc_and_scale(
224 override_batch_shape = distribution_util.pick_vector(
Dsinh_arcsinh.py22 from tensorflow.contrib.distributions.python.ops import distribution_util
158 batch_shape = distribution_util.get_broadcast_shape(
172 asserts = distribution_util.maybe_check_scalar_distribution(
Dshape.py29 from tensorflow.python.ops.distributions import util as distribution_util unknown
401 event_shape = distribution_util.pick_vector(
404 batch_shape = distribution_util.pick_vector(
409 x = distribution_util.rotate_transpose(x, shift=-1)
441 x = distribution_util.rotate_transpose(x, shift=1)
Dpoisson_lognormal.py23 from tensorflow.contrib.distributions.python.ops import distribution_util
373 distribution_util.pick_vector(
377 seed=distribution_util.gen_new_seed(
383 distribution_util.pick_vector(
456 args_ = [distribution_util.static_value(x) for x in args]
/external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/
Dconditional_bijector.py22 from tensorflow.python.ops.distributions import util as distribution_util unknown
31 @distribution_util.AppendDocstring(kwargs_dict={
37 @distribution_util.AppendDocstring(kwargs_dict={
43 @distribution_util.AppendDocstring(kwargs_dict={
52 @distribution_util.AppendDocstring(kwargs_dict={
Dsoftplus.py27 from tensorflow.python.ops.distributions import util as distribution_util unknown
79 @distribution_util.AppendDocstring(
124 return distribution_util.softplus_inverse(y)
126 return hinge_softness * distribution_util.softplus_inverse(
/external/tensorflow/tensorflow/python/ops/distributions/
Ddirichlet_multinomial.py30 from tensorflow.python.ops.distributions import util as distribution_util unknown
216 distribution_util.embed_check_nonnegative_integer_form(
274 seed=distribution_util.gen_new_seed(seed, salt="dirichlet_multinomial"))
280 @distribution_util.AppendDocstring(_dirichlet_multinomial_sample_note)
286 return ordered_prob + distribution_util.log_combinations(
289 @distribution_util.AppendDocstring(_dirichlet_multinomial_sample_note)
297 @distribution_util.AppendDocstring(
338 concentration = distribution_util.embed_check_categorical_event_shape(
350 counts = distribution_util.embed_check_nonnegative_integer_form(counts)
Dmultinomial.py31 from tensorflow.python.ops.distributions import util as distribution_util unknown
199 distribution_util.embed_check_nonnegative_integer_form(
201 self._logits, self._probs = distribution_util.get_logits_and_probs(
279 @distribution_util.AppendDocstring(_multinomial_sample_note)
289 return -distribution_util.log_combinations(self.total_count, counts)
311 counts = distribution_util.embed_check_nonnegative_integer_form(counts)
Dbeta.py35 from tensorflow.python.ops.distributions import util as distribution_util unknown
257 seed=distribution_util.gen_new_seed(seed, "beta"))
261 @distribution_util.AppendDocstring(_beta_sample_note)
265 @distribution_util.AppendDocstring(_beta_sample_note)
269 @distribution_util.AppendDocstring(_beta_sample_note)
273 @distribution_util.AppendDocstring(_beta_sample_note)
301 @distribution_util.AppendDocstring(
Dcategorical.py31 from tensorflow.python.ops.distributions import util as distribution_util unknown
195 self._logits, self._probs = distribution_util.get_logits_and_probs(
203 self._logits = distribution_util.embed_check_categorical_event_shape(
287 k = distribution_util.embed_check_integer_casting_closed(
309 k = distribution_util.embed_check_integer_casting_closed(
Ddirichlet.py32 from tensorflow.python.ops.distributions import util as distribution_util unknown
238 @distribution_util.AppendDocstring(_dirichlet_sample_note)
242 @distribution_util.AppendDocstring(_dirichlet_sample_note)
282 @distribution_util.AppendDocstring(
/external/tensorflow/tensorflow/contrib/distributions/
D__init__.py38 from tensorflow.contrib.distributions.python.ops.distribution_util import fill_triangular
39 from tensorflow.contrib.distributions.python.ops.distribution_util import fill_triangular_inverse
40 from tensorflow.contrib.distributions.python.ops.distribution_util import matrix_diag_transform
41 …from tensorflow.contrib.distributions.python.ops.distribution_util import reduce_weighted_logsumexp
42 from tensorflow.contrib.distributions.python.ops.distribution_util import softplus_inverse
43 from tensorflow.contrib.distributions.python.ops.distribution_util import tridiag

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