| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| D | shape_test.py | 52 def _get_expected(self, x, batch_ndims, event_ndims, expand_batch_dim): argument
56 n = x.ndim - batch_ndims - event_ndims
60 if event_ndims == 0:
66 def _build_graph(self, x, batch_ndims, event_ndims, expand_batch_dim): argument
68 event_ndims=event_ndims)
75 def _test_dynamic(self, x, batch_ndims, event_ndims, expand_batch_dim=True): argument
86 event_ndims_pl: event_ndims})
88 x, batch_ndims, event_ndims, expand_batch_dim)
93 def _test_static(self, x, batch_ndims, event_ndims, expand_batch_dim): argument
96 self._build_graph(x, batch_ndims, event_ndims, expand_batch_dim))
[all …]
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| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| D | bijector_test.py | 78 bij.inverse_log_det_jacobian(0, event_ndims=0)
82 bij.forward_log_det_jacobian(0, event_ndims=0)
124 bij.forward_log_det_jacobian(1., event_ndims=1.5)
126 bij.inverse_log_det_jacobian(1., event_ndims=1.5)
131 bij.forward_log_det_jacobian(1., event_ndims=(1, 2))
133 bij.inverse_log_det_jacobian(1., event_ndims=(1, 2))
138 event_ndims = array_ops.placeholder(dtype=np.int32, shape=None)
141 bij.forward_log_det_jacobian(1., event_ndims=event_ndims).eval({
142 event_ndims: (1, 2)})
144 bij.inverse_log_det_jacobian(1., event_ndims=event_ndims).eval({
[all …]
|
| /external/tensorflow/tensorflow/python/ops/distributions/ |
| D | bijector_impl.py | 818 def _call_inverse_log_det_jacobian(self, y, event_ndims, name, **kwargs): argument
820 if event_ndims in self._constant_ildj_map:
821 return self._constant_ildj_map[event_ndims]
826 event_ndims=event_ndims)):
831 y, ildj, self.inverse_min_event_ndims, event_ndims)
838 x, -fldj, self.forward_min_event_ndims, event_ndims)
844 if mapping.ildj_map is not None and event_ndims in mapping.ildj_map:
845 return mapping.ildj_map[event_ndims]
850 y, ildj, self.inverse_min_event_ndims, event_ndims)
857 x, ildj, self.forward_min_event_ndims, event_ndims)
[all …]
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| D | bijector_test_util.py | 115 uniform_y_samps, event_ndims=0))
126 bijector.inverse(uniform_y_samps), event_ndims=0))
164 bijector, x, y, event_ndims, atol=0, rtol=1e-5, sess=None): argument
205 bijector.inverse_log_det_jacobian(f_x, event_ndims=event_ndims),
206 bijector.forward_log_det_jacobian(x, event_ndims=event_ndims),
207 bijector.inverse_log_det_jacobian(y, event_ndims=event_ndims),
208 bijector.forward_log_det_jacobian(g_y, event_ndims=event_ndims),
|
| D | transformed_distribution.py | 428 event_ndims = self._maybe_get_static_event_ndims()
430 ildj = self.bijector.inverse_log_det_jacobian(y, event_ndims=event_ndims)
432 return self._finish_log_prob_for_one_fiber(y, x, ildj, event_ndims)
435 self._finish_log_prob_for_one_fiber(y, x_i, ildj_i, event_ndims)
439 def _finish_log_prob_for_one_fiber(self, y, x, ildj, event_ndims): argument
446 if self._is_maybe_event_override and isinstance(event_ndims, int):
449 y.get_shape().with_rank_at_least(1)[:-event_ndims],
455 event_ndims = self._maybe_get_static_event_ndims()
456 ildj = self.bijector.inverse_log_det_jacobian(y, event_ndims=event_ndims)
458 return self._finish_prob_for_one_fiber(y, x, ildj, event_ndims)
[all …]
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| D | chain.py | 262 event_ndims = self._maybe_get_static_event_ndims(
265 if _use_static_shape(y, event_ndims):
266 event_shape = y.shape[y.shape.ndims - event_ndims:]
268 event_shape = array_ops.shape(y)[array_ops.rank(y) - event_ndims:]
272 y, event_ndims=event_ndims, **kwargs.get(b.name, {}))
274 if _use_static_shape(y, event_ndims):
276 event_ndims = self._maybe_get_static_event_ndims(
280 event_ndims = array_ops.size(event_shape)
281 event_ndims_ = self._maybe_get_static_event_ndims(event_ndims)
283 event_ndims = event_ndims_
[all …]
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| D | conditional_bijector.py | 47 self, y, event_ndims, name="inverse_log_det_jacobian", argument
50 y, event_ndims, name, **condition_kwargs)
56 self, x, event_ndims, name="forward_log_det_jacobian", argument
59 x, event_ndims, name, **condition_kwargs)
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ |
| D | matrix_inverse_tril_test.py | 55 fldj = inv.forward_log_det_jacobian(x_, event_ndims=2)
56 ildj = inv.inverse_log_det_jacobian(x_inv_, event_ndims=2)
73 fldj = inv.forward_log_det_jacobian(x_, event_ndims=2)
74 ildj = inv.inverse_log_det_jacobian(x_inv_, event_ndims=2)
91 fldj = inv.forward_log_det_jacobian(x_, event_ndims=2)
92 ildj = inv.inverse_log_det_jacobian(x_inv_, event_ndims=2)
115 fldj = inv.forward_log_det_jacobian(x_, event_ndims=2)
116 ildj = inv.inverse_log_det_jacobian(x_inv_, event_ndims=2)
134 self.evaluate(inv.forward_log_det_jacobian(x_, event_ndims=2))
136 self.evaluate(inv.inverse_log_det_jacobian(x_, event_ndims=2))
[all …]
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| D | affine_linear_operator_test.py | 42 y, event_ndims=2).eval())
44 -affine.inverse_log_det_jacobian(y, event_ndims=2).eval(),
45 affine.forward_log_det_jacobian(x, event_ndims=2).eval())
64 ildj, affine.inverse_log_det_jacobian(y, event_ndims=1).eval())
66 -affine.inverse_log_det_jacobian(y, event_ndims=1).eval(),
67 affine.forward_log_det_jacobian(x, event_ndims=1).eval())
99 y, event_ndims=2).eval())
101 -affine.inverse_log_det_jacobian(y, event_ndims=2).eval(),
102 affine.forward_log_det_jacobian(x, event_ndims=2).eval())
|
| D | affine_test.py | 71 0., run(bijector.inverse_log_det_jacobian, x, event_ndims=1))
97 run(bijector.inverse_log_det_jacobian, x, event_ndims=1))
114 run(bijector.inverse_log_det_jacobian, x, event_ndims=1))
136 sess.run(bijector.inverse_log_det_jacobian(x, event_ndims=1),
161 run(bijector.inverse_log_det_jacobian, x, event_ndims=1))
185 run(bijector.inverse_log_det_jacobian, x, event_ndims=1))
209 x, event_ndims=1), feed_dict))
235 run(bijector.inverse_log_det_jacobian, x, event_ndims=1))
261 run(bijector.inverse_log_det_jacobian, x, event_ndims=1))
285 run(bijector.inverse_log_det_jacobian, x, event_ndims=1))
[all …]
|
| D | softmax_centered_test.py | 47 softmax.inverse_log_det_jacobian(y, event_ndims=1).eval(),
51 -softmax.inverse_log_det_jacobian(y, event_ndims=1).eval(),
52 softmax.forward_log_det_jacobian(x, event_ndims=1).eval(),
70 softmax.inverse_log_det_jacobian(y, event_ndims=1).eval(
75 -softmax.inverse_log_det_jacobian(y, event_ndims=1).eval(
77 softmax.forward_log_det_jacobian(x, event_ndims=1).eval(
107 assert_bijective_and_finite(softmax, x, y, event_ndims=1)
|
| D | ordered_test.py | 49 self.evaluate(ordered.inverse_log_det_jacobian(y, event_ndims=1)),
53 self.evaluate(-ordered.inverse_log_det_jacobian(y, event_ndims=1)),
54 self.evaluate(ordered.forward_log_det_jacobian(x, event_ndims=1)),
72 ordered.inverse_log_det_jacobian(y, event_ndims=1).eval(
77 -ordered.inverse_log_det_jacobian(y, event_ndims=1).eval(
79 ordered.forward_log_det_jacobian(x, event_ndims=1).eval(
103 assert_bijective_and_finite(ordered, x, y, event_ndims=1)
|
| D | sinh_arcsinh_bijector_test.py | 53 bijector.inverse_log_det_jacobian(y, event_ndims=1).eval())
55 -bijector.inverse_log_det_jacobian(y, event_ndims=1).eval(),
56 bijector.forward_log_det_jacobian(x, event_ndims=1).eval(),
109 assert_bijective_and_finite(bijector, x, x, event_ndims=0, rtol=1e-3)
117 bijector, x, x, event_ndims=0, rtol=1e-3)
129 bijector, bounds, bounds, event_ndims=0, atol=2e-6)
169 bijector.inverse_log_det_jacobian(y, event_ndims=0).eval(),
173 -bijector.inverse_log_det_jacobian(y, event_ndims=0).eval(),
174 bijector.forward_log_det_jacobian(x, event_ndims=0).eval(),
|
| D | chain_test.py | 58 chain.inverse_log_det_jacobian(x, event_ndims=1).eval())
61 chain.forward_log_det_jacobian(x, event_ndims=1).eval())
72 0., chain.inverse_log_det_jacobian(x, event_ndims=1).eval())
74 0., chain.forward_log_det_jacobian(x, event_ndims=1).eval())
171 self.evaluate(chain.forward_log_det_jacobian(x, event_ndims=1)))
175 self.evaluate(chain.inverse_log_det_jacobian(y, event_ndims=1)))
186 self.evaluate(chain.forward_log_det_jacobian(x, event_ndims=1)))
190 self.evaluate(chain.inverse_log_det_jacobian(y, event_ndims=1)))
196 ildj = chain.inverse_log_det_jacobian(samples, event_ndims=0)
|
| D | exp_test.py | 43 y, event_ndims=1).eval())
46 np.exp(x), event_ndims=1).eval(),
48 x, event_ndims=1).eval())
61 assert_bijective_and_finite(bijector, x, y, event_ndims=0)
|
| D | transform_diagonal_test.py | 51 fldj = self.evaluate(b.forward_log_det_jacobian(x, event_ndims=2))
52 ildj = self.evaluate(b.inverse_log_det_jacobian(y, event_ndims=2))
57 event_ndims=1)))
62 event_ndims=1)))
|
| D | softplus_test.py | 77 y, event_ndims=0).eval())
97 y, event_ndims=1).eval())
123 bijector, x, y, event_ndims=0, rtol=1e-2, atol=1e-2)
131 bijector, x, y, event_ndims=0, rtol=1e-2, atol=1e-2)
139 bijector, x, y, event_ndims=0, rtol=1e-2, atol=1e-2)
151 bijector, x, y, event_ndims=0, rtol=1e-1, atol=1e-3)
|
| D | power_transform_test.py | 43 bijector.inverse_log_det_jacobian(y, event_ndims=1).eval())
45 -bijector.inverse_log_det_jacobian(y, event_ndims=1).eval(),
46 bijector.forward_log_det_jacobian(x, event_ndims=1).eval(),
61 assert_bijective_and_finite(bijector, x, y, event_ndims=0, rtol=1e-3)
|
| D | gumbel_test.py | 47 bijector.forward_log_det_jacobian(x, event_ndims=1).eval())
49 -bijector.inverse_log_det_jacobian(y, event_ndims=1).eval(),
50 bijector.forward_log_det_jacobian(x, event_ndims=1).eval(),
64 assert_bijective_and_finite(bijector, x, y, event_ndims=0, rtol=1e-3)
|
| D | kumaraswamy_bijector_test.py | 49 bijector.inverse_log_det_jacobian(x, event_ndims=1).eval())
51 -bijector.inverse_log_det_jacobian(x, event_ndims=1).eval(),
52 bijector.forward_log_det_jacobian(y, event_ndims=1).eval(),
73 assert_bijective_and_finite(bijector, x, y, event_ndims=0, rtol=1e-3)
|
| D | weibull_test.py | 49 bijector.forward_log_det_jacobian(x, event_ndims=0).eval())
51 -bijector.inverse_log_det_jacobian(y, event_ndims=0).eval(),
52 bijector.forward_log_det_jacobian(x, event_ndims=0).eval(),
70 assert_bijective_and_finite(bijector, x, y, event_ndims=0, rtol=1e-3)
|
| D | softsign_test.py | 49 self.evaluate(bijector.inverse_log_det_jacobian(-3., event_ndims=0))
54 self.evaluate(bijector.inverse_log_det_jacobian(3., event_ndims=0))
74 bijector.inverse_log_det_jacobian(y, event_ndims=0)))
93 bijector.inverse_log_det_jacobian(y, event_ndims=1)))
106 bijector, x, y, event_ndims=0, rtol=1e-3, atol=1e-3)
|
| D | invert_test.py | 49 fwd.forward_log_det_jacobian(x, event_ndims=1).eval(),
50 rev.inverse_log_det_jacobian(x, event_ndims=1).eval())
52 fwd.inverse_log_det_jacobian(x, event_ndims=1).eval(),
53 rev.forward_log_det_jacobian(x, event_ndims=1).eval())
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| D | shape.py | 180 event_ndims=None, argument
210 if event_ndims is None: raise ValueError("event_ndims cannot be None")
212 self._event_ndims = event_ndims
224 event_ndims, name="event_ndims"))
239 def event_ndims(self): member in _DistributionShape
281 self.event_ndims):
292 sample_ndims = ndims - self.batch_ndims - self.event_ndims
339 self.event_ndims, name="event_dims"))
372 slice_shape([sample_ndims, self.batch_ndims], self.event_ndims,
443 if self._is_all_constant_helper(self.batch_ndims, self.event_ndims):
[all …]
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| D | conditional_transformed_distribution.py | 108 event_ndims = self._maybe_get_static_event_ndims()
110 y, event_ndims=event_ndims, **bijector_kwargs)
133 event_ndims = self._maybe_get_static_event_ndims()
135 y, event_ndims=event_ndims, **bijector_kwargs)
226 event_ndims = array_ops.size(self.event_shape_tensor())
227 event_ndims_ = distribution_util.maybe_get_static_value(event_ndims)
232 return event_ndims
|