| /external/tensorflow/tensorflow/python/ops/distributions/ |
| D | bijector_impl.py | 831 y, ildj, self.inverse_min_event_ndims, event_ndims)
832 for ildj in ildjs)
848 ildj = self._inverse_log_det_jacobian(y, **kwargs)
849 ildj = self._reduce_jacobian_det_over_event(
850 y, ildj, self.inverse_min_event_ndims, event_ndims)
855 ildj = -self._forward_log_det_jacobian(x, **kwargs)
856 ildj = self._reduce_jacobian_det_over_event(
857 x, ildj, self.forward_min_event_ndims, event_ndims)
861 mapping = mapping.merge(x=x, ildj_map={event_ndims: ildj})
864 self._constant_ildj_map[event_ndims] = ildj
[all …]
|
| D | transformed_distribution.py | 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)
436 for x_i, ildj_i in zip(x, ildj)]
439 def _finish_log_prob_for_one_fiber(self, y, x, ildj, event_ndims): argument
445 log_prob += math_ops.cast(ildj, log_prob.dtype)
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)
462 for x_i, ildj_i in zip(x, ildj)]
465 def _finish_prob_for_one_fiber(self, y, x, ildj, event_ndims): argument
471 prob *= math_ops.exp(math_ops.cast(ildj, prob.dtype))
[all …]
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| D | conditional_transformed_distribution.py | 109 ildj = self.bijector.inverse_log_det_jacobian(
112 return self._finish_log_prob_for_one_fiber(y, x, ildj,
117 for x_i, ildj_i in zip(x, ildj)]
120 def _finish_log_prob_for_one_fiber(self, y, x, ildj, distribution_kwargs): argument
126 return math_ops.cast(ildj, log_prob.dtype) + log_prob
134 ildj = self.bijector.inverse_log_det_jacobian(
137 return self._finish_prob_for_one_fiber(y, x, ildj, distribution_kwargs)
141 for x_i, ildj_i in zip(x, ildj)]
144 def _finish_prob_for_one_fiber(self, y, x, ildj, distribution_kwargs): argument
150 return math_ops.exp(math_ops.cast(ildj, prob.dtype)) * prob
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ |
| D | affine_linear_operator_test.py | 36 ildj = 0.
41 self.assertAllClose(ildj, affine.inverse_log_det_jacobian(
58 ildj = -np.sum(np.log(np.abs(diag)), axis=-1)
64 ildj, affine.inverse_log_det_jacobian(y, event_ndims=1).eval())
91 ildj = -np.sum(np.log(np.abs(np.diagonal(
98 ildj, affine.inverse_log_det_jacobian(
|
| D | matrix_inverse_tril_test.py | 56 ildj = inv.inverse_log_det_jacobian(x_inv_, event_ndims=2)
58 y_, x_back_, fldj_, ildj_ = self.evaluate([y, x_back, fldj, ildj])
74 ildj = inv.inverse_log_det_jacobian(x_inv_, event_ndims=2)
76 y_, x_back_, fldj_, ildj_ = self.evaluate([y, x_back, fldj, ildj])
92 ildj = inv.inverse_log_det_jacobian(x_inv_, event_ndims=2)
94 y_, x_back_, fldj_, ildj_ = self.evaluate([y, x_back, fldj, ildj])
116 ildj = inv.inverse_log_det_jacobian(x_inv_, event_ndims=2)
118 y_, x_back_, fldj_, ildj_ = self.evaluate([y, x_back, fldj, ildj])
|
| D | softsign_test.py | 71 ildj = self._softsign_ildj_before_reduction(y)
73 self.assertAllClose(ildj, self.evaluate(
90 ildj = np.sum(ildj_before, axis=1)
92 ildj, self.evaluate(
|
| D | sigmoid_test.py | 38 ildj = -np.log(y) - np.log1p(-y)
42 self.assertAllClose(ildj, bijector.inverse_log_det_jacobian(
44 self.assertAllClose(-ildj, bijector.forward_log_det_jacobian(
|
| D | softplus_test.py | 74 ildj = self._softplus_ildj_before_reduction(y)
76 self.assertAllClose(ildj, bijector.inverse_log_det_jacobian(
94 ildj = np.sum(ildj_before, axis=1)
96 self.assertAllClose(ildj, bijector.inverse_log_det_jacobian(
|
| D | square_test.py | 40 ildj = -np.log(2.) - np.log(x)
44 ildj, bijector.inverse_log_det_jacobian(
|
| D | transform_diagonal_test.py | 52 ildj = self.evaluate(b.inverse_log_det_jacobian(y, event_ndims=2))
59 ildj,
|
| D | scale_tril_test.py | 65 ildj = self.evaluate(b.inverse_log_det_jacobian(y, event_ndims=2))
66 self.assertAllClose(fldj, -ildj)
|
| D | affine_test.py | 563 ildj = -np.log(np.abs(np.linalg.det(scale)))
567 if (ildj.ndim > 0 and (len(scale_args) == 1 or (
570 ildj = np.squeeze(ildj[0])
571 elif ildj.ndim < scale.ndim - 2:
572 ildj = np.reshape(ildj, scale.shape[0:-2])
574 ildj, bijector.inverse_log_det_jacobian(x, event_ndims=1).eval())
|
| D | permute_test.py | 51 ildj,
64 self.assertAllClose(0., ildj, rtol=1e-6, atol=0)
|
| D | fill_triangular_test.py | 51 ildj = self.evaluate(b.inverse_log_det_jacobian(y, event_ndims=2))
52 self.assertAllClose(ildj, 0.)
|
| D | real_nvp_test.py | 58 ildj = nvp.inverse_log_det_jacobian(
71 ildj,
|
| D | masked_autoregressive_test.py | 84 ildj = ma.inverse_log_det_jacobian(
95 ildj,
|
| D | chain_test.py | 196 ildj = chain.inverse_log_det_jacobian(samples, event_ndims=0)
197 self.assertTrue(ildj is not None)
199 ildj.eval({samples: np.zeros([2, 10], np.float32)})
|
| D | cholesky_outer_product_test.py | 45 ildj = -np.sum(
54 ildj, bijector.inverse_log_det_jacobian(
|
| D | batch_normalization_test.py | 89 ildj = batch_norm.inverse_log_det_jacobian(
106 ildj,
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| D | chain.py | 257 ildj = math_ops.cast(0., dtype=y.dtype.base_dtype)
260 return ildj
271 ildj += b.inverse_log_det_jacobian(
286 return ildj
|
| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| D | bijector_test.py | 313 ildj = sess.run(bij.inverse_log_det_jacobian(x, event_ndims=event_ndims),
315 self.assertAllClose(-np.log(x_), ildj)
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| D | vector_student_t_test.py | 53 ildj = np.sum(np.log(np.abs(np.diag(scale_tril))), axis=-1)
54 logz = ildj + k * (0.5 * np.log(df) +
|
| D | transformed_distribution_test.py | 288 ildj = np.log(2.)
289 self.assertAllClose(base_log_prob - ildj, log_prob_, rtol=1e-6, atol=0.)
|