/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 …]
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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 …]
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/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
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/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(
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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])
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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(
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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(
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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(
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D | square_test.py | 40 ildj = -np.log(2.) - np.log(x) 44 ildj, bijector.inverse_log_det_jacobian(
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D | transform_diagonal_test.py | 52 ildj = self.evaluate(b.inverse_log_det_jacobian(y, event_ndims=2)) 59 ildj,
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D | scale_tril_test.py | 65 ildj = self.evaluate(b.inverse_log_det_jacobian(y, event_ndims=2)) 66 self.assertAllClose(fldj, -ildj)
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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())
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D | permute_test.py | 51 ildj, 64 self.assertAllClose(0., ildj, rtol=1e-6, atol=0)
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D | fill_triangular_test.py | 51 ildj = self.evaluate(b.inverse_log_det_jacobian(y, event_ndims=2)) 52 self.assertAllClose(ildj, 0.)
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D | real_nvp_test.py | 58 ildj = nvp.inverse_log_det_jacobian( 71 ildj,
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D | masked_autoregressive_test.py | 84 ildj = ma.inverse_log_det_jacobian( 95 ildj,
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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)})
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D | cholesky_outer_product_test.py | 45 ildj = -np.sum( 54 ildj, bijector.inverse_log_det_jacobian(
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D | batch_normalization_test.py | 89 ildj = batch_norm.inverse_log_det_jacobian( 106 ildj,
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/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
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/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)
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/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) +
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D | transformed_distribution_test.py | 288 ildj = np.log(2.) 289 self.assertAllClose(base_log_prob - ildj, log_prob_, rtol=1e-6, atol=0.)
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