Searched refs:batch_jacobian (Results 1 – 12 of 12) sorted by relevance
106 pfor_jacobian = gradients.batch_jacobian(output, inp, use_pfor=True)107 while_jacobian = gradients.batch_jacobian(output, inp, use_pfor=False)114 pfor_jacobian = gradients.batch_jacobian(output, inp, use_pfor=True)115 while_jacobian = gradients.batch_jacobian(output, inp, use_pfor=False)122 pfor_jacobian = gradients.batch_jacobian(final_state.c, inp, use_pfor=True)135 pfor_jacobian = gradients.batch_jacobian(output, inp, use_pfor=True)137 pfor_hessian = gradients.batch_jacobian(pfor_jacobian, inp, use_pfor=True)141 while_hessian = gradients.batch_jacobian(while_jacobian, inp, use_pfor=False)308 pfor_jacobian = gradients.batch_jacobian(logits, images, use_pfor=True)309 while_jacobian = gradients.batch_jacobian(logits, images, use_pfor=False)[all …]
24 from tensorflow.python.ops.parallel_for.gradients import batch_jacobian
83 def batch_jacobian(output, inp, use_pfor=True, parallel_iterations=None): function
873 self.assertAllClose([[[4. * 3. ** 3.]]], g.batch_jacobian(z, x))882 g.batch_jacobian(z, x)885 g.batch_jacobian(y, [x])1760 dy_xx = g.batch_jacobian(dy_x, x)1770 return tape.batch_jacobian(primal_out, primal)1801 return math_ops.reduce_sum(tape.batch_jacobian(reduced, x))1894 batch_jacobian = g.batch_jacobian(1899 return batch_jacobian, answer1902 batch_jacobian, answer = self._batch_jacobian(experimental_use_pfor=True)1903 self.assertAllEqual(answer, batch_jacobian)[all …]
1206 def batch_jacobian(self, member in GradientTape
368 batch_jacobian = g.batch_jacobian(z, x)373 self.assertIsInstance(batch_jacobian, np.ndarray)374 self.assertAllClose(batch_jacobian, answer)
10 name: "batch_jacobian"
99 return tape.batch_jacobian(y, x)
193 def batch_jacobian(self, member in LossScaleGradientTape
536 g.batch_jacobian(y, x)