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Searched refs:grads_and_vars (Results 1 – 25 of 40) sorted by relevance

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/external/tensorflow/tensorflow/contrib/kfac/python/ops/
Doptimizer.py193 def apply_gradients(self, grads_and_vars, *args, **kwargs): argument
207 grads_and_vars = list(grads_and_vars)
210 steps_and_vars = self._compute_update_steps(grads_and_vars)
216 def _squared_fisher_norm(self, grads_and_vars, precon_grads_and_vars): argument
236 for (_, gvar), (_, pgvar) in zip(grads_and_vars, precon_grads_and_vars):
242 for (grad, _), (pgrad, _) in zip(grads_and_vars, precon_grads_and_vars)
246 def _update_clip_coeff(self, grads_and_vars, precon_grads_and_vars): argument
271 sq_norm_grad = self._squared_fisher_norm(grads_and_vars,
277 def _clip_updates(self, grads_and_vars, precon_grads_and_vars): argument
296 coeff = self._update_clip_coeff(grads_and_vars, precon_grads_and_vars)
[all …]
/external/tensorflow/tensorflow/contrib/estimator/python/estimator/
Dextenders.py127 def clip_grads(grads_and_vars): argument
128 gradients, variables = zip(*grads_and_vars)
130 grads_and_vars = list(zip(gradients, variables))
131 return grads_and_vars
286 def apply_gradients(self, grads_and_vars, global_step=None, name=None): argument
306 grads_and_vars = self._transform_grads_fn(grads_and_vars)
307 return self._optimizer.apply_gradients(grads_and_vars, global_step, name)
Dreplicate_model_fn.py304 def apply_gradients(self, grads_and_vars, global_step=None, **kwargs): argument
312 return self._get_optimizer().apply_gradients(grads_and_vars, global_step,
315 self._graph_state().collect_gradients(grads_and_vars)
318 with ops_lib.control_dependencies(_extract_tensors(grads_and_vars)):
391 def collect_gradients(self, grads_and_vars): argument
393 grads_and_vars)
397 grads_and_vars = []
401 grads_and_vars.extend(
403 return grads_and_vars
/external/tensorflow/tensorflow/contrib/kfac/python/kernel_tests/
Doptimizer_test.py80 grads_and_vars = [(array_ops.constant([[1., 2.], [3., 4.]]), None),
85 sq_norm = opt._squared_fisher_norm(grads_and_vars, pgrads_and_vars)
90 grads_and_vars = [(array_ops.constant([[1., 2.], [3., 4.]]), None),
103 coeff = opt._update_clip_coeff(grads_and_vars, pgrads_and_vars)
110 coeff = opt._update_clip_coeff(grads_and_vars, pgrads_and_vars)
111 sq_norm_pgrad = opt._squared_fisher_norm(grads_and_vars, pgrads_and_vars)
189 grads_and_vars = opt.compute_gradients(output, [weights, bias])
190 all_vars = [grad_and_var[1] for grad_and_var in grads_and_vars]
192 op = opt.apply_gradients(grads_and_vars)
/external/tensorflow/tensorflow/contrib/layers/python/layers/
Doptimizers.py305 def _clip_gradients_by_norm(grads_and_vars, clip_gradients): argument
307 gradients, variables = zip(*grads_and_vars)
374 def gradient_clipping(grads_and_vars): argument
376 grads, variables = zip(*grads_and_vars)
412 def _add_scaled_noise_to_gradients(grads_and_vars, gradient_noise_scale): argument
414 gradients, variables = zip(*grads_and_vars)
429 def _multiply_gradients(grads_and_vars, gradient_multipliers): argument
432 for grad, var in grads_and_vars:
Doptimizers_test.py439 grads_and_vars = [(grad, grad)]
440 grads_and_vars = optimizers_lib.adaptive_clipping_fn(
441 decay=0.5)(grads_and_vars)
456 [moving_mean, moving_sq_mean, grads_and_vars[0][0]])
471 grads_and_vars = [(grad, grad)]
472 grads_and_vars = optimizers_lib.adaptive_clipping_fn(
473 decay=0.9, global_step=step)(grads_and_vars)
478 return session.run(grads_and_vars[0][0],
/external/tensorflow/tensorflow/python/training/
Doptimizer.py388 grads_and_vars = self.compute_gradients(
394 vars_with_grad = [v for g, v in grads_and_vars if g is not None]
399 ([str(v) for _, v in grads_and_vars], loss))
401 return self.apply_gradients(grads_and_vars, global_step=global_step,
488 grads_and_vars = list(zip(grads, var_list))
490 [v for g, v in grads_and_vars
492 return grads_and_vars
494 def apply_gradients(self, grads_and_vars, global_step=None, name=None): argument
520 grads_and_vars = tuple(grads_and_vars) # Make sure repeat iteration works.
521 if not grads_and_vars:
[all …]
Doptimizer_test.py190 grads_and_vars = sgd_op.compute_gradients(loss, [var0, var1])
195 for j, gv in enumerate(grads_and_vars)
199 for j, gv in enumerate(grads_and_vars)
224 grads_and_vars = sgd_op.compute_gradients(f, [x])
225 self.assertEqual(1, len(grads_and_vars))
226 grad, x_as_var = grads_and_vars[0]
231 sgd_op.apply_gradients(grads_and_vars)
Dsync_replicas_optimizer.py211 def apply_gradients(self, grads_and_vars, global_step=None, name=None): argument
234 if not grads_and_vars:
262 for grad, var in grads_and_vars:
Dgradient_descent_test.py164 grads_and_vars = opt.compute_gradients(vars_[0] + vars_[1], vars_)
166 for grad, _ in grads_and_vars:
/external/tensorflow/tensorflow/contrib/training/python/training/
Dtraining.py271 def add_gradients_summaries(grads_and_vars): argument
281 for grad, var in grads_and_vars:
327 def multiply_gradients(grads_and_vars, gradient_multipliers): argument
342 if not isinstance(grads_and_vars, list):
350 for grad, var in grads_and_vars:
/external/tensorflow/tensorflow/contrib/opt/python/training/
Ddrop_stale_gradient_optimizer.py78 def apply_gradients(self, grads_and_vars, global_step=None, name=None): argument
90 grads_and_vars, global_step=global_step, name=name)]):
96 for grad_and_var in grads_and_vars:
Dmoving_average_optimizer.py92 def apply_gradients(self, grads_and_vars, global_step=None, name=None): argument
94 grads_and_vars, global_step=global_step, name=name)
95 var_list = [x[1] for x in grads_and_vars if x[0] is not None]
Dvariable_clipping_optimizer.py92 def apply_gradients(self, grads_and_vars, global_step=None, name=None): argument
95 grads_and_vars, global_step=global_step)
98 for grad, var in grads_and_vars:
Dmodel_average_optimizer.py178 def apply_gradients(self, grads_and_vars, global_step=None, name=None): argument
204 if not grads_and_vars:
209 apply_updates = self._opt.apply_gradients(grads_and_vars)
216 local_vars = [v for g, v in grads_and_vars if g is not None]
Delastic_average_optimizer.py222 def apply_gradients(self, grads_and_vars, global_step=None, name=None): argument
244 apply_updates = self._opt.apply_gradients(grads_and_vars)
251 local_vars = [v for g, v in grads_and_vars if g is not None]
Daddsign.py92 def apply_gradients(self, grads_and_vars, global_step=None, name=None): argument
97 grads_and_vars, global_step=global_step, name=name)
Dpowersign.py94 def apply_gradients(self, grads_and_vars, global_step=None, name=None): argument
99 grads_and_vars, global_step=global_step, name=name)
/external/tensorflow/tensorflow/contrib/slim/python/slim/
Dlearning.py302 def multiply_gradients(grads_and_vars, gradient_multipliers): argument
317 if not isinstance(grads_and_vars, list):
325 for grad, var in grads_and_vars:
344 def add_gradients_summaries(grads_and_vars): argument
354 for grad, var in grads_and_vars:
/external/tensorflow/tensorflow/contrib/tpu/python/tpu/
Dtpu_optimizer.py87 def apply_gradients(self, grads_and_vars, global_step=None, name=None): argument
109 for (grad, var) in grads_and_vars:
/external/tensorflow/tensorflow/python/eager/
Dbackprop_test.py94 grads_and_vars = backprop.implicit_grad(fn)()
95 self.assertAllEqual(grads_and_vars[0][0], 1.0)
96 self.assertAllEqual(id(grads_and_vars[0][1]), id(x))
610 grads_and_vars = g()
611 self.assertEqual(1, len(grads_and_vars))
612 grad, var = grads_and_vars[0]
637 loss, grads_and_vars = loss_grads_fn(x)
639 for (grad, var) in grads_and_vars:
Dgraph_callable_test.py244 grads_and_vars = list(zip(*grad_fn()))
245 self.assertAllEqual(6., grads_and_vars[0][0])
/external/tensorflow/tensorflow/contrib/bayesflow/python/kernel_tests/
Dsgld_optimizer_test.py144 grads_and_vars = opt.compute_gradients(vars_[0] + vars_[1], vars_)
146 for grad, _ in grads_and_vars:
Dvariational_sgd_optimizer_test.py194 grads_and_vars = opt.compute_gradients(vars_[0] + vars_[1], vars_)
196 for grad, _ in grads_and_vars:
/external/tensorflow/tensorflow/tools/api/golden/
Dtensorflow.train.-adagrad-optimizer.pbtxt26 …argspec: "args=[\'self\', \'grads_and_vars\', \'global_step\', \'name\'], varargs=None, keywords=N…

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