| /external/tensorflow/tensorflow/contrib/optimizer_v2/ |
| adadelta.py | 59 state.zeros_slot(v, "accum_update")
63 accum_update = state.get_slot(var, "accum_update")
67 accum_update,
76 accum_update = state.get_slot(var, "accum_update")
80 accum_update.handle,
89 accum_update = state.get_slot(var, "accum_update")
93 accum_update,
[all...] |
| adadelta_test.py | 55 accum_update = 0.0
76 self.assertEqual(["accum", "accum_update"],
82 slot_update[0] = adadelta_opt.get_slot(var0, "accum_update")
90 slot_update[1] = adadelta_opt.get_slot(var1, "accum_update")
106 update[step] = (np.sqrt(accum_update + epsilon) *
108 accum_update = (accum_update * rho + (update[step]**2) *
121 [accum_update, accum_update],
|
| /external/tensorflow/tensorflow/python/training/ |
| adadelta.py | 70 self._zeros_slot(v, "accum_update", self._name)
83 accum_update = self.get_slot(var, "accum_update")
87 accum_update,
96 accum_update = self.get_slot(var, "accum_update")
100 accum_update.handle,
109 accum_update = self.get_slot(var, "accum_update")
113 accum_update,
[all...] |
| adadelta_test.py | 56 accum_update = 0.0
86 self.assertEqual(["accum", "accum_update"],
92 slot_update[0] = adadelta_opt.get_slot(var0, "accum_update")
100 slot_update[1] = adadelta_opt.get_slot(var1, "accum_update")
120 np.sqrt(accum_update + epsilon) *
122 accum_update = (
123 accum_update * rho + (update[step]**2) * (1.0 - rho))
137 [accum_update, accum_update],
|
| training_ops_test.py | 109 accum_update = y + grad * grad
110 linear_update = z + grad - (accum_update**(-lr_power) - y**
112 quadratic = 1.0 / (accum_update**(lr_power) * lr) + 2 * l2
117 self.assertAllCloseAccordingToType(accum_update, self.evaluate(accum))
|
| /external/tensorflow/tensorflow/compiler/tests/ |
| adadelta_test.py | 57 accum_update = 0.0
76 self.assertEqual(["accum", "accum_update"],
82 slot_update[0] = adadelta_opt.get_slot(var0, "accum_update")
90 slot_update[1] = adadelta_opt.get_slot(var1, "accum_update")
107 np.sqrt(accum_update + epsilon) *
109 accum_update = (
110 accum_update * rho + (update[step]**2) * (1.0 - rho))
121 np.array([accum_update, accum_update], dtype=dtype),
|
| /external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
| adadelta_test.py | 56 accum_update = 0.0
105 np.sqrt(accum_update + epsilon) *
107 accum_update = (
108 accum_update * rho + (update[step]**2) * (1.0 - rho))
122 [accum_update, accum_update],
|
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| training_ops.cc | 818 xla::XlaOp var, accum, accum_update; variable
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| training_ops_gpu.cu.cc | 60 typename TTypes<T>::Flat accum_update,
73 (accum_update + epsilon.reshape(single).broadcast(bcast)).sqrt() *
76 accum_update.device(d) =
77 accum_update * rho.reshape(single).broadcast(bcast) +
|
| training_ops.cc | 71 typename TTypes<T>::Flat accum_update,
79 (accum_update + epsilon()).sqrt() * (accum + epsilon()).rsqrt() * grad;
81 accum_update.device(d) =
82 accum_update * rho() + update.square() * (static_cast<T>(1) - rho());
636 Tensor accum_update; local
639 sparse, &accum_update));
650 ctx, accum_update.IsInitialized(),
692 Tensor accum_update; local
695 sparse, &accum_update));
703 device, var.flat<T>(), accum.flat<T>(), accum_update.flat<T>()
784 Tensor accum_update; local
[all...] |
| training_ops.h | 41 typename TTypes<T>::Flat accum_update,
|
