| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| lazy_adam_gs_optimizer.py | 51 beta1_power, beta2_power = self._get_beta_accumulators()
53 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
58 lr = (lr_t * math_ops.sqrt(1 - beta2_power) / (1 - beta1_power))
84 beta1_power, beta2_power = self._get_beta_accumulators()
86 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
91 lr = (lr_t * math_ops.sqrt(1 - beta2_power) / (1 - beta1_power))
|
| lazy_adam_optimizer.py | 51 beta1_power, beta2_power = self._get_beta_accumulators()
53 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
58 lr = (lr_t * math_ops.sqrt(1 - beta2_power) / (1 - beta1_power))
84 beta1_power, beta2_power = self._get_beta_accumulators()
86 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
91 lr = (lr_t * math_ops.sqrt(1 - beta2_power) / (1 - beta1_power))
|
| nadam_optimizer.py | 38 beta1_power, beta2_power = self._get_beta_accumulators()
44 math_ops.cast(beta2_power, var.dtype.base_dtype),
56 beta1_power, beta2_power = self._get_beta_accumulators()
62 math_ops.cast(beta2_power, grad.dtype.base_dtype),
72 beta1_power, beta2_power = self._get_beta_accumulators()
74 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
79 lr = (lr_t * math_ops.sqrt(1 - beta2_power) / (1 - beta1_power))
|
| adam_gs_optimizer.py | 148 beta1_power, beta2_power = self._get_beta_accumulators()
154 math_ops.cast(beta2_power, var.dtype.base_dtype),
165 beta1_power, beta2_power = self._get_beta_accumulators()
171 math_ops.cast(beta2_power, grad.dtype.base_dtype),
180 beta1_power, beta2_power = self._get_beta_accumulators()
182 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
187 lr = (lr_t * math_ops.sqrt(1 - beta2_power) / (1 - beta1_power))
|
| adam_gs_optimizer_test.py | 94 beta1_power, beta2_power = opt._get_beta_accumulators()
100 self.evaluate(beta2_power))
206 beta1_power, beta2_power = opt._get_beta_accumulators()
208 self.assertTrue(beta2_power is not None)
210 self.assertNotIn(beta2_power, opt_variables)
228 0.999**(t + 1), self.evaluate(beta2_power))
233 beta1_power, beta2_power = opt._get_beta_accumulators()
237 0.999**t, self.evaluate(beta2_power))
286 beta1_power, beta2_power = opt._get_beta_accumulators()
292 self.evaluate(beta2_power))
[all...] |
| lazy_adam_gs_optimizer_test.py | 97 beta1_power, beta2_power = opt._get_beta_accumulators()
102 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
225 beta1_power, beta2_power = opt._get_beta_accumulators()
227 self.assertIsNotNone(beta2_power is not None)
229 self.assertNotIn(beta2_power, opt_variables)
247 0.999**(t + 1), self.evaluate(beta2_power))
252 beta1_power, beta2_power = opt._get_beta_accumulators()
256 0.999**t, self.evaluate(beta2_power))
305 beta1_power, beta2_power = opt._get_beta_accumulators()
310 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval()
[all...] |
| lazy_adam_optimizer_test.py | 92 beta1_power, beta2_power = opt._get_beta_accumulators()
97 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
199 beta1_power, beta2_power = opt._get_beta_accumulators()
201 self.assertIsNotNone(beta2_power is not None)
203 self.assertIn(beta2_power, opt_variables)
214 beta1_power, beta2_power = opt._get_beta_accumulators()
226 self.evaluate(beta2_power))
272 beta1_power, beta2_power = opt._get_beta_accumulators()
277 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
306 beta1_power, beta2_power = opt._get_beta_accumulators(
[all...] |
| nadam_optimizer_test.py | 91 beta1_power, beta2_power = opt._get_beta_accumulators()
96 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
140 beta1_power, beta2_power = opt._get_beta_accumulators()
145 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
|
| /external/tensorflow/tensorflow/contrib/optimizer_v2/ |
| adam.py | 101 state.get_non_slot("beta2_power"))
108 initial_value=lambda: state.get_hyper("beta2"), name="beta2_power")
118 beta1_power, beta2_power = self._get_beta_accumulators(state)
124 math_ops.cast(beta2_power, var.dtype.base_dtype),
135 beta1_power, beta2_power = self._get_beta_accumulators(state)
141 math_ops.cast(beta2_power, grad.dtype.base_dtype),
150 beta1_power, beta2_power = self._get_beta_accumulators(state)
152 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
157 lr = (lr_t * math_ops.sqrt(1 - beta2_power) / (1 - beta1_power)
[all...] |
| adam_test.py | 89 beta1_power, beta2_power = opt._get_beta_accumulators()
94 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
177 beta1_power, beta2_power = opt._get_beta_accumulators()
179 self.assertTrue(beta2_power is not None)
181 self.assertIn(beta2_power, opt_variables)
193 beta1_power, beta2_power = opt._get_beta_accumulators()
205 self.evaluate(beta2_power))
247 beta1_power, beta2_power = opt._get_beta_accumulators()
252 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
281 beta1_power, beta2_power = opt._get_beta_accumulators(
[all...] |
| /external/tensorflow/tensorflow/python/training/ |
| adam.py | 116 self._get_non_slot_variable("beta2_power", graph=graph))
127 initial_value=self._beta2, name="beta2_power", colocate_with=first_var)
148 beta1_power, beta2_power = self._get_beta_accumulators()
154 math_ops.cast(beta2_power, var.dtype.base_dtype),
165 beta1_power, beta2_power = self._get_beta_accumulators()
171 math_ops.cast(beta2_power, grad.dtype.base_dtype),
180 beta1_power, beta2_power = self._get_beta_accumulators()
182 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
187 lr = (lr_t * math_ops.sqrt(1 - beta2_power) / (1 - beta1_power)
[all...] |
| adam_test.py | 89 beta1_power, beta2_power = opt._get_beta_accumulators()
95 self.evaluate(beta2_power))
195 beta1_power, beta2_power = opt._get_beta_accumulators()
197 self.assertTrue(beta2_power is not None)
199 self.assertIn(beta2_power, opt_variables)
207 resource_variable_ops.is_resource_variable(beta2_power))
218 beta1_power, beta2_power = opt._get_beta_accumulators()
230 self.evaluate(beta2_power))
277 beta1_power, beta2_power = opt._get_beta_accumulators()
283 self.evaluate(beta2_power))
[all...] |
| sync_replicas_optimizer_test.py | 295 beta1_power, beta2_power = opt._opt._get_beta_accumulators()
297 self.assertIn(beta2_power, opt_variables)
|
| training_ops_test.py | 279 beta2_power = beta2**t
285 beta2_power_t = variables.VariableV1(beta2_power)
|
| /external/tensorflow/tensorflow/compiler/tests/ |
| adam_test.py | 81 beta1_power, beta2_power = opt._get_beta_accumulators()
87 self.evaluate(beta2_power))
124 beta1_power, beta2_power = opt._get_beta_accumulators()
130 self.evaluate(beta2_power))
164 beta1_power, beta2_power = opt._get_beta_accumulators()
174 self.evaluate(beta2_power))
|
| /external/tensorflow/tensorflow/core/kernels/ |
| training_ops_gpu.cu.cc | 130 typename TTypes<T>::ConstScalar beta2_power,
149 (lr * (beta2_power.constant(one) - beta2_power).sqrt() /
158 var.device(d) -= (lr * (beta2_power.constant(one) - beta2_power).sqrt() /
174 typename TTypes<T>::ConstScalar beta2_power,
192 var.device(d) -= (lr * (beta2_power.constant(one) - beta2_power).sqrt() /
|
| training_ops.h | 143 typename TTypes<T>::ConstScalar beta2_power,
157 typename TTypes<T>::ConstScalar beta2_power,
|
| training_ops_test.cc | 173 auto beta2_power = Scalar(g, 0.99); local
181 {var, m, v, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad});
|
| training_ops.cc | 307 typename TTypes<T>::ConstScalar beta2_power,
313 const T alpha = lr() * Eigen::numext::sqrt(T(1) - beta2_power()) /
336 T beta1_power, T beta2_power, T lr, T beta1, T beta2,
339 lr * Eigen::numext::sqrt(T(1) - beta2_power) / (T(1) - beta1_power);
356 typename TTypes<T>::ConstScalar beta2_power,
362 const T alpha = lr() * Eigen::numext::sqrt(T(1) - beta2_power()) /
2837 const Tensor& beta2_power = ctx->input(4); variable
2935 T beta2_power = 0; variable
3106 const Tensor& beta2_power = ctx->input(5); variable
[all...] |
| /external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
| nadam_test.py | 107 beta1_power, beta2_power = get_beta_accumulators(opt, dtype)
112 self.assertAllCloseAccordingToType(0.999**(t + 1), beta2_power.eval())
|
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| training_ops.cc | 430 errors::InvalidArgument("beta2_power is not a scalar: ",
459 xla::XlaOp beta2_power = ctx->Input(4); variable
474 xla::XlaOp alpha = lr * xla::Sqrt(one - beta2_power) / (one - beta1_power);
[all...] |
| /external/tensorflow/tensorflow/python/training/tracking/ |
| util_with_v1_optimizers_test.py | 116 "optimizer/beta2_power",
149 "beta2_power",
150 named_variables["optimizer/beta2_power" + suffix].full_name)
226 # Preserve beta1_power and beta2_power when appying gradients so we can
256 beta1_power, beta2_power = on_create_optimizer._get_beta_accumulators()
258 self.assertAllEqual(optimizer_variables[1], self.evaluate(beta2_power))
[all...] |
