| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| lazy_adam_optimizer.py | 50 beta1_power, beta2_power = self._get_beta_accumulators()
52 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
57 lr = (lr_t * math_ops.sqrt(1 - beta2_power) / (1 - beta1_power))
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| nadam_optimizer.py | 37 beta1_power, beta2_power = self._get_beta_accumulators()
43 math_ops.cast(beta2_power, var.dtype.base_dtype),
55 beta1_power, beta2_power = self._get_beta_accumulators()
61 math_ops.cast(beta2_power, grad.dtype.base_dtype),
71 beta1_power, beta2_power = self._get_beta_accumulators()
73 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
78 lr = (lr_t * math_ops.sqrt(1 - beta2_power) / (1 - beta1_power))
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| nadam_optimizer_test.py | 86 beta1_power, beta2_power = opt._get_beta_accumulators()
91 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
133 beta1_power, beta2_power = opt._get_beta_accumulators()
138 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
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| lazy_adam_optimizer_test.py | 82 beta1_power, beta2_power = opt._get_beta_accumulators()
87 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
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| /external/tensorflow/tensorflow/python/training/ |
| adam.py | 114 self._get_non_slot_variable("beta2_power", graph=graph))
126 name="beta2_power",
143 beta1_power, beta2_power = self._get_beta_accumulators()
147 math_ops.cast(beta2_power, var.dtype.base_dtype),
157 beta1_power, beta2_power = self._get_beta_accumulators()
161 math_ops.cast(beta2_power, grad.dtype.base_dtype),
169 beta1_power, beta2_power = self._get_beta_accumulators()
171 beta2_power = math_ops.cast(beta2_power, var.dtype.base_dtype)
176 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...] |
| sync_replicas_optimizer_test.py | 289 beta1_power, beta2_power = opt._opt._get_beta_accumulators()
291 self.assertIn(beta2_power, opt_variables)
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| training_ops_test.py | 268 beta2_power = beta2**t
274 beta2_power_t = variables.Variable(beta2_power)
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| /external/tensorflow/tensorflow/compiler/tests/ |
| adam_test.py | 77 beta1_power, beta2_power = opt._get_beta_accumulators()
82 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
116 beta1_power, beta2_power = opt._get_beta_accumulators()
121 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
152 beta1_power, beta2_power = opt._get_beta_accumulators()
161 self.assertAllCloseAccordingToType(0.999**t, beta2_power.eval())
|
| /external/tensorflow/tensorflow/core/kernels/ |
| training_ops_gpu.cu.cc | 107 typename TTypes<T>::ConstScalar beta2_power,
126 (lr * (beta2_power.constant(one) - beta2_power).sqrt() /
135 var.device(d) -= (lr * (beta2_power.constant(one) - beta2_power).sqrt() /
|
| 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});
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| training_ops.h | 134 typename TTypes<T>::ConstScalar beta2_power,
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| training_ops.cc | 288 typename TTypes<T>::ConstScalar beta2_power,
294 const T alpha = lr() * Eigen::numext::sqrt(T(1) - beta2_power()) /
317 T beta1_power, T beta2_power, T lr, T beta1, T beta2,
320 lr * Eigen::numext::sqrt(T(1) - beta2_power) / (T(1) - beta1_power);
2515 const Tensor& beta2_power = ctx->input(4); variable
2612 T beta2_power = 0; variable
[all...] |
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| training_ops.cc | 188 errors::InvalidArgument("beta2_power is not a scalar: ",
217 xla::ComputationDataHandle beta2_power = ctx->Input(4); variable
235 b->Div(b->Mul(lr, b->Pow(b->Sub(one, beta2_power), half)),
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| /external/tensorflow/tensorflow/contrib/eager/python/ |
| checkpointable_utils_test.py | 308 "optimizer/beta2_power",
336 "beta2_power:0",
337 named_variables["optimizer/beta2_power" + suffix].name)
429 beta1_power, beta2_power = on_create_optimizer._get_beta_accumulators()
431 self.assertAllEqual(optimizer_variables[1], self.evaluate(beta2_power))
[all...] |
