| /external/tensorflow/tensorflow/python/keras/ |
| D | optimizer_v1.py | 482 beta_2=0.999, argument
492 self.beta_2 = K.variable(beta_2, name='beta_2')
524 K.sqrt(1. - math_ops.pow(self.beta_2, t)) /
530 v_t = (self.beta_2 * v) + (1. - self.beta_2) * math_ops.square(g)
553 'beta_2': float(K.get_value(self.beta_2)),
578 beta_2=0.999, argument
587 self.beta_2 = K.variable(beta_2, name='beta_2')
624 u_t = math_ops.maximum(self.beta_2 * u, math_ops.abs(g))
642 'beta_2': float(K.get_value(self.beta_2)),
669 beta_2=0.999, argument
[all …]
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| /external/tensorflow/tensorflow/python/tpu/ |
| D | tpu_embedding_v2_utils.py | 435 beta_2: float = 0.999,
493 if beta_2 < 0. or beta_2 >= 1.:
495 .format(beta_2))
503 self.beta_2 = beta_2
518 parameters.adam.beta2 = self.beta_2
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| D | tpu_embedding_v2_correctness_test.py | 421 v = g**2 * (1 - optimizer.beta_2)
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_ApplyAdam.pbtxt | 85 $$lr_t := \text{learning\_rate} * \sqrt{1 - beta_2^t} / (1 - beta_1^t)$$
87 $$v_t := beta_2 * v_{t-1} + (1 - beta_2) * g * g$$
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| D | api_def_ResourceApplyAdamWithAmsgrad.pbtxt | 79 $$\text{lr}_t := \mathrm{learning_rate} * \sqrt{1 - \beta_2^t} / (1 - \beta_1^t)$$
81 $$v_t := \beta_2 * v_{t-1} + (1 - \beta_2) * g * g$$
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| D | api_def_ResourceApplyAdam.pbtxt | 79 $$\text{lr}_t := \mathrm{learning_rate} * \sqrt{1 - \beta_2^t} / (1 - \beta_1^t)$$
81 $$v_t := \beta_2 * v_{t-1} + (1 - \beta_2) * g * g$$
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| /external/eigen/Eigen/src/Core/ |
| D | MathFunctionsImpl.h | 49 const T beta_2 = pset1<T>(2.26843463243900e-03f); in generic_fast_tanh_float() local
67 q = pmadd(x2, q, beta_2); in generic_fast_tanh_float()
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| /external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
| D | adam.py | 110 beta_2=0.999, argument
119 self._set_hyper('beta_2', beta_2)
334 beta_2=0.999, argument
371 self._set_hyper('beta_2', beta_2)
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| D | adam_test.py | 371 beta_2 = 0.999
378 beta_2=beta_2,
419 beta_2 = 0.999
425 beta_2=beta_2,
827 beta_2 = 0.999
834 beta_2=beta_2,
875 beta_2 = 0.999
881 beta_2=beta_2,
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| D | adamax.py | 95 beta_2=0.999, argument
103 self._set_hyper('beta_2', beta_2)
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| D | nadam.py | 70 beta_2=0.999, argument
86 self._set_hyper('beta_2', beta_2)
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.tpu.experimental.embedding.-adam.pbtxt | 8 …argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'lazy_adam\', \…
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| D | tensorflow.optimizers.-adamax.pbtxt | 29 …argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'name\'], varar…
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| D | tensorflow.optimizers.-nadam.pbtxt | 29 …argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'name\'], varar…
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| D | tensorflow.optimizers.-adam.pbtxt | 29 …argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'amsgrad\', \'n…
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| D | tensorflow.keras.optimizers.-adam.pbtxt | 29 …argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'amsgrad\', \'n…
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| D | tensorflow.keras.optimizers.-adamax.pbtxt | 29 …argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'name\'], varar…
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| D | tensorflow.keras.optimizers.-nadam.pbtxt | 29 …argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'name\'], varar…
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.tpu.experimental.embedding.-adam.pbtxt | 8 …argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'lazy_adam\', \…
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| D | tensorflow.keras.optimizers.-adam.pbtxt | 29 …argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'amsgrad\', \'n…
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| D | tensorflow.keras.optimizers.-nadam.pbtxt | 29 …argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'name\'], varar…
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| D | tensorflow.keras.optimizers.-adamax.pbtxt | 29 …argspec: "args=[\'self\', \'learning_rate\', \'beta_1\', \'beta_2\', \'epsilon\', \'name\'], varar…
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| /external/tensorflow/tensorflow/python/keras/distribute/ |
| D | keras_optimizer_v2_test.py | 59 optimizer = adam.Adam(learning_rate=0.01, beta_1=0.2, beta_2=0.2)
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| /external/eigen/Eigen/src/Core/functors/ |
| D | UnaryFunctors.h | 1021 const Packet beta_2 = pset1<Packet>(1.16817656904453e-01);
1041 q = pmadd(x2, q, beta_2);
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| /external/tensorflow/tensorflow/core/protobuf/tpu/ |
| D | optimization_parameters.proto | 243 // \beta_2 from Algorithm 2 in the paper.
|