| /external/tensorflow/tensorflow/compiler/tests/ |
| adam_test.py | 40 beta2=0.999,
42 alpha_t = alpha * np.sqrt(1 - beta2**t) / (1 - beta1**t)
45 v_t = beta2 * v + (1 - beta2) * g_t * g_t
|
| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| lazy_adam_optimizer_test.py | 41 beta2=0.999,
43 alpha_t = alpha * np.sqrt(1 - beta2**t) / (1 - beta1**t)
46 v_t = beta2 * v + (1 - beta2) * g_t * g_t
|
| nadam_optimizer_test.py | 39 beta2=0.999,
41 alpha_t = alpha * np.sqrt(1 - beta2**t) / (1 - beta1**t)
44 v_t = beta2 * v + (1 - beta2) * g_t * g_t
|
| /external/tensorflow/tensorflow/python/training/ |
| training_ops_test.py | 266 beta2 = np.array(0.999, dtype=var.dtype)
268 beta2_power = beta2**t
272 beta2_t = constant_op.constant(beta2, self._toType(var.dtype), [])
281 beta2, epsilon)
289 def _adamUpdateNumpy(self, param, g_t, t, m, v, alpha, beta1, beta2, epsilon):
290 alpha_t = alpha * np.sqrt(1 - beta2**t) / (1 - beta1**t)
293 v_t = beta2 * v + (1 - beta2) * g_t * g_t
|
| adam_test.py | 44 beta2=0.999,
46 alpha_t = alpha * np.sqrt(1 - beta2**t) / (1 - beta1**t)
49 v_t = beta2 * v + (1 - beta2) * g_t * g_t
|
| adam.py | 40 def __init__(self, learning_rate=0.001, beta1=0.9, beta2=0.999, epsilon=1e-8,
57 lr_t <- learning_rate * sqrt(1 - beta2^t) / (1 - beta1^t)
60 v_t <- beta2 * v_{t-1} + (1 - beta2) * g * g
84 beta2: A float value or a constant float tensor.
96 self._beta2 = beta2
117 # Create the beta1 and beta2 accumulators on the same device as the first
137 self._beta2_t = ops.convert_to_tensor(self._beta2, name="beta2")
184 # v_t = beta2 * v + (1 - beta2) * (g_t * g_t
[all...] |
| /external/speex/libspeex/ |
| scal.c | 152 float beta, beta2; local
182 beta2 = beta;
201 if (max_alpha > .98/(1.+beta2))
202 max_alpha = .98/(1.+beta2);
|
| /external/tensorflow/tensorflow/core/kernels/ |
| training_ops_gpu.cu.cc | 110 typename TTypes<T>::ConstScalar beta2,
121 v + (beta2.constant(one) - beta2).reshape(single).broadcast(bcast) *
|
| training_ops_test.cc | 176 auto beta2 = Scalar(g, 0.99); local
181 {var, m, v, beta1_power, beta2_power, lr, beta1, beta2, epsilon, grad});
|
| training_ops.h | 137 typename TTypes<T>::ConstScalar beta2,
|
| training_ops.cc | 291 typename TTypes<T>::ConstScalar beta2,
297 // beta2 == ?
302 v.device(d) += (grad.square() - v) * (T(1) - beta2());
317 T beta1_power, T beta2_power, T lr, T beta1, T beta2,
322 v.device(d) += (grad.square() - v) * (T(1) - beta2);
2518 const Tensor& beta2 = ctx->input(7); variable
2615 T beta2 = 0; variable
[all...] |
| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| training_ops.cc | 197 errors::InvalidArgument("beta2 is not a scalar: ",
220 xla::ComputationDataHandle beta2 = ctx->Input(7); variable
224 // alpha <- learning_rate * sqrt(1 - beta2^t) / (1 - beta1^t)
226 // v_t <- beta2 * v_{t-1} + (1 - beta2) * g_t * g_t
238 v = b->Add(v, b->Mul(b->Sub(b->Pow(grad, two), v), b->Sub(one, beta2)));
|
| /external/tensorflow/tensorflow/python/kernel_tests/distributions/ |
| beta_test.py | 297 beta2 = beta_lib.Beta(concentration1=a_val,
299 name="beta2")
300 samples2 = beta2.sample(n_val, seed=123456).eval()
|
| /build/make/core/ |
| config.mk | 712 prebuilts/gradle-plugin/com/android/tools/build/manifest-merger/26.0.0-beta2/manifest-merger-26.0.0-beta2.jar \
713 prebuilts/gradle-plugin/com/android/tools/sdk-common/26.0.0-beta2/sdk-common-26.0.0-beta2.jar \
714 prebuilts/gradle-plugin/com/android/tools/common/26.0.0-beta2/common-26.0.0-beta2.jar \
[all...] |
| /external/syslinux/com32/lib/libpng/ |
| CHANGES | [all...] |
| /external/toolchain-utils/cros_utils/ |
| stats.py | [all...] |
