| /external/tensorflow/tensorflow/contrib/kfac/python/ops/ |
| fisher_factors.py | 344 def left_multiply(self, x, damping):
348 D = C + damping * I be its damped variant. This method calculates
353 damping: 0-D Tensor. Damping to add to C's diagonal.
361 def right_multiply(self, x, damping):
365 D = C + damping * I be its damped variant. This method calculates
370 damping: 0-D Tensor. Damping to add to C's diagonal.
378 def left_multiply_inverse(self, x, damping):
382 E = inv(C + damping * I) be its damped inverse. This method calculate
[all...] |
| fisher_blocks.py | 52 # we want to adjust the scale of the damping by
53 # damping /= num_replications ** NORMALIZE_DAMPING_POWER
56 # Methods for adjusting damping for FisherBlocks. See
75 def normalize_damping(damping, num_replications):
76 """Normalize damping after adjusting scale by NORMALIZE_DAMPING_POWER."""
78 return damping / (num_replications ** NORMALIZE_DAMPING_POWER)
79 return damping
83 """Computes the scalar constant pi for Tikhonov regularization/damping.
114 def compute_pi_adjusted_damping(left_cov, right_cov, damping):
118 return (damping * pi, damping / pi
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| utils.py | 177 def posdef_inv(tensor, damping):
178 """Computes the inverse of tensor + damping * identity."""
180 damping = math_ops.cast(damping, dtype=tensor.dtype)
181 return posdef_inv_functions[POSDEF_INV_METHOD](tensor, identity, damping)
184 def posdef_inv_matrix_inverse(tensor, identity, damping):
185 """Computes inverse(tensor + damping * identity) directly."""
186 return linalg_ops.matrix_inverse(tensor + damping * identity)
189 def posdef_inv_cholesky(tensor, identity, damping):
190 """Computes inverse(tensor + damping * identity) with Cholesky.""
[all...] |
| optimizer.py | 41 damping,
61 damping: The damping factor used to stabilize training due to errors in
64 (Higher damping means the update looks more like a standard gradient
111 damping,
171 def damping(self): member in class:KfacOptimizer
172 return self._fisher_est.damping
312 with the usual Tikhonov damping/regularization applied,
314 C = F + damping * I
351 self.damping * _inner_product_list(precon_grads, precon_grads)
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| estimator.py | 88 damping,
102 damping: The damping factor used to stabilize training due to errors in
105 (Higher damping means the update looks more like a standard gradient
141 self._damping = damping
184 def damping(self): member in class:FisherEstimator
262 fb.instantiate_factors(grads_list, self.damping)
|
| /external/sonivox/arm-wt-22k/lib_src/ |
| eas_math.h | 173 linear on dB scale, which is equivalent to exponential damping on
178 (i.e., exponential damping) during the Decay and Release segments of
181 #define MULT_EG1_EG1(gain,damping) /*lint -e(704) <avoid divide for performance>*/ \
184 ((int32_t)(gain)) * ((int32_t)(damping)) \
200 #define MULT_EG1_EG1_X2(gain,damping) /*lint -e(702) <avoid divide for performance>*/ \
203 ((int32_t)(gain)) * ((int32_t)(damping)) \
|
| /frameworks/av/media/libeffects/testlibs/ |
| EffectsMath.h | 163 linear on dB scale, which is equivalent to exponential damping on
168 (i.e., exponential damping) during the Decay and Release segments of
171 #define MULT_EG1_EG1(gain,damping) /*lint -e(704) <avoid divide for performance>*/ \
174 ((int32_t)(gain)) * ((int32_t)(damping)) \
190 #define MULT_EG1_EG1_X2(gain,damping) /*lint -e(702) <avoid divide for performance>*/ \
193 ((int32_t)(gain)) * ((int32_t)(damping)) \
|
| /external/tensorflow/tensorflow/contrib/kfac/python/kernel_tests/ |
| fisher_blocks_test.py | 132 damping = 0.5
133 block.instantiate_factors((grads,), damping)
145 explicit = np.dot(np.linalg.inv(full + damping * np.eye(3)), v_flat)
222 damping = 0.5
223 block.instantiate_factors((grads,), damping)
235 explicit = np.dot(np.linalg.inv(full + damping * np.eye(3)), v_flat)
369 block.instantiate_factors((output_grads,), damping=0.0)
396 damping = array_ops.constant(0.)
397 block.instantiate_factors(([grads],), damping)
414 damping = array_ops.constant(0.
[all...] |
| fisher_factors_test.py | 95 def left_multiply(self, x, damping):
98 def right_multiply(self, x, damping):
101 def left_multiply_inverse(self, x, damping):
104 def right_multiply_inverse(self, x, damping):
251 for damping in dampings:
252 factor.register_damped_inverse(damping)
326 damping = 0.5
328 factor.register_matpower(exp, damping)
334 matpower = sess.run(factor._matpower_by_exp_and_damping[(exp, damping)])
335 matpower_np = np.linalg.matrix_power(cov + np.eye(2) * damping, exp
[all...] |
| estimator_test.py | 135 damping=0.0)
182 damping=0.0)
|
| /external/tensorflow/tensorflow/contrib/kfac/examples/ |
| mlp.py | 128 damping=0.0001,
297 damping=0.0001,
|
| convnet.py | 204 damping=0.001,
286 damping=0.001,
|
