Searched refs:mat_g (Results 1 – 4 of 4) sorted by relevance
| /external/tensorflow/tensorflow/contrib/opt/python/training/ |
| D | shampoo.py | 203 def _update_mat_g(self, mat_g, grad, axes, mat_gbar_decay, argument
228 return self._weighted_average(mat_g, self._mat_gbar_decay, mat_gbar_decay,
231 def _compute_power_svd(self, var, mat_g, mat_g_size, alpha, mat_h_slot_name): argument
248 mat_h = math_ops.pow(mat_g + self._epsilon, alpha)
252 diag_d, mat_u, mat_v = linalg_ops.svd(mat_g + damping, full_matrices=True)
260 def _compute_power_iter(self, var, mat_g, mat_g_size, alpha, mat_h_slot_name, argument
264 mat_g_sqrt = matrix_functions.matrix_square_root(mat_g, mat_g_size,
278 def _compute_power(self, var, mat_g, mat_g_size, alpha, mat_h_slot_name=None): argument
282 return self._compute_power_iter(var, mat_g, mat_g_size, alpha,
285 return self._compute_power_svd(var, mat_g, mat_g_size, alpha,
[all …]
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| D | matrix_functions.py | 76 def matrix_inverse_pth_root(mat_g, argument
137 mat_h = math_ops.pow(mat_g + ridge_epsilon, alpha)
139 damped_mat_g = mat_g + ridge_epsilon * identity
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| D | matrix_functions_test.py | 29 def np_power(mat_g, alpha): argument
32 mat_u, diag_d, mat_v = np.linalg.svd(mat_g)
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| D | shampoo_test.py | 37 def np_power(mat_g, alpha): argument
40 mat_u, diag_d, mat_v = np.linalg.svd(mat_g)
81 mat_g = np.outer(grad_np, grad_np) / grad_np.shape[0]
82 mat_h = np_power(mat_g + RIDGE_EPSILON * np.eye(size), -0.5)
92 mat_g += np.outer(grad_np_2, grad_np_2) / grad_np.shape[0]
93 mat_h = np_power(mat_g + RIDGE_EPSILON * np.eye(size), -0.5)
281 mat_g = (grad_np * grad_np)
282 new_val_np = init_var_np - np.power(mat_g, -0.5) * grad_np
290 mat_g += (grad_np_2 * grad_np_2)
291 new_val_np -= np.power(mat_g, -0.5) * grad_np_2
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