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remove contextual gpr

This commit is contained in:
yangdsh 2019-11-04 03:48:05 +00:00 committed by Dana Van Aken
parent e86fce59d9
commit ee53d0cead
1 changed files with 0 additions and 128 deletions
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128
server/analysis/gpr/gpr_models.py
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@ -126,136 +126,8 @@ class BasicGP(BaseModel):
return k return k
class ContextualGP(BaseModel):
_KERNEL_HP_KEYS = [
[
'GPRC/kern/kernels/0/kernels/0/variance',
'GPRC/kern/kernels/0/kernels/0/lengthscales',
],
[
'GPRC/kern/kernels/0/kernels/1/variance',
'GPRC/kern/kernels/0/kernels/1/lengthscales',
],
[
'GPRC/kern/kernels/1/variance',
]
]
def _get_kernel_kwargs(self, **kwargs):
k0_active_dims = kwargs.pop('k0_active_dims')
k1_active_dims = kwargs.pop('k1_active_dims')
return [
{
'input_dim': len(k0_active_dims),
'active_dims': k0_active_dims,
'ARD': True,
},
{
'input_dim': len(k1_active_dims),
'active_dims': k1_active_dims,
'ARD': True,
},
{
'input_dim': kwargs.pop('X_dim'),
}
]
def _build_kernel(self, kernel_kwargs, **kwargs):
k0 = gpflow.kernels.Exponential(**kernel_kwargs[0])
k1 = gpflow.kernels.Exponential(**kernel_kwargs[1])
k2 = gpflow.kernels.White(**kernel_kwargs[2])
if kwargs['optimize_hyperparameters']:
k0.lengthscales.transform = gpflow.transforms.Logistic(
*self._LENGTHSCALE_BOUNDS)
k1.lengthscales.transform = gpflow.transforms.Logistic(
*self._LENGTHSCALE_BOUNDS)
k = k0 * k1 + k2
return k
class ContextualGP_Alt0(ContextualGP):
def __init__(self, X, y, hyperparameters=None, optimize_hyperparameters=False,
learning_rate=0.001, maxiter=5000, **kwargs):
self._context_lengthscale_const = kwargs.pop('context_lengthscale_const', 9.0)
super(ContextualGP_Alt0, self).__init__(
X, y, hyperparameters=hyperparameters,
optimize_hyperparameters=optimize_hyperparameters,
learning_rate=learning_rate, maxiter=maxiter, **kwargs)
def _build_kernel(self, kernel_kwargs, **kwargs):
kernel_kwargs[1]['lengthscales'] = np.ones((kernel_kwargs[1]['input_dim'],)) * \
self._context_lengthscale_const
k0 = gpflow.kernels.Exponential(**kernel_kwargs[0])
k1 = gpflow.kernels.Exponential(**kernel_kwargs[1])
k1.lengthscales.trainable = False
k2 = gpflow.kernels.White(**kernel_kwargs[2])
if kwargs['optimize_hyperparameters']:
k0.lengthscales.transform = gpflow.transforms.Logistic(
*self._LENGTHSCALE_BOUNDS)
k = k0 * k1 + k2
return k
class ContextualGP_Alt1(ContextualGP):
def __init__(self, X, y, hyperparameters=None, optimize_hyperparameters=False,
learning_rate=0.001, maxiter=5000, **kwargs):
self._hyperparams_path = kwargs.pop('hyperparameters_path')
self._hyperparams_idx = kwargs.pop('hyperparameters_idx', 0)
self._context_only = kwargs.pop('context_only', True)
super(ContextualGP_Alt1, self).__init__(
X, y, hyperparameters=hyperparameters,
optimize_hyperparameters=optimize_hyperparameters,
learning_rate=learning_rate, maxiter=maxiter, **kwargs)
def _build_kernel(self, kernel_kwargs, **kwargs):
hyperparams = self.load_hyperparameters(self._hyperparams_path,
self._hyperparams_idx)
if not self._context_only:
kernel_kwargs[0]['lengthscales'] = np.array(
hyperparams['GPRC/kern/kernels/0/kernels/0/lengthscales'])
kernel_kwargs[1]['lengthscales'] = np.array(
hyperparams['GPRC/kern/kernels/0/kernels/1/lengthscales'])
k0 = gpflow.kernels.Exponential(**kernel_kwargs[0])
k1 = gpflow.kernels.Exponential(**kernel_kwargs[1])
k2 = gpflow.kernels.White(**kernel_kwargs[2])
if not self._context_only:
k0.lengthscales.trainable = False
k1.lengthscales.trainable = False
if self._context_only and kwargs['optimize_hyperparameters']:
k0.lengthscales.transform = gpflow.transforms.Logistic(
*self._LENGTHSCALE_BOUNDS)
k = k0 * k1 + k2
return k
class AdditiveContextualGP(ContextualGP):
def _build_kernel(self, kernel_kwargs, **kwargs):
k0 = gpflow.kernels.Exponential(**kernel_kwargs[0])
k1 = gpflow.kernels.Exponential(**kernel_kwargs[1])
k2 = gpflow.kernels.White(**kernel_kwargs[2])
if kwargs['optimize_hyperparameters']:
k0.lengthscales.transform = gpflow.transforms.Logistic(
*self._LENGTHSCALE_BOUNDS)
k1.lengthscales.transform = gpflow.transforms.Logistic(
*self._LENGTHSCALE_BOUNDS)
k = k0 + k1 + k2
return k
_MODEL_MAP = { _MODEL_MAP = {
'BasicGP': BasicGP, 'BasicGP': BasicGP,
'ContextualGP': ContextualGP,
'ContextualGP_Alt0': ContextualGP_Alt0,
'ContextualGP_Alt1': ContextualGP_Alt1,
'AdditiveContextualGP': AdditiveContextualGP,
} }