def save(self, filename):
"""Save the parameters into a binary file. [**PyCaffe Style**]
Parameters
----------
filename : str
The path of model file.
Returns
-------
None
See Also
--------
`workspace.Snapshot(*args, **kwargs)`_ - How to snapshot tensors into a file.
References
----------
The implementation of `Net_Save(_caffe.cpp, L153)`_.
"""
keys = set()
tensors = []
for layer in self._net.layer:
if layer.name in self.params:
for param in self.params[layer.name]:
if param.data.name not in keys:
tensors.append(param.data)
keys.add(param.data.name)
ws.Snapshot(tensors, filename, suffix='', format='caffe')
def save(self, filename, suffix='.caffemodel'):
""" simply follow the pycaffe style """
if not hasattr(self, '_function'): func = self.function
tensors = []
for layer in self._net.layer:
if layer.name in self.params:
for param in self.params[layer.name]:
tensors.append(param.data)
ws.Snapshot(tensors, filename, suffix=suffix, format=1)
def save(self, sess, save_path, global_step=None):
from ..core.variables import VARIABLES
global VARIABLES
var_list = VARIABLES if self.var_list is None else self.var_list
filename = save_path
if global_step is not None:
if isinstance(global_step, Tensor):
__ndarray__global_step = ws.FetchTensor(global_step)
if __ndarray__global_step.size != 1:
raise ValueError(
'global step must be a scalar of length 1.')
filename += '-' + str(__ndarray__global_step.flatten()[0])
ws.Snapshot(var_list.values(), filename=filename, suffix='')
def snapshot(self):
"""Snapshot the parameters of train net. [**PyCaffe Style**]
Returns
-------
None
See Also
--------
`workspace.Snapshot(*args, **kwargs)`_ - How to snapshot tensors into a file.
References
----------
The implementation of `Snapshot(solver.cpp, L403)`_.
"""
tensors = [blob.data for blob in self._layer_blobs]
filename = "_iter_" + str(self._iter)
ws.Snapshot(tensors, filename,
prefix=self._param.snapshot_prefix,
suffix='.caffemodel', format='caffe')
def save(self, episode):
filename = 'checkpoints/%s_%08d' % (self.model_name, episode)
ws.Snapshot(self.network_params, filename)
