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model.py: load_parameters from different directory #6

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33 changes: 25 additions & 8 deletions DeepSequence/model.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,7 @@
from __future__ import print_function
from collections import OrderedDict
import cPickle
import os

import numpy as np
import theano
Expand All @@ -7,10 +10,6 @@
#import theano.sandbox.linalg as T_linalg
from scipy.special import erfinv

import cPickle

from collections import OrderedDict

if theano.config.floatX == "float16":
print ("using epsilon=1e-6")
epsilon = 1e-6
Expand Down Expand Up @@ -716,20 +715,38 @@ def create_gradientfunctions(self):

def save_parameters(self, file_prefix):
"""Saves all the parameters in a way they can be retrieved later"""
# TODO(Lood): Can also add a flag to save parameters in custom directory (not self.working_dir/params/)
cPickle.dump({name: p.get_value() for name, p in self.params.items()},\
open(self.working_dir+"/params/"+file_prefix + "_params.pkl", "wb"))
cPickle.dump({name: m.get_value() for name, m in self.m.items()}, \
open(self.working_dir+"/params/"+file_prefix +"_m.pkl", "wb"))
cPickle.dump({name: v.get_value() for name, v in self.v.items()}, \
open(self.working_dir+"/params/"+file_prefix +"_v.pkl", "wb"))

def load_parameters(self, file_prefix=""):
def load_parameters(self, file_prefix="", seed=None, override_params_dir=None):
"""Load the variables in a shared variable safe way"""
p_list = cPickle.load(open(self.working_dir+"/params/"+file_prefix \
if override_params_dir is not None:
params_dir = override_params_dir
else:
params_dir = os.path.join(self.working_dir, 'params')
assert os.path.isdir(params_dir), "{} is not a directory".format(params_dir)
# Check _params.pkl exists, then assume the others exist too
file_matches = [file for file in os.listdir(params_dir) if file.startswith(file_prefix)
and file.endswith("_params.pkl") and "epoch" not in file] # Ignoring the intermediate "_theta_<epochs>_params" checkpoints

if seed is not None:
print("Searching for seed {}, files matched so far: {}".format(seed, file_matches))
file_matches = [file for file in file_matches if "seed-" + str(seed) in file]

assert len(file_matches) == 1, "Could not find unique params file for prefix {} in {}, found {} files".format(file_prefix, params_dir, file_matches)
print("Matched file: {}".format(file_matches[0]))
full_prefix = os.path.join(params_dir, file_matches[0].replace("_params.pkl", ""))

p_list = cPickle.load(open(full_prefix \
+ "_params.pkl", "rb"))
m_list = cPickle.load(open(self.working_dir+"/params/"+file_prefix \
m_list = cPickle.load(open(full_prefix \
+ "_m.pkl", "rb"))
v_list = cPickle.load(open(self.working_dir+"/params/"+file_prefix \
v_list = cPickle.load(open(full_prefix \
+ "_v.pkl", "rb"))

for name in p_list.keys():
Expand Down
1 change: 1 addition & 0 deletions DeepSequence/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -44,6 +44,7 @@ def train(data,
batch_order = np.arange(data.x_train.shape[0])

seq_sample_probs = data.weights / np.sum(data.weights)
assert len(seq_sample_probs) == data.x_train.shape[0], "Length of sequence weights {} does not match number of sequences {}".format(len(seq_sample_probs), data.x_train.shape[0])

update_num = 0

Expand Down