import cPickle
import logging
from blocks.serialization import load as load_parameters
from blocks.model import Model
from datasets import parrot_stream
from model import Parrot
from utils import (attention_plot, sample_parse, create_animation,
numpy_one_hot)
from generate import generate_wav
logging.basicConfig()
data_dir = os.environ['FUEL_DATA_PATH']
args = sample_parse()
with open(os.path.join(args.save_dir, 'config',
args.experiment_name + '.pkl')) as f:
saved_args = cPickle.load(f)
assert saved_args.dataset == args.dataset
if args.use_last:
params_mode = 'last_'
else:
params_mode = 'best_'
args.samples_name = params_mode + args.samples_name
with open(
"""
import numpy
import os
import cPickle
import logging
from blocks.serialization import load_parameters
from blocks.model import Model
from model import Scribe
from theano import function
from utils import char2code, sample_parse, full_plot
logging.basicConfig()
parser = sample_parse()
args = parser.parse_args()
with open(os.path.join(args.save_dir, 'config',
args.experiment_name + '.pkl')) as f:
saved_args = cPickle.load(f)
with open(
os.path.join(args.save_dir, "pkl",
"best_" + args.experiment_name + ".tar"), 'rb') as src:
parameters = load_parameters(src)
scribe = Scribe(k=saved_args.num_mixture,
rec_h_dim=saved_args.rnn_size,
att_size=saved_args.size_attention,
num_letters=saved_args.num_letters,