From e8d25b4869c54ae16166bec8df9b615f57265b40 Mon Sep 17 00:00:00 2001
From: Markus Beissinger <mbeissinger@gmail.com>
Date: Wed, 4 Nov 2015 05:47:08 -0800
Subject: [PATCH] import autoencoder hotfix

---
 opendeep/models/single_layer/__init__.py      |  2 +-
 .../single_layer/tests/autoencoder_mnist.py   | 45 -------------------
 2 files changed, 1 insertion(+), 46 deletions(-)
 delete mode 100644 opendeep/models/single_layer/tests/autoencoder_mnist.py

diff --git a/opendeep/models/single_layer/__init__.py b/opendeep/models/single_layer/__init__.py
index 7536f70..c01e595 100644
--- a/opendeep/models/single_layer/__init__.py
+++ b/opendeep/models/single_layer/__init__.py
@@ -1,6 +1,6 @@
 from __future__ import division, absolute_import, print_function
 
-from .autoencoder import *
+# from .autoencoder import *
 from .basic import *
 from .convolutional import *
 from .restricted_boltzmann_machine import *
diff --git a/opendeep/models/single_layer/tests/autoencoder_mnist.py b/opendeep/models/single_layer/tests/autoencoder_mnist.py
deleted file mode 100644
index 71e1f62..0000000
--- a/opendeep/models/single_layer/tests/autoencoder_mnist.py
+++ /dev/null
@@ -1,45 +0,0 @@
-# standard libraries
-import logging
-# internal imports
-from opendeep.log.logger import config_root_logger
-from opendeep.models.single_layer.autoencoder import DenoisingAutoencoder
-from opendeep.data.standard_datasets.image.mnist import MNIST
-from opendeep.optimization.adadelta import AdaDelta
-
-log = logging.getLogger(__name__)
-
-###############################################
-# MAIN METHOD FOR RUNNING DEFAULT DAE EXAMPLE #
-###############################################
-def run_dae():
-    ########################################
-    # Initialization things with arguments #
-    ########################################
-    config_root_logger()
-    log.info("Creating a new DAE")
-
-    mnist = MNIST()
-    config = {
-        "outdir": 'outputs/dae/mnist/',
-        "input_size": 28*28,
-        "tied_weights": True
-    }
-    dae = DenoisingAutoencoder(**config)
-
-    # # Load initial weights and biases from file
-    # params_to_load = 'dae_params.pkl'
-    # dae.load_params(params_to_load)
-
-    optimizer = AdaDelta(model=dae, dataset=mnist, epochs=100)
-    optimizer.train()
-
-    # Save some reconstruction output images
-    n_examples = 100
-    test_xs = mnist.test_inputs[:n_examples]
-    dae.create_reconstruction_image(test_xs)
-
-    del dae, mnist
-
-
-if __name__ == '__main__':
-    run_dae()