added a dataset, tried testing (unsuccessfully)

6 files changed, 12 insertions, 12 deletions

diff --git a/.DS_Store b/.DS_Store
new file mode 100644
index 00000000..bba36123
--- /dev/null
+++ b/.DS_Store
diff --git a/__pycache__/hyperparameters.cpython-38.pyc b/__pycache__/hyperparameters.cpython-38.pyc
new file mode 100644
index 00000000..637c2796
--- /dev/null
+++ b/__pycache__/hyperparameters.cpython-38.pyc
diff --git a/__pycache__/losses.cpython-38.pyc b/__pycache__/losses.cpython-38.pyc
new file mode 100644
index 00000000..398e9cb3
--- /dev/null
+++ b/__pycache__/losses.cpython-38.pyc
diff --git a/__pycache__/preprocess.cpython-38.pyc b/__pycache__/preprocess.cpython-38.pyc
new file mode 100644
index 00000000..e2f42bca
--- /dev/null
+++ b/__pycache__/preprocess.cpython-38.pyc
diff --git a/losses.py b/losses.py
index 93449962..6ebba671 100644
--- a/losses.py
+++ b/losses.py
@@ -63,13 +63,13 @@ class YourModel(tf.keras.Model):
         #       Dense(15,  activation='softmax')
         ]
 
-        self.vgg16 = tf.keras.Sequential(self.vgg16, name="vgg_base")
-        self.head = tf.keras.Sequential(self.head, name="vgg_head")
+       #  self.vgg16 = tf.keras.Sequential(self.vgg16, name="vgg_base")
+       #  self.head = tf.keras.Sequential(self.head, name="vgg_head")
 
-        self.indexed_layers = [layer for layer in self.vgg16 if layer.name.contains("conv1")]
-        self.desired = [layer.name for layer in self.vgg16 if layer.name.contains("conv1")]
+        self.indexed_layers = [layer for layer in self.vgg16 if layer.name == "conv1"]
+        self.desired = [layer.name for layer in self.vgg16 if layer.name == "conv1"]
 
-    def forward_pass(self, x):
+    def call(self, x):
         layers = []
         for layer in self.vgg16.layers:
             # pass the x through
@@ -83,7 +83,7 @@ class YourModel(tf.keras.Model):
             return x, np.array(layers)
 
 
-    def loss_function(self, p, a, x):
+    def loss_fn(self, p, a, x):
         _, photo_layers = self.forward_pass(p)
         _, art_layers = self.forward_pass(a)
         _, input_layers = self.forward_pass(x)
diff --git a/main.py b/main.py
index ca87788d..837dea81 100644
--- a/main.py
+++ b/main.py
@@ -6,11 +6,11 @@ from datetime import datetime
 import tensorflow as tf
 
 import hyperparameters as hp
-from models import YourModel, VGGModel
+from losses import YourModel
 from preprocess import Datasets
 from skimage.transform import resize
-from tensorboard_utils import \
-        ImageLabelingLogger, ConfusionMatrixLogger, CustomModelSaver
+# from tensorboard_utils import \
+#         ImageLabelingLogger, ConfusionMatrixLogger, CustomModelSaver
 
 from skimage.io import imread
 from lime import lime_image
@@ -128,9 +128,9 @@ def train(model, datasets, checkpoint_path, logs_path, init_epoch):
         tf.keras.callbacks.TensorBoard(
             log_dir=logs_path,
             update_freq='batch',
-            profile_batch=0),
-        ImageLabelingLogger(logs_path, datasets),
-        CustomModelSaver(checkpoint_path, ARGS.task, hp.max_num_weights)
+            profile_batch=0)
+        # ImageLabelingLogger(logs_path, datasets),
+        # CustomModelSaver(checkpoint_path, ARGS.task, hp.max_num_weights)
     ]
 
     # Include confusion logger in callbacks if flag set