update to tf2

.gitignore

@@ -1,3 +1,4 @@
 .venv/
 modules/__pycache__/
 runs/
+*.swp

README.md

@@ -19,7 +19,7 @@ Learn more at <a href="http://kstaats.github.io/karoo_gp/">kstaats.github.io/kar
 
 # Debian Install
 
-To install on Debian (Buster, Stable, 10):
+To install on Debian (Buster/Stable/10):
 
 ```
 # Install Dependencies:
@@ -42,3 +42,31 @@ pip3 install numpy==1.16.4 sympy==1.4 tensorflow==1.13.1 scikit-learn==0.21.2
 python3 karoo_gp.py
 ```
 
+# Tensorflow 2 Install
+Using karoo_gp with Tensorflow 2 on Debian (Buster/Stable/10).
+
+```
+# Install Dependencies:
+sudo apt install python3 python3-pip python3-venv
+
+# Clone repo (choose this one or upstream):
+# git clone https://github.com/kstaats/karoo_gp
+git clone https://spacecruft.org/spacecruft/karoo_gp
+
+# Setup
+cd karoo_gp
+python3 -m venv .venv
+source .venv/bin/activate
+
+pip3 install --upgrade pip
+pip3 install --upgrade setuptools
+
+# Install python dependencies
+pip3 install wheel
+pip3 install sklearn sympy
+# This will install Tensorflow 2.1:
+pip3 install tensorflow
+
+# Run application
+python3 karoo_gp.py
+```

modules/karoo_gp_base_class.py

@@ -56,8 +56,8 @@ operators = {ast.Add: tf.add, # e.g., a + b
 	'square': tf.square, # e.g., square(a)
 	'sqrt': tf.sqrt, # e.g., sqrt(a)
 	'pow': tf.pow, # e.g., pow(a, b)
-	'log': tf.log, # e.g., log(a)
-	'log1p': tf.log1p, # e.g., log1p(a)
+	'log': tf.math.log, # e.g., log(a)
+	'log1p': tf.math.log1p, # e.g., log1p(a)
 	'cos': tf.cos, # e.g., cos(a)
 	'sin': tf.sin, # e.g., sin(a)
 	'tan': tf.tan, # e.g., tan(a)
@@ -1228,11 +1228,11 @@ class Base_GP(object):
 		'''
 		
 		# Initialize TensorFlow session
-		tf.reset_default_graph() # Reset TF internal state and cache (after previous processing)
-		config = tf.ConfigProto(log_device_placement=self.tf_device_log, allow_soft_placement=True)
+		tf.compat.v1.reset_default_graph() # Reset TF internal state and cache (after previous processing)
+		config = tf.compat.v1.ConfigProto(log_device_placement=self.tf_device_log, allow_soft_placement=True)
 		config.gpu_options.allow_growth = True
 		
-		with tf.Session(config=config) as sess:
+		with tf.compat.v1.Session(config=config) as sess:
 			with sess.graph.device(self.tf_device):
 			
 				# 1 - Load data into TF vectors
@@ -1314,7 +1314,7 @@ class Base_GP(object):
 					
 				else: raise Exception('Kernel type is wrong or missing. You entered {}'.format(self.kernel))
 				
-				fitness = tf.reduce_sum(pairwise_fitness)
+				fitness = tf.reduce_sum(input_tensor=pairwise_fitness)
 				
 				# Process TF graph and collect the results
 				result, pred_labels, solution, fitness, pairwise_fitness = sess.run([result, pred_labels, solution, fitness, pairwise_fitness])
@@ -1433,9 +1433,9 @@ class Base_GP(object):
 		
 		for class_label in range(self.class_labels - 2, 0, -1):
 			cond = (class_label - 1 - skew < result) & (result <= class_label - skew)
-			label_rules[class_label] = tf.cond(cond, lambda: (tf.constant(class_label), tf.constant(' <= {}'.format(class_label - skew))), lambda: label_rules[class_label + 1])
+			label_rules[class_label] = tf.cond(pred=cond, true_fn=lambda: (tf.constant(class_label), tf.constant(' <= {}'.format(class_label - skew))), false_fn=lambda: label_rules[class_label + 1])
 			
-		pred_label = tf.cond(result <= 0 - skew, lambda: (tf.constant(0), tf.constant(' <= {}'.format(0 - skew))), lambda: label_rules[1])
+		pred_label = tf.cond(pred=result <= 0 - skew, true_fn=lambda: (tf.constant(0), tf.constant(' <= {}'.format(0 - skew))), false_fn=lambda: label_rules[1])
 			
 		return pred_label