Recursion

TESTS/2DimensionOutput.py

@@ -0,0 +1,29 @@
+import tensorflow as tf
+from tensorflow.python.framework import function
+
+fac = function.Declare("Fac", [("n", tf.int32)], [("ret", tf.int32)])
+
+@function.Defun(tf.int32, func_name="Fac", out_names=["ret"])
+def FacImpl(n):
+	return tf.cond(tf.less_equal(n, 1),
+		lambda: tf.constant([1,1]),
+		lambda: [n,n]*fac(n-1))
+
+
+FacImpl.add_to_graph(tf.get_default_graph())
+
+n = tf.placeholder(tf.int32, shape=[])
+x = tf.add(n, 1)
+result = fac(x)
+y = tf.add(result, [1,1])
+
+#print(tf.get_default_graph().as_graph_def())
+
+writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())
+
+sess = tf.Session()
+print(sess.run(y, feed_dict={n: 5}))
+
+writer.close()
+
+sess.close()

TESTS/ackermann.py

@@ -0,0 +1,44 @@
+import tensorflow as tf
+from tensorflow.python.framework import function
+
+ack = function.Declare("Ack", [("m", tf.int32), ("n", tf.int32)], [("ret", tf.int32)])
+
+@function.Defun(tf.int32, tf.int32, func_name="Ack", out_names=["ret"])
+def AckImpl(m,n):
+
+	def f1(): 
+		ret = n + 1
+		return ret
+
+	def f2():
+		def ff1():
+			r = ack(m-1,1)
+			return r
+
+		def ff2():
+			r = ack(m-1, ack(m, n-1))
+			return r
+
+		ret = tf.cond(tf.equal(n, 0), ff1, ff2)
+		return ret
+
+	return tf.cond(tf.equal(m, 0), f1, f2)
+
+
+AckImpl.add_to_graph(tf.get_default_graph())
+
+n = tf.placeholder(tf.int32, shape=[])
+m = tf.placeholder(tf.int32, shape=[])
+res = ack(m,n)
+
+writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())
+
+sess = tf.Session()
+
+#print(tf.get_default_graph().as_graph_def())
+
+print(sess.run(res, feed_dict={m:2, n:3}))
+
+sess.close()
+
+writer.close()

TESTS/create_worker.py

@@ -0,0 +1,13 @@
+# Get task number from command line
+import sys
+task_number = int(sys.argv[1])
+
+import tensorflow as tf
+
+cluster = tf.train.ClusterSpec({"local": ["localhost:2222", "localhost:2223"]})
+server = tf.train.Server(cluster, job_name="local", task_index=task_number)
+
+print("Starting server #{}".format(task_number))
+
+server.start()
+server.join()

TESTS/distributed/distr_factorial.py

@@ -0,0 +1,40 @@
+import tensorflow as tf
+from tensorflow.python.framework import function
+
+cluster = tf.train.ClusterSpec({"local": ["localhost:2222", "localhost:2223"]})
+
+fac = function.Declare("Fac", [("n", tf.int32)], [("ret", tf.int32)])
+
+@function.Defun(tf.int32, func_name="Fac", out_names=["ret"])
+def FacImpl(n):
+
+	def f1(): 
+		with tf.device("/job:local/replica:0/task:0/device:CPU:0"):
+			ret = tf.constant(1)
+		return ret
+	def f2(): 
+		with tf.device("/job:local/replica:0/task:1/device:CPU:0"):
+			ret = n * fac(n - 1)
+		return ret
+
+	with tf.device("/job:local/replica:0/task:1/device:CPU:0"):
+		pred = tf.less_equal(n, 1)
+
+	return tf.cond(pred, f1, f2)
+
+FacImpl.add_to_graph(tf.get_default_graph())
+
+n = tf.placeholder(tf.int32, shape=[])
+x = tf.add(n, 1)
+result = fac(x)
+y = tf.add(result, 1)
+
+#print(tf.get_default_graph().as_graph_def())
+
+writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())
+
+with tf.Session("grpc://localhost:2222") as sess:
+	print(sess.run(y, feed_dict={n: 5}))
+
+writer.close()
+

TESTS/distributed/distr_fcallsg.py

@@ -0,0 +1,44 @@
+import tensorflow as tf
+from tensorflow.python.framework import function
+
+cluster = tf.train.ClusterSpec({"local": ["localhost:2222", "localhost:2223"]})
+
+@function.Defun(tf.float32)
+def G(x):
+
+	with tf.device("/job:local/replica:0/task:1/device:CPU:0"):
+		ret = x + x	
+
+	return ret
+
+
+@function.Defun(tf.float32, tf.float32)
+def MyFunc(x, y):
+
+	with tf.device("/job:local/replica:0/task:0/device:CPU:0"):
+		g1 = G(x)
+		g2 = G(y)
+
+		ret = g1 + g2			
+
+	return ret
+
+
+# Building the graph.
+
+a = tf.constant([4.0], name="a")
+b = tf.placeholder(tf.float32, name="MyPlaceHolder")
+
+add = tf.add(a, b, name="add")
+sub = tf.subtract(a, b, name="sub")
+
+ret = MyFunc(add, sub, name='mycall')
+
+#x = tf.add(c, d)
+
+writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())
+
+with tf.Session("grpc://localhost:2222") as sess:
+	print(sess.run([ret], feed_dict={b:1}))
+
+writer.close()

TESTS/distributed/distr_fibonacci.py

@@ -0,0 +1,39 @@
+import tensorflow as tf
+from tensorflow.python.framework import function
+
+cluster = tf.train.ClusterSpec({"local": ["localhost:2222", "localhost:2223"]})
+
+fib = function.Declare("Fib", [("n", tf.int32)], [("ret", tf.int32)])
+
+@function.Defun(tf.int32, func_name="Fib", out_names=["ret"])
+def FibImpl(n):
+
+	def f1(): 
+		with tf.device("/job:local/replica:0/task:0/device:CPU:0"):
+			ret = tf.constant(1)
+		return ret
+	def f2(): 
+		with tf.device("/job:local/replica:0/task:0/device:CPU:0"):
+			fib1 = fib(n-1)
+		with tf.device("/job:local/replica:0/task:1/device:CPU:0"): 
+			fib2 = fib(n-2)
+
+		return fib1 + fib2
+
+	return tf.cond(tf.less_equal(n, 1), f1, f2)
+
+FibImpl.add_to_graph(tf.get_default_graph())
+
+n = tf.placeholder(tf.int32, shape=[])
+x = fib(n)
+
+res = tf.add(x, 1)
+
+#print(tf.get_default_graph().as_graph_def())
+
+writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())
+
+with tf.Session("grpc://localhost:2222") as sess:
+	print(sess.run(res, feed_dict={n: 20}))
+
+writer.close()

TESTS/distributed/distr_fog.py

@@ -0,0 +1,36 @@
+import tensorflow as tf
+from tensorflow.python.framework import function
+
+cluster = tf.train.ClusterSpec({"local": ["localhost:2222", "localhost:2223"]})
+
+@function.Defun(tf.float32)
+def G(x):
+	with tf.device("/job:local/replica:0/task:0/device:CPU:0"):
+		add = x + 1
+	with tf.device("/job:local/replica:0/task:1/device:CPU:0"):
+		ret = x * add 
+	return ret
+
+@function.Defun(tf.float32)
+def F(x):
+	with tf.device("/job:local/replica:0/task:1/device:CPU:0"):
+		add = x + 1 
+	with tf.device("/job:local/replica:0/task:0/device:CPU:0"):
+		ret = x * add
+	return ret
+
+
+a = tf.constant([4.0], name="a")
+b = tf.placeholder(tf.float32, name="MyPlaceHolder")
+
+add = tf.add(a, b, name="add")
+
+ret = F(G(add), name='mycall')
+
+writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())
+
+with tf.Session("grpc://localhost:2222") as sess:
+	print(sess.run([ret], feed_dict={b:1}))
+
+writer.close()
+

TESTS/distributed/distr_funcSimple.py

@@ -0,0 +1,36 @@
+import tensorflow as tf
+from tensorflow.python.framework import function
+
+cluster = tf.train.ClusterSpec({"local": ["localhost:2222", "localhost:2223"]})
+
+@function.Defun(tf.int32, tf.int32)
+def MyFunc(x, y):
+
+	with tf.device("/job:local/replica:0/task:1/device:CPU:0"):
+		add1 = x + y
+
+	return [add1, x - y]
+
+
+# Building the graph.
+
+a = tf.constant([4], name="x")
+b = tf.placeholder(tf.int32, name="MyPlaceHolder")
+
+with tf.device("/job:local/replica:0/task:0/device:CPU:0"):
+	add = tf.add(a, b, name="add")
+
+with tf.device("/job:local/replica:0/task:1/device:CPU:0"):
+	sub = tf.subtract(a, b, name="sub")
+
+[c,d] = MyFunc(add, sub, name='mycall')
+
+x = tf.add(c, d)
+
+#print(tf.get_default_graph().as_graph_def())
+
+writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())
+
+with tf.Session("grpc://localhost:2222") as sess:
+	print(sess.run([x], feed_dict={b:1}))
+writer.close()

TESTS/distributed/distr_mutrec.py

@@ -0,0 +1,49 @@
+import tensorflow as tf
+from tensorflow.python.framework import function
+
+cluster = tf.train.ClusterSpec({"local": ["localhost:2222", "localhost:2223"]})
+
+f = function.Declare("F", [("n", tf.int32)], [("ret", tf.int32)])
+g = function.Declare("G", [("n", tf.int32)], [("ret", tf.int32)])
+
+@function.Defun(tf.int32, func_name="F", out_names=["ret"])
+def FImpl(n):
+
+	def f1(): 
+		with tf.device("/job:local/replica:0/task:0/device:CPU:0"):
+			ret = tf.constant(1)
+		return ret
+	def f2(): 
+		with tf.device("/job:local/replica:0/task:0/device:CPU:0"):
+			x = n - 1
+			ret = g(x)
+		return ret
+
+#	with tf.device("/job:local/replica:0/task:1/device:CPU:0"):
+	pred = tf.less_equal(n, 1)
+
+	return tf.cond(pred, f1, f2)
+
+
+@function.Defun(tf.int32, func_name="G", out_names=["ret"])
+def GImpl(n):
+
+	with tf.device("/job:local/replica:0/task:1/device:CPU:0"):
+		x = n - 1
+		ret = f(x)
+	return ret
+
+
+FImpl.add_to_graph(tf.get_default_graph())
+GImpl.add_to_graph(tf.get_default_graph())
+
+
+n = tf.placeholder(tf.int32, name="MyPlaceHolder")
+x = f(n)
+
+writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())
+
+with tf.Session("grpc://localhost:2222") as sess:
+	print(sess.run([x], feed_dict={n:4}))
+
+writer.close()

TESTS/factorial.py

@@ -0,0 +1,29 @@
+import tensorflow as tf
+from tensorflow.python.framework import function
+
+fac = function.Declare("Fac", [("n", tf.int32)], [("ret", tf.int32)])
+
+@function.Defun(tf.int32, func_name="Fac", out_names=["ret"])
+def FacImpl(n):
+	return tf.cond(tf.less_equal(n, 1),
+		lambda: tf.constant(1),
+		lambda: n * fac(n - 1))
+
+
+FacImpl.add_to_graph(tf.get_default_graph())
+
+n = tf.placeholder(tf.int32, shape=[])
+x = tf.add(n, 1)
+result = fac(x)
+y = tf.add(result, 1)
+
+#print(tf.get_default_graph().as_graph_def())
+
+writer = tf.summary.FileWriter('./graphs', tf.get_default_graph())
+
+sess = tf.Session()
+print(sess.run(y, feed_dict={n: 5}))
+
+writer.close()
+
+sess.close()