def test_value(self):
def fn1(): return 'fn1'
def fn2(): return 'fn2'
def expected(v): return 'fn1' if v else 'fn2'
for v in [True, False, 1, 0]:
o = utils.smart_cond(constant_op.constant(v), fn1, fn2)
self.assertEqual(o, expected(v))
def test_tensors(self):
def fn1(): return constant_op.constant(0) - constant_op.constant(1)
def fn2(): return constant_op.constant(0) - constant_op.constant(2)
def expected(v): return -1 if v else -2
for v in [True, False, 1, 0]:
o = utils.smart_cond(constant_op.constant(v), fn1, fn2)
with self.cached_session():
self.assertEqual(o.eval(), expected(v))
def test_constant(self):
def fn1(): return constant_op.constant('fn1')
def fn2(): return constant_op.constant('fn2')
def expected(v): return b'fn1' if v else b'fn2'
for v in [True, False, 1, 0]:
o = utils.smart_cond(constant_op.constant(v), fn1, fn2)
with self.cached_session():
self.assertEqual(o.eval(), expected(v))
def test_tensors(self):
def fn1(): return constant_op.constant(0) - constant_op.constant(1)
def fn2(): return constant_op.constant(0) - constant_op.constant(2)
def expected(v): return -1 if v else -2
p = array_ops.placeholder(dtypes.bool, [])
for v in [True, False, 1, 0]:
o = utils.smart_cond(p, fn1, fn2)
with self.cached_session():
self.assertEqual(o.eval(feed_dict={p: v}), expected(v))
def test_value(self):
def fn1(): return ops.convert_to_tensor('fn1')
def fn2(): return ops.convert_to_tensor('fn2')
def expected(v): return b'fn1' if v else b'fn2'
p = array_ops.placeholder(dtypes.bool, [])
for v in [True, False, 1, 0]:
o = utils.smart_cond(p, fn1, fn2)
with self.cached_session():
self.assertEqual(o.eval(feed_dict={p: v}), expected(v))
def test_variable(self):
with tf.Graph().as_default():
def fn1(): return variables.Variable('fn1')
def fn2(): return variables.Variable('fn2')
def expected(v): return b'fn1' if v else b'fn2'
p = array_ops.placeholder(dtypes.bool, [])
for v in [True, False, 1, 0]:
o = utils.smart_cond(p, fn1, fn2)
with self.cached_session() as sess:
sess.run(variables.global_variables_initializer())
self.assertEqual(o.eval(feed_dict={p: v}), expected(v))
def test_variable(self):
with tf.Graph().as_default():
def fn1(): return variables.Variable('fn1')
def fn2(): return variables.Variable('fn2')
def expected(v): return b'fn1' if v else b'fn2'
for v in [True, False, 1, 0]:
o = utils.smart_cond(constant_op.constant(v), fn1, fn2)
with self.cached_session() as sess:
sess.run(variables.global_variables_initializer())
self.assertEqual(o.eval(), expected(v))