def test_generate_name(self):
with self.test_session():
ops = TensorflowOps()
ops.describe("generator")
self.assertEqual(ops.generate_name(), "generator_1")
self.assertEqual(ops.generate_name(), "generator_2")
self.assertEqual(ops.generate_name("custom"), "custom")
self.assertEqual(ops.generate_name(), "generator_3")
def gan_factory(*args, **kw_args):
if 'config' in kw_args:
config = kw_args['config']
elif len(args) > 0:
config = args[0]
else:
config = None
if config and 'class' in config:
return TensorflowOps.lookup_function(None, config['class'])(*args,
**kw_args)
else:
return StandardGAN(*args, **kw_args)
def test_generate_name(self):
with self.test_session():
ops = TensorflowOps()
ops.describe("generator")
self.assertEqual(ops.generate_name(), "generator_1")
self.assertEqual(ops.generate_name(), "generator_2")
self.assertEqual(ops.generate_name("custom"), "custom")
self.assertEqual(ops.generate_name(), "generator_3")
def test_variable_constructor(self):
with self.test_session():
ops = TensorflowOps()
self.assertEqual(len(ops.weights), 0)
self.assertEqual(len(ops.biases), 0)
self.assertEqual(len(ops.variables()), 0)
def test_generate_scope(self):
with self.test_session():
ops = TensorflowOps()
self.assertEqual(ops.generate_scope(), "1")
self.assertEqual(ops.generate_scope(), "2")
def test_get_bias(self):
with self.test_session():
ops = TensorflowOps({'dtype': 'float32'})
ops.get_bias([1, 1])
self.assertTrue('float32' in str(ops.biases[0].dtype))
self.assertEqual(ops.shape(ops.biases[0]), [1, 1])
import tensorflow as tf
import hypergan as hg
from hypergan.ops.tensorflow.ops import TensorflowOps
from unittest.mock import MagicMock
ops = TensorflowOps()
tanh_str = "function:tensorflow.python.ops.math_ops.tanh"
class OpsTest(tf.test.TestCase):
def test_lookup_activations(self):
x = tf.constant(-1.0, shape=[2, 2])
with self.test_session():
activations = ['relu', 'prelu', 'selu', 'crelu']
for activation in activations:
activation = ops.lookup(activation)(x)
tf.get_default_session().run(tf.global_variables_initializer())
self.assertNotEqual(x.eval()[0][0], activation.eval()[0][0])
def test_lookup_function(self):
with self.test_session():
self.assertEqual(ops.lookup_function(tanh_str), tf.nn.tanh)
def test_lookup_class(self):
with self.test_session():
self.assertEqual(ops.lookup_class('class:hypergan.GAN'), hg.GAN)
def test_lookup(self):
def test_get_weight(self):
with self.test_session():
ops = TensorflowOps({'dtype':'float32'})
ops.get_weight([1,1])
self.assertTrue('float32' in str(ops.weights[0].dtype))
self.assertEqual(ops.shape(ops.weights[0]), [1, 1])
def test_variable_constructor(self):
with self.test_session():
ops = TensorflowOps()
self.assertEqual(len(ops.weights), 0)
self.assertEqual(len(ops.biases), 0)
self.assertEqual(len(ops.variables()), 0)
def test_generate_scope(self):
with self.test_session():
ops = TensorflowOps()
self.assertEqual(ops.generate_scope(), "1")
self.assertEqual(ops.generate_scope(), "2")