def testUniEncoderForwardPass(self):
with self.session(use_gpu=False):
tf.set_random_seed(8372749040)
p = self._UniEncoderParams()
mt_enc = encoder.MTEncoderUniRNN(p)
batch = py_utils.NestedMap()
batch.ids = tf.transpose(tf.reshape(tf.range(0, 8, 1), [4, 2]))
batch.paddings = tf.zeros([2, 4])
enc_out = mt_enc.FPropDefaultTheta(batch).encoded
tf.global_variables_initializer().run()
actual_enc_out = enc_out.eval()
expected_enc_out = [[[-1.74790625e-06, -5.04228524e-07],
[2.04836829e-06, 1.48639378e-06]],
[[-1.10486064e-06, -5.77133278e-07],
[4.66779238e-06, 3.72350723e-06]],
[[-5.65139544e-07, -1.84634030e-06],
[3.99908731e-06, 1.90148887e-06]],
[[7.14102157e-07, -2.31352783e-06],
[7.05981620e-06, 2.68004328e-06]]]
self.assertAllClose(expected_enc_out, actual_enc_out)
def testUniEncoderForwardPass(self):
with self.session(use_gpu=False):
tf.random.set_seed(8372749040)
p = self._UniEncoderParams()
mt_enc = encoder.MTEncoderUniRNN(p)
batch = py_utils.NestedMap()
batch.ids = tf.transpose(tf.reshape(tf.range(0, 8, 1), [4, 2]))
batch.paddings = tf.zeros([2, 4])
enc_out = mt_enc.FPropDefaultTheta(batch).encoded
self.evaluate(tf.global_variables_initializer())
actual_enc_out = enc_out.eval()
expected_enc_out = [[[4.3564430e-07, -2.3954138e-07],
[-9.8339186e-08, 8.5873717e-07]],
[[1.4911951e-07, -3.4084817e-07],
[-7.1341539e-08, 2.1979017e-06]],
[[-6.4054962e-07, -1.1942817e-06],
[-6.6461860e-07, 1.0963676e-06]],
[[-1.3252994e-06, -1.5549912e-06],
[-1.4652252e-06, 1.4637867e-06]]]
self.assertAllClose(expected_enc_out, actual_enc_out)
def testUniEncoderForwardPass(self):
with self.session(use_gpu=False):
tf.random.set_seed(8372749040)
p = self._UniEncoderParams()
mt_enc = encoder.MTEncoderUniRNN(p)
batch = py_utils.NestedMap()
batch.ids = tf.transpose(tf.reshape(tf.range(0, 8, 1), [4, 2]))
batch.paddings = tf.zeros([2, 4])
enc_out = mt_enc.FPropDefaultTheta(batch).encoded
self.evaluate(tf.global_variables_initializer())
actual_enc_out = enc_out.eval()
tf.logging.info('testUniEncoderForwardPass actual_enc_out %r' %
actual_enc_out)
expected_enc_out = [[[-4.3304257e-07, 5.4100457e-07],
[-4.0170832e-07, -2.6441572e-07]],
[[-1.7024040e-07, -1.8555815e-07],
[-6.4563977e-07, -3.7835261e-07]],
[[-2.4001852e-07, 5.1114228e-07],
[-3.4349023e-07, -1.0049351e-06]],
[[1.8068013e-07, -6.8982729e-08],
[3.3005003e-07, -8.8834116e-07]]]
self.assertAllClose(expected_enc_out, actual_enc_out)