def testBiEncoderForwardPassWithInputPacking(self):
with self.session(use_gpu=False):
with tf.variable_scope('bienc_test', reuse=tf.AUTO_REUSE):
bs = 3
sl = 3
tf.random.set_seed(8372749040)
p = self._BiEncoderParams()
mt_enc = encoder.MTEncoderBiRNN(p)
packed_params = p.Copy()
packed_params.packed_input = True
mt_enc_packed = encoder.MTEncoderBiRNN(packed_params)
batch = py_utils.NestedMap()
batch.ids = tf.constant(
np.random.randint(low=0, high=15, size=[bs, sl], dtype=np.int32))
batch.paddings = tf.zeros([bs, sl])
packed_batch = py_utils.NestedMap()
packed_batch.ids = tf.reshape(batch.ids, [1, -1])
packed_batch.paddings = tf.reshape(batch.paddings, [1, -1])
packed_batch.segment_ids = tf.constant(
[[0, 0, 0, 1, 1, 1, 2, 2, 2]], dtype=tf.float32)
packed_batch.segment_pos = tf.constant(
[[0, 1, 2, 0, 1, 2, 0, 1, 2]], dtype=tf.int32)
enc_out = mt_enc.FPropDefaultTheta(batch).encoded
enc_out = tf.transpose(enc_out, [1, 0, 2])
packed_enc_out = mt_enc_packed.FPropDefaultTheta(packed_batch)
packed_enc_out = tf.reshape(packed_enc_out.encoded, tf.shape(enc_out))
self.evaluate(tf.global_variables_initializer())
actual_enc_out, actual_packed_enc_out = self.evaluate(
[enc_out, packed_enc_out])
self.assertAllClose(actual_packed_enc_out, actual_enc_out)
def testBiEncoderForwardPassWithTransparent(self):
with self.session(use_gpu=False):
tf.set_random_seed(8372749040)
p = self._BiEncoderParams()
p.is_transparent = True
mt_enc = encoder.MTEncoderBiRNN(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()
# pylint: disable=bad-whitespace,bad-continuation
# pyformat: disable
expected_enc_out = [[[-4.95129862e-05, 1.92920983e-04],
[-2.18278728e-10, -1.56396545e-05]],
[[1.80083007e-04, 6.55014810e-05],
[8.51639197e-05, 6.82225800e-05]],
[[2.12642481e-05, -2.92667974e-05],
[-8.88068098e-05, 5.24776005e-05]],
[[-1.33993672e-04, 3.61708371e-05],
[-1.35903974e-04, 1.31157576e-05]]]
# pyformat: enable
# pylint: enable=bad-whitespace,bad-continuation
self.assertAllClose(expected_enc_out, actual_enc_out)
def testBiEncoderForwardPassWithDropout(self):
with self.session(use_gpu=False):
tf.set_random_seed(8372749040)
p = self._BiEncoderParams()
p.dropout_prob = 0.5
mt_enc = encoder.MTEncoderBiRNN(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()
print('bi_enc_actual_enc_out_with_dropout',
np.array_repr(actual_enc_out))
# pylint: disable=bad-whitespace,bad-continuation
# pyformat: disable
expected_enc_out = [[[-2.25614094e-05, 1.19781353e-05],
[-2.74532852e-07, 8.17993077e-06]],
[[2.66865045e-05, 1.02941645e-04],
[1.51371260e-05, 3.78371587e-05]],
[[3.50117516e-05, 7.65562072e-06],
[-1.30227636e-05, 3.01171349e-06]],
[[2.27566215e-06, 1.42354111e-07],
[1.04521234e-06, 2.50320113e-06]]]
# pyformat: enable
# pylint: enable=bad-whitespace,bad-continuation
self.assertAllClose(expected_enc_out, actual_enc_out)
def testBiEncoderForwardPassWithTransparent(self):
with self.session(use_gpu=False):
tf.random.set_seed(8372749040)
p = self._BiEncoderParams()
p.is_transparent = True
mt_enc = encoder.MTEncoderBiRNN(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(
'testBiEncoderForwardPassWithTransparent actual_enc_out %r' %
actual_enc_out)
expected_enc_out = [[[1.53976856e-04, -1.66475205e-04],
[-1.02031634e-04, 1.39693424e-04]],
[[1.62726530e-04, -2.22654475e-04],
[-4.89080339e-05, 1.10912690e-04]],
[[1.28586107e-04, -1.62333992e-04],
[7.22907062e-05, -9.17545694e-05]],
[[9.02724860e-05, -1.71898617e-04],
[-9.77059244e-06, 7.55862275e-05]]]
self.assertAllClose(expected_enc_out, actual_enc_out)
def testBiEncoderForwardPass(self):
with self.session(use_gpu=False):
tf.set_random_seed(8372749040)
p = self._BiEncoderParams()
mt_enc = encoder.MTEncoderBiRNN(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 = [[[1.42110639e-06, 1.31101151e-05], [
-6.62138473e-06, -1.11313329e-06
]], [[1.14506956e-05, 2.98347204e-05], [-5.89276988e-06, 5.54328744e-06]],
[[1.35346390e-05, 1.00745674e-05],
[-4.80002745e-06, -1.23648788e-05]],
[[2.00507566e-06, -1.51463591e-05],
[-5.71241526e-06, -1.87959231e-05]]]
self.assertAllClose(expected_enc_out, actual_enc_out)
def testBiEncoderForwardPass(self):
with self.session(use_gpu=False):
tf.random.set_seed(8372749040)
p = self._BiEncoderParams()
mt_enc = encoder.MTEncoderBiRNN(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 = [[[4.0744379e-07, -2.0108675e-06],
[-4.2056736e-06, 9.2221135e-06]],
[[1.2086311e-06, -2.2510878e-07],
[-2.2938407e-06, 9.3108029e-06]],
[[3.4632390e-06, -3.1495360e-06],
[9.1814104e-07, 1.9459947e-06]],
[[-9.0593801e-08, -1.2912932e-06],
[-5.8420886e-07, -6.5603672e-07]]]
self.assertAllClose(expected_enc_out, actual_enc_out)
def testBiEncoderForwardPassWithTransparent(self):
with self.session(use_gpu=False):
tf.random.set_seed(8372749040)
p = self._BiEncoderParams()
p.is_transparent = True
mt_enc = encoder.MTEncoderBiRNN(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 = [[[-7.4536911e-05, 8.8465633e-05],
[2.8940600e-05, 3.2297492e-05]],
[[-1.9775725e-05, 9.8312848e-05],
[5.1837378e-05, 1.2998647e-05]],
[[4.5528584e-05, -6.8125606e-05],
[1.0955606e-04, -2.1024598e-04]],
[[8.5454740e-05, -1.8263397e-04],
[5.2042866e-05, -1.6407830e-04]]]
self.assertAllClose(expected_enc_out, actual_enc_out)
def testBiEncoderForwardPassWithDropout(self):
with self.session(use_gpu=False):
tf.random.set_seed(8372749040)
p = self._BiEncoderParams()
p.dropout_prob = 0.5
mt_enc = encoder.MTEncoderBiRNN(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()
print('bi_enc_actual_enc_out_with_dropout', np.array_repr(actual_enc_out))
expected_enc_out = [[[1.60383240e-06, 1.22550023e-06],
[-7.21660126e-06, 1.05704457e-05]],
[[1.42539475e-05, -2.06075638e-05],
[-4.98754298e-06, 1.51066461e-05]],
[[-7.15192800e-06, -6.44075908e-06],
[5.02962678e-07, -3.40795486e-06]],
[[-6.54424548e-06, 9.88359807e-06],
[1.42836643e-06, -1.68607176e-06]]]
self.assertAllClose(expected_enc_out, actual_enc_out)
def testBiEncoderForwardPass(self):
with self.session(use_gpu=False):
tf.random.set_seed(8372749040)
p = self._BiEncoderParams()
mt_enc = encoder.MTEncoderBiRNN(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('testBiEncoderForwardPass actual_enc_out %r' %
actual_enc_out)
expected_enc_out = [[[-2.47998378e-06, 7.36457878e-06],
[7.89248020e-07, -2.67464316e-06]],
[[-2.98803275e-06, 8.20233890e-06],
[1.00139073e-06, -2.24554151e-06]],
[[-5.06675951e-06, 1.15983785e-05],
[-4.58391014e-07, -2.99553108e-07]],
[[-4.34937465e-06, 8.58816838e-06],
[-1.74859031e-06, 3.99598093e-06]]]
self.assertAllClose(expected_enc_out, actual_enc_out)
def testBiEncoderForwardPassWithDropout(self):
with self.session(use_gpu=False):
tf.random.set_seed(8372749040)
p = self._BiEncoderParams()
p.dropout_prob = 0.5
mt_enc = encoder.MTEncoderBiRNN(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()
print('bi_enc_actual_enc_out_with_dropout',
np.array_repr(actual_enc_out))
expected_enc_out = [[[-1.8358192e-05, 1.2103478e-05],
[2.9347059e-06, -3.0652325e-06]],
[[-8.1282624e-06, 4.5443494e-06],
[3.0826509e-06, -5.2950490e-06]],
[[-4.6669629e-07, 2.4246765e-05],
[-1.5221613e-06, -1.9654153e-06]],
[[-1.1511075e-05, 1.9061190e-05],
[-5.7250163e-06, 9.2785704e-06]]]
self.assertAllClose(expected_enc_out, actual_enc_out)
def testTransparentEncoderConstruction(self): p = self._BiEncoderParams() p.is_transparent = True _ = encoder.MTEncoderBiRNN(p)
