def test_single_input_sequence_with_implicit_lengths(self):
use_log_space = True
use_start_and_end_states = False
scores = np.array([[10.0, 13.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0],
[13.0, 12.0, 11.0, 10.0]])
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_weights = np.array(
[[-1.0, 1.0, -2.0, 2.0], [3.0, -3.0, 4.0, -4.0],
[5.0, 1.0, 10.0, 1.0], [-7.0, 7.0, -8.0, 8.0]],
dtype=np.float32)
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
sequence, _ = viterbi_decode.decode(
scores,
transition_weights,
use_log_space=use_log_space,
use_start_and_end_states=use_start_and_end_states)
# Test a multi-item batch.
multiple_input = np.array([scores], dtype=np.float32)
single_sequence_op = sequence_op.viterbi_constrained_sequence(
multiple_input,
transition_weights=transition_weights,
use_log_space=use_log_space,
use_start_and_end_states=use_start_and_end_states)
single_sequence_result = self.evaluate(single_sequence_op)
self.assertRaggedEqual(single_sequence_result, [sequence])
def test_ragged_input_sequence(self):
use_log_space = True
use_start_and_end_states = False
input_1 = np.array([[10.0, 13.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0],
[13.0, 12.0, 11.0, 10.0]])
input_2 = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
# TODO(b/122968457): Extend RT support to lists-of-ndarrays.
scores = ragged_factory_ops.constant(
[input_1.tolist(), input_2.tolist()])
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_weights = np.array(
[[-1.0, 1.0, -2.0, 2.0], [3.0, -3.0, 4.0, -4.0],
[5.0, 1.0, 10.0, 1.0], [-7.0, 7.0, -8.0, 8.0]],
dtype=np.float32)
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
sequence_1, _ = viterbi_decode.decode(
input_1,
transition_weights,
use_log_space=use_log_space,
use_start_and_end_states=use_start_and_end_states)
sequence_2, _ = viterbi_decode.decode(
input_2,
transition_weights,
use_log_space=use_log_space,
use_start_and_end_states=use_start_and_end_states)
expected_sequence = ragged_factory_ops.constant(
[sequence_1, sequence_2])
# Test a ragged batch
single_sequence_op = sequence_op.viterbi_constrained_sequence(
scores,
transition_weights=transition_weights,
use_log_space=use_log_space,
use_start_and_end_states=use_start_and_end_states)
single_sequence_result = self.evaluate(single_sequence_op)
self.assertRaggedEqual(single_sequence_result, expected_sequence)
def test_viterbi_in_exp_space_with_negative_weights_fails(self):
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
x = 0.0
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[.1, .2, .3, .4], [.5, -.6, .7, .8],
[.9, x, .15, x], [.25, .35, .45, .55]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
with self.assertRaises(ValueError):
_, _ = viterbi_decode.decode(scores,
transition_params,
use_log_space=False)
def test_viterbi_in_log_space_with_start_and_end(self):
scores = np.array([[10.0, 12.0, 7.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
x = -float('inf')
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[-1.0, 1.0, -2.0, 2.0, 0.0],
[3.0, -3.0, 4.0, -4.0, 0.0],
[5.0, x, 10.0, x, x],
[-7.0, 7.0, -8.0, 8.0, 0.0],
[0.0, x, 2.0, 3.0, 0.0]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
# STEP 1:
# All scores should be summed with the last row in the weight tensor, so the
# 'real' scores are:
# B0: { 10.0, X, 9.0, 7.0}
#
# STEP 2:
# Raw scores are: {13.0, 12.0, 11.0, 10.0}
#
# Final state 0: (13.0) Weighted scores are {12.0, 16.0, 18.0, 6.0}
# New totals are {22, X, 27, 18} [max 27 from 2]
#
# Final state 1: (12.0) Weighted scores are {13.0, 9.0, X, 19.0},
# New totals are {23, X, X, 26} [max 26 from 3]
#
# Final state 2: (11.0) Weighted scores are {9, 15, 21, 3},
# New totals are {19, X, 30, 10} [max 30 from 2]
#
# Final state 3: (10.0) Weighted scores are {12, 6, X, 18},
# New totals are {19, X, X, 25} [max 25 from 3]
#
# Top scores are [27, 26, 30, 25] from [2, 3, 2, 3].
# 2->OUT is X, so final scores are [27, 26, X, 25] for a
# final state of [0] with a sequence of [2->0].
sequence, score = viterbi_decode.decode(scores,
transition_params,
use_start_and_end_states=True)
self.assertAlmostEqual(27.0, score)
self.assertEqual([2, 0], sequence)
def test_viterbi_in_exp_space_with_start_and_end(self):
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
x = 0.0
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[ .1, .2, .3, .4, .1],
[ .5, .6, .7, .8, .1],
[ .9, x, .15, x, .1],
[.25, .35, .45, .55, .5],
[ .1, .5, .1, .1, x]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
# STEP 1:
# Starting scores are {.5, 6.0, .6, .4}
# Raw scores are: {13.0, 12.0, 11.0, 10.0}
#
# Final state 0: (13.0) Weighted scores are {1.3, 6.5, 11.7, 3.25}
# New totals are {0.13, 39, 7.02, 1.3} [max 39 from 1]
#
# Final state 1: (12.0) Weighted scores are {2.4, 7.2, 0, 4.2},
# New totals are {0.24, 43.2, 0, 1.68} [max 43.2 from 1]
#
# Final state 2: (11.0) Weighted scores are {3.3, 7.7, 1.65, 4.95},
# New totals are {0.33, 46.2, 0.99, 1.98} [max 46.2 from 1]
#
# Final state 3: (10.0) Weighted scores are {4, 8, 0, 5.5},
# New totals are {0.4, 48, 0, 2.2} [max 48 from 1]
#
# Top scores are [39, 43.2, 46.2, 48] from [1, 1, 1, 1].
# Final multiplication results in [3.9, 4.32, 4.62, 24]
# Final state is [3] with a sequence of [1->3].
sequence, score = viterbi_decode.decode(
scores,
transition_params,
use_log_space=False,
use_start_and_end_states=True)
self.assertAlmostEqual(24.0, score)
self.assertEqual([1, 3], sequence)
def test_viterbi_with_allowed_transitions(self):
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[-1.0, 1.0, -2.0, 2.0],
[3.0, -3.0, 4.0, -4.0],
[5.0, 100.0, 10.0, 200.0],
[-7.0, 7.0, -8.0, 8.0]])
allowed_transitions = np.array([[True, True, True, True],
[True, True, True, True],
[True, False, True, False],
[True, True, True, True]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
# STEP 1:
# Starting scores are {10.0, 12.0, 6.0, 4.0}
# Raw scores are: {13.0, 12.0, 11.0, 10.0}
#
# Final state 0: (13.0) Weighted scores are {12.0, 16.0, 18.0, 6.0}
# New totals are {22, 28, 24, 10} [max 28 from 1]
#
# Final state 1: (12.0) Weighted scores are {13.0, 9.0, X, 19.0},
# New totals are {23, 21, X, 23} [max 23 from 3]
#
# Final state 2: (11.0) Weighted scores are {9, 15, 21, 3},
# New totals are {19, 27, 27, 7} [max 27 from 2]
#
# Final state 3: (10.0) Weighted scores are {12, 6, X, 18},
# New totals are {19, 18, X, 22} [max 22 from 3]
#
# Top scores are [28, 26, 27, 25] from [1, 3, 2, 3].
# Final state is [0] with a sequence of [1->0].
sequence, score = viterbi_decode.decode(scores, transition_params,
allowed_transitions)
self.assertAlmostEqual(28.0, score)
self.assertEqual([1, 0], sequence)
def test_viterbi_in_exp_space_with_allowed_transitions(self):
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[.1, .2, .3, .4], [.5, .6, .7, .8],
[.9, .5, .15, .5], [.25, .35, .45, .55]])
allowed_transitions = np.array([[True, True, True, True],
[True, True, True, True],
[True, False, True, False],
[True, True, True, True]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
# STEP 1:
# Starting scores are {10.0, 12.0, 6.0, 4.0}
# Raw scores are: {13.0, 12.0, 11.0, 10.0}
#
# Final state 0: (13.0) Weighted scores are {1.3, 6.5, 11.7, 3.25}
# New totals are {13, 78, 70.2, 13} [max 78 from 1]
#
# Final state 1: (12.0) Weighted scores are {2.4, 7.2, 0, 4.2},
# New totals are {24, 86.4, 0, 16.8} [max 86.4 from 1]
#
# Final state 2: (11.0) Weighted scores are {3.3, 7.7, 1.65, 4.95},
# New totals are {33, 92.4, 9.9, 19.8} [max 92.4 from 1]
#
# Final state 3: (10.0) Weighted scores are {4, 8, 0, 5.5},
# New totals are {40, 96, 0, 22} [max 96 from 1]
#
# Top scores are [78, 86.4, 92.4, 96] from [1, 1, 1, 1].
# Final state is [3] with a sequence of [1->3].
sequence, score = viterbi_decode.decode(scores,
transition_params,
allowed_transitions,
use_log_space=False)
self.assertAlmostEqual(96.0, score)
self.assertEqual([1, 3], sequence)
def test_sequence_in_log_space_with_start_end_states_multi_input(self):
use_log_space = True
use_start_and_end_states = True
scores = np.array([[10.0, 12.0, 7.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_weights = np.array([[-1.0, 1.0, -2.0, 2.0, 0.0],
[ 3.0, -3.0, 4.0, -4.0, 0.0],
[ 5.0, 1.0, 10.0, 1.0, 1.0],
[-7.0, 7.0, -8.0, 8.0, 0.0],
[ 0.0, 1.0, 2.0, 3.0, 0.0]],
dtype=np.float32)
allowed_transitions = np.array([[True, True, True, True, True],
[True, True, True, True, True],
[True, False, True, False, False],
[True, True, True, True, True],
[True, False, True, True, True]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
sequence, _ = viterbi_decode.decode(
scores,
transition_weights,
allowed_transitions,
use_log_space=use_log_space,
use_start_and_end_states=use_start_and_end_states)
# Test a multi-item batch.
multiple_input = np.array([scores, scores, scores], dtype=np.float32)
multiple_sequence_op = sequence_op.viterbi_constrained_sequence(
multiple_input, [2, 2, 2],
allowed_transitions=allowed_transitions,
transition_weights=transition_weights,
use_log_space=use_log_space,
use_start_and_end_states=use_start_and_end_states)
multiple_sequence_result = self.evaluate(multiple_sequence_op)
self.assertRaggedEqual(multiple_sequence_result,
[sequence, sequence, sequence])
def test_sequence_in_exp_space_with_start_end_states_multi_input(self):
use_log_space = False
use_start_and_end_states = True
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_weights = np.array([[ .1, .2, .3, .4, .1],
[ .5, .6, .7, .8, .1],
[ .9, 1, .15, 1, .1],
[.25, .35, .45, .55, .5],
[ .1, .5, .1, .1, 1]], dtype=np.float32)
allowed_transitions = np.array([[True, True, True, True, True],
[True, True, True, True, True],
[True, False, True, False, True],
[True, True, True, True, True],
[True, True, True, True, False]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
sequence, _ = viterbi_decode.decode(
scores,
transition_weights,
allowed_transitions,
use_log_space=use_log_space,
use_start_and_end_states=use_start_and_end_states)
# Test a multi-item batch.
multiple_input = np.array([scores, scores, scores], dtype=np.float32)
multiple_sequence_op = sequence_op.viterbi_constrained_sequence(
multiple_input, [2, 2, 2],
allowed_transitions=allowed_transitions,
transition_weights=transition_weights,
use_log_space=use_log_space,
use_start_and_end_states=use_start_and_end_states)
multiple_sequence_result = self.evaluate(multiple_sequence_op)
self.assertRaggedEqual(multiple_sequence_result,
[sequence, sequence, sequence])
def test_viterbi_in_log_space(self):
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
x = -float('inf')
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[-1.0, 1.0, -2.0, 2.0],
[3.0, -3.0, 4.0,
-4.0], [5.0, x, 10.0, x],
[-7.0, 7.0, -8.0, 8.0]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
# STEP 1:
# Starting scores are {10.0, 12.0, 6.0, 4.0}
# Raw scores are: {13.0, 12.0, 11.0, 10.0}
#
# To get the weighted scores, add the column of the final state to
# the raw score.
#
# Final state 0: (13.0) Weighted scores are {12.0, 16.0, 18.0, 6.0}
# New totals are {22, 28, 24, 10} [max 28 from 1]
#
# Final state 1: (12.0) Weighted scores are {13.0, 9.0, X, 19.0},
# New totals are {23, 21, X, 23} [max 23 from 3]
#
# Final state 2: (11.0) Weighted scores are {9, 15, 21, 3},
# New totals are {19, 27, 27, 7} [max 27 from 2]
#
# Final state 3: (10.0) Weighted scores are {12, 6, X, 18},
# New totals are {19, 18, X, 22} [max 25 from 3]
#
# Top scores are [28, 26, 27, 25] from [1, 3, 2, 3].
# Final state is [0] with a sequence of [1->0].
sequence, score = viterbi_decode.decode(scores, transition_params)
self.assertAlmostEqual(28.0, score)
self.assertEqual([1, 0], sequence)
