def setUp(self):
super(self.__class__, self).setUp()
self.input_data = numpy.array(
[[[1.], [2.], [3.], [4.]], [[5.], [6.], [7.], [8.]],
[[5.], [6.], [7.], [8.]], [[9.], [10.], [11.], [12.]]],
dtype=numpy.float)
self.sequence = SequenceInputMock(self.bookkeeper, self.input_data,
[[0.], [0.], [0.], [1.]], 13)
self.input, self.output = recurrent_networks.create_sequence_pretty_tensor(
self.sequence)
def setUp(self):
super(self.__class__, self).setUp()
self.input_data = numpy.array(
[
[[1.], [2.], [3.], [4.]], [[5.], [6.], [7.], [8.]],
[[5.], [6.], [7.], [8.]], [[9.], [10.], [11.], [12.]]
],
dtype=numpy.float)
self.sequence = SequenceInputMock(self.bookkeeper, self.input_data,
[[0.], [0.], [0.], [1.]], 13)
self.input, self.output = recurrent_networks.create_sequence_pretty_tensor(
self.sequence)
def testSquashAndCleaveLength1(self):
input_data = numpy.array([[[1.], [2.], [3.], [4.]]], dtype=numpy.float)
sequence = SequenceInputMock(self.bookkeeper, input_data, [[0.]], 13)
inp, _ = recurrent_networks.create_sequence_pretty_tensor(sequence)
squashed = inp.squash_sequence()
result = self.RunTensor(squashed)
testing.assert_allclose(input_data.reshape(4, 1),
result,
rtol=TOLERANCE)
result = self.RunTensor(squashed.cleave_sequence())
testing.assert_allclose(input_data[0], result[0], rtol=TOLERANCE)
self.assertEquals(1, len(result))
def testSquashAndCleaveLength1(self):
input_data = numpy.array(
[[[1.], [2.], [3.], [4.]]], dtype=numpy.float)
sequence = SequenceInputMock(self.bookkeeper, input_data, [[0.]], 13)
inp, _ = recurrent_networks.create_sequence_pretty_tensor(sequence)
squashed = inp.squash_sequence()
result = self.RunTensor(squashed)
testing.assert_allclose(
input_data.reshape(4, 1), result,
rtol=TOLERANCE)
result = self.RunTensor(squashed.cleave_sequence())
testing.assert_allclose(input_data[0], result[0], rtol=TOLERANCE)
self.assertEquals(1, len(result))
