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))