def test_lookup_table(): lt = LookupTable(5, 3) lt.allocate() lt.W.set_value(numpy.arange(15).reshape(5, 3).astype(theano.config.floatX)) x = tensor.lmatrix("x") y = lt.apply(x) f = theano.function([x], [y]) x_val = [[1, 2], [0, 3]] desired = numpy.array([[[3, 4, 5], [6, 7, 8]], [[0, 1, 2], [9, 10, 11]]], dtype=theano.config.floatX) assert_equal(f(x_val)[0], desired) # Test get_dim assert_equal(lt.get_dim(lt.apply.inputs[0]), 0) assert_equal(lt.get_dim(lt.apply.outputs[0]), lt.dim) assert_raises(ValueError, lt.get_dim, 'random_name') # Test feedforward interface assert lt.input_dim == 0 assert lt.output_dim == 3 lt.output_dim = 4 assert lt.output_dim == 4 def assign_input_dim(): lt.input_dim = 11 assert_raises(ValueError, assign_input_dim) lt.input_dim = 0
def test_lookup_table(): lt = LookupTable(5, 3) lt.allocate() lt.W.set_value(numpy.arange(15).reshape(5, 3).astype(theano.config.floatX)) x = tensor.lmatrix("x") y = lt.apply(x) f = theano.function([x], [y]) x_val = [[1, 2], [0, 3]] desired = numpy.array([[[3, 4, 5], [6, 7, 8]], [[0, 1, 2], [9, 10, 11]]], dtype=theano.config.floatX) assert_equal(f(x_val)[0], desired) # Test get_dim assert_equal(lt.get_dim(lt.apply.inputs[0]), 0) assert_equal(lt.get_dim(lt.apply.outputs[0]), lt.dim)