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)
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)
