def test_op_constant(dtype, diff, sess):
ops = (SimNeurons(LIF(tau_rc=1), Signal(np.zeros(10)), None),
SimNeurons(LIF(tau_rc=2 if diff else 1), Signal(np.zeros(10)),
None))
signals = SignalDict(tf.float32, 1)
const = signals.op_constant(
[op.neurons for op in ops], [op.J.shape[0] for op in ops],
"tau_rc", dtype)
const1 = signals.op_constant(
[op.neurons for op in ops], [op.J.shape[0] for op in ops],
"tau_rc", dtype, ndims=1)
const3 = signals.op_constant(
[op.neurons for op in ops], [op.J.shape[0] for op in ops],
"tau_rc", dtype, ndims=3)
assert const.dtype.base_dtype == dtype
sess.run(tf.variables_initializer(tf.get_collection("constants")),
feed_dict=signals.constant_phs)
x, x1, x3 = sess.run([const, const1, const3])
if diff:
assert np.array_equal(x, [[1]] * 10 + [[2]] * 10)
assert np.array_equal(x[:, 0], x1)
assert np.array_equal(x, x3[..., 0])
else:
assert np.array_equal(x, 1.0)
assert np.array_equal(x, x1)
assert np.array_equal(x, x3)
def test_op_constant(dtype, diff):
ops = (
SimNeurons(LIF(tau_rc=1), Signal(np.zeros(10)), None),
SimNeurons(LIF(tau_rc=2 if diff else 1), Signal(np.zeros(10)), None),
)
signals = SignalDict(tf.float32, 1)
const = signals.op_constant(
[op.neurons for op in ops], [op.J.shape[0] for op in ops], "tau_rc", dtype
)
const1 = signals.op_constant(
[op.neurons for op in ops],
[op.J.shape[0] for op in ops],
"tau_rc",
dtype,
shape=(-1,),
)
const3 = signals.op_constant(
[op.neurons for op in ops],
[op.J.shape[0] for op in ops],
"tau_rc",
dtype,
shape=(1, -1, 1),
)
assert const.dtype.base_dtype == dtype
if diff:
assert np.array_equal(const, [[1.0] * 10 + [2.0] * 10])
assert np.array_equal(const[0], const1)
assert np.array_equal(const, const3[..., 0])
else:
assert np.array_equal(const, 1.0)
assert np.array_equal(const, const1)
assert np.array_equal(const, const3)