def test_pack_padded_long_sequence_forward_backward(total_length, padding_value,
batch_first, shapes, seed, ctx, func_name):
if not func_name.endswith("Cuda"):
pytest.skip(
"PackPaddedSequence tests except for Cuda for very long sequence skips.")
from nbla_test_utils import function_tester
rng = np.random.RandomState(seed)
sequences = [rng.randn(*shape).astype(np.float32) for shape in shapes]
padded_sequence = pad_sequence(sequences, batch_first)
lengths = np.array([seq.shape[0] for seq in sequences])
inputs = [padded_sequence, lengths]
func_args0 = [batch_first]
func_args1 = [batch_first, padding_value, total_length]
insert_identity = [True, False]
# Forward
function_tester(rng, F.pack_padded_sequence, ref_pack_padded_sequence, inputs,
ctx=ctx, func_name=func_name, func_args=func_args0,
backward=[False, False],
atol_f=1e-3, atol_b=1e-2, insert_identity=insert_identity)
# Backward
import nnabla as nn
padded_sequence0 = nn.Variable.from_numpy_array(
inputs[0]).apply(need_grad=True)
lengths = nn.Variable.from_numpy_array(inputs[1])
with nn.context_scope(ctx), nn.auto_forward():
# Pack backward
padded_sequence0.g = rng.randn(*padded_sequence0.shape)
packed_sequence0, batch_sizes = F.pack_padded_sequence(
padded_sequence0, lengths, *func_args0)
g = rng.randn(*packed_sequence0.shape)
packed_sequence0.g = g
packed_sequence0.parent.backward([padded_sequence0, lengths], [packed_sequence0, batch_sizes],
[False, False])
# Unpack
packed_sequence1 = nn.Variable.from_numpy_array(g)
padded_sequence1, lengths = F.pad_packed_sequence(
packed_sequence1, batch_sizes, *func_args1)
# Compare w/o accum
np.testing.assert_allclose(padded_sequence0.g.flatten(),
padded_sequence1.d.flatten(
)[:np.prod(padded_sequence0.shape)],
atol=1e-4,
err_msg="{} test (w/o accum) with long sequence failed.".format(func_name))
# Compare w/ accum
packed_sequence0.parent.backward([padded_sequence0, lengths], [packed_sequence0, batch_sizes],
[True, False])
np.testing.assert_allclose(padded_sequence0.g.flatten() / 2,
padded_sequence1.d.flatten(
)[:np.prod(padded_sequence0.shape)],
atol=1e-4,
err_msg="{} test (w/ accum) with long sequence failed.".format(func_name))
def test_pack_padded_sequence_forward_backward(batch_first, shapes, seed, ctx, func_name):
from nbla_test_utils import function_tester
rng = np.random.RandomState(seed)
sequences = [rng.randn(*shape).astype(np.float32) for shape in shapes]
padded_sequence = pad_sequence(sequences, batch_first)
lengths = np.array([seq.shape[0] for seq in sequences])
inputs = [padded_sequence, lengths]
func_args = [batch_first]
insert_identity = [True, False]
function_tester(rng, F.pack_padded_sequence, ref_pack_padded_sequence, inputs,
ctx=ctx, func_name=func_name, func_args=func_args,
backward=[True, False], disable_half_test=False,
atol_f=1e-3, atol_b=1e-2, insert_identity=insert_identity)