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Merged
merged 4 commits into from
Sep 21, 2021
Merged

Extend test check rec moved out helper #676

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16173f8
test check rec opt out, ignore :i
albertz Sep 20, 2021
e95e485
test check rec opt out, support extended output shape
albertz Sep 21, 2021
91d228e
test check rec opt out, use masking before comparison
albertz Sep 21, 2021
ac9e75a
test check rec opt out, better out comparison debug
albertz Sep 21, 2021
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26 changes: 18 additions & 8 deletions tests/test_TFNetworkRecLayer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3416,33 +3416,43 @@ def check_reclayer_optimize_out(subnet_layer_dict, other_subnet_layers=None, sha
assert_equal(set(net2_subnet.input_layers_moved_out), set())
assert_equal(set(net1_subnet.output_layers_moved_out), set())
# output_layers_moved_out will contain sublayers if present
output_root_layers_moved_out = [name for name in net2_subnet.output_layers_moved_out if '/' not in name]
output_root_layers_moved_out = [
name for name in net2_subnet.output_layers_moved_out if '/' not in name and name != ":i"]
assert_equal(set(output_root_layers_moved_out), {"output"}.union(set(other_subnet_layers or [])))
assert_equal([
v.name.split("/")[1:] for v in net1.get_params_list()], [v.name.split("/")[1:] for v in net2.get_params_list()])
net1.initialize_params(session=session)
net1_params = net1.layers["output_not_opt"].get_param_values_dict(session=session)
net2.layers["output_opt"].set_param_values_by_dict(values_dict=net1_params, session=session)
x_np = net1.random.normal(size=(n_batch, n_time, n_in))
net1_output = net1.layers["output_not_opt"].output.get_placeholder_as_batch_major()
net2_output = net2.layers["output_opt"].output.get_placeholder_as_batch_major()
net1_output = net1.layers["output_not_opt"].output.copy_masked(0.).get_placeholder_as_batch_major()
net2_output = net2.layers["output_opt"].output.copy_masked(0.).get_placeholder_as_batch_major()
feed_dict = {
net1.extern_data.data["data"].placeholder: x_np,
net1.extern_data.data["data"].size_placeholder[0]: [n_time] * n_batch}
y1_np = session.run(net1_output, feed_dict=feed_dict)
print("y: (shape %r)" % (y1_np.shape,))
print(y1_np)
y2_np = session.run(net2_output, feed_dict=feed_dict)
assert_equal(y1_np.shape, (n_batch, n_time, n_out))
assert_equal(y2_np.shape, (n_batch, n_time, n_out))
assert y1_np.shape == y2_np.shape
assert y1_np.shape[:2] == y2_np.shape[:2] == (n_batch, n_time)
assert y1_np.any() and y2_np.any()
if not numpy.allclose(y1_np, y2_np, rtol=rtol):
print("Not equal!")
print("Iterating over shape [B,T,...] = %s" % (y1_np.shape,))
for b in range(n_batch):
for t in range(n_time):
for d in range(n_out):
assert_allclose(y1_np[b, t, d], y2_np[b, t, d], rtol=rtol)
assert_allclose(y1_np, y2_np, rtol=rtol)
print("check batch %i, time %i" % (b, t))
y1_np_, y2_np_ = y1_np[b, t], y2_np[b, t]
for idx in numpy.ndindex(*y1_np_.shape):
y1_np__, y2_np__ = y1_np_[idx], y2_np_[idx]
allclose = numpy.allclose(y1_np__, y2_np__, rtol=rtol)
if allclose:
details = ["all close"]
else:
details = ["not all close", "max1:", numpy.max(y1_np__), "max2:", numpy.max(y2_np__)]
print(" check", idx, *details)
assert_allclose(y1_np, y2_np, rtol=rtol) # fail now


def test_reclayer_optimize_out_linear():
Expand Down