saymrwulf/onnxruntime
1
0
Fork 0
mirror of https://github.com/saymrwulf/onnxruntime.git synced 2026-07-03 03:58:54 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

Improved test cases by using paramerters (#14246)

Browse source 
### Description
Completing some missing parts of some test cases for python bindings

### Motivation and Context
Some test cases like test_training_module_checkpoint and test_optimizer
step were not completed before because we had no access to parameters to
check if the parameters are changing after the optimizer step or that
the checkpoint saved parameters remains the same.
now that we have access to the vector or parameters by exposing
get_contiguous_parameters() method.
we can complete the tests.
This commit is contained in:
Adam Louly 2023-01-13 14:54:23 -06:00 committed by GitHub
parent 6ac7c894bf
commit f0555eb437
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
1 changed files with 15 additions and 2 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

17
orttraining/orttraining/test/python/orttraining_test_python_bindings.py
View file

@ -137,9 +137,13 @@ def test_optimizer_step():
optimizer = Optimizer(optimizer_file_path, model)
model.train()
old_flatten_params = model.get_contiguous_parameters()
model(forward_inputs)
optimizer.step()
# TODO : Check if parameters changed from before and after optimizer step.
new_params = model.get_contiguous_parameters()
# Assert that the parameters are updated.
assert not np.array_equal(old_flatten_params.numpy(), new_params.numpy())
def test_get_and_set_lr():
@ -226,10 +230,19 @@ def test_training_module_checkpoint():
checkpoint_save_path = os.path.join(temp_dir, "checkpoint_export.ckpt")
model.save_checkpoint(checkpoint_save_path)
old_flatten_params = model.get_contiguous_parameters()
# TODO : Load checkpoint to a zeroed model and assert parameters are different.
# Assert the checkpoint was saved.
assert os.path.exists(checkpoint_save_path)
# Assert the checkpoint parameters remain after saving.
state = CheckpointState(checkpoint_save_path)
new_model = Module(model_file_path, state)
new_params = new_model.get_contiguous_parameters()
assert np.array_equal(old_flatten_params.numpy(), new_params.numpy())
def test_copy_buffer_to_parameters():
# Initialize Models