hardcoded paths in training validation_step

[linminhtoo]

hello wenhao & rocio,

the unittests are great and gives a great overview of how different modules should be run. however, I saw that in these lines, the path to the building block embeddings are hardcoded to the path on the HPC cluster.

SynNet/syn_net/models/mlp.py

Lines 78 to 89 in 56917a6

	if out_feat == 'gin':
	bb_emb_gin = np.load('/pool001/whgao/data/synth_net/st_hb/enamine_us_emb_gin.npy')
	kdtree = BallTree(bb_emb_gin, metric='euclidean')
	elif out_feat == 'fp_4096':
	bb_emb_fp_4096 = np.load('/pool001/whgao/data/synth_net/st_hb/enamine_us_emb_fp_4096.npy')
	kdtree = BallTree(bb_emb_fp_4096, metric='euclidean')
	elif out_feat == 'fp_256':
	bb_emb_fp_256 = np.load('/pool001/whgao/data/synth_net/st_hb/enamine_us_emb_fp_256.npy')
	kdtree = BallTree(bb_emb_fp_256, metric=cosine_distance)
	elif out_feat == 'rdkit2d':
	bb_emb_rdkit2d = np.load('/pool001/whgao/data/synth_net/st_hb/enamine_us_emb_rdkit2d.npy')
	kdtree = BallTree(bb_emb_rdkit2d, metric='euclidean')

so, I am unable to make pytest pass, specifically:

FAILED tests/test_Training.py::TestTraining::test_reactant1_network - UnboundLocalError: local variable 'kdtree' referenced before assignment
FAILED tests/test_Training.py::TestTraining::test_reactant2_network - UnboundLocalError: local variable 'kdtree' referenced before assignment

at least for the unittest, what should the correct path be? and would it be possible to make these paths user-passable arguments?

---

SynNet/scripts/predict_multireactant_mp.py

Line 29 in 56917a6

path_to_data = f'/pool001/whgao/data/synth_net/st_{args.rxn_template}/st_{args.data}.json.gz'

there's a similar hardcoding in this line, so I suppose we'll have to generate the .json.gz ourselves

[rociomer]

We have addressed this and other issues in the new version of SynNet (thanks to @chrulm!). Closing this for now.