Params.json example about ast HOT 3 OPEN

I managed to create a json file which works. Here is the example I come up with:

{
"d_model": 160,
"h": 8,
"attn_type": "entmax15",
"d_ff": 16,
"dropout": 0.3,
"num_class": 2000,
"embedding_dim": 20,
"cov_dim": 16,
"N": 3,
"predict_steps": 24,
"train_window": 192,
"batch_size": 64,
"predict_batch": 64,
"num_epochs": 500,
"lr_d": 0.0001,
"lr": 6.25e-5,
"lr_schedule": "warmup_cosine",
"lr_warmup": 0.002,
"predict_start": 168,
"gan": true,
"test_predict_start": 168
}

it must be added under: experiments\test\parameters.json. Most of the attributes are self explanatory, except for num_class, which I couldn't figure it out yet. If you're noticing any difference from the paper please let me know, so I can modify the example.

from ast.

+1

from ast.

I managed to create a json file which works. Here is the example I come up with:

{
"d_model": 160,
"h": 8,
"attn_type": "entmax15",
"d_ff": 16,
"dropout": 0.3,
"num_class": 2000,
"embedding_dim": 20,
"cov_dim": 16,
"N": 3,
"predict_steps": 24,
"train_window": 192,
"batch_size": 64,
"predict_batch": 64,
"num_epochs": 500,
"lr_d": 0.0001,
"lr": 6.25e-5,
"lr_schedule": "warmup_cosine",
"lr_warmup": 0.002,
"predict_start": 168,
"gan": true,
"test_predict_start": 168
}

it must be added under: experiments\test\parameters.json. Most of the attributes are self explanatory, except for num_class, which I couldn't figure it out yet. If you're noticing any difference from the paper please let me know, so I can modify the example.

@razvanc92 thanks for share the json,I tried to run the training process, but I am stuck in many Ipython sections

from ast.