VictorMylle/Thesis
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Non autregressive gru model load

Browse Source
This commit is contained in:
Victor Mylle
2024-05-06 16:11:15 +02:00
parent 19ab597ae6
commit d7f4c1849b
7 changed files with 55 additions and 22 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
src/training_scripts/non_autoregressive_quantiles.py
View File

@@ -2,7 +2,7 @@ from src.utils.clearml import ClearMLHelper
#### ClearML ####
clearml_helper = ClearMLHelper(project_name="Thesis/NAQR: GRU")
task = clearml_helper.get_task(task_name="NAQR: GRU (2 - 256)")
task = clearml_helper.get_task(task_name="NAQR: GRU (2 - 256) + Load")
task.execute_remotely(queue_name="default", exit_process=True)
from src.policies.PolicyEvaluator import PolicyEvaluator
@@ -27,8 +27,8 @@ from src.models.time_embedding_layer import TimeEmbedding
data_config = DataConfig()
data_config.NRV_HISTORY = True
data_config.LOAD_HISTORY = False
data_config.LOAD_FORECAST = False
data_config.LOAD_HISTORY = True
data_config.LOAD_FORECAST = True
data_config.WIND_FORECAST = False
data_config.WIND_HISTORY = False
@@ -64,8 +64,8 @@ else:
model_parameters = {
"learning_rate": 0.0001,
"hidden_size": 256,
"num_layers": 2,
"hidden_size": 512,
"num_layers": 8,
"dropout": 0.2,
}
@@ -83,7 +83,7 @@ model_parameters = task.connect(model_parameters, name="model_parameters")
lstm_model = GRUModel(
inputDim,
len(quantiles),
len(quantiles) * 96,
hidden_size=model_parameters["hidden_size"],
num_layers=model_parameters["num_layers"],
dropout=model_parameters["dropout"],