afdee1c/symbolic-regression
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Silviu Marian Udrescu 2020-06-20 04:36:49 -04:00 • committed by GitHub
parent 31e7f76672
commit b709df5840
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2 changed files with 9 additions and 1 deletions
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4
Code/RPN_to_pytorch.py
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@ -109,6 +109,10 @@ def RPN_to_pytorch(pathdir,filename, math_expr, lr = 1e-2, N_epochs = 500):
trainable_parameters[j] -= lr * trainable_parameters[j].grad trainable_parameters[j] -= lr * trainable_parameters[j].grad
trainable_parameters[j].grad.zero_() trainable_parameters[j].grad.zero_()
for nan_i in range(len(trainable_parameters)):
if torch.isnan(trainable_parameters[nan_i])==True or abs(trainable_parameters[nan_i])>1e7:
return 1000000, 10000000, "1"
ii = -1 ii = -1
for parm in unsnapped_param_dict: for parm in unsnapped_param_dict:
if ii == -1: if ii == -1:

6
Code/S_final_gd.py
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@ -119,7 +119,11 @@ def final_gd(pathdir,filename, math_expr, lr = 1e-2, N_epochs = 5000):
for j in range(N_params-1): for j in range(N_params-1):
trainable_parameters[j] -= lr/10 * trainable_parameters[j].grad trainable_parameters[j] -= lr/10 * trainable_parameters[j].grad
trainable_parameters[j].grad.zero_() trainable_parameters[j].grad.zero_()
for nan_i in range(len(trainable_parameters)):
if torch.isnan(trainable_parameters[nan_i])==True or abs(trainable_parameters[nan_i])>1e7:
return 1000000, 10000000, "1"
# get the updated symbolic regression # get the updated symbolic regression
ii = -1 ii = -1
for parm in unsnapped_param_dict: for parm in unsnapped_param_dict: