fanasina/y_project
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

debug : nan, it's the learning rate too high,s try to find optimum: 0.001

Browse Source
This commit is contained in:
fanasina
2025-12-13 05:00:23 +01:00
parent 32207170f6
commit 3d54639d4c
18 changed files with 834 additions and 148 deletions
Download Patch File Download Diff File Expand all files Collapse all files
deepQlearn_0/test/is_good.c
+8 -8
View File
@@ -458,7 +458,7 @@ TEST(first_learn_vehicle_rev50_8){
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0.001; // 0.00001 /*0.001*/;
struct networks_qlearning *nnetworks = create_nework_qlearning(
struct networks_qlearning *nnetworks = create_network_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,
@@ -622,7 +622,7 @@ TEST(first_learn_vehicle_50__9){
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0.00001 /* 0.001*/;
struct networks_qlearning *nnetworks = create_nework_qlearning(
struct networks_qlearning *nnetworks = create_network_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,
@@ -792,7 +792,7 @@ TEST(first_learn_vehicle_50__10){
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0.00001 /* 0.001*/;
struct networks_qlearning *nnetworks = create_nework_qlearning(
struct networks_qlearning *nnetworks = create_network_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,
@@ -964,7 +964,7 @@ copy_coordinate(path->lower_bound_block[0], (float[]){0,0});
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0; /* 0.000001*/ /* 0.001*/;
struct networks_qlearning *nnetworks = create_nework_qlearning(
struct networks_qlearning *nnetworks = create_network_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,
@@ -1143,7 +1143,7 @@ copy_coordinate(path->lower_bound_block[0], (float[]){0,0});
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0.0000001 /* 0.001*/;
struct networks_qlearning *nnetworks = create_nework_qlearning(
struct networks_qlearning *nnetworks = create_network_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,
@@ -1265,7 +1265,7 @@ TEST(first_learn_vehicle13){
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0.1;
struct networks_qlearning *nnetworks = create_nework_qlearning(
struct networks_qlearning *nnetworks = create_network_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,
@@ -1375,7 +1375,7 @@ TEST(first_learn_vehicle){
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0.1;
struct networks_qlearning *nnetworks = create_nework_qlearning(
struct networks_qlearning *nnetworks = create_network_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,
@@ -1486,7 +1486,7 @@ TEST(first_learn_vehicle){
size_t nb_prod_thread = 2;
size_t nb_calc_thread = 4;
float learning_rate = 0.1;
struct networks_qlearning *nnetworks = create_nework_qlearning(
struct networks_qlearning *nnetworks = create_network_qlearning(
pconf,
randomize, minR, maxR, randomRange,
nb_prod_thread, nb_calc_thread,