train_ambiguity_solver.py File Reference

Go to the source code of this file.

Namespaces
namespace	train_ambiguity_solver

Functions
def	train_ambiguity_solver.readDataSet
def	train_ambiguity_solver.prepareTrainingData
def	train_ambiguity_solver.batchSplit
def	train_ambiguity_solver.computeLoss
def	train_ambiguity_solver.scoringBatch
def	train_ambiguity_solver.train

Variables
list	train_ambiguity_solver.avg_mean [0, 0, 0, 0, 0, 0, 0, 0]
list	train_ambiguity_solver.avg_sdv [0, 0, 0, 0, 0, 0, 0, 0]
int	train_ambiguity_solver.events 0
tuple	train_ambiguity_solver.CKF_files sorted(glob.glob("odd_output" + "/event0000000[0-7][0-9]-tracks_ckf.csv"))
tuple	train_ambiguity_solver.data readDataSet(CKF_files)
tuple	train_ambiguity_solver.input_dim np.shape(x_train)
list	train_ambiguity_solver.layers_dim [10, 15, 10]
tuple	train_ambiguity_solver.duplicateClassifier
	train_ambiguity_solver.input data.index,x_train,y_train
tuple	train_ambiguity_solver.input_test torch.tensor(x_train, dtype=torch.float32)
list	train_ambiguity_solver.input_names ["x"]
list	train_ambiguity_solver.output_names ["y"]
dictionary	train_ambiguity_solver.dynamic_axes {"x": {0: "batch_size"}, "y": {0: "batch_size"}}
tuple	train_ambiguity_solver.CKF_files_test
tuple	train_ambiguity_solver.test readDataSet(CKF_files_test)
list	train_ambiguity_solver.output_predict []
tuple	train_ambiguity_solver.x_test torch.tensor(x_test, dtype=torch.float32)
int	train_ambiguity_solver.id 0
list	train_ambiguity_solver.pid test.index[0]
int	train_ambiguity_solver.nb_part 1
int	train_ambiguity_solver.nb_good_match 0
int	train_ambiguity_solver.max_match 0
int	train_ambiguity_solver.max_score 0