def test_loss_multilabelmargin(system_dict): forward = True; test = "test_loss_multilabelmargin"; system_dict["total_tests"] += 1; print_start(test, system_dict["total_tests"]) if(forward): try: gtf = prototype(verbose=0); gtf.Prototype("sample-project-1", "sample-experiment-1"); label = torch.tensor([[3, 0, -1, 1, 2]]) y = torch.randn(1, 5); gtf.loss_multilabel_margin(); load_loss(gtf.system_dict); loss_obj = gtf.system_dict["local"]["criterion"]; loss_val = loss_obj(y, label); system_dict["successful_tests"] += 1; print_status("Pass"); except Exception as e: system_dict["failed_tests_exceptions"].append(e); system_dict["failed_tests_lists"].append(test); forward = False; print_status("Fail"); else: system_dict["skipped_tests_lists"].append(test); print_status("Skipped"); return system_dict
def test_loss_multimargin(system_dict): forward = True test = "test_loss_multimargin" system_dict["total_tests"] += 1 print_start(test, system_dict["total_tests"]) if (forward): try: gtf = prototype(verbose=0) gtf.Prototype("sample-project-1", "sample-experiment-1") label = torch.empty(1, dtype=torch.long).random_(5) y = torch.randn(1, 5) gtf.loss_multimargin() load_loss(gtf.system_dict) loss_obj = gtf.system_dict["local"]["criterion"] loss_val = loss_obj(y, label) system_dict["successful_tests"] += 1 print_status("Pass") except Exception as e: system_dict["failed_tests_exceptions"].append(e) system_dict["failed_tests_lists"].append(test) forward = False print_status("Fail") else: system_dict["skipped_tests_lists"].append(test) print_status("Skipped") return system_dict
def test_loss_binary_crossentropy(system_dict): forward = True; test = "test_loss_binary_crossentropy"; system_dict["total_tests"] += 1; print_start(test, system_dict["total_tests"]) if(forward): try: gtf = prototype(verbose=0); gtf.Prototype("sample-project-1", "sample-experiment-1"); label = torch.empty((1, 5)).random_(2); y = torch.randn(1, 5); m = torch.nn.Sigmoid(); y = m(y); gtf.loss_binary_crossentropy(); load_loss(gtf.system_dict); loss_obj = gtf.system_dict["local"]["criterion"]; loss_val = loss_obj(y, label); system_dict["successful_tests"] += 1; print_status("Pass"); except Exception as e: system_dict["failed_tests_exceptions"].append(e); system_dict["failed_tests_lists"].append(test); forward = False; print_status("Fail"); else: system_dict["skipped_tests_lists"].append(test); print_status("Skipped"); return system_dict