From 67e346738296917270f5467c84e6b49dc92be422 Mon Sep 17 00:00:00 2001 From: "Edwards, Brandon" Date: Thu, 10 Oct 2024 12:12:03 -0700 Subject: [PATCH] removing some testing output --- examples/fl_post/fl/project/src/nnunet_v1.py | 7 ------- examples/fl_post/fl/project/src/runner_nnunetv1.py | 4 ++-- 2 files changed, 2 insertions(+), 9 deletions(-) diff --git a/examples/fl_post/fl/project/src/nnunet_v1.py b/examples/fl_post/fl/project/src/nnunet_v1.py index 3f117e8a0..ffab4f131 100644 --- a/examples/fl_post/fl/project/src/nnunet_v1.py +++ b/examples/fl_post/fl/project/src/nnunet_v1.py @@ -239,13 +239,8 @@ def __init__(self, **kwargs): trainer.max_num_epochs = current_epoch + epochs trainer.epoch = current_epoch - print(f"Brandon DEBUG - about to initialize trainer, currently t.max_num:{trainer.max_num_epochs}, t.epo:{trainer.epoch}") - - # TODO: call validation separately trainer.initialize(not validation_only) - print(f"Brandon DEBUG - after initialize trainer, currently t.max_num:{trainer.max_num_epochs}, t.epo:{trainer.epoch}") - # infer total data size and batch size in order to get how many batches to apply so that over many epochs, each data # point is expected to be seen epochs number of times @@ -276,8 +271,6 @@ def __init__(self, **kwargs): else: # new training without pretraine weights, do nothing pass - print(f"Brandon DEBUG - Calling trainer.run_training, trainer epoch: {trainer.epoch}, trainer max_num_epochs:{trainer.max_num_epochs}") - print(f"Brandon DEBUG - NOTE: this is where I had just loaded checkpoint.") batches_applied_train, \ batches_applied_val, \ diff --git a/examples/fl_post/fl/project/src/runner_nnunetv1.py b/examples/fl_post/fl/project/src/runner_nnunetv1.py index 4a60c931d..3cb52de50 100644 --- a/examples/fl_post/fl/project/src/runner_nnunetv1.py +++ b/examples/fl_post/fl/project/src/runner_nnunetv1.py @@ -245,8 +245,8 @@ def compare_tensor_dicts(td_1, td_2, tag="", epsilon=0.1, verbose=True): metrics = {'val_eval': this_val_eval_metrics} else: checkpoint_dict = self.load_checkpoint() - # double check - compare_tensor_dicts(td_1=input_tensor_dict,td_2=checkpoint_dict['state_dict'], tag="checkpoint VS fromOpenFL") + # double check uncomment below for testing + # compare_tensor_dicts(td_1=input_tensor_dict,td_2=checkpoint_dict['state_dict'], tag="checkpoint VS fromOpenFL") all_tr_losses, \ all_val_losses, \