From 4671743678ec4b00e74426d1b1319ee8fba11f38 Mon Sep 17 00:00:00 2001 From: Vandana Kannan Date: Thu, 2 Jan 2020 16:54:41 -0800 Subject: [PATCH] Update comments --- smdebug/core/collection.py | 2 +- smdebug/core/hook.py | 6 +++--- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/smdebug/core/collection.py b/smdebug/core/collection.py index cc2be138b..d9cd87e4c 100644 --- a/smdebug/core/collection.py +++ b/smdebug/core/collection.py @@ -27,7 +27,7 @@ class CollectionKeys: LOSSES = "losses" BIASES = "biases" - # Use this collection to log scalars other than losses/metrics to Minerva. + # Use this collection to log scalars other than losses/metrics to SageMaker. # Mainly for Tensorflow. For all other frameworks, call save_scalar() API # with details of the scalar to be saved. SM_METRICS = "sm_metrics" diff --git a/smdebug/core/hook.py b/smdebug/core/hook.py index 4506d8a4d..ef6853506 100644 --- a/smdebug/core/hook.py +++ b/smdebug/core/hook.py @@ -564,7 +564,7 @@ def _write_scalars(self): """ This function writes all the scalar values saved in the scalar_cache to file. If sm_metric is set to True for certain scalars, then that scalar is written to - Minerva as well. By default, loss values are sm_metric. + SageMaker as well. By default, loss values are sm_metric. """ for scalar_obj in self.scalar_cache: scalar_name = scalar_obj.name @@ -598,7 +598,7 @@ def save_scalar(self, name, value, sm_metric=False): :param name: Name of the scalar. A prefix 'scalar/' will be added to it :param value: Scalar value :param sm_metric: True/False. If set to True, the scalar value will be written to - SageMaker Minerva + SageMaker """ name = CallbackHook.SCALAR_PREFIX + name val = self._make_numpy_array(value) @@ -662,7 +662,7 @@ def _save_for_tensor(self, tensor_name, tensor_value, check_before_write=True): for s_col in save_collections_for_tensor: if s_col.name in SM_METRIC_COLLECTIONS: np_val = self._make_numpy_array(tensor_value) - # Always log loss to Minerva + # Always log loss to SageMaker tensor_val = np.mean(np_val) scalar_obj = ScalarCache( tensor_name,