From f4e3e36c446daa0b3755299cb5e40a991d418bdc Mon Sep 17 00:00:00 2001 From: William Chargin Date: Tue, 21 May 2019 11:29:50 -0700 Subject: [PATCH 1/2] hparams: fix demo (remove `group_name` argument) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Summary: In #2188, I removed the `group_name` parameter from the Keras callback, but forgot to remove it from the call site in the demo code. Test Plan: Running `bazel run //tensorboard/plugins/hparams:hparams_demo` now works. Previously, it failed with the error, “unexpected keyword argument 'group_name'”. wchargin-branch: hparams-demo-no-group-name --- tensorboard/plugins/hparams/hparams_demo.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tensorboard/plugins/hparams/hparams_demo.py b/tensorboard/plugins/hparams/hparams_demo.py index 9cb7bacb06..b9c16cca88 100644 --- a/tensorboard/plugins/hparams/hparams_demo.py +++ b/tensorboard/plugins/hparams/hparams_demo.py @@ -182,7 +182,7 @@ def run(data, base_logdir, session_id, group_id, hparams): update_freq=flags.FLAGS.summary_freq, profile_batch=0, # workaround for issue #2084 ) - hparams_callback = hp.KerasCallback(logdir, hparams, group_name=group_id) + hparams_callback = hp.KerasCallback(logdir, hparams) ((x_train, y_train), (x_test, y_test)) = data result = model.fit( x=x_train, From 3978068d6f2924ad46d7224dae8f1ef7d9ab8635 Mon Sep 17 00:00:00 2001 From: William Chargin Date: Tue, 21 May 2019 11:36:33 -0700 Subject: [PATCH 2/2] [integrate] wchargin-source: 06c2f4386074c7c867f857e0c4f785386afa5655 wchargin-branch: hparams-demo-no-group-name --- tensorboard/plugins/hparams/hparams_demo.py | 7 +------ 1 file changed, 1 insertion(+), 6 deletions(-) diff --git a/tensorboard/plugins/hparams/hparams_demo.py b/tensorboard/plugins/hparams/hparams_demo.py index b9c16cca88..6d20972860 100644 --- a/tensorboard/plugins/hparams/hparams_demo.py +++ b/tensorboard/plugins/hparams/hparams_demo.py @@ -23,7 +23,6 @@ from __future__ import division from __future__ import print_function -import hashlib import math import os.path import random @@ -161,7 +160,7 @@ def model_fn(hparams, seed): return model -def run(data, base_logdir, session_id, group_id, hparams): +def run(data, base_logdir, session_id, hparams): """Run a training/validation session. Flags must have been parsed for this function to behave. @@ -170,8 +169,6 @@ def run(data, base_logdir, session_id, group_id, hparams): data: The data as loaded by `prepare_data()`. base_logdir: The top-level logdir to which to write summary data. session_id: A unique string ID for this session. - group_id: The string ID of the session group that includes this - session. hparams: A dict mapping hyperparameters in `HPARAMS` to values. """ model = model_fn(hparams=hparams, seed=session_id) @@ -224,7 +221,6 @@ def run_all(logdir, verbose=False): for group_index in xrange(flags.FLAGS.num_session_groups): hparams = {h: sample_uniform(h.domain, rng) for h in HPARAMS} hparams_string = str(hparams) - group_id = hashlib.sha256(hparams_string.encode("utf-8")).hexdigest() for repeat_index in xrange(sessions_per_group): session_id = str(session_index) session_index += 1 @@ -239,7 +235,6 @@ def run_all(logdir, verbose=False): data=data, base_logdir=logdir, session_id=session_id, - group_id=group_id, hparams=hparams, )