From 9f3b752be42e67885970ac5ec2814da6808a1b01 Mon Sep 17 00:00:00 2001
From: Amir MOHAMMADI <amir.mohammadi@idiap.ch>
Date: Wed, 17 Apr 2019 16:24:01 +0200
Subject: [PATCH] Add bob tf predict command
---
bob/learn/tensorflow/script/predict_bio.py | 112 ++++++++++++++++-----
1 file changed, 87 insertions(+), 25 deletions(-)
diff --git a/bob/learn/tensorflow/script/predict_bio.py b/bob/learn/tensorflow/script/predict_bio.py
index f13081ca..29f8343a 100644
--- a/bob/learn/tensorflow/script/predict_bio.py
+++ b/bob/learn/tensorflow/script/predict_bio.py
@@ -55,7 +55,7 @@ def non_existing_files(paths, force=False):
yield i
-def save_predictions(pool, output_dir, key, pred_buffer, video_container):
+def save_predictions(output_dir, key, pred_buffer, video_container):
outpath = make_output_path(output_dir, key)
create_directories_safe(os.path.dirname(outpath))
logger.debug("Saving predictions for %s", key)
@@ -66,7 +66,7 @@ def save_predictions(pool, output_dir, key, pred_buffer, video_container):
data = fc
else:
data = np.mean(pred_buffer[key], axis=0)
- pool.apply_async(save, (data, outpath))
+ save(data, outpath)
@click.command(
@@ -247,6 +247,68 @@ def predict_bio(estimator, database, biofiles, bio_predict_input_fn,
video_container=video_container)
+@click.command(
+ entry_point_group='bob.learn.tensorflow.config', cls=ConfigCommand)
+@click.option(
+ '--estimator',
+ '-e',
+ required=True,
+ cls=ResourceOption,
+ entry_point_group='bob.learn.tensorflow.estimator',
+ help='The estimator that will be evaluated.')
+@click.option(
+ '--predict-input-fn',
+ required=True,
+ cls=ResourceOption,
+ entry_point_group='bob.learn.tensorflow.input_fn',
+ help='A callable with no arguments which will be used in estimator.predict.')
+@click.option(
+ '--output-dir',
+ '-o',
+ required=True,
+ cls=ResourceOption,
+ help='The directory to save the predictions.')
+@click.option(
+ '--predict-keys',
+ '-k',
+ multiple=True,
+ default=None,
+ cls=ResourceOption,
+ help='List of `str`, name of the keys to predict. It is used if the '
+ '`EstimatorSpec.predictions` is a `dict`. If `predict_keys` is used '
+ 'then rest of the predictions will be filtered from the dictionary. '
+ 'If `None`, returns all.')
+@click.option(
+ '--checkpoint-path',
+ '-c',
+ cls=ResourceOption,
+ help='Path of a specific checkpoint to predict. If `None`, the '
+ 'latest checkpoint in `model_dir` is used. This can also '
+ 'be a folder which contains a "checkpoint" file where the '
+ 'latest checkpoint from inside this file will be used as '
+ 'checkpoint_path.')
+@click.option(
+ '--hooks',
+ cls=ResourceOption,
+ multiple=True,
+ entry_point_group='bob.learn.tensorflow.hook',
+ help='List of SessionRunHook subclass instances.')
+@click.option(
+ '--video-container',
+ '-vc',
+ is_flag=True,
+ cls=ResourceOption,
+ help='If provided, the predictions will be written in FrameContainers from'
+ ' bob.bio.video. You need to install bob.bio.video as well.')
+@verbosity_option(cls=ResourceOption)
+def predict(estimator, predict_input_fn, output_dir, predict_keys,
+ checkpoint_path, hooks, video_container, **kwargs):
+
+ generic_predict(
+ estimator, predict_input_fn, output_dir, predict_keys,
+ checkpoint_path, hooks, video_container)
+
+
def generic_predict(estimator, predict_input_fn, output_dir, predict_keys=None,
checkpoint_path=None, hooks=None, video_container=False):
# if the checkpoint_path is a directory, pick the latest checkpoint from
@@ -273,28 +335,28 @@ def generic_predict(estimator, predict_input_fn, output_dir, predict_keys=None,
raise click.ClickException(
'Could not import bob.bio.video. Have you installed it?')
- pool = Pool()
+ pred_buffer = defaultdict(list)
+ for i, pred in enumerate(predictions):
+ key = pred['key']
+ # key is in bytes format in Python 3
+ if sys.version_info >= (3, ):
+ key = key.decode(errors='replace')
+ prob = pred.get('probabilities', pred.get(
+ 'embeddings', pred.get('predictions')))
+ assert prob is not None
+ pred_buffer[key].append(prob)
+ if i == 0:
+ last_key = key
+ if last_key == key:
+ continue
+ else:
+ save_predictions(
+ output_dir, last_key, pred_buffer, video_container)
+ last_key = key
try:
- pred_buffer = defaultdict(list)
- for i, pred in enumerate(predictions):
- key = pred['key']
- # key is in bytes format in Python 3
- if sys.version_info >= (3, ):
- key = key.decode(errors='replace')
- prob = pred.get('probabilities', pred.get(
- 'embeddings', pred.get('predictions')))
- assert prob is not None
- pred_buffer[key].append(prob)
- if i == 0:
- last_key = key
- if last_key == key:
- continue
- else:
- save_predictions(
- pool, output_dir, last_key, pred_buffer, video_container)
- last_key = key
+ key
# save the final returned key as well:
- save_predictions(pool, output_dir, key, pred_buffer, video_container)
- finally:
- pool.close()
- pool.join()
+ save_predictions(output_dir, key, pred_buffer, video_container)
+ except UnboundLocalError:
+ # if the input_fn was empty and hence key is not defined
+ pass
--
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