[NCF/TF] Adding new logging

Author: nvpstr

TensorFlow/Recommendation/NCF/.gitmodules

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-ARG FROM_IMAGE_NAME=nvcr.io/nvidia/tensorflow:19.06-py3
+ARG FROM_IMAGE_NAME=nvcr.io/nvidia/tensorflow:19.10-py3
 FROM ${FROM_IMAGE_NAME}
 
 RUN apt-get update && \

TensorFlow/Recommendation/NCF/Dockerfile

@@ -217,7 +217,7 @@ To run evaluation on a specific checkpoint, simply run the following command:
 
 ```bash
 checkpoint=/data/checkpoints/model.ckpt
-python ncf.py --data /data/cache/ml-20m --mode test --checkpoint-dir $checkpoint
+python ncf.py --data /data/cache/ml-20m --mode test --load-checkpoint-path $checkpoint
 ```
 
 Note: TensorFlow checkpoints consist of 3 files each with a `*.ckpt` prefix.
@@ -389,11 +389,7 @@ performance in training and inference modes.
 To benchmark the training and inference performance, run: 
 
 ```
-numgpu=4
-datadir=/data/cache/ml-20m
-mpirun -np $numgpu \
-    --allow-run-as-root \
-    python ncf.py --data $datadir
+mpirun -np 1 --allow-run-as-root python ncf.py --data /data/cache/ml-20m
 ```
 
 By default, the `ncf.py` script outputs metrics describing the following:

TensorFlow/Recommendation/NCF/README.md

@@ -32,16 +32,12 @@
 import pandas as pd
 from load import implicit_load
 
-from logger.logger import LOGGER
-from logger import tags
-
 import tensorflow as tf
 
 MIN_RATINGS = 20
 USER_COLUMN = 'user_id'
 ITEM_COLUMN = 'item_id'
 
-LOGGER.model = 'ncf'
 
 def parse_args():
     parser = ArgumentParser()
@@ -59,7 +55,6 @@ def main():
 
     print("Filtering out users with less than {} ratings".format(MIN_RATINGS))
     grouped = df.groupby(USER_COLUMN)
-    LOGGER.log(key=tags.PREPROC_HP_MIN_RATINGS, value=MIN_RATINGS)
     df = grouped.filter(lambda x: len(x) >= MIN_RATINGS)
 
     print("Mapping original user and item IDs to new sequential IDs")

TensorFlow/Recommendation/NCF/convert.py

@@ -1,3 +1,20 @@
+# -----------------------------------------------------------------------
+#
+# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
 import numpy as np
 import cupy as cp