From 960ab0490bb6e3600b031d0aa5ccfcf754d41915 Mon Sep 17 00:00:00 2001
From: MrStronger <1274552194@qq.com>
Date: Mon, 25 Jun 2018 12:25:11 +0800
Subject: [PATCH] fix version bugs

---
 README.md | 10 ++++++++++
 model.py  |  2 +-
 train.py  |  8 ++++----
 3 files changed, 15 insertions(+), 5 deletions(-)

diff --git a/README.md b/README.md
index 534a842..4d35f70 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,16 @@
 # Autopilot-TensorFlow
 A TensorFlow implementation of this [Nvidia paper](https://arxiv.org/pdf/1604.07316.pdf) with some changes.
 
+# Installation
+Download the latest version of [python](https://www.python.org/downloads/) and [pip](https://pip.pypa.io/en/stable/installing/)
+
+Install TensorFlow [How](https://www.tensorflow.org/install/)
+
+Use pip to install several packages
+`pip install scipy Pillow opencv-python`
+
+Activate tensorflow and enter the project directory
+
 # How to Use
 Download the [dataset](https://drive.google.com/file/d/0B-KJCaaF7elleG1RbzVPZWV4Tlk/view?usp=sharing) and extract into the repository folder
 
diff --git a/model.py b/model.py
index 0bc4576..84984a8 100644
--- a/model.py
+++ b/model.py
@@ -85,4 +85,4 @@ def conv2d(x, W, stride):
 W_fc5 = weight_variable([10, 1])
 b_fc5 = bias_variable([1])
 
-y = tf.mul(tf.atan(tf.matmul(h_fc4_drop, W_fc5) + b_fc5), 2) #scale the atan output
+y = tf.multiply(tf.atan(tf.matmul(h_fc4_drop, W_fc5) + b_fc5), 2) #scale the atan output
diff --git a/train.py b/train.py
index b1fad04..f21fbd0 100644
--- a/train.py
+++ b/train.py
@@ -12,20 +12,20 @@
 
 train_vars = tf.trainable_variables()
 
-loss = tf.reduce_mean(tf.square(tf.sub(model.y_, model.y))) + tf.add_n([tf.nn.l2_loss(v) for v in train_vars]) * L2NormConst
+loss = tf.reduce_mean(tf.square(tf.subtract(model.y_, model.y))) + tf.add_n([tf.nn.l2_loss(v) for v in train_vars]) * L2NormConst
 train_step = tf.train.AdamOptimizer(1e-4).minimize(loss)
 sess.run(tf.initialize_all_variables())
 
 # create a summary to monitor cost tensor
-tf.scalar_summary("loss", loss)
+tf.summary.scalar("loss", loss)
 # merge all summaries into a single op
-merged_summary_op = tf.merge_all_summaries()
+merged_summary_op = tf.summary.merge_all()
 
 saver = tf.train.Saver(write_version = saver_pb2.SaverDef.V1)
 
 # op to write logs to Tensorboard
 logs_path = './logs'
-summary_writer = tf.train.SummaryWriter(logs_path, graph=tf.get_default_graph())
+summary_writer = tf.summary.FileWriter(logs_path, graph=tf.get_default_graph())
 
 epochs = 30
 batch_size = 100