Merge pull request #38 from PPPLDeepLearning/hotfix/package-deprecations

Address warnings from dependencies

Author: jnkh

.gitignore

@@ -1,6 +1,8 @@
 # Emacs
 *~
 \#*\#
+.auctex-auto/
+.dir-locals.el
 
 # Generated by test
 plot_*.html

examples/notebooks/Signal Influence.ipynb

@@ -26,20 +26,16 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "dat = np.load('./temp_data/signal_influence/signal_influence_results_155191_2017-12-01-01-42-33.npz')"
+    "dat = np.load('./temp_data/signal_influence/signal_influence_results_155191_2017-12-01-01-42-33.npz', allow_pickle=False)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -60,9 +56,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -102,9 +96,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -139,9 +131,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -211,9 +201,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -315,15 +303,13 @@
    },
    "outputs": [],
    "source": [
-    "dat = np.load('./temp_data/signal_influence/signal_influence_results_2017-11-30-20-13-39.npz')"
+    "dat = np.load('./temp_data/signal_influence/signal_influence_results_2017-11-30-20-13-39.npz', allow_pickle=False)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "y_gold = dat['y_gold']\n",
@@ -333,9 +319,7 @@
   {
    "cell_type": "code",
    "execution_count": 97,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -362,9 +346,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "t_range = np.linspace(0,len(y_gold[0]),10,dtype=np.int)"
@@ -373,9 +355,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -395,9 +375,7 @@
   {
    "cell_type": "code",
    "execution_count": 95,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "def difference_metric(y_prime,y_prime_orig):\n",
@@ -422,9 +400,7 @@
   {
    "cell_type": "code",
    "execution_count": 96,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "differences = get_importance_measure(y_prime,difference_metric)"
@@ -433,9 +409,7 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "metadata": {
-    "collapsed": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -464,21 +438,21 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python [conda root]",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "conda-root-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
-    "version": 2
+    "version": 3
    },
    "file_extension": ".py",
    "mimetype": "text/x-python",
    "name": "python",
    "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.12"
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
   },
   "latex_envs": {
    "LaTeX_envs_menu_present": true,

examples/submit_batch_job.py

@@ -31,7 +31,7 @@ def copy_conf_file(
     pathdst = os.path.join(save_path, conf_name)
 
     with open(pathsrc, 'r') as yaml_file:
-        conf = yaml.load(yaml_file)
+        conf = yaml.load(yaml_file, Loader=yaml.SafeLoader)
     # make sure all files like checkpoints and normalization are done locally
     conf['training']['hyperparam_tuning'] = True
     with open(pathdst, 'w') as outfile:
@@ -40,7 +40,7 @@ def copy_conf_file(
 
 def get_conf(template_path, conf_name):
     with open(os.path.join(template_path, conf_name), 'r') as yaml_file:
-        conf = yaml.load(yaml_file)
+        conf = yaml.load(yaml_file, Loader=yaml.SafeLoader)
     return conf
 
 

examples/tune_hyperparams.py

@@ -107,7 +107,7 @@ def generate_conf_file(tunables, shallow, template_path="../", save_path="./",
                        conf_name="conf.yaml"):
     assert(template_path != save_path)
     with open(os.path.join(template_path, conf_name), 'r') as yaml_file:
-        conf = yaml.load(yaml_file)
+        conf = yaml.load(yaml_file, Loader=yaml.SafeLoader)
     for tunable in tunables:
         tunable.assign_to_conf(conf, save_path)
     # rely on early stopping to terminate training

jenkins-ci/run_jenkins.py

@@ -23,7 +23,7 @@ def generate_conf_file(
         conf_name="conf.yaml"):
     assert(template_path != save_path)
     with open(os.path.join(template_path, conf_name), 'r') as yaml_file:
-        conf = yaml.load(yaml_file)
+        conf = yaml.load(yaml_file, Loader=yaml.SafeLoader)
     conf['training']['num_epochs'] = 2
     conf['paths']['data'] = test_configuration[1]
     if test_configuration[1] == "Python3":

plasma/conf.py

@@ -2,6 +2,7 @@
 import os
 import errno
 
+# TODO(KGF): this conf.py feels like an unnecessary level of indirection
 if os.path.exists(os.path.join(os.path.abspath(os.path.dirname(__file__)),
                                '../examples/conf.yaml')):
     conf = parameters(os.path.join(os.path.abspath(os.path.dirname(__file__)),

plasma/conf_parser.py

@@ -16,21 +16,22 @@ def parameters(input_file):
         TTDTarget, TTDInvTarget, TTDLinearTarget
         )
     with open(input_file, 'r') as yaml_file:
-        params = yaml.load(yaml_file)
+        params = yaml.load(yaml_file, Loader=yaml.SafeLoader)
 
         params['user_name'] = getpass.getuser()
         output_path = params['fs_path'] + "/" + params['user_name']
         base_path = output_path
 
         params['paths']['base_path'] = base_path
-        params['paths']['signal_prepath'] = base_path + \
-            params['paths']['signal_prepath']
-        params['paths']['shot_list_dir'] = base_path + \
-            params['paths']['shot_list_dir']
+        params['paths']['signal_prepath'] = (
+            base_path + params['paths']['signal_prepath'])
+        params['paths']['shot_list_dir'] = (
+            base_path + params['paths']['shot_list_dir'])
         params['paths']['output_path'] = output_path
         h = get_unique_signal_hash(sig.all_signals.values())
-        params['paths']['global_normalizer_path'] = output_path + \
-            '/normalization/normalization_signal_group_{}.npz'.format(h)
+        params['paths']['global_normalizer_path'] = (
+            output_path
+            + '/normalization/normalization_signal_group_{}.npz'.format(h))
         if params['training']['hyperparam_tuning']:
             # params['paths']['saved_shotlist_path'] =
             # './normalization/shot_lists.npz'
@@ -44,12 +45,12 @@ def parameters(input_file):
             # '/normalization/shot_lists.npz'
             params['paths']['normalizer_path'] = (
                 params['paths']['global_normalizer_path'])
-            params['paths']['model_save_path'] = (
-                output_path + '/model_checkpoints/')
+            params['paths']['model_save_path'] = (output_path
+                                                  + '/model_checkpoints/')
             params['paths']['csvlog_save_path'] = output_path + '/csv_logs/'
             params['paths']['results_prepath'] = output_path + '/results/'
-        params['paths']['tensorboard_save_path'] = output_path + \
-            params['paths']['tensorboard_save_path']
+        params['paths']['tensorboard_save_path'] = (
+            output_path + params['paths']['tensorboard_save_path'])
         params['paths']['saved_shotlist_path'] = (
             params['paths']['base_path'] + '/processed_shotlists/'
             + params['paths']['data']

plasma/models/mpi_runner.py

@@ -662,7 +662,7 @@ def save_shotlists(conf, shot_list_train, shot_list_validate, shot_list_test):
 
 def load_shotlists(conf):
     path = get_shot_list_path(conf)
-    data = np.load(path)
+    data = np.load(path, allow_pickle=False)
     shot_list_train = data['shot_list_train'][()]
     shot_list_validate = data['shot_list_validate'][()]
     shot_list_test = data['shot_list_test'][()]

plasma/models/runner.py

@@ -10,9 +10,9 @@
 from hyperopt import hp, STATUS_OK
 import numpy as np
 import sys
-import matplotlib.pyplot as plt
 import matplotlib
 matplotlib.use('Agg')
+import matplotlib.pyplot as plt  # noqa
 
 # if sys.version_info[0] < 3:
 #     from itertools import imap

plasma/models/shallow_runner.py

@@ -20,11 +20,12 @@
 import datetime
 import time
 import numpy as np
+
 from copy import deepcopy
 
-# import matplotlib.pyplot as plt
 import matplotlib
 matplotlib.use('Agg')
+# import matplotlib.pyplot as plt
 
 # import sys
 # if sys.version_info[0] < 3:
@@ -134,7 +135,7 @@ def process(self, shot):
             # print(X.shape, Y.shape)
         else:
             try:
-                dat = np.load(save_path)
+                dat = np.load(save_path, allow_pickle=False)
                 # X, Y, disr = dat["X"], dat["Y"], dat["disr"][()]
                 X = dat["X"]
             except BaseException: