Make the "predict" time series example more user friendly.

Doesn't require an input_filename flag, uses the default example input instead.

PiperOrigin-RevId: 209518060

2 files changed, 13 insertions, 5 deletions

diff --git a/tensorflow/contrib/timeseries/examples/BUILD b/tensorflow/contrib/timeseries/examples/BUILD
index 355303acf6..71b0d48798 100644
--- a/tensorflow/contrib/timeseries/examples/BUILD
+++ b/tensorflow/contrib/timeseries/examples/BUILD
@@ -16,6 +16,7 @@ config_setting(
 py_binary(
     name = "predict",
     srcs = ["predict.py"],
+    data = ["data/period_trend.csv"],
     srcs_version = "PY2AND3",
     tags = ["no_pip"],
     deps = select({
@@ -31,7 +32,6 @@ py_test(
     name = "predict_test",
     timeout = "long",  # Moderate but for asan
     srcs = ["predict_test.py"],
-    data = ["data/period_trend.csv"],
     srcs_version = "PY2AND3",
     tags = [
         "no_windows",  # TODO: needs investigation on Windows
diff --git a/tensorflow/contrib/timeseries/examples/predict.py b/tensorflow/contrib/timeseries/examples/predict.py
index 8147d40caa..b036911314 100644
--- a/tensorflow/contrib/timeseries/examples/predict.py
+++ b/tensorflow/contrib/timeseries/examples/predict.py
@@ -19,6 +19,7 @@ from __future__ import division
 from __future__ import print_function
 
 import argparse
+import os
 import sys
 
 import numpy as np
@@ -40,6 +41,10 @@ except ImportError:
 FLAGS = None
 
 
+_MODULE_PATH = os.path.dirname(__file__)
+_DEFAULT_DATA_FILE = os.path.join(_MODULE_PATH, "data/period_trend.csv")
+
+
 def structural_ensemble_train_and_predict(csv_file_name):
   # Cycle between 5 latent values over a period of 100. This leads to a very
   # smooth periodic component (and a small model), which is a good fit for our
@@ -115,9 +120,12 @@ def main(unused_argv):
   if not HAS_MATPLOTLIB:
     raise ImportError(
         "Please install matplotlib to generate a plot from this example.")
+  input_filename = FLAGS.input_filename
+  if input_filename is None:
+    input_filename = _DEFAULT_DATA_FILE
   make_plot("Structural ensemble",
-            *structural_ensemble_train_and_predict(FLAGS.input_filename))
-  make_plot("AR", *ar_train_and_predict(FLAGS.input_filename))
+            *structural_ensemble_train_and_predict(input_filename))
+  make_plot("AR", *ar_train_and_predict(input_filename))
   pyplot.show()
 
 
@@ -126,7 +134,7 @@ if __name__ == "__main__":
   parser.add_argument(
       "--input_filename",
       type=str,
-      required=True,
-      help="Input csv file.")
+      required=False,
+      help="Input csv file (omit to use the data/period_trend.csv).")
   FLAGS, unparsed = parser.parse_known_args()
   tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)