Downloading text8.zip to temporary directory so that writing rights to the current directory is no longer required.

If a library is missing when displaying the plot - it shows now details, which one is missing.

PiperOrigin-RevId: 166161780

1 files changed, 17 insertions, 9 deletions

diff --git a/tensorflow/examples/tutorials/word2vec/word2vec_basic.py b/tensorflow/examples/tutorials/word2vec/word2vec_basic.py
index e67442b14b..6c93617ae5 100644
--- a/tensorflow/examples/tutorials/word2vec/word2vec_basic.py
+++ b/tensorflow/examples/tutorials/word2vec/word2vec_basic.py
@@ -22,6 +22,7 @@ import collections
 import math
 import os
 import random
+from tempfile import gettempdir
 import zipfile
 
 import numpy as np
@@ -33,18 +34,22 @@ import tensorflow as tf
 url = 'http://mattmahoney.net/dc/'
 
 
+# pylint: disable=redefined-outer-name
 def maybe_download(filename, expected_bytes):
   """Download a file if not present, and make sure it's the right size."""
-  if not os.path.exists(filename):
-    filename, _ = urllib.request.urlretrieve(url + filename, filename)
-  statinfo = os.stat(filename)
+  local_filename = os.path.join(gettempdir(), filename)
+  if not os.path.exists(local_filename):
+    local_filename, _ = urllib.request.urlretrieve(url + filename,
+                                                   local_filename)
+  statinfo = os.stat(local_filename)
   if statinfo.st_size == expected_bytes:
     print('Found and verified', filename)
   else:
     print(statinfo.st_size)
-    raise Exception(
-        'Failed to verify ' + filename + '. Can you get to it with a browser?')
-  return filename
+    raise Exception('Failed to verify ' + local_filename +
+                    '. Can you get to it with a browser?')
+  return local_filename
+
 
 filename = maybe_download('text8.zip', 31344016)
 
@@ -233,7 +238,9 @@ with tf.Session(graph=graph) as session:
 # Step 6: Visualize the embeddings.
 
 
-def plot_with_labels(low_dim_embs, labels, filename='tsne.png'):
+# pylint: disable=missing-docstring
+# Function to draw visualization of distance between embeddings.
+def plot_with_labels(low_dim_embs, labels, filename):
   assert low_dim_embs.shape[0] >= len(labels), 'More labels than embeddings'
   plt.figure(figsize=(18, 18))  # in inches
   for i, label in enumerate(labels):
@@ -257,7 +264,8 @@ try:
   plot_only = 500
   low_dim_embs = tsne.fit_transform(final_embeddings[:plot_only, :])
   labels = [reverse_dictionary[i] for i in xrange(plot_only)]
-  plot_with_labels(low_dim_embs, labels)
+  plot_with_labels(low_dim_embs, labels, os.path.join(gettempdir(), 'tsne.png'))
 
-except ImportError:
+except ImportError as ex:
   print('Please install sklearn, matplotlib, and scipy to show embeddings.')
+  print(ex)