Histogram data download

tensorboard/plugins/histogram/histograms_plugin.py

@@ -23,10 +23,12 @@
 from __future__ import print_function
 
 import collections
+import csv
 import random
 
 import numpy as np
 import six
+from six import StringIO
 from werkzeug import wrappers
 
 from tensorboard import plugin_util
@@ -36,6 +38,10 @@
 from tensorboard.plugins.histogram import metadata
 from tensorboard.util import tensor_util
 
+class OutputFormat(object):
+  """An enum used to list the valid output formats for API calls."""
+  JSON = 'json'
+  CSV = 'csv'
 
 class HistogramsPlugin(base_plugin.TBPlugin):
   """Histograms Plugin for TensorBoard.
@@ -63,8 +69,8 @@ def __init__(self, context):
 
   def get_plugin_apps(self):
     return {
-        '/histograms': self.histograms_route,
-        '/tags': self.tags_route,
+      '/histograms': self.histograms_route,
+      '/tags': self.tags_route,
     }
 
   def is_active(self):
@@ -124,7 +130,35 @@ def index_impl(self):
 
     return result
 
-  def histograms_impl(self, tag, run, downsample_to=None):
+  def _get_csv_response(self, events):
+    """
+
+    Args:
+      events: A list of (wall_time, step, tensor_as_list) event tuples.
+
+    Returns:
+      CSV string representation of the given events.
+    """
+    string_io = StringIO()
+    writer = csv.writer(string_io)
+    writer.writerow(['Wall time', 'Step', 'BinStart', 'BinEnd', 'BinValue'])
+    # Convert the events in a way that we can sensibly export
+    # them as csv. Therefore, we split the start, end, value of
+    # each bin by semicolon.
+    for e in events:
+      writer.writerows(
+        [
+          e[0],
+          e[1],
+          ';'.join(['{:.17f}'.format(el[0]) for el in e[2]]),
+          ';'.join(['{:.17f}'.format(el[1]) for el in e[2]]),
+          ';'.join(['{}'.format(el[2]) for el in e[2]]),
+        ]
+      )
+    return string_io.getvalue()
+
+  def histograms_impl(self, tag, run, downsample_to=None,
+                      output_format=OutputFormat.JSON):
     """Result of the form `(body, mime_type)`, or `ValueError`.
 
     At most `downsample_to` events will be returned. If this value is
@@ -136,17 +170,17 @@ def histograms_impl(self, tag, run, downsample_to=None):
       cursor = db.cursor()
       # Prefetch the tag ID matching this run and tag.
       cursor.execute(
-          '''
-          SELECT
-            tag_id
-          FROM Tags
-          JOIN Runs USING (run_id)
-          WHERE
-            Runs.run_name = :run
-            AND Tags.tag_name = :tag
-            AND Tags.plugin_name = :plugin
-          ''',
-          {'run': run, 'tag': tag, 'plugin': metadata.PLUGIN_NAME})
+        '''
+        SELECT
+          tag_id
+        FROM Tags
+        JOIN Runs USING (run_id)
+        WHERE
+          Runs.run_name = :run
+          AND Tags.tag_name = :tag
+          AND Tags.plugin_name = :plugin
+        ''',
+        {'run': run, 'tag': tag, 'plugin': metadata.PLUGIN_NAME})
       row = cursor.fetchone()
       if not row:
         raise ValueError('No histogram tag %r for run %r' % (tag, run))
@@ -160,32 +194,32 @@ def histograms_impl(self, tag, run, downsample_to=None):
       # can be formally expressed as the following:
       #   [s_min + math.ceil(i / k * (s_max - s_min)) for i in range(0, k + 1)]
       cursor.execute(
-          '''
+        '''
+        SELECT
+          MIN(step) AS step,
+          computed_time,
+          data,
+          dtype,
+          shape
+        FROM Tensors
+        INNER JOIN (
           SELECT
-            MIN(step) AS step,
-            computed_time,
-            data,
-            dtype,
-            shape
+            MIN(step) AS min_step,
+            MAX(step) AS max_step
           FROM Tensors
-          INNER JOIN (
-            SELECT
-              MIN(step) AS min_step,
-              MAX(step) AS max_step
-            FROM Tensors
-            /* Filter out NULL so we can use TensorSeriesStepIndex. */
-            WHERE series = :tag_id AND step IS NOT NULL
-          )
-          /* Ensure we omit reserved rows, which have NULL step values. */
+          /* Filter out NULL so we can use TensorSeriesStepIndex. */
           WHERE series = :tag_id AND step IS NOT NULL
-          /* Bucket rows into sample_size linearly spaced buckets, or do
-             no sampling if sample_size is NULL. */
-          GROUP BY
-            IFNULL(:sample_size - 1, max_step - min_step)
-            * (step - min_step) / (max_step - min_step)
-          ORDER BY step
-          ''',
-          {'tag_id': tag_id, 'sample_size': downsample_to})
+        )
+        /* Ensure we omit reserved rows, which have NULL step values. */
+        WHERE series = :tag_id AND step IS NOT NULL
+        /* Bucket rows into sample_size linearly spaced buckets, or do
+           no sampling if sample_size is NULL. */
+        GROUP BY
+          IFNULL(:sample_size - 1, max_step - min_step)
+          * (step - min_step) / (max_step - min_step)
+        ORDER BY step
+        ''',
+        {'tag_id': tag_id, 'sample_size': downsample_to})
       events = [(computed_time, step, self._get_values(data, dtype, shape))
                 for step, computed_time, data, dtype, shape in cursor]
     else:
@@ -196,11 +230,15 @@ def histograms_impl(self, tag, run, downsample_to=None):
         raise ValueError('No histogram tag %r for run %r' % (tag, run))
       if downsample_to is not None and len(tensor_events) > downsample_to:
         rand_indices = random.Random(0).sample(
-            six.moves.xrange(len(tensor_events)), downsample_to)
+          six.moves.xrange(len(tensor_events)), downsample_to)
         indices = sorted(rand_indices)
         tensor_events = [tensor_events[i] for i in indices]
       events = [[e.wall_time, e.step, tensor_util.make_ndarray(e.tensor_proto).tolist()]
                 for e in tensor_events]
+
+    if output_format == OutputFormat.CSV:
+      return (self._get_csv_response(events), 'text/csv')
+
     return (events, 'application/json')
 
   def _get_values(self, data_blob, dtype_enum, shape_string):
@@ -225,9 +263,11 @@ def histograms_route(self, request):
     """Given a tag and single run, return array of histogram values."""
     tag = request.args.get('tag')
     run = request.args.get('run')
+    output_format = request.args.get('format')
     try:
       (body, mime_type) = self.histograms_impl(
-          tag, run, downsample_to=self.SAMPLE_SIZE)
+        tag, run, downsample_to=self.SAMPLE_SIZE,
+        output_format=output_format)
       code = 200
     except ValueError as e:
       (body, mime_type) = (str(e), 'text/plain')

tensorboard/plugins/histogram/histograms_plugin_test.py

@@ -20,9 +20,11 @@
 from __future__ import print_function
 
 import collections
+import csv
 import os.path
 
 import six
+from six import StringIO
 from six.moves import xrange  # pylint: disable=redefined-builtin
 import tensorflow as tf
 
@@ -173,6 +175,33 @@ def test_histograms_with_histogram(self):
     self._test_histograms(self._RUN_WITH_HISTOGRAM,
                           '%s/histogram_summary' % self._HISTOGRAM_TAG)
 
+  def _test_histograms_csv(self, run_name, tag_name, should_work=True):
+    self.set_up_with_runs([self._RUN_WITH_LEGACY_HISTOGRAM,
+                           self._RUN_WITH_HISTOGRAM])
+    if should_work:
+      (data, mime_type) = self.plugin.histograms_impl(
+        tag_name, run_name,
+        output_format=histograms_plugin.OutputFormat.CSV)
+      self.assertEqual('text/csv', mime_type)
+      s = StringIO(data)
+      reader = csv.reader(s)
+      self.assertEqual(['Wall time', 'Step', 'BinStart',
+                        'BinEnd', 'BinValue'], next(reader))
+      self.assertEqual(len(list(reader)), self._STEPS)
+    else:
+      with self.assertRaises(KeyError):
+        self.plugin.histograms_impl(
+          self._HISTOGRAM_TAG, run_name,
+          output_format=histograms_plugin.OutputFormat.CSV)
+
+  def test_histograms_csv_with_legacy_histograms(self):
+    self._test_histograms_csv(self._RUN_WITH_LEGACY_HISTOGRAM,
+                              self._LEGACY_HISTOGRAM_TAG)
+
+  def test_histograms_csv_with_histogram(self):
+    self._test_histograms_csv(self._RUN_WITH_HISTOGRAM, self._HISTOGRAM_TAG,
+                              should_work=False)
+
   def test_active_with_legacy_histogram(self):
     self.set_up_with_runs([self._RUN_WITH_LEGACY_HISTOGRAM])
     self.assertTrue(self.plugin.is_active())

tensorboard/plugins/histogram/tf_histogram_dashboard/tf-histogram-dashboard.html

@@ -41,6 +41,14 @@
   <template>
     <tf-dashboard-layout>
       <div class="sidebar">
+        <div class="sidebar-section">
+          <div class="line-item">
+            <paper-checkbox
+              id="show-download-links"
+              checked="{{_showDownloadLinks}}"
+            >Show data download links</paper-checkbox>
+          </div>
+        </div>
         <div class="sidebar-section">
           <tf-option-selector
             id="histogramModeSelector"
@@ -66,7 +74,7 @@
           <tf-runs-selector selected-runs="{{_selectedRuns}}">
           </tf-runs-selector>
         </div>
-       </div>
+      </div>
       </div>
       <div class="center">
         <template is="dom-if" if="[[_dataNotFound]]">
@@ -107,6 +115,7 @@ <h3>No histogram data was found.</h3>
                     tag="[[item.tag]]"
                     tag-metadata="[[_tagMetadata(_runToTagInfo, item.run, item.tag)]]"
                     time-property="[[_timeProperty]]"
+                    show-download-links="[[_showDownloadLinks]]"
                     histogram-mode="[[_histogramMode]]"
                     request-manager="[[_requestManager]]"
                   ></tf-histogram-loader>
@@ -141,6 +150,13 @@ <h3>No histogram data was found.</h3>
           type: String,
           value: "step",
         },
+        _showDownloadLinks: {
+          type: Boolean,
+          notify: true,
+          value: tf_storage.getBooleanInitializer('_showDownloadLinks',
+            {defaultValue: false, useLocalStorage: true}),
+          observer: '_showDownloadLinksObserver',
+        },
 
         _selectedRuns: Array,
         _runToTag: Object,  // map<run: string, tags: string[]>
@@ -179,6 +195,9 @@ <h3>No histogram data was found.</h3>
         'content-visibility-changed': '_redrawCategoryPane',
       },
 
+      _showDownloadLinksObserver: tf_storage.getBooleanObserver(
+        '_showDownloadLinks', {defaultValue: false, useLocalStorage: true}),
+
       _redrawCategoryPane(event, val) {
         if (!val) return;
         event.target.querySelectorAll('tf-histogram-loader')

tensorboard/plugins/histogram/tf_histogram_dashboard/tf-histogram-loader.html

@@ -54,6 +54,28 @@
         icon="fullscreen"
         on-tap="_toggleExpanded"
       ></paper-icon-button>
+      <template is="dom-if" if="[[showDownloadLinks]]">
+        <div class="download-links" style="display: flex; flex-direction: row;">
+          <paper-dropdown-menu
+            no-label-float="true"
+            label="run to download"
+            selected-item-label="{{_runToDownload}}"
+          >
+            <paper-menu class="dropdown-content" slot="dropdown-content">
+              <template is="dom-repeat" items="[[dataToLoad]]">
+                <paper-item no-label-float=true>[[item.run]]</paper-item>
+              </template>
+            </paper-menu>
+          </paper-dropdown-menu>
+          <a
+            download="run_[[_runToDownload]]-tag-[[tag]].csv"
+            href="[[_csvUrl(tag, _runToDownload)]]"
+          >CSV</a> <a
+          download="run_[[_runToDownload]]-tag-[[tag]].json"
+          href="[[_jsonUrl(tag, _runToDownload)]]"
+        >JSON</a>
+        </div>
+      </template>
     </div>
     <style>
       :host {
@@ -91,6 +113,36 @@
         margin-bottom: 10px;
         width: 90%;
       }
+
+      .download-links {
+        display: flex;
+        height: 32px;
+      }
+
+      .download-links a {
+        align-self: center;
+        font-size: 10px;
+        margin: 2px;
+      }
+
+      .download-links paper-dropdown-menu {
+        width: 100px;
+        --paper-input-container-label: {
+          font-size: 10px;
+        };
+        --paper-input-container-input: {
+          font-size: 10px;
+        }
+      }
+
+      paper-menu-button {
+        padding: 0;
+      }
+      paper-item a {
+        color: inherit;
+        text-decoration: none;
+        white-space: nowrap;
+      }
     </style>
   </template>
   <script>
@@ -114,8 +166,11 @@
           value: () => ({tag, run}) => {
             const router = tf_backend.getRouter();
             return tf_backend.addParams(
-                router.pluginRoute('histograms', '/histograms'),
-                {tag, run});
+              router.pluginRoute('histograms', '/histograms'),
+              {
+                tag,
+                run,
+              });
           },
         },
         loadDataCallback: {
@@ -128,6 +183,7 @@
             };
           },
         },
+
         /** @type {{description: string, displayName: string}} */
         tagMetadata: Object,
         timeProperty: String,
@@ -155,6 +211,16 @@
 
       behaviors: [tf_dashboard_common.DataLoaderBehavior],
 
+
+      _csvUrl(tag, run) {
+        return tf_backend.addParams(
+          this.getDataLoadUrl({tag, run}),
+          {format: 'csv'});
+      },
+      _jsonUrl(tag, run) {
+        return this.getDataLoadUrl({tag, run});
+      },
+
       _computeDataToLoad(run, tag) {
         return [{run, tag}];
       },

tensorboard/plugins/scalar/scalars_plugin.py

@@ -198,4 +198,5 @@ def scalars_route(self, request):
     experiment = request.args.get('experiment')
     output_format = request.args.get('format')
     (body, mime_type) = self.scalars_impl(tag, run, experiment, output_format)
+
     return http_util.Respond(request, body, mime_type)