!80 optimize parsing for out-of-order events

Merge pull request !80 from luopengting/datavisual_lpt

mindinsight/datavisual/data_transform/events_data.py

@@ -23,9 +23,9 @@ from mindinsight.conf import settings
 
 
 # Type of the tensor event from external component
-_Tensor = collections.namedtuple('_Tensor', ['wall_time', 'step', 'value'])
+_Tensor = collections.namedtuple('_Tensor', ['wall_time', 'step', 'value', 'filename'])
 TensorEvent = collections.namedtuple(
-    'TensorEvent', ['wall_time', 'step', 'tag', 'plugin_name', 'value'])
+    'TensorEvent', ['wall_time', 'step', 'tag', 'plugin_name', 'value', 'filename'])
 
 # config for `EventsData`
 _DEFAULT_STEP_SIZES_PER_TAG = settings.DEFAULT_STEP_SIZES_PER_TAG
@@ -99,10 +99,11 @@ class EventsData:
 
         tensor = _Tensor(wall_time=tensor_event.wall_time,
                          step=tensor_event.step,
-                         value=tensor_event.value)
+                         value=tensor_event.value,
+                         filename=tensor_event.filename)
 
         if self._is_out_of_order_step(tensor_event.step, tensor_event.tag):
-            self.purge_reservoir_data(tensor_event.step, self._reservoir_by_tag[tag])
+            self.purge_reservoir_data(tensor_event.filename, tensor_event.step, self._reservoir_by_tag[tag])
 
         self._reservoir_by_tag[tag].add_sample(tensor)
 
@@ -176,7 +177,7 @@ class EventsData:
         return False
 
     @staticmethod
-    def purge_reservoir_data(start_step, tensor_reservoir):
+    def purge_reservoir_data(filename, start_step, tensor_reservoir):
         """
         Purge all tensor event that are out-of-order step after the given start step.
 
@@ -188,7 +189,8 @@ class EventsData:
         Returns:
             int, the number of items removed.
         """
-        cnt_out_of_order = tensor_reservoir.remove_sample(lambda x: x.step < start_step)
+        cnt_out_of_order = tensor_reservoir.remove_sample(
+            lambda x: x.step < start_step or (x.step > start_step and x.filename == filename))
 
         return cnt_out_of_order
 

mindinsight/datavisual/data_transform/ms_data_loader.py

@@ -223,7 +223,8 @@ class MSDataLoader:
                                                step=event.step,
                                                tag=tag,
                                                plugin_name=PluginNameEnum.SCALAR.value,
-                                               value=value.scalar_value)
+                                               value=value.scalar_value,
+                                               filename=self._latest_summary_filename)
                     self._events_data.add_tensor_event(tensor_event)
 
                 if value.HasField('image'):
@@ -232,7 +233,8 @@ class MSDataLoader:
                                                step=event.step,
                                                tag=tag,
                                                plugin_name=PluginNameEnum.IMAGE.value,
-                                               value=value.image)
+                                               value=value.image,
+                                               filename=self._latest_summary_filename)
                     self._events_data.add_tensor_event(tensor_event)
 
                 if value.HasField('histogram'):
@@ -242,7 +244,8 @@ class MSDataLoader:
                                                step=event.step,
                                                tag=tag,
                                                plugin_name=PluginNameEnum.HISTOGRAM.value,
-                                               value=histogram_msg)
+                                               value=histogram_msg,
+                                               filename=self._latest_summary_filename)
                     self._events_data.add_tensor_event(tensor_event)
 
         if event.HasField('graph_def'):
@@ -253,7 +256,8 @@ class MSDataLoader:
                                        step=event.step,
                                        tag=self._latest_summary_filename,
                                        plugin_name=PluginNameEnum.GRAPH.value,
-                                       value=graph)
+                                       value=graph,
+                                       filename=self._latest_summary_filename)
 
             try:
                 graph_tags = self._events_data.list_tags_by_plugin(PluginNameEnum.GRAPH.value)
@@ -436,7 +440,8 @@ class _PbParser:
                                    step=0,
                                    tag=filename,
                                    plugin_name=PluginNameEnum.GRAPH.value,
-                                   value=graph)
+                                   value=graph,
+                                   filename=filename)
 
         logger.info("Build graph success, file path: %s.", file_path)
         return tensor_event

mindinsight/datavisual/data_transform/reservoir.py

@@ -23,6 +23,24 @@ from mindinsight.utils.exceptions import ParamValueError
 from mindinsight.datavisual.utils.utils import calc_histogram_bins
 
 
+def binary_search(samples, target):
+    """Binary search target in samples."""
+    left = 0
+    right = len(samples) - 1
+    while left <= right:
+        mid = (left + right) // 2
+        if target < samples[mid].step:
+            right = mid - 1
+        elif target > samples[mid].step:
+            left = mid + 1
+        else:
+            return mid
+
+    # if right is -1, it is less than the first one.
+    # if list is [1, 2, 4], target is 3, right will be 1, so wo will insert by 2.
+    return right + 1
+
+
 class Reservoir:
     """
     A container based on Reservoir Sampling algorithm.
@@ -68,18 +86,28 @@ class Reservoir:
         """
         with self._mutex:
             if len(self._samples) < self._samples_max_size or self._samples_max_size == 0:
-                self._samples.append(sample)
+                self._add_sample(sample)
             else:
                 # Use the Reservoir Sampling algorithm to replace the old sample.
-                rand_int = self._sample_selector.randint(
-                    0, self._sample_counter)
+                rand_int = self._sample_selector.randint(0, self._sample_counter)
                 if rand_int < self._samples_max_size:
                     self._samples.pop(rand_int)
-                    self._samples.append(sample)
                 else:
-                    self._samples[-1] = sample
+                    self._samples = self._samples[:-1]
+                self._add_sample(sample)
             self._sample_counter += 1
 
+    def _add_sample(self, sample):
+        """Search the index and add sample."""
+        if not self._samples or sample.step > self._samples[-1].step:
+            self._samples.append(sample)
+            return
+        index = binary_search(self._samples, sample.step)
+        if index == len(self._samples):
+            self._samples.append(sample)
+        else:
+            self._samples.insert(index, sample)
+
     def remove_sample(self, filter_fun):
         """
         Remove the samples from Reservoir that do not meet the filter criteria.

tests/ut/datavisual/data_transform/test_events_data.py

@@ -36,9 +36,9 @@ class MockReservoir:
     def __init__(self, size):
         self.size = size
         self._samples = [
-            _Tensor('wall_time1', 1, 'value1'),
-            _Tensor('wall_time2', 2, 'value2'),
-            _Tensor('wall_time3', 3, 'value3')
+            _Tensor('wall_time1', 1, 'value1', 'filename1'),
+            _Tensor('wall_time2', 2, 'value2', 'filename2'),
+            _Tensor('wall_time3', 3, 'value3', 'filename3')
         ]
 
     def samples(self):
@@ -107,7 +107,8 @@ class TestEventsData:
         """Test add_tensor_event success."""
 
         ev_data = self.get_ev_data()
-        t_event = TensorEvent(wall_time=1, step=4, tag='new_tag', plugin_name='plugin_name1', value='value1')
+        t_event = TensorEvent(wall_time=1, step=4, tag='new_tag',
+                              plugin_name='plugin_name1', value='value1', filename='filename')
 
         ev_data.add_tensor_event(t_event)
         assert 'tag0' not in ev_data._tags
@@ -116,4 +117,54 @@ class TestEventsData:
         assert 'tag0' not in ev_data._reservoir_by_tag
         assert 'new_tag' in ev_data._tags_by_plugin['plugin_name1']
         assert ev_data._reservoir_by_tag['new_tag'].samples()[-1] == _Tensor(t_event.wall_time, t_event.step,
-                                                                             t_event.value)
+                                                                             t_event.value, 'filename')
+
+    def test_add_tensor_event_out_of_order(self):
+        """Test add_tensor_event success for out_of_order summaries."""
+        wall_time = 1
+        value = '1'
+        tag = 'tag'
+        plugin_name = 'scalar'
+        file1 = 'file1'
+        ev_data = EventsData()
+        steps = [i for i in range(2, 10)]
+        for step in steps:
+            t_event = TensorEvent(wall_time=1, step=step, tag=tag,
+                                  plugin_name=plugin_name, value=value, filename=file1)
+            ev_data.add_tensor_event(t_event)
+
+        t_event = TensorEvent(wall_time=1, step=1, tag=tag,
+                              plugin_name=plugin_name, value=value, filename=file1)
+        ev_data.add_tensor_event(t_event)
+
+        # Current steps should be: [1, 2, 3, 4, 5, 6, 7, 8, 9]
+        assert len(ev_data._reservoir_by_tag[tag].samples()) == len(steps) + 1
+
+        file2 = 'file2'
+        new_steps_1 = [5, 10]
+        for step in new_steps_1:
+            t_event = TensorEvent(wall_time=1, step=step, tag=tag,
+                                  plugin_name=plugin_name, value=value, filename=file2)
+            ev_data.add_tensor_event(t_event)
+            assert ev_data._reservoir_by_tag[tag].samples()[-1] == _Tensor(wall_time, step, value, file2)
+
+        # Current steps should be: [1, 2, 3, 4, 5, 10]
+        steps = [1, 2, 3, 4, 5, 10]
+        samples = ev_data._reservoir_by_tag[tag].samples()
+        for step, sample in zip(steps, samples):
+            filename = file1 if sample.step < 5 else file2
+            assert sample == _Tensor(wall_time, step, value, filename)
+
+        new_steps_2 = [7, 11, 3]
+        for step in new_steps_2:
+            t_event = TensorEvent(wall_time=1, step=step, tag=tag,
+                                  plugin_name=plugin_name, value=value, filename=file2)
+            ev_data.add_tensor_event(t_event)
+
+        # Current steps should be: [1, 2, 3, 5, 7, 10, 11], file2: [3, 5, 7, 10, 11]
+        steps = [1, 2, 3, 5, 7, 10, 11]
+        new_steps_2.extend(new_steps_1)
+        samples = ev_data._reservoir_by_tag[tag].samples()
+        for step, sample in zip(steps, samples):
+            filename = file2 if sample.step in new_steps_2 else file1
+            assert sample == _Tensor(wall_time, step, value, filename)

tests/ut/datavisual/data_transform/test_reservoir.py

@@ -27,10 +27,14 @@ class TestHistogramReservoir:
         sample1.value.count = 1
         sample1.value.max = 102
         sample1.value.min = 101
+        sample1.step = 2
+        sample1.filename = 'filename'
         sample2 = mock.MagicMock()
         sample2.value.count = 2
         sample2.value.max = 102
         sample2.value.min = 101
+        sample2.step = 1
+        sample2.filename = 'filename'
         my_reservoir.add_sample(sample1)
         my_reservoir.add_sample(sample2)
         samples = my_reservoir.samples()

tests/ut/datavisual/processors/test_images_processor.py

@@ -216,9 +216,8 @@ class TestImagesProcessor:
         """
         Test removing sample in reservoir.
 
-        If step list is [1, 3, 5, 7, 9, 2, 3, 4, 15],
-        and then [3, 5, 7, 9] will be deleted.
-        Results will be [1, 2, 3, 4, 15].
+        If step list is [1, 3, 5, 7, 9, 2, 3, 4, 15] in one summary,
+        Results will be [1, 2, 3, 4, 5, 7, 9, 15].
         """
         test_tag_name = self._complete_tag_name
 
@@ -237,5 +236,4 @@ class TestImagesProcessor:
             except ImageNotExistError:
                 not_found_step_list.append(test_step)
 
-        assert current_step_list == [1, 2, 3, 4, 15]
-        assert not_found_step_list == [5, 7, 9]
+        assert current_step_list == [1, 2, 3, 4, 5, 7, 9, 15]