change all `as_mode` to `with mode`

server/visualdl/lib.py

@@ -16,47 +16,47 @@ def get_modes(storage):
 def get_scalar_tags(storage, mode):
     result = {}
     for mode in storage.modes():
-        reader = storage.as_mode(mode)
-        tags = reader.tags('scalar')
-        if tags:
-            result[mode] = {}
-            for tag in tags:
-                result[mode][tag] = {
-                    'displayName': reader.scalar(tag).caption(),
-                    'description': "",
-                }
+        with storage.mode(mode) as reader:
+            tags = reader.tags('scalar')
+            if tags:
+                result[mode] = {}
+                for tag in tags:
+                    result[mode][tag] = {
+                        'displayName': reader.scalar(tag).caption(),
+                        'description': "",
+                    }
     return result
 
 
 def get_scalar(storage, mode, tag):
-    reader = storage.as_mode(mode)
-    scalar = reader.scalar(tag)
+    with storage.mode(mode) as reader:
+        scalar = reader.scalar(tag)
 
-    records = scalar.records()
-    ids = scalar.ids()
-    timestamps = scalar.timestamps()
+        records = scalar.records()
+        ids = scalar.ids()
+        timestamps = scalar.timestamps()
 
-    result = zip(timestamps, ids, records)
-    return result
+        result = zip(timestamps, ids, records)
+        return result
 
 
 def get_image_tags(storage):
     result = {}
 
     for mode in storage.modes():
-        reader = storage.as_mode(mode)
-        tags = reader.tags('image')
-        if tags:
-            result[mode] = {}
-            for tag in tags:
-                image = reader.image(tag)
-                for i in xrange(max(1, image.num_samples())):
-                    caption = tag if image.num_samples() <= 1 else '%s/%d'%(tag, i)
-                    result[mode][caption] = {
-                        'displayName': caption,
-                        'description': "",
-                        'samples': 1,
-                    }
+        with storage.mode(mode) as reader:
+            tags = reader.tags('image')
+            if tags:
+                result[mode] = {}
+                for tag in tags:
+                    image = reader.image(tag)
+                    for i in xrange(max(1, image.num_samples())):
+                        caption = tag if image.num_samples() <= 1 else '%s/%d'%(tag, i)
+                        result[mode][caption] = {
+                            'displayName': caption,
+                            'description': "",
+                            'samples': 1,
+                        }
     return result
 
 
@@ -70,9 +70,9 @@ def get_image_tag_steps(storage, mode, tag):
         tag = tag[:tag.rfind('/')]
         sample_index = int(res.groups()[0])
 
-    reader = storage.as_mode(mode)
-    image = reader.image(tag)
-    res = []
+    with storage.mode(mode) as reader:
+        image = reader.image(tag)
+        res = []
 
     for step_index in range(image.num_records()):
         record = image.record(step_index, sample_index)
@@ -95,22 +95,22 @@ def get_image_tag_steps(storage, mode, tag):
 
 
 def get_invididual_image(storage, mode, tag, step_index):
-    reader = storage.as_mode(mode)
-    res = re.search(r".*/([0-9]+$)", tag)
-    # remove suffix '/x'
-    if res:
-        offset = int(res.groups()[0])
-        tag = tag[:tag.rfind('/')]
-
-    image = reader.image(tag)
-    record = image.record(step_index, offset)
-
-    data = np.array(record.data(), dtype='uint8').reshape(record.shape())
-    tempfile = NamedTemporaryFile(mode='w+b', suffix='.png')
-    with Image.fromarray(data) as im:
-        im.save(tempfile)
-    tempfile.seek(0, 0)
-    return tempfile
+    with storage.mode(mode) as reader:
+        res = re.search(r".*/([0-9]+$)", tag)
+        # remove suffix '/x'
+        if res:
+            offset = int(res.groups()[0])
+            tag = tag[:tag.rfind('/')]
+
+        image = reader.image(tag)
+        record = image.record(step_index, offset)
+
+        data = np.array(record.data(), dtype='uint8').reshape(record.shape())
+        tempfile = NamedTemporaryFile(mode='w+b', suffix='.png')
+        with Image.fromarray(data) as im:
+            im.save(tempfile)
+        tempfile.seek(0, 0)
+        return tempfile
 
 
 if __name__ == '__main__':

server/visualdl/storage_mock.py

@@ -6,11 +6,11 @@ import numpy as np
 
 
 def add_scalar(writer, mode, tag, num_steps, skip):
-    my_writer = writer.as_mode(mode)
-    scalar = my_writer.scalar(tag)
-    for i in range(num_steps):
-        if i % skip == 0:
-            scalar.add_record(i, random.random())
+    with writer.mode(mode) as my_writer:
+        scalar = my_writer.scalar(tag)
+        for i in range(num_steps):
+            if i % skip == 0:
+                scalar.add_record(i, random.random())
 
 
 def add_image(writer,
@@ -20,20 +20,20 @@ def add_image(writer,
               num_passes,
               step_cycle,
               shape=[50, 50, 3]):
-    writer_ = writer.as_mode(mode)
-    image_writer = writer_.image(tag, num_samples, step_cycle)
-
-    for pass_ in xrange(num_passes):
-        image_writer.start_sampling()
-        for ins in xrange(2 * num_samples):
-            index = image_writer.is_sample_taken()
-            if index != -1:
-                data = np.random.random(shape) * 256
-                data = np.ndarray.flatten(data)
-                assert shape
-                assert len(data) > 0
-                image_writer.set_sample(index, shape, list(data))
-        image_writer.finish_sampling()
+    with writer.mode(mode) as writer_:
+        image_writer = writer_.image(tag, num_samples, step_cycle)
+
+        for pass_ in xrange(num_passes):
+            image_writer.start_sampling()
+            for ins in xrange(2 * num_samples):
+                index = image_writer.is_sample_taken()
+                if index != -1:
+                    data = np.random.random(shape) * 256
+                    data = np.ndarray.flatten(data)
+                    assert shape
+                    assert len(data) > 0
+                    image_writer.set_sample(index, shape, list(data))
+            image_writer.finish_sampling()
 
 
 if __name__ == '__main__':

visualdl/python/test_storage.py

@@ -22,15 +22,16 @@ class StorageTest(unittest.TestCase):
             scalar.add_record(i, float(i))
 
         print 'test read'
-        self.reader = storage.StorageReader(self.dir).as_mode("train")
-        scalar = self.reader.scalar("model/scalar/min")
-        self.assertEqual(scalar.caption(), "train")
-        records = scalar.records()
-        ids = scalar.ids()
-        self.assertTrue(np.equal(records, [float(i) for i in range(10)]).all())
-        self.assertTrue(np.equal(ids, [float(i) for i in range(10)]).all())
-        print 'records', records
-        print 'ids', ids
+        self.reader = storage.StorageReader(self.dir)
+        with self.reader.mode("train") as reader:
+            scalar = reader.scalar("model/scalar/min")
+            self.assertEqual(scalar.caption(), "train")
+            records = scalar.records()
+            ids = scalar.ids()
+            self.assertTrue(np.equal(records, [float(i) for i in range(10)]).all())
+            self.assertTrue(np.equal(ids, [float(i) for i in range(10)]).all())
+            print 'records', records
+            print 'ids', ids
 
     def test_image(self):
         tag = "layer1/layer2/image0"
@@ -49,19 +50,20 @@ class StorageTest(unittest.TestCase):
                     image_writer.set_sample(index, shape, list(data))
             image_writer.finish_sampling()
 
-        self.reader = storage.StorageReader(self.dir).as_mode("train")
-        image_reader = self.reader.image(tag)
-        self.assertEqual(image_reader.caption(), tag)
-        self.assertEqual(image_reader.num_records(), num_passes)
+        self.reader = storage.StorageReader(self.dir)
+        with self.reader.mode("train") as reader:
+            image_reader = reader.image(tag)
+            self.assertEqual(image_reader.caption(), tag)
+            self.assertEqual(image_reader.num_records(), num_passes)
 
-        image_record = image_reader.record(0, 1)
-        self.assertTrue(np.equal(image_record.shape(), shape).all())
-        data = image_record.data()
-        self.assertEqual(len(data), np.prod(shape))
+            image_record = image_reader.record(0, 1)
+            self.assertTrue(np.equal(image_record.shape(), shape).all())
+            data = image_record.data()
+            self.assertEqual(len(data), np.prod(shape))
 
-        image_tags = self.reader.tags("image")
-        self.assertTrue(image_tags)
-        self.assertEqual(len(image_tags), 1)
+            image_tags = reader.tags("image")
+            self.assertTrue(image_tags)
+            self.assertEqual(len(image_tags), 1)
 
     def test_check_image(self):
         '''
@@ -75,31 +77,32 @@ class StorageTest(unittest.TestCase):
         shape = [image.size[1], image.size[0], 3]
         origin_data = np.array(image.getdata()).flatten()
 
-        self.reader = storage.StorageReader(self.dir).as_mode("train")
+        self.reader = storage.StorageReader(self.dir)
+        with self.reader.mode("train") as reader:
 
-        image_writer.start_sampling()
-        index = image_writer.is_sample_taken()
-        image_writer.set_sample(index, shape, list(origin_data))
-        image_writer.finish_sampling()
+            image_writer.start_sampling()
+            index = image_writer.is_sample_taken()
+            image_writer.set_sample(index, shape, list(origin_data))
+            image_writer.finish_sampling()
 
-        # read and check whether the original image will be displayed
+            # read and check whether the original image will be displayed
 
-        image_reader = self.reader.image(tag)
-        image_record = image_reader.record(0, 0)
-        data = image_record.data()
-        shape = image_record.shape()
+            image_reader = reader.image(tag)
+            image_record = image_reader.record(0, 0)
+            data = image_record.data()
+            shape = image_record.shape()
 
-        PIL_image_shape = (shape[0] * shape[1], shape[2])
-        data = np.array(data, dtype='uint8').reshape(PIL_image_shape)
-        print 'origin', origin_data.flatten()
-        print 'data', data.flatten()
-        image = Image.fromarray(data.reshape(shape))
-        # manully check the image and found that nothing wrong with the image storage.
-        # image.show()
+            PIL_image_shape = (shape[0] * shape[1], shape[2])
+            data = np.array(data, dtype='uint8').reshape(PIL_image_shape)
+            print 'origin', origin_data.flatten()
+            print 'data', data.flatten()
+            image = Image.fromarray(data.reshape(shape))
+            # manully check the image and found that nothing wrong with the image storage.
+            # image.show()
 
-        # after scale, elements are changed.
-        # self.assertTrue(
-        #     np.equal(origin_data.reshape(PIL_image_shape), data).all())
+            # after scale, elements are changed.
+            # self.assertTrue(
+            #     np.equal(origin_data.reshape(PIL_image_shape), data).all())
 
     def test_with_syntax(self):
         with self.writer.mode("train") as writer: