Image Summary: Officially start using vectorized EncodePng Op (#6611)

See #6344 for context. Googlers, see b/276803093 for more details. Tested internally: cl/570508513 #oncall #summary #image
tensorflow · Oct 4, 2023 · d295fad · d295fad
1 parent a718ebc
commit d295fad
Showing 1 changed file with 1 addition and 18 deletions.
diff --git a/tensorboard/plugins/image/summary_v2.py b/tensorboard/plugins/image/summary_v2.py
@@ -113,24 +113,7 @@ def lazy_tensor():
             tf.debugging.assert_non_negative(max_outputs)
             images = tf.image.convert_image_dtype(data, tf.uint8, saturate=True)
             limited_images = images[:max_outputs]
-            if tf.compat.forward_compatible(2023, 5, 1):
-                encoded_images = tf.image.encode_png(limited_images)
-            else:
-                # TODO(b/276803093): The kernel was updated around 2023/04/15.
-                # After 90 days (2023/07/15), please remove the False branch.
-                encoded_images = tf.map_fn(
-                    tf.image.encode_png,
-                    limited_images,
-                    dtype=tf.string,
-                    name="encode_each_image",
-                )
-                # Workaround for map_fn returning float dtype for an empty
-                # elems input.
-                encoded_images = tf.cond(
-                    tf.shape(input=encoded_images)[0] > 0,
-                    lambda: encoded_images,
-                    lambda: tf.constant([], tf.string),
-                )
+            encoded_images = tf.image.encode_png(limited_images)
             image_shape = tf.shape(input=images)
             dimensions = tf.stack(
                 [