Merge pull request #37558 from Angus-Luo:master

PiperOrigin-RevId: 301172077
Change-Id: Id2a2d3dd49f198fb463eef7838d38d62c49adb6b

tensorflow/core/api_def/base_api/api_def_DecodeGif.pbtxt

@@ -21,6 +21,6 @@ uncompressed by running:
     convert $src.gif -coalesce $dst.gif
 
 This op also supports decoding JPEGs and PNGs, though it is cleaner to use
-`tf.image.decode_image`.
+`tf.io.decode_image`.
 END
 }

tensorflow/core/api_def/base_api/api_def_DecodeJpeg.pbtxt

@@ -75,6 +75,6 @@ downscaling the image later.
 
 
 This op also supports decoding PNGs and non-animated GIFs since the interface is
-the same, though it is cleaner to use `tf.image.decode_image`.
+the same, though it is cleaner to use `tf.io.decode_image`.
 END
 }

tensorflow/core/api_def/base_api/api_def_DecodePng.pbtxt

@@ -34,6 +34,6 @@ If needed, the PNG-encoded image is transformed to match the requested number
 of color channels.
 
 This op also supports decoding JPEGs and non-animated GIFs since the interface
-is the same, though it is cleaner to use `tf.image.decode_image`.
+is the same, though it is cleaner to use `tf.io.decode_image`.
 END
 }

tensorflow/core/kernels/decode_image_op.cc

@@ -317,8 +317,8 @@ class DecodeImageOp : public OpKernel {
                       } else {
                         status = errors::InvalidArgument(
                             "Got ", num_frames, " frames, but animated gifs ",
-                            "can only be decoded by tf.image.decode_gif or ",
-                            "tf.image.decode_image");
+                            "can only be decoded by tf.io.decode_gif or ",
+                            "tf.io.decode_image");
                       }
                       if (!status.ok()) {
                         VLOG(1) << status;

tensorflow/examples/label_image/label_image.py

@@ -44,15 +44,13 @@ def read_tensor_from_image_file(file_name,
   output_name = "normalized"
   file_reader = tf.read_file(file_name, input_name)
   if file_name.endswith(".png"):
-    image_reader = tf.image.decode_png(
-        file_reader, channels=3, name="png_reader")
+    image_reader = tf.io.decode_png(file_reader, channels=3, name="png_reader")
   elif file_name.endswith(".gif"):
-    image_reader = tf.squeeze(
-        tf.image.decode_gif(file_reader, name="gif_reader"))
+    image_reader = tf.squeeze(tf.io.decode_gif(file_reader, name="gif_reader"))
   elif file_name.endswith(".bmp"):
-    image_reader = tf.image.decode_bmp(file_reader, name="bmp_reader")
+    image_reader = tf.io.decode_bmp(file_reader, name="bmp_reader")
   else:
-    image_reader = tf.image.decode_jpeg(
+    image_reader = tf.io.decode_jpeg(
         file_reader, channels=3, name="jpeg_reader")
   float_caster = tf.cast(image_reader, tf.float32)
   dims_expander = tf.expand_dims(float_caster, 0)

tensorflow/lite/g3doc/models/style_transfer/overview.ipynb

@@ -250,7 +250,7 @@
         "# Function to load an image from a file, and add a batch dimension.\n",
         "def load_img(path_to_img):\n",
         "  img = tf.io.read_file(path_to_img)\n",
-        "  img = tf.image.decode_image(img, channels=3)\n",
+        "  img = tf.io.decode_image(img, channels=3)\n",
         "  img = tf.image.convert_image_dtype(img, tf.float32)\n",
         "  img = img[tf.newaxis, :]\n",
         "\n",

tensorflow/python/framework/ops.py

@@ -605,7 +605,7 @@ class Tensor(_TensorLike):
 
     ```python
     _, image_data = tf.compat.v1.TFRecordReader(...).read(...)
-    image = tf.image.decode_png(image_data, channels=3)
+    image = tf.io.decode_png(image_data, channels=3)
 
     # The height and width dimensions of `image` are data dependent, and
     # cannot be computed without executing the op.