Add missing dtype and shape specifications for tf.image API functions.

PiperOrigin-RevId: 348693895
Change-Id: Iff26cad4e37dcb3a261af79f8b1d3aab2b68da9a

Author: hyeygit

tensorflow/python/ops/image_ops_impl.py

@@ -3091,16 +3091,17 @@ def decode_image(contents,
   frame to fill the unoccupied areas.
 
   Args:
-    contents: 0-D `string`. The encoded image bytes.
+    contents: A `Tensor` of type `string`. 0-D. The encoded image bytes.
     channels: An optional `int`. Defaults to `0`. Number of color channels for
       the decoded image.
     dtype: The desired DType of the returned `Tensor`.
     name: A name for the operation (optional)
-    expand_animations: Controls the shape of the returned op's output. If
-      `True`, the returned op will produce a 3-D tensor for PNG, JPEG, and BMP
-      files; and a 4-D tensor for all GIFs, whether animated or not. If,
-      `False`, the returned op will produce a 3-D tensor for all file types and
-      will truncate animated GIFs to the first frame.
+    expand_animations: An optional `bool`. Defaults to `True`. Controls the
+      shape of the returned op's output. If `True`, the returned op will produce
+      a 3-D tensor for PNG, JPEG, and BMP files; and a 4-D tensor for all GIFs,
+      whether animated or not. If, `False`, the returned op will produce a 3-D
+      tensor for all file types and will truncate animated GIFs to the first
+      frame.
 
   Returns:
     `Tensor` with type `dtype` and a 3- or 4-dimensional shape, depending on
@@ -3663,10 +3664,10 @@ def non_max_suppression(boxes,
       score corresponding to each box (each row of boxes).
     max_output_size: A scalar integer `Tensor` representing the maximum number
       of boxes to be selected by non-max suppression.
-    iou_threshold: A float representing the threshold for deciding whether boxes
-      overlap too much with respect to IOU.
-    score_threshold: A float representing the threshold for deciding when to
-      remove boxes based on score.
+    iou_threshold: A 0-D float tensor representing the threshold for deciding
+      whether boxes overlap too much with respect to IOU.
+    score_threshold: A 0-D float tensor representing the threshold for deciding
+      when to remove boxes based on score.
     name: A name for the operation (optional).
 
   Returns:
@@ -3732,14 +3733,14 @@ def non_max_suppression_with_scores(boxes,
       score corresponding to each box (each row of boxes).
     max_output_size: A scalar integer `Tensor` representing the maximum number
       of boxes to be selected by non-max suppression.
-    iou_threshold: A float representing the threshold for deciding whether boxes
-      overlap too much with respect to IOU.
-    score_threshold: A float representing the threshold for deciding when to
-      remove boxes based on score.
-    soft_nms_sigma: A scalar float representing the Soft NMS sigma parameter;
-      See Bodla et al, https://arxiv.org/abs/1704.04503).  When
-        `soft_nms_sigma=0.0` (which is default), we fall back to standard (hard)
-        NMS.
+    iou_threshold: A 0-D float tensor representing the threshold for deciding
+      whether boxes overlap too much with respect to IOU.
+    score_threshold: A 0-D float tensor representing the threshold for deciding
+      when to remove boxes based on score.
+    soft_nms_sigma: A 0-D float tensor representing the sigma parameter for Soft
+      NMS; see Bodla et al (c.f. https://arxiv.org/abs/1704.04503).  When
+      `soft_nms_sigma=0.0` (which is default), we fall back to standard (hard)
+      NMS.
     name: A name for the operation (optional).
 
   Returns:
@@ -3791,15 +3792,17 @@ def non_max_suppression_with_overlaps(overlaps,
     ```
 
   Args:
-    overlaps: A 2-D float `Tensor` of shape `[num_boxes, num_boxes]`.
+    overlaps: A 2-D float `Tensor` of shape `[num_boxes, num_boxes]`
+      representing the n-by-n box overlap values.
     scores: A 1-D float `Tensor` of shape `[num_boxes]` representing a single
       score corresponding to each box (each row of boxes).
     max_output_size: A scalar integer `Tensor` representing the maximum number
       of boxes to be selected by non-max suppression.
-    overlap_threshold: A float representing the threshold for deciding whether
-      boxes overlap too much with respect to the provided overlap values.
-    score_threshold: A float representing the threshold for deciding when to
-      remove boxes based on score.
+    overlap_threshold: A 0-D float tensor representing the threshold for
+      deciding whether boxes overlap too much with respect to the provided
+      overlap values.
+    score_threshold: A 0-D float tensor representing the threshold for deciding
+      when to remove boxes based on score.
     name: A name for the operation (optional).
 
   Returns: