Fix rank limits for various data layout operations

This commit removes the maximum rank 4 restriction
from REVERSE, SLICE and TILE operations so that the
new maximum is now MAX_RANK.

In doing so some rank inconsistencies were also
cleaned up, including:
* Adding a minimum rank to the PAD op description
* Adding level limit checks to SLICE and TILE ops
* Adding checks for rank(shape1) == rank(shape)
  for TILE and TRANSPOSE ops
* Add tensor_size(shape1) == tensor_size(shape)
  check for TRANSPOSE
* Replace tensor name with shape name in pesudo
  code where necessary

Change-Id: I94bb8ee0b6b720b2ba5a884ce9300dca6281245a
Signed-off-by: Luke Hutton <luke.hutton@arm.com>

2 files changed, 23 insertions, 16 deletions

diff --git a/chapters/data_layout.adoc b/chapters/data_layout.adoc
index 395cb6b..2dc7057 100644
--- a/chapters/data_layout.adoc
+++ b/chapters/data_layout.adoc
@@ -1,7 +1,7 @@
 //
 // This confidential and proprietary software may be used only as
 // authorised by a licensing agreement from ARM Limited
-// (C) COPYRIGHT 2020-2022 ARM Limited
+// (C) COPYRIGHT 2020-2023 ARM Limited
 // ALL RIGHTS RESERVED
 // The entire notice above must be reproduced on all authorised
 // copies and copies may only be made to the extent permitted
@@ -89,7 +89,7 @@ for_each(index in shape) {
     dim_t tmp_index = tensor_offset_to_index(shape1, offset);
 
     // Now read/write the value
-    in_out_t val = tensor_read<in_out_t>(input, shape1, tmp_index);
+    in_out_t val = tensor_read<in_out_t>(input1, shape1, tmp_index);
     tensor_write<in_out_t>(output, shape, index, val);
 }
 ----
@@ -120,11 +120,11 @@ include::{generated}/operators/SLICE.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(rank(input1) != length(start) || rank(input1) != length(size));
-ERROR_IF(rank(input1) != rank(output))
+ERROR_IF(rank(shape1) != length(start) || rank(shape1) != length(size));
+ERROR_IF(rank(shape1) != rank(shape));
 // Sanity check the given coordinates, ensure start and end are
 // within tensor bounds
-for_each(index in rank(input1)) {
+for_each(index in rank(shape1)) {
     ERROR_IF(start[index] < 0);
     ERROR_IF(size[index] <= 0); //Output must be positive size
     ERROR_IF(start[index] + size[index] > shape1[index]);
@@ -136,7 +136,7 @@ for_each(index in shape) {
     for(i = 0; i < rank(shape); i++) {
        tmp_index[i] = index[i] + start[i];
     }
-    in_out_t value = tensor_read<in_out_t>(input, shape1, tmp_index);
+    in_out_t value = tensor_read<in_out_t>(input1, shape1, tmp_index);
     tensor_write<in_out_t>(output, shape, index, value);
 }
 ----
@@ -149,13 +149,15 @@ include::{generated}/operators/TILE.adoc[]
 
 [source,c++]
 ----
+ERROR_IF(rank(shape1) != rank(shape));
+
 for_each(index in shape) {
     dim_t tmp_index = index;
     for(i = 0; i < rank(shape); i++) {
         ERROR_IF(shape1[i] * multiples[i] != shape[i]);
         tmp_index[i] = index[i] % shape1[i];
     }
-    in_out_t value = tensor_read<in_out_t>(input, shape1, tmp_index);
+    in_out_t value = tensor_read<in_out_t>(input1, shape1, tmp_index);
     tensor_write<in_out_t>(output, shape, index, value);
 }
 ----
@@ -169,6 +171,9 @@ include::{generated}/operators/TRANSPOSE.adoc[]
 
 [source,c++]
 ----
+ERROR_IF(rank(shape1) != rank(shape));
+ERROR_IF(tensor_size(shape1) != tensor_size(shape));
+
 for_each(index in perms) {
     // Ensure each perms value is a valid value
     ERROR_IF(index >= rank(shape1));
@@ -189,7 +194,7 @@ for_each(index in shape) {
     for(i = 0; i < rank(shape); i++) {
         tmp_index[perms[i]] = index[i]
     }
-    in_out_t value = tensor_read<in_out_t>(input, shape1, tmp_index);
+    in_out_t value = tensor_read<in_out_t>(input1, shape1, tmp_index);
     tensor_write<in_out_t>(output, shape, index, value);
 }
 ----
diff --git a/tosa.xml b/tosa.xml
index 811513a..43f7908 100644
--- a/tosa.xml
+++ b/tosa.xml
@@ -1679,7 +1679,7 @@
         <name>PAD</name>
         <arguments>
           <argument category="input" name="input1" type="in_out_t*" shape="shape1">
-            <description>Input tensor</description>
+            <description>Input tensor with minimum rank of one.</description>
           </argument>
           <argument category="attribute" name="padding" type="int32_t" shape="[rank(shape1),2]">
             <description>Number of pad elements at the start and end of each dimension</description>
@@ -1719,7 +1719,7 @@
             <description>Input tensor</description>
             <levellimit value="rank(shape1)" limit="MAX_RANK"/>
           </argument>
-          <argument category="attribute" name="new_shape" type="int32_t" shape="[rank(output)]">
+          <argument category="attribute" name="new_shape" type="int32_t" shape="[rank(shape)]">
             <description>List of values, with each element giving the size of the result tensor for the given dimension. At most one dimension may be given as -1 to automatically calculate the dimension size.</description>
           </argument>
           <argument category="output" name="output" type="in_out_t*" shape="shape">
@@ -1751,7 +1751,7 @@
         <name>REVERSE</name>
         <arguments>
           <argument category="input" name="input" type="in_out_t*" shape="shape">
-            <description>Input tensor with rank from 1 to 4</description>
+            <description>Input tensor with minimum rank of one.</description>
             <levellimit value="rank(shape)" limit="MAX_RANK"/>
           </argument>
           <argument category="attribute" name="axis" type="int32_t" shape="-">
@@ -1785,14 +1785,15 @@
         <name>SLICE</name>
         <arguments>
           <argument category="input" name="input1" type="in_out_t*" shape="shape1">
-            <description>Input tensor with rank from 1 to 4</description>
+            <description>Input tensor with minimum rank of one.</description>
           </argument>
-          <argument category="attribute" name="start" type="int32_t" shape="[rank(input1)]">
+          <argument category="attribute" name="start" type="int32_t" shape="[rank(shape1)]">
             <description>List of integer coordinates, of length equal to the rank of input1. Start coordinate for slicing.</description>
           </argument>
-          <argument category="attribute" name="size" type="int32_t" shape="[rank(input1)]">
+          <argument category="attribute" name="size" type="int32_t" shape="[rank(shape1)]">
             <description>List of integer size values, of length equal to the rank of input1. Size of the input to be
 used.</description>
+            <levellimit value="rank(shape)" limit="MAX_RANK"/>
           </argument>
           <argument category="output" name="output" type="in_out_t*" shape="shape">
             <description>Output tensor of same type as the input tensor</description>
@@ -1822,13 +1823,14 @@ used.</description>
         <name>TILE</name>
         <arguments>
           <argument category="input" name="input1" type="in_out_t*" shape="shape1">
-            <description>Input tensor with rank from 1 to 4</description>
+            <description>Input tensor with minimum rank of one.</description>
           </argument>
           <argument category="attribute" name="multiplies" type="int32_t" shape="[rank(shape1)]">
             <description>Number of times to replicate input1 in each dimension</description>
           </argument>
           <argument category="output" name="output" type="in_out_t*" shape="shape">
             <description>Output tensor of same type, rank as the input tensor</description>
+            <levellimit value="rank(shape)" limit="MAX_RANK"/>
           </argument>
         </arguments>
         <types>
@@ -1857,7 +1859,7 @@ used.</description>
           <argument category="input" name="input1" type="in_out_t*" shape="shape1">
             <description>Input tensor with minimum rank of one.</description>
           </argument>
-          <argument category="attribute" name="perms" type="int32_t" shape="[rank(input1)]">
+          <argument category="attribute" name="perms" type="int32_t" shape="[rank(shape1)]">
             <description>List of integers of length equal to the rank of input1. Values must be valid dimensions within shape1, and may not be repeated.</description>
           </argument>
           <argument category="output" name="output" type="in_out_t*" shape="shape">