Machine parsable specification

This converts portions of the asciidoc specification into an xml
document and schema. For the html and pdf outputs, the xml is
converted to asciidoc files that are included into the existing
specification.

The xml allows future automated uses of the tosa specification
while maintaining rough compatibility with the existing document.
No significant functional changes are included in this change.

Change-Id: I7f1f95c527638e270c157d58fcdec6a3510daea5
Signed-off-by: Eric Kunze <eric.kunze@arm.com>

1 files changed, 17 insertions, 322 deletions

diff --git a/chapters/ewise_binary.adoc b/chapters/ewise_binary.adoc
index 27efb44..dcd44b4 100644
--- a/chapters/ewise_binary.adoc
+++ b/chapters/ewise_binary.adoc
@@ -14,15 +14,7 @@
 Elementwise addition of input1 and input2.
 Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/ADD.adoc[]
 
 *Operation Function:*
 
@@ -38,32 +30,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|signed 32|int32_t
-|MI, MT|fp16|fp16_t
-|MI, MT|bf16|bf16_t
-|MI, MT|fp32|fp32_t
-|===
-
 ==== ARITHMETIC_RIGHT_SHIFT
 
 Elementwise arithmetic right shift of input1 by the amount specified in input2.
 Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Attribute|bool_t|round|-|If true then the shift is rounded
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/ARITHMETIC_RIGHT_SHIFT.adoc[]
 
 *Operation Function:*
 
@@ -89,30 +61,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|signed 8|int8_t
-|Any|signed 16|int16_t
-|Any|signed 32|int32_t
-|===
-
 ==== BITWISE_AND
 
 Elementwise bitwise AND of input1 and input2.
 Axis of size 1 will be broadcast as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor of same type as the input tensors, with broadcast shape if necessary
-|===
+include::{generated}/operators/BITWISE_AND.adoc[]
 
 *Operation Function:*
 
@@ -128,30 +82,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|signed 8|int8_t
-|Any|signed 16|int16_t
-|Any|signed 32|int32_t
-|===
-
 ==== BITWISE_OR
 
 Elementwise bitwise OR of input1 and input2.
 Axis of size 1 will be broadcast as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/BITWISE_OR.adoc[]
 
 *Operation Function:*
 
@@ -167,30 +103,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|signed 8|int8_t
-|Any|signed 16|int16_t
-|Any|signed 32|int32_t
-|===
-
 ==== BITWISE_XOR
 
 Elementwise bitwise XOR of input1 and input2.
 Axis of size 1 will be broadcast as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/BITWISE_XOR.adoc[]
 
 *Operation Function:*
 
@@ -206,16 +124,6 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|signed 8|int8_t
-|Any|signed 16|int16_t
-|Any|signed 32|int32_t
-|===
-
 ==== INTDIV
 
 Elementwise integer divide of input1 by input2.
@@ -224,15 +132,7 @@ Expected use is for operations on non-scaled integers.
 Floating point divide should use RECIPROCAL and MUL.
 Quantized integer divide should use TABLE (for 1/x) and MUL.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/INTDIV.adoc[]
 
 *Operation Function:*
 
@@ -252,27 +152,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-|===
-|Profile|Mode|in_out_t
-
-|Any|signed 32|int32_t
-|===
-
 ==== LOGICAL_AND
 
 Elementwise logical AND of input1 and input2.
 Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/LOGICAL_AND.adoc[]
 
 *Operation Function:*
 
@@ -288,28 +173,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|Bool|bool_t
-|===
-
 ==== LOGICAL_LEFT_SHIFT
 
 Elementwise left shift of input1 and input2.
 Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/LOGICAL_LEFT_SHIFT.adoc[]
 
 *Operation Function:*
 
@@ -326,30 +195,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|signed 8|int8_t
-|Any|signed 16|int16_t
-|Any|signed 32|int32_t
-|===
-
 ==== LOGICAL_RIGHT_SHIFT
 
 Elementwise logical right shift of input1 by the amount specified in input2.
 Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/LOGICAL_RIGHT_SHIFT.adoc[]
 
 *Operation Function:*
 
@@ -366,30 +217,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|signed 8|int8_t
-|Any|signed 16|int16_t
-|Any|signed 32|int32_t
-|===
-
 ==== LOGICAL_OR
 
 Elementwise logical OR of input1 and input2.
 Axis of size 1 will be broadcast as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/LOGICAL_OR.adoc[]
 
 *Operation Function:*
 
@@ -405,28 +238,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|Bool|bool_t
-|===
-
 ==== LOGICAL_XOR
 
 Elementwise logical XOR of input1 and input2.
 Axis of size 1 will be broadcast as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor of same type as the input tensors, with broadcast shape if necessary
-|===
+include::{generated}/operators/LOGICAL_XOR.adoc[]
 
 *Operation Function:*
 
@@ -442,28 +259,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|Bool|bool_t
-|===
-
 ==== MAXIMUM
 
 Elementwise max of input1 and input2.
 Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/MAXIMUM.adoc[]
 
 *Operation Function:*
 
@@ -479,31 +280,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|signed 32|int32_t
-|MI, MT|fp16|fp16_t
-|MI, MT|bf16|bf16_t
-|MI, MT|fp32|fp32_t
-|===
-
 ==== MINIMUM
 
 Elementwise minimum of input1 and input2.
 Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/MINIMUM.adoc[]
 
 *Operation Function:*
 
@@ -519,32 +301,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|signed 32|int32_t
-|MI, MT|fp16|fp16_t
-|MI, MT|bf16|bf16_t
-|MI, MT|fp32|fp32_t
-|===
-
 ==== MUL
 
 Elementwise multiplication (Hadamard product) of input1 and input2.
 Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_t*|input1|shape1|Input tensor
-|Input|in_t*|input2|shape2|Input tensor with the same rank as input1
-|Input (MT profile) Attribute (BI/MI profiles)|uint6_t|shift|-|Result right shift (int32_t data type only)
-|Output|out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/MUL.adoc[]
 
 *Operation Function:*
 
@@ -570,32 +332,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-|===
-|Profile|Mode|in_t|out_t
-
-|Any|signed 8|int8_t|int32_t
-|Any|signed 16|int16_t|int32_t
-|Any|signed 32|int32_t|int32_t
-|MI, MT|fp16|fp16_t|fp16_t
-|MI, MT|bf16|bf16_t|bf16_t
-|MI, MT|fp32|fp32_t|fp32_t
-|===
-
 ==== POW
 
 Elementwise input1 value raised to the power of input2.
 Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor from 1 to 4 dims
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor of same type as the input tensors, with broadcast shape if necessary
-|===
+include::{generated}/operators/POW.adoc[]
 
 *Operation Function:*
 
@@ -611,30 +353,12 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|MI, MT|fp16|fp16_t
-|MI, MT|bf16|bf16_t
-|MI, MT|fp32|fp32_t
-|===
-
 ==== SUB
 
 Elementwise subtraction of input1 and input2.
 Axis of size 1 will be broadcast as necessary. Rank of input tensors must match.
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_out_t*|input1|shape1|Input tensor
-|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1
-|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary
-|===
+include::{generated}/operators/SUB.adoc[]
 
 *Operation Function:*
 
@@ -650,17 +374,6 @@ for_each(index in shape) {
 }
 ----
 
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_out_t
-
-|Any|signed 32|int32_t
-|MI, MT|fp16|fp16_t
-|MI, MT|bf16|bf16_t
-|MI, MT|fp32|fp32_t
-|===
-
 ====   TABLE
 
 Table lookup operation.
@@ -677,15 +390,7 @@ An int16_t to int16_t table lookup can be constructed in TOSA as follows:
 * Use the TABLE operator to produce a fixed point 16.7 interpolated result
 * Use RESCALE (in_t=int32_t, out_t=int16_t, scale=1<<14, shift=21) to scale the output to int16_t range (or alternate scale as required)
 
-*Arguments:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Input|in_t*|Input|shape|Input tensor
-|Input (MT profile) Attribute (BI/MI profiles)|table_t*|table|[TABLE_SIZE]|Lookup table tensor
-|Output|out_t*|output|shape|Output tensor
-|===
+include::{generated}/operators/TABLE.adoc[]
 
 *Operation Function:*
 
@@ -704,13 +409,3 @@ for_each(index in shape) {
     tensor_write<out_t>(output, shape, index, result);
 }
 ----
-
-*Supported Data Types:*
-
-|===
-|Profile|Mode|in_t|table_t|TABLE_SIZE|out_t
-
-|Any|signed 8|int8_t|int8_t|256|int8_t
-|Any|signed 16|int16_t|int16_t|513|int32_t
-|===
-