Move operator pseudocode to separate files

This makes it easier to process the pseudocode automatically.

Change-Id: I84394192598e589de07d43a7af60b96788e14f86
Signed-off-by: Kevin Petit <kevin.petit@arm.com>

87 files changed, 1888 insertions, 1158 deletions

diff --git a/Makefile b/Makefile
index c294fbb..877a8a2 100644
--- a/Makefile
+++ b/Makefile
@@ -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 2020-2024 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
@@ -17,11 +17,13 @@ XMLLINT = xmllint
 HTMLDIR=out/html
 PDFDIR=out/pdf
 GENDIR=out/gen
+PSEUDOCODEDIR := pseudocode
 
-COMMON_ARGS= -a generated="$(abspath $(GENDIR))"
+COMMON_ARGS= -a generated="$(abspath $(GENDIR))" -a pseudocode="$(abspath $(PSEUDOCODEDIR))"
 
 SPECSRC := tosa_spec.adoc
 ADOCFILES = $(wildcard chapters/[A-Za-z]*.adoc) $(wildcard $(GENDIR)/*/*.adoc)
+PSEUDOCODEFILES = $(wildcard $(PSEUDOCODEDIR)/operators/*.tosac) $(wildcard $(PSEUDOCODEDIR)/operators/tables/*.tosac)
 SPECFILES = $(ADOCFILES) tosa.css
 FIGURES = $(wildcard figures/*.svg)
 SPECXML := tosa.xml
@@ -76,11 +78,11 @@ $(GEN): $(SPECXML) $(GENSCRIPTS)
 	tools/genspec.py --xml $(SPECXML) --outdir $(GENDIR)
 	@touch $@
 
-$(HTMLDIR)/tosa_spec.html: $(SPECSRC) $(SPECFILES) $(GEN)
+$(HTMLDIR)/tosa_spec.html: $(SPECSRC) $(SPECFILES) $(GEN) $(PSEUDOCODEFILES)
 	$(MKDIR) $(HTMLDIR)
 	$(ASCIIDOC) -b html5 -a stylesheet=tosa.css $(COMMON_ARGS) -o $@ $<
 
-$(PDFDIR)/tosa_spec.pdf: $(SPECSRC) $(SPECFILES) $(GEN)
+$(PDFDIR)/tosa_spec.pdf: $(SPECSRC) $(SPECFILES) $(GEN) $(PSEUDOCODEFILES)
 	$(MKDIR) $(PDFDIR)
 	$(ASCIIDOC) -r asciidoctor-pdf -b pdf $(COMMON_ARGS) -o $@ $(SPECSRC)
 
diff --git a/chapters/activation_funcs.adoc b/chapters/activation_funcs.adoc
index 1acaf56..1be3168 100644
--- a/chapters/activation_funcs.adoc
+++ b/chapters/activation_funcs.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 2020-2021 ARM Limited
+// (C) COPYRIGHT 2020-2024 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
@@ -20,12 +20,7 @@ include::{generated}/operators/CLAMP.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(max_val < min_val);
-for_each(index in shape) {
-    in_out_t value = tensor_read<in_out_t>(input, shape, index);
-    value = apply_clip<in_out_t>(value, min_val, max_val);
-    tensor_write<in_out_t>(output, shape, index, value);
-}
+include::{pseudocode}/operators/CLAMP.tosac[lines=10..-1]
 ----
 
 ==== ERF
@@ -43,13 +38,7 @@ The ERF table has 513 entries each of 16-bit precision and covering the input ra
 
 [source,c++]
 ----
-int16_t erf_reference(int16_t x) { // input x range is -256 to + 256 inclusive
-    F64 v = (double)x / (double)64;
-    v = erf(v);
-    return round_to_nearest_int(32768.0 * v);
-}
-
-generate_lookup_table(&erf_table, &erf_reference);
+include::{pseudocode}/operators/tables/ERF.tosac[lines=10..-1]
 ----
 
 include::{generated}/operators/ERF.adoc[]
@@ -72,24 +61,14 @@ This sigmoid table has 513 entries each of 16-bit precision and covering the inp
 .Code for generating 16-bit sigmoid table
 [source,c++]
 ----
-int16_t sigmoid_reference(int16_t x) { // input x range is -256 to + 256 inclusive
-    fp64_t v = (fp64_t)x / (fp64_t)16;
-    v = 1.0/(1.0 + exp(-v));
-    return round_to_nearest_int(32768.0 * v);
-}
-
-generate_lookup_table(&sigmoid_table, &sigmoid_reference);
+include::{pseudocode}/operators/tables/SIGMOID.tosac[lines=10..-1]
 ----
 
 include::{generated}/operators/SIGMOID.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input, shape, index);
-    value = sigmoid<in_out_t>(value1);
-    tensor_write<in_out_t>(output, shape, index, value);
-}
+include::{pseudocode}/operators/SIGMOID.tosac[lines=10..-1]
 ----
 
 ==== TANH
@@ -109,23 +88,12 @@ This tanh_table has 513 entries each of 16-bit precision and covering the input
 .Calculation of an example 16-bit tanh table
 [source,c++]
 ----
-int16_t tanh_reference(int16_t x) {  // input x range is -256 to +256 inclusive
-    fp64_t v = (fp64_t)x/(fp64_t)32;
-    v = exp(-2.0*v);
-    v = (1.0-v)/(1.0+v);
-    return round_to_nearest_int(32768.0 * v);
-}
-
-generate_lookup_table(&tanh_table, &tanh_reference);
+include::{pseudocode}/operators/tables/TANH.tosac[lines=10..-1]
 ----
 
 include::{generated}/operators/TANH.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input, shape, index);
-    value = tanh<in_out_t>(value1);
-    tensor_write<in_out_t>(output, shape, index, value);
-}
+include::{pseudocode}/operators/TANH.tosac[lines=10..-1]
 ----
diff --git a/chapters/comparison.adoc b/chapters/comparison.adoc
index 4ef52d6..5535b40 100644
--- a/chapters/comparison.adoc
+++ b/chapters/comparison.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 2020-2024 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
@@ -17,19 +17,7 @@ include::{generated}/operators/EQUAL.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_t value1 = tensor_read<in_t>(input1, shape1, index1);
-    in_t value2 = tensor_read<in_t>(input2, shape2, index2);
-    out_t result;
-    if (isNaN(value1) || isNaN(value2))
-        result = False;
-    else
-        result = (value1 == value2) ? True : False;
-    tensor_write<out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/EQUAL.tosac[lines=10..-1]
 ----
 
 ==== GREATER
@@ -40,19 +28,7 @@ include::{generated}/operators/GREATER.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_t value1 = tensor_read<in_t>(input1, shape1, index1);
-    in_t value2 = tensor_read<in_t>(input2, shape2, index2);
-    out_t result;
-    if (isNaN(value1) || isNaN(value2))
-        result = False;
-    else
-        result = (value1 > value2) ? True : False;
-    tensor_write<out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/GREATER.tosac[lines=10..-1]
 ----
 
 ==== GREATER_EQUAL
@@ -63,17 +39,5 @@ include::{generated}/operators/GREATER_EQUAL.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_t value1 = tensor_read<in_t>(input1, shape1, index1);
-    in_t value2 = tensor_read<in_t>(input2, shape2, index2);
-    out_t result;
-    if (isNaN(value1) || isNaN(value2))
-        result = False;
-    else
-        result = (value1 >= value2) ? True : False;
-    tensor_write<out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/GREATER_EQUAL.tosac[lines=10..-1]
 ----
diff --git a/chapters/control_flow.adoc b/chapters/control_flow.adoc
index 9de9c72..2da2424 100644
--- a/chapters/control_flow.adoc
+++ b/chapters/control_flow.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 2020-2021 ARM Limited
+// (C) COPYRIGHT 2020-2024 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
@@ -19,20 +19,7 @@ include::{generated}/operators/COND_IF.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(tosa_nesting_depth >= MAX_NESTING);
-ERROR_IF(tensor_list_shape(input_list) != tosa_input_shape(then_graph));
-ERROR_IF(tensor_list_shape(input_list) != tosa_input_shape(else_graph));
-ERROR_IF(tensor_list_shape(output_list) != tosa_output_shape(then_graph));
-ERROR_IF(tensor_list_shape(output_list) != tosa_output_shape(else_graph));
-ERROR_IF(tensor_size(shape) != 1);
-
-tosa_nesting_depth++;
-if (condition[0]) {
-    tosa_execute_graph(then_graph, input_list, output_list);
-} else {
-    tosa_execute_graph(else_graph, input_list, output_list);
-}
-tosa_nesting_depth--;
+include::{pseudocode}/operators/COND_IF.tosac[lines=10..-1]
 ----
 
 ==== WHILE_LOOP
@@ -43,28 +30,5 @@ include::{generated}/operators/WHILE_LOOP.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(tosa_nesting_depth >= MAX_NESTING);
-ERROR_IF(tensor_list_shape(input_list) != tosa_list_shape(output_list));
-ERROR_IF(tensor_list_shape(input_list) != tosa_input_shape(cond_graph));
-ERROR_IF(tensor_list_shape(input_list) != tosa_input_shape(body_graph));
-ERROR_IF(tensor_list_shape(input_list) != tosa_output_shape(body_graph));
-// Condition graph output must be a single element tensor with a single bool value
-ERROR_IF(tensor_size(tosa_output_shape(cond_graph)) != 1);
-ERROR_IF(tosa_output_type(cond_graph) != bool_t);
-
-// The iteration number 'i' is included to give unique names to variables
-// in each iteration of the loop and is not required by implementations
-int32_t i=0;             // iteration number
-tensor_list_t list[];    // array of tensor lists indexed by iteration
-bool_t *condition[];     // array of condition tensors indexed by iteration
-list[i] = input_list;    // copy input data as list[0]
-tosa_nesting_depth++;
-tosa_execute_graph(cond_graph, list[i], [ condition[i] ]);   // initial condition
-while (condition[i][0]) {
-    tosa_execute_graph(body_graph, list[i], list[i+1]);
-    i = i+1;
-    tosa_execute_graph(cond_graph, list[i], [ condition[i] ]);
-}
-tosa_nesting_depth--;
-output_list = list[i];
+include::{pseudocode}/operators/WHILE_LOOP.tosac[lines=10..-1]
 ----
diff --git a/chapters/data_layout.adoc b/chapters/data_layout.adoc
index 2d48eb1..1ce92be 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 2020-2023 ARM Limited
+// (C) COPYRIGHT 2020-2024 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
@@ -17,30 +17,7 @@ include::{generated}/operators/CONCAT.adoc[]
 
 [source,c]
 ----
-ERROR_IF(axis < 0 || axis >= max(1,rank(shapes1[0])));
-ERROR_IF(shape[axis] != sum(shape_dim(shapes1[k], axis) for all k))
-ERROR_IF(in_out_t == shape_t && rank(shape) > 1);
-// The following checks ensure all inputs are compatible for concatenation
-for_each(input_shape in shapes1) {
-    ERROR_IF(rank(input_shape) != rank(shapes1[0]));
-    for_each(index in input_shape) {
-        ERROR_IF(index != axis && input_shape[index] != shapes1[0][index]);
-    }
-}
-for_each(index1 in shape) {
-    dim_t index2 = index1;
-    for (tensor t = 0; t < length(input1); t++) {
-        // Continue to concatenate along axis from each tensor
-        // For each output location, we are looking for the
-        // appropriate input tensor
-        if (index2[axis] >= 0 && index2[axis] < shape_dim(shapes1[t], axis)) {
-            in_out_t value = tensor_read<in_out_t>(input1[t], shapes1[t], index2);
-            tensor_write<in_out_t>(output, shape, index1, value);
-        }
-        index2[axis] = index2[axis] - shape_dim(shapes1[t], axis);
-    }
-}
-
+include::{pseudocode}/operators/CONCAT.tosac[lines=10..-1]
 ----
 
 ==== PAD
@@ -53,24 +30,7 @@ include::{generated}/operators/PAD.adoc[]
 
 [source,c++]
 ----
-// Check output shape matches the padded input shape
-ERROR_IF(rank(shape) != rank(shape1));
-for (i = 0; i < rank(shape); i++) {
-    ERROR_IF(padding[i,0] < 0 || padding[i,1] < 0);
-    ERROR_IF(shape[i] != padding[i, 0] + shape1[i] + padding[i, 1]);
-}
-for_each(index in shape) {
-    dim_t index1 = index;
-    bool_t is_pad = false;
-    for(i = 0; i < rank(shape); i++) {
-        index1[i] = index1[i] - padding[i,0];
-        if (index1[i] < 0 || index[i] >= length(shape[i])) {
-            is_pad = true;
-        }
-    }
-    in_out_t value = is_pad ? pad_const : tensor_read<in_out_t>(input1, shape1, index1);
-    tensor_write<in_out_t>(output, shape, index, value);
-}
+include::{pseudocode}/operators/PAD.tosac[lines=10..-1]
 ----
 
 ==== DIM
@@ -81,8 +41,7 @@ include::{generated}/operators/DIM.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(axis >= rank(shape));
-tensor_write<shape_t>(output, [], [], shape_dim(shape, axis));
+include::{pseudocode}/operators/DIM.tosac[lines=10..-1]
 ----
 
 ==== RESHAPE
@@ -93,18 +52,7 @@ include::{generated}/operators/RESHAPE.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(tensor_size(shape1) != tensor_size(shape));
-
-for_each(index in shape) {
-    // Calculate flattened index for the output location (index)
-    size_t offset = tensor_index_to_offset(shape, index);
-    // Now convert to the location in the input
-    dim_t tmp_index = tensor_offset_to_index(shape1, offset);
-
-    // Now read/write the value
-    in_out_t val = tensor_read<in_out_t>(input1, shape1, tmp_index);
-    tensor_write<in_out_t>(output, shape, index, val);
-}
+include::{pseudocode}/operators/RESHAPE.tosac[lines=10..-1]
 ----
 
 ==== REVERSE
@@ -115,13 +63,7 @@ include::{generated}/operators/REVERSE.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(axis < 0 || axis >= rank(shape));
-for_each(index in shape) {
-    dim_t tmp_index = index;
-    tmp_index[axis] = shape[axis] - 1 - index[axis];
-    in_out_t value = tensor_read<in_out_t>(input, shape, tmp_index);
-    tensor_write<in_out_t>(output, shape, index, value);
-}
+include::{pseudocode}/operators/REVERSE.tosac[lines=10..-1]
 ----
 
 ==== SLICE
@@ -133,25 +75,7 @@ include::{generated}/operators/SLICE.adoc[]
 
 [source,c++]
 ----
-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(shape1)) {
-    ERROR_IF(start[index] < 0);
-    ERROR_IF(size[index] <= 0); //Output must be positive size
-    ERROR_IF(start[index] + size[index] > shape1[index]);
-    ERROR_IF(shape[index] != size[index]);
-}
-
-for_each(index in shape) {
-    dim_t tmp_index = index;
-    for(i = 0; i < rank(shape); i++) {
-       tmp_index[i] = index[i] + start[i];
-    }
-    in_out_t value = tensor_read<in_out_t>(input1, shape1, tmp_index);
-    tensor_write<in_out_t>(output, shape, index, value);
-}
+include::{pseudocode}/operators/SLICE.tosac[lines=10..-1]
 ----
 
 ==== TILE
@@ -162,17 +86,7 @@ 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>(input1, shape1, tmp_index);
-    tensor_write<in_out_t>(output, shape, index, value);
-}
+include::{pseudocode}/operators/TILE.tosac[lines=10..-1]
 ----
 
 ==== TRANSPOSE
@@ -184,30 +98,5 @@ 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));
-    ERROR_IF(index < 0);
-    // Ensure ranks aren't repeated
-    ERROR_IF(indexes_used[index] == true);
-    indexes_used[index] = true;
-}
-
-// Ensure that the output shapes have the properly
-// permuted shapes
-for(i = 0; i < rank(shape); i++) {
-    ERROR_IF(shape1[perms[i]] != shape[i])
-}
-
-for_each(index in shape) {
-    dim_t tmp_index = index;
-    for(i = 0; i < rank(shape); i++) {
-        tmp_index[perms[i]] = index[i]
-    }
-    in_out_t value = tensor_read<in_out_t>(input1, shape1, tmp_index);
-    tensor_write<in_out_t>(output, shape, index, value);
-}
+include::{pseudocode}/operators/TRANSPOSE.tosac[lines=10..-1]
 ----
diff --git a/chapters/ewise_binary.adoc b/chapters/ewise_binary.adoc
index 876ab4b..3cc2ecb 100644
--- a/chapters/ewise_binary.adoc
+++ b/chapters/ewise_binary.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 2020-2023 ARM Limited
+// (C) COPYRIGHT 2020-2024 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
@@ -18,23 +18,7 @@ include::{generated}/operators/ADD.adoc[]
 
 [source,c++]
 ----
-if (in_out_t == shape_t) {
-    ERROR_IF(rank(shape) != 0 || rank(shape1) != 0 || rank(shape2) != 0);
-    shape_t value1 = tensor_read<shape_t>(input1, [], []);
-    shape_t value2 = tensor_read<shape_t>(input2, [], []);
-    shape_t result = apply_add_s<shape_t>(value1, value2);
-    tensor_write<shape_t>(output, [], [], result);
-} else {
-    ERROR_IF(shape != broadcast_shape(shape1, shape2));
-    for_each(index in shape) {
-        dim_t index1 = apply_broadcast(shape, shape1, index);
-        dim_t index2 = apply_broadcast(shape, shape2, index);
-        in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-        in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-        in_out_t result = apply_add_s<in_out_t>(value1, value2);
-        tensor_write<in_out_t>(output, shape, index, result);
-    }
-}
+include::{pseudocode}/operators/ADD.tosac[lines=10..-1]
 ----
 
 ==== ARITHMETIC_RIGHT_SHIFT
@@ -46,26 +30,7 @@ include::{generated}/operators/ARITHMETIC_RIGHT_SHIFT.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-
-    // Ensure that shift amount is appropriate for the data type
-    REQUIRE((in_out_t == i32_t && 0 <= value2 && value2 <= 31) ||
-            (in_out_t == i16_t && 0 <= value2 && value2 <= 15) ||
-            (in_out_t == i8_t && 0 <= value2 && value2 <= 7));
-
-    in_out_t result = apply_arith_rshift<in_out_t>(value1, value2);
-    if (round == true && static_cast<int32_t>(value2) > 0 &&
-        (apply_arith_rshift<in_out_t>(value1, apply_sub_s<in_out_t>(value2, 1)) & 1 != 0) {
-        result = result + 1;
-    }
-    result = apply_clip_s<in_out_t>(result, minimum_s<in_out_t>, maximum_s<in_out_t>);
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/ARITHMETIC_RIGHT_SHIFT.tosac[lines=10..-1]
 ----
 
 ==== BITWISE_AND
@@ -77,15 +42,7 @@ include::{generated}/operators/BITWISE_AND.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    in_out_t result = value1 & value2;
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/BITWISE_AND.tosac[lines=10..-1]
 ----
 
 ==== BITWISE_OR
@@ -97,15 +54,7 @@ include::{generated}/operators/BITWISE_OR.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    in_out_t result = value1 | value2;
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/BITWISE_OR.tosac[lines=10..-1]
 ----
 
 ==== BITWISE_XOR
@@ -117,15 +66,7 @@ include::{generated}/operators/BITWISE_XOR.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    in_out_t result = value1 ^ value2;
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/BITWISE_XOR.tosac[lines=10..-1]
 ----
 
 ==== INTDIV
@@ -140,28 +81,7 @@ include::{generated}/operators/INTDIV.adoc[]
 
 [source,c++]
 ----
-if (in_out_t == shape_t) {
-    ERROR_IF(rank(shape) != 0 || rank(shape1) != 0 || rank(shape2) != 0);
-    shape_t value1 = tensor_read<shape_t>(input1, [], []);
-    shape_t value2 = tensor_read<shape_t>(input2, [], []);
-    REQUIRE(value2 != 0);
-    shape_t result = value1 / value2;
-    tensor_write<shape_t>(output, [], [], result);
-} else {
-    ERROR_IF(shape != broadcast_shape(shape1, shape2));
-    for_each(index in shape) {
-        dim_t index1 = apply_broadcast(shape, shape1, index);
-        dim_t index2 = apply_broadcast(shape, shape2, index);
-        in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-        in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-        REQUIRE(value2 != 0);
-        // This catches the case where we divide minimum<in_out_t> by -1
-        // which is not representable in two's complement
-        REQUIRE(static_cast<int64_t>(value1) / static_cast<int64_t>(value2) <= maximum_s<in_out_t>);
-        in_out_t result = apply_intdiv_s<in_out_t>(value1, value2);
-        tensor_write<in_out_t>(output, shape, index, result);
-    }
-}
+include::{pseudocode}/operators/INTDIV.tosac[lines=10..-1]
 ----
 
 ==== LOGICAL_AND
@@ -173,15 +93,7 @@ include::{generated}/operators/LOGICAL_AND.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    in_out_t result = value1 && value2;
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/LOGICAL_AND.tosac[lines=10..-1]
 ----
 
 ==== LOGICAL_LEFT_SHIFT
@@ -193,16 +105,7 @@ include::{generated}/operators/LOGICAL_LEFT_SHIFT.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    REQUIRE(0 <= value2 && value2 <= 31);
-    in_out_t result = value1 << value2;
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/LOGICAL_LEFT_SHIFT.tosac[lines=10..-1]
 ----
 
 ==== LOGICAL_RIGHT_SHIFT
@@ -214,17 +117,7 @@ include::{generated}/operators/LOGICAL_RIGHT_SHIFT.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    REQUIRE(0 <= static_cast<int32_t>(value2) && static_cast<int32_t>(value2) <= 31);
-    // Logical shifts happen as unsigned types internally
-    in_out_t result = apply_logical_rshift<in_out_t>(value1, value2);
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/LOGICAL_RIGHT_SHIFT.tosac[lines=10..-1]
 ----
 
 ==== LOGICAL_OR
@@ -236,15 +129,7 @@ include::{generated}/operators/LOGICAL_OR.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    in_out_t result = value1 || value2;
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/LOGICAL_OR.tosac[lines=10..-1]
 ----
 
 ==== LOGICAL_XOR
@@ -256,15 +141,7 @@ include::{generated}/operators/LOGICAL_XOR.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    in_out_t result = value1 != value2;
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/LOGICAL_XOR.tosac[lines=10..-1]
 ----
 
 ==== MAXIMUM
@@ -276,15 +153,7 @@ include::{generated}/operators/MAXIMUM.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    in_out_t result = apply_max_s<in_out_t>(value1, value2);
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/MAXIMUM.tosac[lines=10..-1]
 ----
 
 ==== MINIMUM
@@ -296,15 +165,7 @@ include::{generated}/operators/MINIMUM.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    in_out_t result = apply_min_s(value1, value2);
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/MINIMUM.tosac[lines=10..-1]
 ----
 
 ==== MUL
@@ -316,34 +177,7 @@ include::{generated}/operators/MUL.adoc[]
 
 [source,c++]
 ----
-if (in_out_t == shape_t) {
-    ERROR_IF(rank(shape) != 0 || rank(shape1) != 0 || rank(shape2) != 0);
-    shape_t value1 = tensor_read<shape_t>(input1, [], []);
-    shape_t value2 = tensor_read<shape_t>(input2, [], []);
-    shape_t result = value1 * value2;
-    tensor_write<shape_t>(output, [], [], result);
-} else {
-    REQUIRE(0 <= shift && shift <= 63);
-    REQUIRE(in_t == int32_t || shift == 0);
-    ERROR_IF(shape != broadcast_shape(shape1, shape2));
-    for_each(index in shape) {
-        dim_t index1 = apply_broadcast(shape, shape1, index);
-        dim_t index2 = apply_broadcast(shape, shape2, index);
-        in_t value1 = tensor_read<in_t>(input1, shape1, index1);
-        in_t value2 = tensor_read<in_t>(input2, shape2, index2);
-        out_t result;
-        if (in_t == i32_t && shift > 0) {
-            int64_t product = sign_extend<int64_t>(value1) * sign_extend<int64_t>(value2);
-            int64_t round   = static_cast<int64_t>(1) << (shift - 1);
-            product = (product + round) >> shift;
-            REQUIRE(product >= minimum_s<i32_t> && product <= maximum_s<i32_t>)
-            result = product;
-        } else {
-            result = apply_mul_s(value1, value2);  // low 32-bits of result for i32_t
-        }
-        tensor_write<out_t>(output, shape, index, result);
-    }
-}
+include::{pseudocode}/operators/MUL.tosac[lines=10..-1]
 ----
 
 ==== POW
@@ -355,15 +189,7 @@ include::{generated}/operators/POW.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(shape1, shape2));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    in_out_t result = apply_pow<in_out_t>(value1, value2);
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/POW.tosac[lines=10..-1]
 ----
 
 ==== SUB
@@ -375,23 +201,7 @@ include::{generated}/operators/SUB.adoc[]
 
 [source,c++]
 ----
-if (in_out_t == shape_t) {
-    ERROR_IF(rank(shape) != 0 || rank(shape1) != 0 || rank(shape2) != 0);
-    shape_t value1 = tensor_read<shape_t>(input1, [], []);
-    shape_t value2 = tensor_read<shape_t>(input2, [], []);
-    shape_t result = apply_sub<shape_t>(value1, value2);
-    tensor_write<shape_t>(output, [], [], result);
-} else {
-    ERROR_IF(shape != broadcast_shape(shape1, shape2));
-    for_each(index in shape) {
-        dim_t index1 = apply_broadcast(shape, shape1, index);
-        dim_t index2 = apply_broadcast(shape, shape2, index);
-        in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
-        in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-        in_out_t result = apply_sub_s<in_out_t>(value1, value2);
-        tensor_write<in_out_t>(output, shape, index, result);
-    }
-}
+include::{pseudocode}/operators/SUB.tosac[lines=10..-1]
 ----
 
 ====   TABLE
@@ -414,16 +224,5 @@ include::{generated}/operators/TABLE.adoc[]
 
 [source,c++]
 ----
-REQUIRE(length(table) == TABLE_SIZE);
-for_each(index in shape) {
-    in_t value = tensor_read<in_t>(input, shape, index);
-    out_t result;
-    if (in_t == i8_t) {
-        // value is a signed int, convert to a 0 based index
-        result = table[static_cast<int16_t>(value) + 128];
-    } else {
-        result = apply_lookup_s(static_cast<int16_t>(table), static_cast<int16_t>(value));
-    }
-    tensor_write<out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/TABLE.tosac[lines=10..-1]
 ----
diff --git a/chapters/ewise_ternary.adoc b/chapters/ewise_ternary.adoc
index 57cf599..d6ea453 100644
--- a/chapters/ewise_ternary.adoc
+++ b/chapters/ewise_ternary.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 2020-2021 ARM Limited
+// (C) COPYRIGHT 2020-2024 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
@@ -17,20 +17,5 @@ include::{generated}/operators/SELECT.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(shape != broadcast_shape(broadcast_shape(shape1, shape2), shape3));
-for_each(index in shape) {
-    dim_t index1 = apply_broadcast(shape, shape1, index);
-    dim_t index2 = apply_broadcast(shape, shape2, index);
-    dim_t index3 = apply_broadcast(shape, shape3, index);
-    bool_t value1 = tensor_read<bool_t>(input1, shape1, index1);
-    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
-    in_out_t value3 = tensor_read<in_out_t>(input3, shape3, index3);
-    in_out_t result;
-    if (value1) {
-         result = value2;
-    } else {
-         result = value3;
-    }
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/SELECT.tosac[lines=10..-1]
 ----
diff --git a/chapters/ewise_unary.adoc b/chapters/ewise_unary.adoc
index d3eacc4..4b8cd4d 100644
--- a/chapters/ewise_unary.adoc
+++ b/chapters/ewise_unary.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 2020-2023 ARM Limited
+// (C) COPYRIGHT 2020-2024 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
@@ -24,16 +24,7 @@ include::{generated}/operators/ABS.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
-    if (is_floating_point(in_out_t) && value1 == -0.0) {
-        value1 = 0.0;
-    }
-    if (static_cast<int32_t>(value1) < 0.0) {
-        value1 = apply_sub_s<in_out_t>(0, value1);
-    }
-    tensor_write<in_out_t>(output, shape, index, value1);
-}
+include::{pseudocode}/operators/ABS.tosac[lines=10..-1]
 ----
 
 ==== BITWISE_NOT
@@ -44,11 +35,7 @@ include::{generated}/operators/BITWISE_NOT.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
-    in_out_t result = ~value1;
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/BITWISE_NOT.tosac[lines=10..-1]
 ----
 
 ==== CEIL
@@ -66,11 +53,7 @@ include::{generated}/operators/CEIL.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
-    in_out_t result = apply_ceil<in_out_t>(value1);
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/CEIL.tosac[lines=10..-1]
 ----
 
 ==== CLZ
@@ -81,11 +64,7 @@ include::{generated}/operators/CLZ.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
-    in_out_t result = count_leading_zeros(value1);
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/CLZ.tosac[lines=10..-1]
 ----
 
 ==== EXP
@@ -103,11 +82,7 @@ include::{generated}/operators/EXP.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
-    in_out_t result = apply_exp<in_out_t>(value1);
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/EXP.tosac[lines=10..-1]
 ----
 
 ==== FLOOR
@@ -125,11 +100,7 @@ include::{generated}/operators/FLOOR.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
-    in_out_t result = apply_floor<in_out_t>(value1);
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/FLOOR.tosac[lines=10..-1]
 ----
 
 ==== LOG
@@ -147,11 +118,7 @@ include::{generated}/operators/LOG.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
-    in_out_t result = apply_log<in_out_t>(value1);
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/LOG.tosac[lines=10..-1]
 ----
 
 ==== LOGICAL_NOT
@@ -162,11 +129,7 @@ include::{generated}/operators/LOGICAL_NOT.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index);
-    in_out_t result = !value1;
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/LOGICAL_NOT.tosac[lines=10..-1]
 ----
 
 ==== NEGATE
@@ -184,19 +147,7 @@ include::{generated}/operators/NEGATE.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(in_out_t != i8_t && input1_zp != 0) // Zero point only for int8_t
-ERROR_IF(in_out_t != i8_t && output_zp != 0) // Zero point only for int8_t
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
-    acc_t value = apply_sub_s<acc_t>(sign_extend<acc_t>(value1),
-                                     sign_extend<acc_t>(input1_zp));
-    value = apply_sub_s<acc_t>(0, value);
-    value = apply_add_s<acc_t>(value, sign_extend<acc_t>(output_zp));
-    in_out_t result = truncate<in_out_t>(apply_clip_s<acc_t>(value,
-                                                             minimum_s<in_out_t>,
-                                                             maximum_s<in_out_t>));
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/NEGATE.tosac[lines=10..-1]
 ----
 
 ==== RECIPROCAL
@@ -214,11 +165,7 @@ include::{generated}/operators/RECIPROCAL.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index);
-    in_out_t result = 1.0 / value1;
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/RECIPROCAL.tosac[lines=10..-1]
 ----
 
 ==== RSQRT
@@ -236,15 +183,5 @@ include::{generated}/operators/RSQRT.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index);
-    in_out_t result;
-    if (value1 < 0) {
-        result = NaN;
-    }
-    else {
-        result = 1.0 / apply_sqrt<in_out_t>(value1);
-    }
-    tensor_write<in_out_t>(output, shape, index, result);
-}
+include::{pseudocode}/operators/RSQRT.tosac[lines=10..-1]
 ----
diff --git a/chapters/image.adoc b/chapters/image.adoc
index 59e5ddf..1d2a212 100644
--- a/chapters/image.adoc
+++ b/chapters/image.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 2020-2023 ARM Limited
+// (C) COPYRIGHT 2020-2024 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
@@ -61,69 +61,5 @@ include::{generated}/operators/RESIZE.adoc[]
 
 [source,c++]
 ----
-// Ensure the image size is supported by GPU APIs and that for integer
-// implementations, position * stride does not overflow int32_t.
-ERROR_IF(max(OH,OW,IH,IW) >= 16384);
-ERROR_IF(scale_y_n <= 0 || scale_y_d <= 0 || scale_x_n <= 0 || scale_x_d <= 0);
-// if in_t=int8_t ensure that an int32_t accumulator can be used
-ERROR_IF(scale_y_n > (1 << 11) || scale_x_n > (1 << 11));
-// set a consistent lower limit of 1/16 downscale to simplify implementations
-ERROR_IF(scale_y_d >= 16 * scale_y_n || scale_x_d >= 16 * scale_x_n);
-ERROR_IF(offset_y < -scale_y_n || offset_y >= 16 * scale_y_n);
-ERROR_IF(offset_x < -scale_x_n || offset_x >= 16 * scale_x_n);
-ERROR_IF(border_y < -16 * scale_y_n || border_y >= scale_y_n);
-ERROR_IF(border_x < -16 * scale_x_n || border_x >= scale_x_n);
-ERROR_IF(OH != idiv_check((IH - 1) * scale_y_n - offset_y + border_y, scale_y_d) + 1);
-ERROR_IF(OW != idiv_check((IW - 1) * scale_x_n - offset_x + border_x, scale_x_d) + 1);
-for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW; 0 <= c < C) {
-    out_t acc;
-    resize_t dx, dy;
-    resize_t unit_x, unit_y;
-
-    unit_x = (is_floating_point(resize_t)) ? 1.0 : scale_x_n;
-    unit_y = (is_floating_point(resize_t)) ? 1.0 : scale_y_n;
-
-    int32_t y = oy * scale_y_d + offset_y;
-    int32_t x = ox * scale_x_d + offset_x;
-    int16_t iy = idiv_floor(y, scale_y_n);
-    int16_t ix = idiv_floor(x, scale_x_n);
-    int16_t ry = y - iy * scale_y_n;  // (y % scale_y_n)
-    int16_t rx = x - ix * scale_x_n;  // (x % scale_x_n)
-
-    if (is_floating_point(resize_t)) {
-        dy = static_cast<resize_t>(ry) / static_cast<resize_t>(scale_y_n);
-        dx = static_cast<resize_t>(rx) / static_cast<resize_t>(scale_x_n);
-    } else {
-        dy = ry;
-        dx = rx;
-    }
-    // Note that -1 <= iy < IH and -1 <= ix < IW
-    int16_t iy0 = apply_max_s(iy, 0);
-    int16_t iy1 = apply_min_s(iy + 1, IH - 1);
-    int16_t ix0 = apply_max_s(ix, 0);
-    int16_t ix1 = apply_min_s(ix + 1, IW - 1);
-    if (mode==BILINEAR) {
-        using in_s_t = make_signed(in_t); // Use signed calculations for i8/i16
-        in_s_t v00 = static_cast<in_s_t>(tensor_read<in_t>(input, [N,IH,IW,C], [n,iy0,ix0,c]));
-        in_s_t v01 = static_cast<in_s_t>(tensor_read<in_t>(input, [N,IH,IW,C], [n,iy0,ix1,c]));
-        in_s_t v10 = static_cast<in_s_t>(tensor_read<in_t>(input, [N,IH,IW,C], [n,iy1,ix0,c]));
-        in_s_t v11 = static_cast<in_s_t>(tensor_read<in_t>(input, [N,IH,IW,C], [n,iy1,ix1,c]));
-        acc  = v00 * (unit_y - dy) * (unit_x - dx);
-        acc += v01 * (unit_y - dy) * dx;
-        acc += v10 * dy * (unit_x - dx);
-        acc += v11 * dy * dx;
-        tensor_write<out_t>(output, [N,OH,OW,C], [n,oy,ox,c], acc);
-    } else if (mode==NEAREST) {
-        int32_t iy, ix;
-        if (is_floating_point(resize_t)) {
-            iy = (dy >= 0.5) ? iy1 : iy0;
-            ix = (dx >= 0.5) ? ix1 : ix0;
-        } else {
-            iy = (2 * dy >= scale_y_n) ? iy1 : iy0;
-            ix = (2 * dx >= scale_x_n) ? ix1 : ix0;
-        }
-        in_t v = tensor_read<in_t>(input, [N,IH,IW,C], [n,iy,ix,c]);
-        tensor_write<out_t>(output, [N,OH,OW,C], [n,oy,ox,c], v);
-    }
-}
+include::{pseudocode}/operators/RESIZE.tosac[lines=10..-1]
 ----
diff --git a/chapters/reduction.adoc b/chapters/reduction.adoc
index 19ff4ed..e3692de 100644
--- a/chapters/reduction.adoc
+++ b/chapters/reduction.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 2020-2023 ARM Limited
+// (C) COPYRIGHT 2020-2024 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
@@ -17,22 +17,7 @@ include::{generated}/operators/REDUCE_ALL.adoc[]
 
 [source,c]
 ----
-ERROR_IF(axis < 0  || axis >= rank(shape1));
-ERROR_IF(shape[axis] != 1);
-left_shape  = (axis > 1) ? shape[0:axis-1] : [];
-right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
-for_each(left_index in left_shape) {
-    for_each(right_index in right_shape) {
-        in_out_t acc = true;
-        for (i = 0; i < shape1[axis]; i++) {
-            index = flatten(left_index, [i], right_index);
-            in_out_t value = tensor_read<in_out_t>(input, shape1, index);
-            acc = acc && value;
-        }
-        out_index = flatten(left_index, [0], right_index);
-        tensor_write<in_out_t>(output, shape, out_index, acc);
-    }
-}
+include::{pseudocode}/operators/REDUCE_ALL.tosac[lines=10..-1]
 ----
 
 ==== REDUCE_ANY
@@ -43,22 +28,7 @@ include::{generated}/operators/REDUCE_ANY.adoc[]
 
 [source,c]
 ----
-ERROR_IF(axis < 0  || axis >= rank(shape1));
-ERROR_IF(shape[axis] != 1);
-left_shape  = (axis > 1) ? shape[0:axis-1] : [];
-right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
-for_each(left_index in left_shape) {
-    for_each(right_index in right_shape) {
-        in_out_t acc = false;
-        for (i = 0; i < shape1[axis]; i++) {
-            index = flatten(left_index, [i], right_index);
-            in_out_t value = tensor_read<in_out_t>(input, shape1, index);
-            acc = acc || value;
-        }
-        out_index = flatten(left_index, [0], right_index);
-        tensor_write<in_out_t>(output, shape, out_index, acc);
-    }
-}
+include::{pseudocode}/operators/REDUCE_ANY.tosac[lines=10..-1]
 ----
 
 ==== REDUCE_MAX
@@ -69,22 +39,7 @@ include::{generated}/operators/REDUCE_MAX.adoc[]
 
 [source,c]
 ----
-ERROR_IF(axis < 0  || axis >= rank(shape1));
-ERROR_IF(shape[axis] != 1);
-left_shape  = (axis > 1) ? shape[0:axis-1] : [];
-right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
-for_each(left_index in left_shape) {
-    for_each(right_index in right_shape) {
-        in_out_t acc = minimum<in_out_t>;
-        for (i = 0; i < shape1[axis]; i++) {
-            index = flatten(left_index, [i], right_index);
-            in_out_t value = tensor_read<in_out_t>(input, shape1, index);
-            acc = apply_max_s<in_out_t>(acc, value);
-        }
-        out_index = flatten(left_index, [0], right_index);
-        tensor_write<in_out_t>(output, shape, out_index, acc);
-    }
-}
+include::{pseudocode}/operators/REDUCE_MAX.tosac[lines=10..-1]
 ----
 
 ==== REDUCE_MIN
@@ -95,22 +50,7 @@ include::{generated}/operators/REDUCE_MIN.adoc[]
 
 [source,c]
 ----
-ERROR_IF(axis < 0  || axis >= rank(shape1));
-ERROR_IF(shape[axis] != 1);
-left_shape  = (axis > 1) ? shape[0:axis-1] : [];
-right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
-for_each(left_index in left_shape) {
-    for_each(right_index in right_shape) {
-        in_out_t acc = maximum<in_out_t>;
-        for (i = 0; i < shape1[axis]; i++) {
-            index = flatten(left_index, [i], right_index);
-            in_out_t value = tensor_read<in_out_t>(input, shape1, index);
-            acc = apply_min_s<in_out_t>(acc, value);
-        }
-        out_index = flatten(left_index, [0], right_index);
-        tensor_write<in_out_t>(output, shape, out_index, out);
-    }
-}
+include::{pseudocode}/operators/REDUCE_MIN.tosac[lines=10..-1]
 ----
 
 ==== REDUCE_PRODUCT
@@ -121,22 +61,7 @@ include::{generated}/operators/REDUCE_PRODUCT.adoc[]
 
 [source,c]
 ----
-ERROR_IF(axis < 0  || axis >= rank(shape1));
-ERROR_IF(shape[axis] != 1);
-left_shape  = (axis > 1) ? shape[0:axis-1] : [];
-right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
-for_each(left_index in left_shape) {
-    for_each(right_index in right_shape) {
-        in_out_t acc = 1.0;
-        for (i = 0; i < shape1[axis]; i++) {
-            index = flatten(left_index, [i], right_index);
-            in_out_t value = tensor_read<in_out_t>(input, shape1, index);
-            acc = apply_mul_s<in_out_t>(acc, value);
-        }
-        out_index = flatten(left_index, [0], right_index);
-        tensor_write<in_out_t>(output, shape, out_index, acc);
-    }
-}
+include::{pseudocode}/operators/REDUCE_PRODUCT.tosac[lines=10..-1]
 ----
 
 ==== REDUCE_SUM
@@ -147,21 +72,5 @@ include::{generated}/operators/REDUCE_SUM.adoc[]
 
 [source,c]
 ----
-ERROR_IF(axis < 0  || axis >= rank(shape1));
-ERROR_IF(shape[axis] != 1);
-left_shape  = (axis > 1) ? shape[0:axis-1] : [];
-right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
-for_each(left_index in left_shape) {
-    for_each(right_index in right_shape) {
-        acc_t acc = 0;
-        for (i = 0; i < shape1[axis]; i++) {
-            index = flatten(left_index, [i], right_index);
-            acc_t value = tensor_read<in_out_t>(input, shape1, index);
-            acc = apply_add_s<acc_t>(acc, value);
-        }
-        out_index = flatten(left_index, [0], right_index);
-        in_out_t result = static_cast<in_out_t>(acc);
-        tensor_write<in_out_t>(output, shape, out_index, result);
-    }
-}
+include::{pseudocode}/operators/REDUCE_SUM.tosac[lines=10..-1]
 ----
diff --git a/chapters/scatter_gather.adoc b/chapters/scatter_gather.adoc
index d694d39..4632e3a 100644
--- a/chapters/scatter_gather.adoc
+++ b/chapters/scatter_gather.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 2020-2021 ARM Limited
+// (C) COPYRIGHT 2020-2024 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
@@ -18,12 +18,7 @@ include::{generated}/operators/GATHER.adoc[]
 
 [source,c++]
 ----
-for_each(0 <= n < N, 0 <= w < W, 0 <= c < C) {
-    index_t k = tensor_read<index_t>(indices, [N,W], [n,w]);
-    REQUIRE(0 <= k && k < K);
-    in_out_t value = tensor_read<in_out_t>(values, [N,K,C], [n,k,c]);
-    tensor_write<in_out_t>(output, [N,W,C], [n,w,c], value);
-}
+include::{pseudocode}/operators/GATHER.tosac[lines=10..-1]
 ----
 
 ==== SCATTER
@@ -38,26 +33,5 @@ include::{generated}/operators/SCATTER.adoc[]
 
 [source,c++]
 ----
-
-// The following array is used to check compliance that an output position
-// is modified at most once.
-bool_t output_modified[N,K,C];
-
-// Copy the values_in tensor to the values_out tensor.
-// Values not written by the scatter operation are unchanged in the output.
-for_each(0 <= n < N, 0 <= k < K, 0 <= c < C) {
-    in_out_t value = tensor_read<in_out_t>(values_in, [N,K,C], [n,k,c]);
-    tensor_write<in_out_t>(values_out, [N,K,C], [n, k, c], value);
-    output_modified[n,k,c]=false;
-}
-
-// Now perform the SCATTER operation, modifying the positions from the indices tensor
-for_each(0 <= n < N, 0 <= w < W, 0 <= c < C) {
-    index_t k = tensor_read<index_t>(indices, [N,W], [n,w]);
-    REQUIRE(0 <= k && k < K);
-    REQUIRE(output_modified[n,k,c] == false);
-    in_out_t value = tensor_read<in_out_t>(input, [N,W,C], [n,w,c]);
-    tensor_write<in_out_t>(values_out, [N,K,C], [n, k, c], value);
-    output_modified[n,k,c] = true;
-}
+include::{pseudocode}/operators/SCATTER.tosac[lines=10..-1]
 ----
diff --git a/chapters/tensor_ops.adoc b/chapters/tensor_ops.adoc
index b3de433..3de5150 100644
--- a/chapters/tensor_ops.adoc
+++ b/chapters/tensor_ops.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 2020-2023 ARM Limited
+// (C) COPYRIGHT 2020-2024 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
@@ -17,34 +17,7 @@ include::{generated}/operators/ARGMAX.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(axis < 0 || axis >= rank(shape1));
-if (axis == 0) {
-    left_shape = [];
-} else {
-    left_shape = shape1[0:axis - 1];
-}
-if (axis == rank(shape1)-1) {
-    right_shape = [];
-} else {
-    right_shape = shape1[axis+1:rank(shape1) - 1];
-}
-ERROR_IF(flatten(left_shape, right_shape) != shape);
-for_each(left_index in left_shape) {
-    for_each(right_index in right_shape) {
-        in_t max_value = minimum_s<in_t>;
-        out_t max_index = 0;
-        for (i = 0; i < shape[axis]; i++) {
-            dim_t index = flatten(left_index, [i], right_index);
-            in_t value = tensor_read<in_t>(input, shape1, index);
-            if (apply_max_s<in_t>(value, max_value) != max_value) {
-                max_value = value;
-                max_index = i;
-            }
-        }
-        dim_t index = flatten(left_index, right_index);
-        tensor_write<out_t>(output, shape, index, max_index);
-    }
-}
+include::{pseudocode}/operators/ARGMAX.tosac[lines=10..-1]
 ----
 
 ==== AVG_POOL2D
@@ -57,47 +30,7 @@ include::{generated}/operators/AVG_POOL2D.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(in_out_t != i8_t && input_zp != 0); // Zero point only for int8_t
-ERROR_IF(in_out_t != i8_t && output_zp != 0); // Zero point only for int8_t
-ERROR_IF(kernel_y < 1 || kernel_x < 1); // kernel size must be >= 1
-ERROR_IF(stride_y < 1 || stride_x < 1);
-ERROR_IF(pad_top < 0 || pad_bottom < 0 || pad_left < 0 || pad_right < 0);
-// Padding must be less than kernel size to avoid
-// a divide-by-zero.
-ERROR_IF(pad_right >= kernel_x || pad_left >= kernel_x);
-ERROR_IF(pad_top >= kernel_y || pad_bottom >= kernel_y);
-ERROR_IF(OH != idiv_check(IH + pad_top + pad_bottom - kernel_y, stride_y) + 1);
-ERROR_IF(OW != idiv_check(IW + pad_left + pad_right - kernel_x, stride_x) + 1);
-
-for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW, 0 <= c < C ) {
-    in_out_t output_val;
-    acc_t acc = 0;
-    int count = 0;
-    index_t iy = oy * stride_y - pad_top;
-    index_t ix = ox * stride_x - pad_left;
-    for_each(0 <= ky < kernel_y, 0 <= kx < kernel_x) {
-        index_t y = iy + ky;
-        index_t x = ix + kx;
-        // Only values from the input tensor are used to calculate the
-        // average, padding does not count
-        if (0 <= y < IH and 0 <= x < IW) {
-            count++;
-            acc_t value = sign_extend<acc_t>(tensor_read<in_out_t>(input, [N,IH,IW,C], [n,y,x,c]));
-            value = apply_sub_s<acc_t>(value, sign_extend<acc_t>(input_zp));
-            acc = apply_add_s<acc_t>(acc, value);
-        }
-    }
-    if (is_float(in_out_t)) {
-        output_val = acc / static_cast<in_out_t>(count);
-    } else {
-        scale_t scale = reciprocal_scale(count);
-        acc = apply_scale_32(acc, scale.multiplier, scale.shift, false);
-        acc = apply_add_s<acc_t>(acc, sign_extend<acc_t>(output_zp));
-        acc = apply_clip_s<acc_t>(acc, minimum_s<in_out_t>, maximum_s<in_out_t>);
-        output_val = static_cast<in_out_t>(acc);
-    }
-    tensor_write<in_out_t>(output, [N,OH,OW,C], [n,oy,ox,c], output_val);
-}
+include::{pseudocode}/operators/AVG_POOL2D.tosac[lines=10..-1]
 ----
 
 ==== CONV2D
@@ -108,37 +41,7 @@ include::{generated}/operators/CONV2D.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(in_t != i8_t && input_zp != 0); // Zero point only for int8_t
-ERROR_IF(weight_t != int8_t && weight_zp != 0);
-ERROR_IF(pad_top < 0 || pad_bottom < 0 || pad_left < 0 || pad_right < 0);
-ERROR_IF(stride_y < 1 || stride_x < 1);
-ERROR_IF(dilation_y < 1 || dilation_x < 1);
-ERROR_IF(OH != idiv_check(IH - 1 + pad_top + pad_bottom - (KH - 1) * dilation_y, stride_y) + 1);
-ERROR_IF(OW != idiv_check(IW - 1 + pad_left + pad_right - (KW - 1) * dilation_x, stride_x) + 1);
-ERROR_IF(BC != OC && BC != 1);
-
-for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW; 0 <= oc < OC) {
-    out_t acc = 0;
-    index_t iy = oy * stride_y - pad_top;
-    index_t ix = ox * stride_x - pad_left;
-    for_each(0 <= ky < KH, 0 <= kx < KW, 0 <= ic < IC) {
-        index_t y = iy + ky * dilation_y;
-        index_t x = ix + kx * dilation_x;
-        if (0 <= y < IH && 0 <= x < IW) {
-            out_t value  = static_cast<out_t>(tensor_read<in_t>(input,
-                                                                [N,IH,IW,IC],
-                                                                [n,y,x,ic]));
-            out_t weight = static_cast<out_t>(tensor_read<weight_t>(weight,
-                                                                   [OC,KH,KW,IC],
-                                                                   [oc,ky,kx,ic]));
-            value  = apply_sub_s<out_t>(value, static_cast<out_t>(input_zp));
-            weight = apply_sub_s<out_t>(weight, static_cast<out_t>(weight_zp));
-            acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value, weight));
-        }
-    }
-    acc = apply_add_s<out_t>(acc, bias[(BC == 1) ? 0 : oc]);
-    tensor_write<out_t>(output, [N,OH,OW,OC], [n,oy,ox,oc], acc);
-}
+include::{pseudocode}/operators/CONV2D.tosac[lines=10..-1]
 ----
 
 ==== CONV3D
@@ -149,40 +52,7 @@ include::{generated}/operators/CONV3D.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(in_t != i8_t && input_zp != 0); // Zero point only for int8_t
-ERROR_IF(weight_t != i8_t && weight_zp != 0);
-ERROR_IF(pad_d0 < 0 || pad_d1 < 0 || pad_top < 0 || pad_bottom < 0 || pad_left < 0 || pad_right < 0);
-ERROR_IF(stride_d < 1 || stride_y < 1 || stride_x < 1);
-ERROR_IF(dilation_d < 1 || dilation_y < 1 || dilation_x < 1);
-ERROR_IF(OD != idiv_check(ID - 1 + pad_d0 + pad_d1      - (KD - 1) * dilation_d, stride_d) + 1);
-ERROR_IF(OH != idiv_check(IH - 1 + pad_top + pad_bottom - (KH - 1) * dilation_y, stride_y) + 1);
-ERROR_IF(OW != idiv_check(IW - 1 + pad_left + pad_right - (KW - 1) * dilation_x, stride_x) + 1);
-ERROR_IF(BC != OC && BC != 1);
-
-for_each(0 <= n < N, 0 <= od < OD, 0 <= oy < OH, 0 <= ox < OW; 0 <= oc < OC) {
-    out_t acc = 0;
-    index_t id = od * stride_d - pad_d0;
-    index_t iy = oy * stride_y - pad_top;
-    index_t ix = ox * stride_x - pad_left;
-    for_each(0 <= kd < KD, 0 <= ky < KH, 0 <= kx < KW, 0 <= ic < IC) {
-        index_t d = id + kd * dilation_d;
-        index_t y = iy + ky * dilation_y;
-        index_t x = ix + kx * dilation_x;
-        if (0 <= x < IW && 0 <= y < IH && 0 <= d < ID) {
-            out_t value  = static_cast<out_t>(tensor_read<in_t>(input,
-                                                                [N,ID,IH,IW,IC],
-                                                                [n,d,y,x,ic]));
-            out_t weight = static_cast<out_t>(tensor_read<weight_t>(weight,
-                                                                    [OC,KD,KH,KW,IC],
-                                                                    [oc,kd,ky,kx,ic]));
-            value  = apply_sub_s<out_t>(value, static_cast<out_t>(input_zp));
-            weight = apply_sub_s<out_t>(weight, static_cast<out_t>(weight_zp));
-            acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value, weight));
-        }
-    }
-    acc = apply_add_s<out_t>(acc, bias[(BC == 1) ? 0 : oc]);
-    tensor_write<out_t>(output, [N,OD,OH,OW,OC], [n,od,oy,ox,oc], acc);
-}
+include::{pseudocode}/operators/CONV3D.tosac[lines=10..-1]
 ----
 
 ==== DEPTHWISE_CONV2D
@@ -193,37 +63,7 @@ include::{generated}/operators/DEPTHWISE_CONV2D.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(in_t != i8_t && input_zp != 0); // Zero point only for int8_t
-ERROR_IF(weight_t != i8_t && weight_zp != 0);
-ERROR_IF(pad_top < 0 || pad_bottom < 0 || pad_left < 0 || pad_right < 0);
-ERROR_IF(stride_y < 1 || stride_x < 1);
-ERROR_IF(dilation_y < 1 || dilation_x < 1);
-ERROR_IF(OH != idiv_check(IH - 1 + pad_top + pad_bottom - (KH - 1) * dilation_y, stride_y) + 1);
-ERROR_IF(OW != idiv_check(IW - 1 + pad_left + pad_right - (KW - 1) * dilation_x, stride_x) + 1);
-ERROR_IF(BC != C*M && BC != 1);
-
-for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW; 0 <= c < C, 0 <= m < M) {
-    out_t acc = 0;
-    index_t iy = oy * stride_y - pad_top;
-    index_t ix = ox * stride_x - pad_left;
-    for_each(0 <= ky < KH, 0 <= kx < KW) {
-        index_t y = iy + ky * dilation_y;
-        index_t x = ix + kx * dilation_x;
-        if (0 <= y < IH && 0 <= x < IW) {
-            out_t value  = static_cast<out_t>(tensor_read<in_t>(input,
-                                                                [N,IH,IW,C],
-                                                                [n,y,x,c]));
-            out_t weight = static_cast<out_t>(tensor_read<weight_t>(weight,
-                                                                    [KH,KW,C,M],
-                                                                    [ky,kx,c,m]));
-            value  = apply_sub_s<out_t>(value, static_cast<out_t>input_zp);
-            weight = apply_sub_s<out_t>(weight, static_cast<out_t>weight_zp);
-            acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value, weight));
-        }
-    }
-    acc = apply_add_s<out_t>(acc, bias[(BC == 1) ? 0 : (c * M) + m]);
-    tensor_write<out_t>(output, [N,OH,OW,C * M], [n,oy,ox,c * M + m], acc);
-}
+include::{pseudocode}/operators/DEPTHWISE_CONV2D.tosac[lines=10..-1]
 ----
 
 ==== FFT2D
@@ -247,28 +87,7 @@ include::{generated}/operators/FFT2D.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(!power_of_two(H));
-ERROR_IF(!power_of_two(W));
-
-float sign_val = 1.0;
-
-if (inverse) {
-    sign_val = -1.0;
-}
-
-for_each(0 <= n < N, 0 <= oy < H, 0 <= ox < W) {
-    in_out_t sum_real = 0.0;
-    in_out_t sum_imag = 0.0;
-    for_each(0 <= iy < H, 0 <= ix < W) {
-        in_out_t val_real = tensor_read<in_out_t>(input_real, [N,H,W], [n,iy,ix]);
-        in_out_t val_imag = tensor_read<in_out_t>(input_imag, [N,H,W], [n,iy,ix]);
-        float_t a = sign_val * 2 * pi() * ((iy * oy) / H + (ix * ox) / W);
-        sum_real += val_real * cos(a) + val_imag * sin(a);
-        sum_imag += -val_real * sin(a) + val_imag * cos(a);
-    }
-    tensor_write<in_out_t>(output_real, [N,H,W], [n,oy,ox], sum_real);
-    tensor_write<in_out_t>(output_imag, [N,H,W], [n,oy,ox], sum_imag);
-}
+include::{pseudocode}/operators/FFT2D.tosac[lines=10..-1]
 ----
 
 ==== FULLY_CONNECTED
@@ -279,22 +98,7 @@ include::{generated}/operators/FULLY_CONNECTED.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(in_t != i8_t && input_zp != 0); // Zero point only for int8_t
-ERROR_IF(weight_t != i8_t && weight_zp != 0);
-ERROR_IF(BC != OC && BC != 1);
-
-for_each(0 <= n < N, 0 <= oc < OC) {
-    out_t acc = 0;
-    for_each(0 <= ic < IC) {
-        out_t value  = static_cast<out_t>(tensor_read<in_t>(input, [N,IC], [n,ic]));
-        out_t weight = static_cast<out_t>(tensor_read<weight_t>(weight, [OC,IC], [oc,ic]));
-        value  = apply_sub_s<out_t>(value, static_cast<out_t>(input_zp));
-        weight = apply_sub_s<out_t>(weight, static_cast<out_t>(weight_zp));
-        acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value, weight));
-    }
-    acc = apply_add_s<out_t>(acc, bias[(BC == 1) ? 0 : oc]);
-    tensor_write<out_t>(output, [N,OC], [n,oc], acc);
-}
+include::{pseudocode}/operators/FULLY_CONNECTED.tosac[lines=10..-1]
 ----
 
 ==== MATMUL
@@ -305,18 +109,7 @@ include::{generated}/operators/MATMUL.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(in_t != i8_t && (A_zp != 0 || B_zp != 0)); // Zero point only for int8_t
-for_each(0 <= n < N, 0 <= h < H, 0 <= w < W) {
-    out_t acc = 0;
-    for_each(0 <= c < C) {
-        out_t value1 = static_cast<out_t>(tensor_read<in_t>(A, [N,H,C], [n,h,c]));
-        out_t value2 = static_cast<out_t>(tensor_read<in_t>(B, [N,C,W], [n,c,w]));
-        value1 = apply_sub_s<out_t>(value1, static_cast<out_t>(A_zp));
-        value2 = apply_sub_s<out_t>(value2, static_cast<out_t>(B_zp));
-        acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value1 * value2));
-    }
-    tensor_write<out_t>(output, [N,H,W], [n,h,w], acc);
-}
+include::{pseudocode}/operators/MATMUL.tosac[lines=10..-1]
 ----
 
 ==== MAX_POOL2D
@@ -327,30 +120,7 @@ include::{generated}/operators/MAX_POOL2D.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(kernel_y < 1 || kernel_x < 1); // kernel size must be >= 1
-ERROR_IF(stride_y < 1 || stride_x < 1);
-ERROR_IF(pad_top < 0 || pad_bottom < 0 || pad_left < 0 || pad_right < 0);
-// Padding must be less than kernel size, otherwise no
-// input values will be used.
-ERROR_IF(pad_right >= kernel_x || pad_left >= kernel_x);
-ERROR_IF(pad_top >= kernel_y || pad_bottom >= kernel_y);
-ERROR_IF(OH != idiv_check(IH + pad_top + pad_bottom - kernel_y, stride_y) + 1);
-ERROR_IF(OW != idiv_check(IW + pad_left + pad_right - kernel_x, stride_x) + 1);
-
-for_each(0 <= n < N, 0 <= oy < H, 0 <= ox < W, 0 <= c < C ) {
-    in_out_t acc = minimum_value<in_out_t>;
-    index_t iy = oy * stride_y - pad_top;
-    index_t ix = ox * stride_x - pad_left;
-    for_each( 0 <= ky < kernel_y, 0 <= kx < kernel_x ) {
-        index_t y = iy + ky;
-        index_t x = ix + kx;
-        if (y >= 0 && y < IH && x >= 0 && x < IW) {
-            in_out_t value = tensor_read<in_out_t>(input, [N,IH,IW,C], [n,y,x,c]);
-            acc = apply_max_s<in_out_t>(acc, value);
-        }
-    }
-    tensor_write<in_out_t>(output, [N,OH,OW,C], [n,oy,ox,c], acc);
-}
+include::{pseudocode}/operators/MAX_POOL2D.tosac[lines=10..-1]
 ----
 
 ==== RFFT2D
@@ -368,21 +138,7 @@ include::{generated}/operators/RFFT2D.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(!power_of_two(H));
-ERROR_IF(!power_of_two(W));
-
-for_each(0 <= n < N, 0 <= oy < H, 0 <= ox < W/2 + 1) {
-    in_out_t sum_real = 0.0;
-    in_out_t sum_imag = 0.0;
-    for_each(0 <= iy < H, 0 <= ix < W) {
-        in_out_t val_real = tensor_read<in_out_t>(input_real, [N,H,W], [n,iy,ix]);
-        float_t a = 2 * pi() * ((iy * oy) / H + (ix * ox) / W);
-        sum_real += val_real * cos(a);
-        sum_imag += -val_real * sin(a);
-    }
-    tensor_write<in_out_t>(output_real, [N,H,W], [n,oy,ox], sum_real);
-    tensor_write<in_out_t>(output_imag, [N,H,W], [n,oy,ox], sum_imag);
-}
+include::{pseudocode}/operators/RFFT2D.tosac[lines=10..-1]
 ----
 
 ==== TRANSPOSE_CONV2D
@@ -393,30 +149,5 @@ include::{generated}/operators/TRANSPOSE_CONV2D.adoc[]
 
 [source,c++]
 ----
-ERROR_IF(in_t != i8_t  && input_zp != 0); // Zero point only allowed for int8_t
-ERROR_IF(weight_t != i8_t && weight_zp != 0);
-ERROR_IF(out_pad_top <= -KH || out_pad_bottom <= -KH);
-ERROR_IF(out_pad_left <= -KW || out_pad_right <= -KW);
-ERROR_IF(stride_y < 1 || stride_x < 1);
-ERROR_IF(OH != (IH - 1) * stride_y + out_pad_top + out_pad_bottom + KH);
-ERROR_IF(OW != (IW - 1) * stride_x + out_pad_left + out_pad_right + KW);
-ERROR_IF(BC != OC && BC != 1);
-
-for_each(index in [N, OH, OW, OC]) {
-    tensor_write<out_t>(output, [N,OH,OW,OC], index, bias[(BC == 1) ? 0 : index[3]])
-}
-for_each(0 <= n < N, 0 <= iy < IH, 0 <= ix < IW, 0 <= oc < OC,
-          0 <= ic < IC, 0 <= ky < KH,  0 <= kx < KW) {
-    index_t oy = iy * stride_y + out_pad_top + ky;
-    index_t ox = ix * stride_x + out_pad_left + kx;
-    if (oy >= 0 && oy < OH && ox >= 0 && ox < OW) {
-        out_t acc = static_cast<out_t>(tensor_read<out_t>(output, [N,OH,OW,OC], [n,oy,ox,oc]));
-        out_t value = static_cast<out_t>(tensor_read<in_t>(input, [N,IH,IW,IC], [n,iy,ix,ic]));
-        out_t weight = static_cast<out_t>(tensor_read<weight_t>(weight, [OC,KH,KW,IC], [oc,ky,kx,ic]));
-        value = apply_sub_s<out_t>(value, static_cast<out_t>(input_zp));
-        weight = apply_sub_s<out_t>(weight, static_cast<out_t>(weight_zp));
-        acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value, weight));
-        tensor_write<out_t>(output, [N,OH,OW,OC], [n,oy,ox,oc], acc);
-    }
-}
+include::{pseudocode}/operators/TRANSPOSE_CONV2D.tosac[lines=10..-1]
 ----
diff --git a/chapters/type_conversion.adoc b/chapters/type_conversion.adoc
index 90aca2d..71be3ac 100644
--- a/chapters/type_conversion.adoc
+++ b/chapters/type_conversion.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 2020-2023 ARM Limited
+// (C) COPYRIGHT 2020-2024 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
@@ -17,24 +17,7 @@ include::{generated}/operators/CAST.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    in_t in = tensor_read<in_t>(input, shape, index);
-    out_t out;
-    if (out_t == bool_t) {
-        out = (in != 0) ? true : false;
-    } else if (in_t == bool_t) {
-        out = (in) ? 1 : 0;
-    } else if (out_t == fp16_t || out_t == bf16_t || out_t == fp32_t) {
-        out = round_to_nearest_float(in);
-    } else if (in_t == fp16_t || in_t == bf16_t || in_t == fp32_t) {
-        out = apply_clip<out_t>(round_to_nearest_int(in), minimum<out_t>, maximum<out_t>);
-    } else if (sizeof(out_t) >= sizeof(in_t)) {
-        out = sign_extend<out_t>(in);
-    } else {
-        out = truncate(in);
-    }
-    tensor_write<out_t>(output, shape, index, out)
-}
+include::{pseudocode}/operators/CAST.tosac[lines=10..-1]
 ----
 
 ==== RESCALE
@@ -45,53 +28,5 @@ include::{generated}/operators/RESCALE.adoc[]
 
 [source,c++]
 ----
-for_each(index in shape) {
-    // uint16 values can have zero_point 0 or 32768
-    // int8/uint8 can have zero point within their valid range
-    // No other types can have zero point != 0
-    ERROR_IF(in_t != i8_t &&
-             (in_t != i16_t || input_unsigned == False) && input_zp != 0);
-    ERROR_IF(out_t != i8_t &&
-             (out_t != i16_t || output_unsigned == False) && output_zp != 0);
-    ERROR_IF(in_t == i16_t && input_unsigned == True && input_zp != 0 && input_zp != 32768);
-    ERROR_IF(out_t == i16_t && output_unsigned == True && output_zp != 0 && output_zp != 32768);
-    ERROR_IF(scale32 && in_t == i48_t);
-    ERROR_IF(!scale32 && double_round);
-    ERROR_IF(in_t == i16_t && out_t == i32_t && input_unsigned);
-    ERROR_IF(in_t == i32_t && out_t == i16_t && output_unsigned);
-
-    in_t in_value = tensor_read<in_t>(input, shape, index);
-
-    int48_t value, extended_in_zp;
-    if (input_unsigned) {
-        value = zero_extend<int48_t>(in_value);
-        extended_in_zp = zero_extend<int48_t>(input_zp);
-    }
-    else {
-        value = sign_extend<int48_t>(value);
-        extended_in_zp = sign_extend<int48_t>(input_zp);
-    }
-
-    value = value - extended_in_zp;
-    int c = (per_channel) ? index[rank(input) - 1] : 0;
-    int32_t result = (scale32) ?
-        apply_scale_32(value, multiplier[c], shift[c], double_round) :
-        apply_scale_16(value, multiplier[c], shift[c]);
-
-    if (output_unsigned) {
-        int32_t extended_out_zp = zero_extend<int32_t>(output_zp);
-        result = apply_add_s<int32_t>(result, extended_out_zp);
-        out_t out = static_cast<out_t>(apply_clip<int32_t>(result,
-                                                           minimum_u<out_t>,
-                                                           maximum_u<out_t>));
-    }
-    else {
-        int32_t extended_out_zp = sign_extend<int32_t>(output_zp);
-        result = apply_add_s<int32_t>(result, extended_out_zp);
-        out_t out = static_cast<out_t>(apply_clip<int32_t>(result,
-                                                           minimum_s<out_t>,
-                                                           maximum_s<out_t>));
-    }
-    tensor_write<out_t>(output, shape, index, out);
-}
+include::{pseudocode}/operators/RESCALE.tosac[lines=10..-1]
 ----
diff --git a/chapters/variable.adoc b/chapters/variable.adoc
index 1f7da51..8522f5e 100644
--- a/chapters/variable.adoc
+++ b/chapters/variable.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 2023 ARM Limited
+// (C) COPYRIGHT 2023-2024 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
@@ -21,31 +21,7 @@ include::{generated}/operators/VARIABLE.adoc[]
 
 [source,c++]
 ----
-
-tensor_t var_tensor = variable_tensor_lookup(uid);
-
-// Invocation for the first time
-if (var_tensor == NULL) {
-  // Allocate the persistent mutable memory for the variable tensor
-  tensor_t var_tensor = variable_tensor_allocate<var_t>(var_shape, uid);
-
-  if (initial_value != NULL) {
-    REQUIRE(var_t == in_t);
-    REQUIRE(var_shape == shape);
-    for_each (index in shape) {
-      // Copy data from initial_value to var_tensor
-      in_t value = tensor_read<in_t>(initial_value, shape, index);
-      tensor_write<in_t>(var_tensor.data, var_shape, index, value);
-    }
-    var_tensor.is_written = true;
-  }
-} else { // Variable tensor has already been declared
-  // It's invalid to declare the second variable with the same uid in a single graph execution,
-  REQUIRE(!var_tensor.seen);
-}
-
-var_tensor.seen = true;
-
+include::{pseudocode}/operators/VARIABLE.tosac[lines=10..-1]
 ----
 
 ==== VARIABLE_WRITE
@@ -56,26 +32,7 @@ include::{generated}/operators/VARIABLE_WRITE.adoc[]
 
 [source,c++]
 ----
-
-tensor_t. variable_tensor = variable_tensor_lookup(uid);
-// Check this variable tensor has been declared
-REQUIRE(variable_tensor);
-// The tensor has to be seen before to be written to
-// The seen variable is cleared before each graph execution and set in declaration
-REQUIRE(variable_tensor.seen);
-//  Input tensor's shape and variable_tensor's shape have to match
-REQUIRE(variable_tensor.shape == shape);
-//  Input tensor's shape and variable_tensor's type have to match
-REQUIRE(variable_tensor.type == in_t);
-
-for_each (index in shape) {
-    // Write data from the input to the pseudo-buffer resource
-    in_t value = tensor_read<in_t>(input1, shape, index);
-    tensor_write<tensor_t>(variable_tensor.data, variable_tensor.shape, index, value);
-}
-
-variable_tensor.is_written = true;
-
+include::{pseudocode}/operators/VARIABLE_WRITE.tosac[lines=10..-1]
 ----
 
 ==== VARIABLE_READ
@@ -86,21 +43,5 @@ include::{generated}/operators/VARIABLE_READ.adoc[]
 
 [source,c++]
 ----
-
-tensor_t variable_tensor = variable_tensor_lookup(uid);
-// Check this variable tensor has been decalred
-REQUIRE(variable_tensor != NULL);
-// Check this variable tensor has been written
-REQUIRE(variable_tensor.is_written);
-// Output tensor's shape and variable_tensor's shape have to match
-REQUIRE(variable_tensor.shape == shape);
-//  Output tensor's shape and variable_tensor's type have to match
-REQUIRE(variable_tensor.type == out_t);
-
-for_each (index in shape) {
-    // Read data from pseudo-buffer resource to the output
-    out_t value = tensor_read<tensor_t>(variable_tensor.data, variable_tensor.shape, index);
-    tensor_write<out_t>(input1, shape, index, value);
-}
-
+include::{pseudocode}/operators/VARIABLE_READ.tosac[lines=10..-1]
 ----
diff --git a/pseudocode/operators/ABS.tosac b/pseudocode/operators/ABS.tosac
new file mode 100644
index 0000000..5f7f56e
--- /dev/null
+++ b/pseudocode/operators/ABS.tosac
@@ -0,0 +1,19 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
+    if (is_floating_point(in_out_t) && value1 == -0.0) {
+        value1 = 0.0;
+    }
+    if (static_cast<int32_t>(value1) < 0.0) {
+        value1 = apply_sub_s<in_out_t>(0, value1);
+    }
+    tensor_write<in_out_t>(output, shape, index, value1);
+}
diff --git a/pseudocode/operators/ADD.tosac b/pseudocode/operators/ADD.tosac
new file mode 100644
index 0000000..61db3f6
--- /dev/null
+++ b/pseudocode/operators/ADD.tosac
@@ -0,0 +1,26 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+if (in_out_t == shape_t) {
+    ERROR_IF(rank(shape) != 0 || rank(shape1) != 0 || rank(shape2) != 0);
+    shape_t value1 = tensor_read<shape_t>(input1, [], []);
+    shape_t value2 = tensor_read<shape_t>(input2, [], []);
+    shape_t result = apply_add_s<shape_t>(value1, value2);
+    tensor_write<shape_t>(output, [], [], result);
+} else {
+    ERROR_IF(shape != broadcast_shape(shape1, shape2));
+    for_each(index in shape) {
+        dim_t index1 = apply_broadcast(shape, shape1, index);
+        dim_t index2 = apply_broadcast(shape, shape2, index);
+        in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+        in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+        in_out_t result = apply_add_s<in_out_t>(value1, value2);
+        tensor_write<in_out_t>(output, shape, index, result);
+    }
+}
diff --git a/pseudocode/operators/ARGMAX.tosac b/pseudocode/operators/ARGMAX.tosac
new file mode 100644
index 0000000..bbe301f
--- /dev/null
+++ b/pseudocode/operators/ARGMAX.tosac
@@ -0,0 +1,37 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(axis < 0 || axis >= rank(shape1));
+if (axis == 0) {
+    left_shape = [];
+} else {
+    left_shape = shape1[0:axis - 1];
+}
+if (axis == rank(shape1)-1) {
+    right_shape = [];
+} else {
+    right_shape = shape1[axis+1:rank(shape1) - 1];
+}
+ERROR_IF(flatten(left_shape, right_shape) != shape);
+for_each(left_index in left_shape) {
+    for_each(right_index in right_shape) {
+        in_t max_value = minimum_s<in_t>;
+        out_t max_index = 0;
+        for (i = 0; i < shape[axis]; i++) {
+            dim_t index = flatten(left_index, [i], right_index);
+            in_t value = tensor_read<in_t>(input, shape1, index);
+            if (apply_max_s<in_t>(value, max_value) != max_value) {
+                max_value = value;
+                max_index = i;
+            }
+        }
+        dim_t index = flatten(left_index, right_index);
+        tensor_write<out_t>(output, shape, index, max_index);
+    }
+}
diff --git a/pseudocode/operators/ARITHMETIC_RIGHT_SHIFT.tosac b/pseudocode/operators/ARITHMETIC_RIGHT_SHIFT.tosac
new file mode 100644
index 0000000..4077146
--- /dev/null
+++ b/pseudocode/operators/ARITHMETIC_RIGHT_SHIFT.tosac
@@ -0,0 +1,29 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+
+    // Ensure that shift amount is appropriate for the data type
+    REQUIRE((in_out_t == i32_t && 0 <= value2 && value2 <= 31) ||
+            (in_out_t == i16_t && 0 <= value2 && value2 <= 15) ||
+            (in_out_t == i8_t && 0 <= value2 && value2 <= 7));
+
+    in_out_t result = apply_arith_rshift<in_out_t>(value1, value2);
+    if (round == true && static_cast<int32_t>(value2) > 0 &&
+        (apply_arith_rshift<in_out_t>(value1, apply_sub_s<in_out_t>(value2, 1)) & 1 != 0) {
+        result = result + 1;
+    }
+    result = apply_clip_s<in_out_t>(result, minimum_s<in_out_t>, maximum_s<in_out_t>);
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/AVG_POOL2D.tosac b/pseudocode/operators/AVG_POOL2D.tosac
new file mode 100644
index 0000000..f452d12
--- /dev/null
+++ b/pseudocode/operators/AVG_POOL2D.tosac
@@ -0,0 +1,50 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(in_out_t != i8_t && input_zp != 0); // Zero point only for int8_t
+ERROR_IF(in_out_t != i8_t && output_zp != 0); // Zero point only for int8_t
+ERROR_IF(kernel_y < 1 || kernel_x < 1); // kernel size must be >= 1
+ERROR_IF(stride_y < 1 || stride_x < 1);
+ERROR_IF(pad_top < 0 || pad_bottom < 0 || pad_left < 0 || pad_right < 0);
+// Padding must be less than kernel size to avoid
+// a divide-by-zero.
+ERROR_IF(pad_right >= kernel_x || pad_left >= kernel_x);
+ERROR_IF(pad_top >= kernel_y || pad_bottom >= kernel_y);
+ERROR_IF(OH != idiv_check(IH + pad_top + pad_bottom - kernel_y, stride_y) + 1);
+ERROR_IF(OW != idiv_check(IW + pad_left + pad_right - kernel_x, stride_x) + 1);
+
+for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW, 0 <= c < C ) {
+    in_out_t output_val;
+    acc_t acc = 0;
+    int count = 0;
+    index_t iy = oy * stride_y - pad_top;
+    index_t ix = ox * stride_x - pad_left;
+    for_each(0 <= ky < kernel_y, 0 <= kx < kernel_x) {
+        index_t y = iy + ky;
+        index_t x = ix + kx;
+        // Only values from the input tensor are used to calculate the
+        // average, padding does not count
+        if (0 <= y < IH and 0 <= x < IW) {
+            count++;
+            acc_t value = sign_extend<acc_t>(tensor_read<in_out_t>(input, [N,IH,IW,C], [n,y,x,c]));
+            value = apply_sub_s<acc_t>(value, sign_extend<acc_t>(input_zp));
+            acc = apply_add_s<acc_t>(acc, value);
+        }
+    }
+    if (is_float(in_out_t)) {
+        output_val = acc / static_cast<in_out_t>(count);
+    } else {
+        scale_t scale = reciprocal_scale(count);
+        acc = apply_scale_32(acc, scale.multiplier, scale.shift, false);
+        acc = apply_add_s<acc_t>(acc, sign_extend<acc_t>(output_zp));
+        acc = apply_clip_s<acc_t>(acc, minimum_s<in_out_t>, maximum_s<in_out_t>);
+        output_val = static_cast<in_out_t>(acc);
+    }
+    tensor_write<in_out_t>(output, [N,OH,OW,C], [n,oy,ox,c], output_val);
+}
diff --git a/pseudocode/operators/BITWISE_AND.tosac b/pseudocode/operators/BITWISE_AND.tosac
new file mode 100644
index 0000000..5efe3ee
--- /dev/null
+++ b/pseudocode/operators/BITWISE_AND.tosac
@@ -0,0 +1,18 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    in_out_t result = value1 & value2;
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/BITWISE_NOT.tosac b/pseudocode/operators/BITWISE_NOT.tosac
new file mode 100644
index 0000000..1831e75
--- /dev/null
+++ b/pseudocode/operators/BITWISE_NOT.tosac
@@ -0,0 +1,14 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
+    in_out_t result = ~value1;
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/BITWISE_OR.tosac b/pseudocode/operators/BITWISE_OR.tosac
new file mode 100644
index 0000000..b2b7fc6
--- /dev/null
+++ b/pseudocode/operators/BITWISE_OR.tosac
@@ -0,0 +1,18 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    in_out_t result = value1 | value2;
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/BITWISE_XOR.tosac b/pseudocode/operators/BITWISE_XOR.tosac
new file mode 100644
index 0000000..98f0d2c
--- /dev/null
+++ b/pseudocode/operators/BITWISE_XOR.tosac
@@ -0,0 +1,18 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    in_out_t result = value1 ^ value2;
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/CAST.tosac b/pseudocode/operators/CAST.tosac
new file mode 100644
index 0000000..f6306b3
--- /dev/null
+++ b/pseudocode/operators/CAST.tosac
@@ -0,0 +1,27 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_t in = tensor_read<in_t>(input, shape, index);
+    out_t out;
+    if (out_t == bool_t) {
+        out = (in != 0) ? true : false;
+    } else if (in_t == bool_t) {
+        out = (in) ? 1 : 0;
+    } else if (out_t == fp16_t || out_t == bf16_t || out_t == fp32_t) {
+        out = round_to_nearest_float(in);
+    } else if (in_t == fp16_t || in_t == bf16_t || in_t == fp32_t) {
+        out = apply_clip<out_t>(round_to_nearest_int(in), minimum<out_t>, maximum<out_t>);
+    } else if (sizeof(out_t) >= sizeof(in_t)) {
+        out = sign_extend<out_t>(in);
+    } else {
+        out = truncate(in);
+    }
+    tensor_write<out_t>(output, shape, index, out)
+}
diff --git a/pseudocode/operators/CEIL.tosac b/pseudocode/operators/CEIL.tosac
new file mode 100644
index 0000000..890eb8a
--- /dev/null
+++ b/pseudocode/operators/CEIL.tosac
@@ -0,0 +1,14 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
+    in_out_t result = apply_ceil<in_out_t>(value1);
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/CLAMP.tosac b/pseudocode/operators/CLAMP.tosac
new file mode 100644
index 0000000..7a26d50
--- /dev/null
+++ b/pseudocode/operators/CLAMP.tosac
@@ -0,0 +1,15 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(max_val < min_val);
+for_each(index in shape) {
+    in_out_t value = tensor_read<in_out_t>(input, shape, index);
+    value = apply_clip<in_out_t>(value, min_val, max_val);
+    tensor_write<in_out_t>(output, shape, index, value);
+}
diff --git a/pseudocode/operators/CLZ.tosac b/pseudocode/operators/CLZ.tosac
new file mode 100644
index 0000000..a3a7180
--- /dev/null
+++ b/pseudocode/operators/CLZ.tosac
@@ -0,0 +1,14 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
+    in_out_t result = count_leading_zeros(value1);
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/CONCAT.tosac b/pseudocode/operators/CONCAT.tosac
new file mode 100644
index 0000000..f9329af
--- /dev/null
+++ b/pseudocode/operators/CONCAT.tosac
@@ -0,0 +1,32 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(axis < 0 || axis >= max(1,rank(shapes1[0])));
+ERROR_IF(shape[axis] != sum(shape_dim(shapes1[k], axis) for all k))
+ERROR_IF(in_out_t == shape_t && rank(shape) > 1);
+// The following checks ensure all inputs are compatible for concatenation
+for_each(input_shape in shapes1) {
+    ERROR_IF(rank(input_shape) != rank(shapes1[0]));
+    for_each(index in input_shape) {
+        ERROR_IF(index != axis && input_shape[index] != shapes1[0][index]);
+    }
+}
+for_each(index1 in shape) {
+    dim_t index2 = index1;
+    for (tensor t = 0; t < length(input1); t++) {
+        // Continue to concatenate along axis from each tensor
+        // For each output location, we are looking for the
+        // appropriate input tensor
+        if (index2[axis] >= 0 && index2[axis] < shape_dim(shapes1[t], axis)) {
+            in_out_t value = tensor_read<in_out_t>(input1[t], shapes1[t], index2);
+            tensor_write<in_out_t>(output, shape, index1, value);
+        }
+        index2[axis] = index2[axis] - shape_dim(shapes1[t], axis);
+    }
+}
diff --git a/pseudocode/operators/COND_IF.tosac b/pseudocode/operators/COND_IF.tosac
new file mode 100644
index 0000000..584cc83
--- /dev/null
+++ b/pseudocode/operators/COND_IF.tosac
@@ -0,0 +1,23 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(tosa_nesting_depth >= MAX_NESTING);
+ERROR_IF(tensor_list_shape(input_list) != tosa_input_shape(then_graph));
+ERROR_IF(tensor_list_shape(input_list) != tosa_input_shape(else_graph));
+ERROR_IF(tensor_list_shape(output_list) != tosa_output_shape(then_graph));
+ERROR_IF(tensor_list_shape(output_list) != tosa_output_shape(else_graph));
+ERROR_IF(tensor_size(shape) != 1);
+
+tosa_nesting_depth++;
+if (condition[0]) {
+    tosa_execute_graph(then_graph, input_list, output_list);
+} else {
+    tosa_execute_graph(else_graph, input_list, output_list);
+}
+tosa_nesting_depth--;
diff --git a/pseudocode/operators/CONV2D.tosac b/pseudocode/operators/CONV2D.tosac
new file mode 100644
index 0000000..12620e9
--- /dev/null
+++ b/pseudocode/operators/CONV2D.tosac
@@ -0,0 +1,40 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(in_t != i8_t && input_zp != 0); // Zero point only for int8_t
+ERROR_IF(weight_t != int8_t && weight_zp != 0);
+ERROR_IF(pad_top < 0 || pad_bottom < 0 || pad_left < 0 || pad_right < 0);
+ERROR_IF(stride_y < 1 || stride_x < 1);
+ERROR_IF(dilation_y < 1 || dilation_x < 1);
+ERROR_IF(OH != idiv_check(IH - 1 + pad_top + pad_bottom - (KH - 1) * dilation_y, stride_y) + 1);
+ERROR_IF(OW != idiv_check(IW - 1 + pad_left + pad_right - (KW - 1) * dilation_x, stride_x) + 1);
+ERROR_IF(BC != OC && BC != 1);
+
+for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW; 0 <= oc < OC) {
+    out_t acc = 0;
+    index_t iy = oy * stride_y - pad_top;
+    index_t ix = ox * stride_x - pad_left;
+    for_each(0 <= ky < KH, 0 <= kx < KW, 0 <= ic < IC) {
+        index_t y = iy + ky * dilation_y;
+        index_t x = ix + kx * dilation_x;
+        if (0 <= y < IH && 0 <= x < IW) {
+            out_t value  = static_cast<out_t>(tensor_read<in_t>(input,
+                                                                [N,IH,IW,IC],
+                                                                [n,y,x,ic]));
+            out_t weight = static_cast<out_t>(tensor_read<weight_t>(weight,
+                                                                   [OC,KH,KW,IC],
+                                                                   [oc,ky,kx,ic]));
+            value  = apply_sub_s<out_t>(value, static_cast<out_t>(input_zp));
+            weight = apply_sub_s<out_t>(weight, static_cast<out_t>(weight_zp));
+            acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value, weight));
+        }
+    }
+    acc = apply_add_s<out_t>(acc, bias[(BC == 1) ? 0 : oc]);
+    tensor_write<out_t>(output, [N,OH,OW,OC], [n,oy,ox,oc], acc);
+}
diff --git a/pseudocode/operators/CONV3D.tosac b/pseudocode/operators/CONV3D.tosac
new file mode 100644
index 0000000..a0f9130
--- /dev/null
+++ b/pseudocode/operators/CONV3D.tosac
@@ -0,0 +1,43 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(in_t != i8_t && input_zp != 0); // Zero point only for int8_t
+ERROR_IF(weight_t != i8_t && weight_zp != 0);
+ERROR_IF(pad_d0 < 0 || pad_d1 < 0 || pad_top < 0 || pad_bottom < 0 || pad_left < 0 || pad_right < 0);
+ERROR_IF(stride_d < 1 || stride_y < 1 || stride_x < 1);
+ERROR_IF(dilation_d < 1 || dilation_y < 1 || dilation_x < 1);
+ERROR_IF(OD != idiv_check(ID - 1 + pad_d0 + pad_d1      - (KD - 1) * dilation_d, stride_d) + 1);
+ERROR_IF(OH != idiv_check(IH - 1 + pad_top + pad_bottom - (KH - 1) * dilation_y, stride_y) + 1);
+ERROR_IF(OW != idiv_check(IW - 1 + pad_left + pad_right - (KW - 1) * dilation_x, stride_x) + 1);
+ERROR_IF(BC != OC && BC != 1);
+
+for_each(0 <= n < N, 0 <= od < OD, 0 <= oy < OH, 0 <= ox < OW; 0 <= oc < OC) {
+    out_t acc = 0;
+    index_t id = od * stride_d - pad_d0;
+    index_t iy = oy * stride_y - pad_top;
+    index_t ix = ox * stride_x - pad_left;
+    for_each(0 <= kd < KD, 0 <= ky < KH, 0 <= kx < KW, 0 <= ic < IC) {
+        index_t d = id + kd * dilation_d;
+        index_t y = iy + ky * dilation_y;
+        index_t x = ix + kx * dilation_x;
+        if (0 <= x < IW && 0 <= y < IH && 0 <= d < ID) {
+            out_t value  = static_cast<out_t>(tensor_read<in_t>(input,
+                                                                [N,ID,IH,IW,IC],
+                                                                [n,d,y,x,ic]));
+            out_t weight = static_cast<out_t>(tensor_read<weight_t>(weight,
+                                                                    [OC,KD,KH,KW,IC],
+                                                                    [oc,kd,ky,kx,ic]));
+            value  = apply_sub_s<out_t>(value, static_cast<out_t>(input_zp));
+            weight = apply_sub_s<out_t>(weight, static_cast<out_t>(weight_zp));
+            acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value, weight));
+        }
+    }
+    acc = apply_add_s<out_t>(acc, bias[(BC == 1) ? 0 : oc]);
+    tensor_write<out_t>(output, [N,OD,OH,OW,OC], [n,od,oy,ox,oc], acc);
+}
diff --git a/pseudocode/operators/DEPTHWISE_CONV2D.tosac b/pseudocode/operators/DEPTHWISE_CONV2D.tosac
new file mode 100644
index 0000000..c7a0f0f
--- /dev/null
+++ b/pseudocode/operators/DEPTHWISE_CONV2D.tosac
@@ -0,0 +1,40 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(in_t != i8_t && input_zp != 0); // Zero point only for int8_t
+ERROR_IF(weight_t != i8_t && weight_zp != 0);
+ERROR_IF(pad_top < 0 || pad_bottom < 0 || pad_left < 0 || pad_right < 0);
+ERROR_IF(stride_y < 1 || stride_x < 1);
+ERROR_IF(dilation_y < 1 || dilation_x < 1);
+ERROR_IF(OH != idiv_check(IH - 1 + pad_top + pad_bottom - (KH - 1) * dilation_y, stride_y) + 1);
+ERROR_IF(OW != idiv_check(IW - 1 + pad_left + pad_right - (KW - 1) * dilation_x, stride_x) + 1);
+ERROR_IF(BC != C*M && BC != 1);
+
+for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW; 0 <= c < C, 0 <= m < M) {
+    out_t acc = 0;
+    index_t iy = oy * stride_y - pad_top;
+    index_t ix = ox * stride_x - pad_left;
+    for_each(0 <= ky < KH, 0 <= kx < KW) {
+        index_t y = iy + ky * dilation_y;
+        index_t x = ix + kx * dilation_x;
+        if (0 <= y < IH && 0 <= x < IW) {
+            out_t value  = static_cast<out_t>(tensor_read<in_t>(input,
+                                                                [N,IH,IW,C],
+                                                                [n,y,x,c]));
+            out_t weight = static_cast<out_t>(tensor_read<weight_t>(weight,
+                                                                    [KH,KW,C,M],
+                                                                    [ky,kx,c,m]));
+            value  = apply_sub_s<out_t>(value, static_cast<out_t>input_zp);
+            weight = apply_sub_s<out_t>(weight, static_cast<out_t>weight_zp);
+            acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value, weight));
+        }
+    }
+    acc = apply_add_s<out_t>(acc, bias[(BC == 1) ? 0 : (c * M) + m]);
+    tensor_write<out_t>(output, [N,OH,OW,C * M], [n,oy,ox,c * M + m], acc);
+}
diff --git a/pseudocode/operators/DIM.tosac b/pseudocode/operators/DIM.tosac
new file mode 100644
index 0000000..7131173
--- /dev/null
+++ b/pseudocode/operators/DIM.tosac
@@ -0,0 +1,11 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(axis >= rank(shape));
+tensor_write<shape_t>(output, [], [], shape_dim(shape, axis));
diff --git a/pseudocode/operators/EQUAL.tosac b/pseudocode/operators/EQUAL.tosac
new file mode 100644
index 0000000..67e0b64
--- /dev/null
+++ b/pseudocode/operators/EQUAL.tosac
@@ -0,0 +1,22 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_t value1 = tensor_read<in_t>(input1, shape1, index1);
+    in_t value2 = tensor_read<in_t>(input2, shape2, index2);
+    out_t result;
+    if (isNaN(value1) || isNaN(value2))
+        result = False;
+    else
+        result = (value1 == value2) ? True : False;
+    tensor_write<out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/EXP.tosac b/pseudocode/operators/EXP.tosac
new file mode 100644
index 0000000..4ef74a0
--- /dev/null
+++ b/pseudocode/operators/EXP.tosac
@@ -0,0 +1,14 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
+    in_out_t result = apply_exp<in_out_t>(value1);
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/FFT2D.tosac b/pseudocode/operators/FFT2D.tosac
new file mode 100644
index 0000000..a958aa4
--- /dev/null
+++ b/pseudocode/operators/FFT2D.tosac
@@ -0,0 +1,31 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(!power_of_two(H));
+ERROR_IF(!power_of_two(W));
+
+float sign_val = 1.0;
+
+if (inverse) {
+    sign_val = -1.0;
+}
+
+for_each(0 <= n < N, 0 <= oy < H, 0 <= ox < W) {
+    in_out_t sum_real = 0.0;
+    in_out_t sum_imag = 0.0;
+    for_each(0 <= iy < H, 0 <= ix < W) {
+        in_out_t val_real = tensor_read<in_out_t>(input_real, [N,H,W], [n,iy,ix]);
+        in_out_t val_imag = tensor_read<in_out_t>(input_imag, [N,H,W], [n,iy,ix]);
+        float_t a = sign_val * 2 * pi() * ((iy * oy) / H + (ix * ox) / W);
+        sum_real += val_real * cos(a) + val_imag * sin(a);
+        sum_imag += -val_real * sin(a) + val_imag * cos(a);
+    }
+    tensor_write<in_out_t>(output_real, [N,H,W], [n,oy,ox], sum_real);
+    tensor_write<in_out_t>(output_imag, [N,H,W], [n,oy,ox], sum_imag);
+}
diff --git a/pseudocode/operators/FLOOR.tosac b/pseudocode/operators/FLOOR.tosac
new file mode 100644
index 0000000..fc893b6
--- /dev/null
+++ b/pseudocode/operators/FLOOR.tosac
@@ -0,0 +1,14 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
+    in_out_t result = apply_floor<in_out_t>(value1);
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/FULLY_CONNECTED.tosac b/pseudocode/operators/FULLY_CONNECTED.tosac
new file mode 100644
index 0000000..fbacccc
--- /dev/null
+++ b/pseudocode/operators/FULLY_CONNECTED.tosac
@@ -0,0 +1,25 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(in_t != i8_t && input_zp != 0); // Zero point only for int8_t
+ERROR_IF(weight_t != i8_t && weight_zp != 0);
+ERROR_IF(BC != OC && BC != 1);
+
+for_each(0 <= n < N, 0 <= oc < OC) {
+    out_t acc = 0;
+    for_each(0 <= ic < IC) {
+        out_t value  = static_cast<out_t>(tensor_read<in_t>(input, [N,IC], [n,ic]));
+        out_t weight = static_cast<out_t>(tensor_read<weight_t>(weight, [OC,IC], [oc,ic]));
+        value  = apply_sub_s<out_t>(value, static_cast<out_t>(input_zp));
+        weight = apply_sub_s<out_t>(weight, static_cast<out_t>(weight_zp));
+        acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value, weight));
+    }
+    acc = apply_add_s<out_t>(acc, bias[(BC == 1) ? 0 : oc]);
+    tensor_write<out_t>(output, [N,OC], [n,oc], acc);
+}
diff --git a/pseudocode/operators/GATHER.tosac b/pseudocode/operators/GATHER.tosac
new file mode 100644
index 0000000..82c159d
--- /dev/null
+++ b/pseudocode/operators/GATHER.tosac
@@ -0,0 +1,15 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(0 <= n < N, 0 <= w < W, 0 <= c < C) {
+    index_t k = tensor_read<index_t>(indices, [N,W], [n,w]);
+    REQUIRE(0 <= k && k < K);
+    in_out_t value = tensor_read<in_out_t>(values, [N,K,C], [n,k,c]);
+    tensor_write<in_out_t>(output, [N,W,C], [n,w,c], value);
+}
diff --git a/pseudocode/operators/GREATER.tosac b/pseudocode/operators/GREATER.tosac
new file mode 100644
index 0000000..af8b4c9
--- /dev/null
+++ b/pseudocode/operators/GREATER.tosac
@@ -0,0 +1,22 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_t value1 = tensor_read<in_t>(input1, shape1, index1);
+    in_t value2 = tensor_read<in_t>(input2, shape2, index2);
+    out_t result;
+    if (isNaN(value1) || isNaN(value2))
+        result = False;
+    else
+        result = (value1 > value2) ? True : False;
+    tensor_write<out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/GREATER_EQUAL.tosac b/pseudocode/operators/GREATER_EQUAL.tosac
new file mode 100644
index 0000000..e45990d
--- /dev/null
+++ b/pseudocode/operators/GREATER_EQUAL.tosac
@@ -0,0 +1,22 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_t value1 = tensor_read<in_t>(input1, shape1, index1);
+    in_t value2 = tensor_read<in_t>(input2, shape2, index2);
+    out_t result;
+    if (isNaN(value1) || isNaN(value2))
+        result = False;
+    else
+        result = (value1 >= value2) ? True : False;
+    tensor_write<out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/INTDIV.tosac b/pseudocode/operators/INTDIV.tosac
new file mode 100644
index 0000000..b6d46cc
--- /dev/null
+++ b/pseudocode/operators/INTDIV.tosac
@@ -0,0 +1,31 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+if (in_out_t == shape_t) {
+    ERROR_IF(rank(shape) != 0 || rank(shape1) != 0 || rank(shape2) != 0);
+    shape_t value1 = tensor_read<shape_t>(input1, [], []);
+    shape_t value2 = tensor_read<shape_t>(input2, [], []);
+    REQUIRE(value2 != 0);
+    shape_t result = value1 / value2;
+    tensor_write<shape_t>(output, [], [], result);
+} else {
+    ERROR_IF(shape != broadcast_shape(shape1, shape2));
+    for_each(index in shape) {
+        dim_t index1 = apply_broadcast(shape, shape1, index);
+        dim_t index2 = apply_broadcast(shape, shape2, index);
+        in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+        in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+        REQUIRE(value2 != 0);
+        // This catches the case where we divide minimum<in_out_t> by -1
+        // which is not representable in two's complement
+        REQUIRE(static_cast<int64_t>(value1) / static_cast<int64_t>(value2) <= maximum_s<in_out_t>);
+        in_out_t result = apply_intdiv_s<in_out_t>(value1, value2);
+        tensor_write<in_out_t>(output, shape, index, result);
+    }
+}
diff --git a/pseudocode/operators/LOG.tosac b/pseudocode/operators/LOG.tosac
new file mode 100644
index 0000000..2c56105
--- /dev/null
+++ b/pseudocode/operators/LOG.tosac
@@ -0,0 +1,14 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
+    in_out_t result = apply_log<in_out_t>(value1);
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/LOGICAL_AND.tosac b/pseudocode/operators/LOGICAL_AND.tosac
new file mode 100644
index 0000000..ff03804
--- /dev/null
+++ b/pseudocode/operators/LOGICAL_AND.tosac
@@ -0,0 +1,18 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    in_out_t result = value1 && value2;
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/LOGICAL_LEFT_SHIFT.tosac b/pseudocode/operators/LOGICAL_LEFT_SHIFT.tosac
new file mode 100644
index 0000000..4057163
--- /dev/null
+++ b/pseudocode/operators/LOGICAL_LEFT_SHIFT.tosac
@@ -0,0 +1,19 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    REQUIRE(0 <= value2 && value2 <= 31);
+    in_out_t result = value1 << value2;
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/LOGICAL_NOT.tosac b/pseudocode/operators/LOGICAL_NOT.tosac
new file mode 100644
index 0000000..b07e668
--- /dev/null
+++ b/pseudocode/operators/LOGICAL_NOT.tosac
@@ -0,0 +1,14 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index);
+    in_out_t result = !value1;
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/LOGICAL_OR.tosac b/pseudocode/operators/LOGICAL_OR.tosac
new file mode 100644
index 0000000..4e3aa9e
--- /dev/null
+++ b/pseudocode/operators/LOGICAL_OR.tosac
@@ -0,0 +1,18 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    in_out_t result = value1 || value2;
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/LOGICAL_RIGHT_SHIFT.tosac b/pseudocode/operators/LOGICAL_RIGHT_SHIFT.tosac
new file mode 100644
index 0000000..5e80211
--- /dev/null
+++ b/pseudocode/operators/LOGICAL_RIGHT_SHIFT.tosac
@@ -0,0 +1,20 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    REQUIRE(0 <= static_cast<int32_t>(value2) && static_cast<int32_t>(value2) <= 31);
+    // Logical shifts happen as unsigned types internally
+    in_out_t result = apply_logical_rshift<in_out_t>(value1, value2);
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/LOGICAL_XOR.tosac b/pseudocode/operators/LOGICAL_XOR.tosac
new file mode 100644
index 0000000..fbb485b
--- /dev/null
+++ b/pseudocode/operators/LOGICAL_XOR.tosac
@@ -0,0 +1,18 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    in_out_t result = value1 != value2;
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/MATMUL.tosac b/pseudocode/operators/MATMUL.tosac
new file mode 100644
index 0000000..3afda4d
--- /dev/null
+++ b/pseudocode/operators/MATMUL.tosac
@@ -0,0 +1,21 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(in_t != i8_t && (A_zp != 0 || B_zp != 0)); // Zero point only for int8_t
+for_each(0 <= n < N, 0 <= h < H, 0 <= w < W) {
+    out_t acc = 0;
+    for_each(0 <= c < C) {
+        out_t value1 = static_cast<out_t>(tensor_read<in_t>(A, [N,H,C], [n,h,c]));
+        out_t value2 = static_cast<out_t>(tensor_read<in_t>(B, [N,C,W], [n,c,w]));
+        value1 = apply_sub_s<out_t>(value1, static_cast<out_t>(A_zp));
+        value2 = apply_sub_s<out_t>(value2, static_cast<out_t>(B_zp));
+        acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value1 * value2));
+    }
+    tensor_write<out_t>(output, [N,H,W], [n,h,w], acc);
+}
diff --git a/pseudocode/operators/MAXIMUM.tosac b/pseudocode/operators/MAXIMUM.tosac
new file mode 100644
index 0000000..0f4f3b7
--- /dev/null
+++ b/pseudocode/operators/MAXIMUM.tosac
@@ -0,0 +1,18 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    in_out_t result = apply_max_s<in_out_t>(value1, value2);
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/MAX_POOL2D.tosac b/pseudocode/operators/MAX_POOL2D.tosac
new file mode 100644
index 0000000..a33b80a
--- /dev/null
+++ b/pseudocode/operators/MAX_POOL2D.tosac
@@ -0,0 +1,33 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(kernel_y < 1 || kernel_x < 1); // kernel size must be >= 1
+ERROR_IF(stride_y < 1 || stride_x < 1);
+ERROR_IF(pad_top < 0 || pad_bottom < 0 || pad_left < 0 || pad_right < 0);
+// Padding must be less than kernel size, otherwise no
+// input values will be used.
+ERROR_IF(pad_right >= kernel_x || pad_left >= kernel_x);
+ERROR_IF(pad_top >= kernel_y || pad_bottom >= kernel_y);
+ERROR_IF(OH != idiv_check(IH + pad_top + pad_bottom - kernel_y, stride_y) + 1);
+ERROR_IF(OW != idiv_check(IW + pad_left + pad_right - kernel_x, stride_x) + 1);
+
+for_each(0 <= n < N, 0 <= oy < H, 0 <= ox < W, 0 <= c < C ) {
+    in_out_t acc = minimum_value<in_out_t>;
+    index_t iy = oy * stride_y - pad_top;
+    index_t ix = ox * stride_x - pad_left;
+    for_each( 0 <= ky < kernel_y, 0 <= kx < kernel_x ) {
+        index_t y = iy + ky;
+        index_t x = ix + kx;
+        if (y >= 0 && y < IH && x >= 0 && x < IW) {
+            in_out_t value = tensor_read<in_out_t>(input, [N,IH,IW,C], [n,y,x,c]);
+            acc = apply_max_s<in_out_t>(acc, value);
+        }
+    }
+    tensor_write<in_out_t>(output, [N,OH,OW,C], [n,oy,ox,c], acc);
+}
diff --git a/pseudocode/operators/MINIMUM.tosac b/pseudocode/operators/MINIMUM.tosac
new file mode 100644
index 0000000..fa47b03
--- /dev/null
+++ b/pseudocode/operators/MINIMUM.tosac
@@ -0,0 +1,18 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    in_out_t result = apply_min_s(value1, value2);
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/MUL.tosac b/pseudocode/operators/MUL.tosac
new file mode 100644
index 0000000..078525e
--- /dev/null
+++ b/pseudocode/operators/MUL.tosac
@@ -0,0 +1,37 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+if (in_out_t == shape_t) {
+    ERROR_IF(rank(shape) != 0 || rank(shape1) != 0 || rank(shape2) != 0);
+    shape_t value1 = tensor_read<shape_t>(input1, [], []);
+    shape_t value2 = tensor_read<shape_t>(input2, [], []);
+    shape_t result = value1 * value2;
+    tensor_write<shape_t>(output, [], [], result);
+} else {
+    REQUIRE(0 <= shift && shift <= 63);
+    REQUIRE(in_t == int32_t || shift == 0);
+    ERROR_IF(shape != broadcast_shape(shape1, shape2));
+    for_each(index in shape) {
+        dim_t index1 = apply_broadcast(shape, shape1, index);
+        dim_t index2 = apply_broadcast(shape, shape2, index);
+        in_t value1 = tensor_read<in_t>(input1, shape1, index1);
+        in_t value2 = tensor_read<in_t>(input2, shape2, index2);
+        out_t result;
+        if (in_t == i32_t && shift > 0) {
+            int64_t product = sign_extend<int64_t>(value1) * sign_extend<int64_t>(value2);
+            int64_t round   = static_cast<int64_t>(1) << (shift - 1);
+            product = (product + round) >> shift;
+            REQUIRE(product >= minimum_s<i32_t> && product <= maximum_s<i32_t>)
+            result = product;
+        } else {
+            result = apply_mul_s(value1, value2);  // low 32-bits of result for i32_t
+        }
+        tensor_write<out_t>(output, shape, index, result);
+    }
+}
diff --git a/pseudocode/operators/NEGATE.tosac b/pseudocode/operators/NEGATE.tosac
new file mode 100644
index 0000000..8c235f1
--- /dev/null
+++ b/pseudocode/operators/NEGATE.tosac
@@ -0,0 +1,22 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(in_out_t != i8_t && input1_zp != 0) // Zero point only for int8_t
+ERROR_IF(in_out_t != i8_t && output_zp != 0) // Zero point only for int8_t
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape, index);
+    acc_t value = apply_sub_s<acc_t>(sign_extend<acc_t>(value1),
+                                     sign_extend<acc_t>(input1_zp));
+    value = apply_sub_s<acc_t>(0, value);
+    value = apply_add_s<acc_t>(value, sign_extend<acc_t>(output_zp));
+    in_out_t result = truncate<in_out_t>(apply_clip_s<acc_t>(value,
+                                                             minimum_s<in_out_t>,
+                                                             maximum_s<in_out_t>));
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/PAD.tosac b/pseudocode/operators/PAD.tosac
new file mode 100644
index 0000000..4adf114
--- /dev/null
+++ b/pseudocode/operators/PAD.tosac
@@ -0,0 +1,27 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+// Check output shape matches the padded input shape
+ERROR_IF(rank(shape) != rank(shape1));
+for (i = 0; i < rank(shape); i++) {
+    ERROR_IF(padding[i,0] < 0 || padding[i,1] < 0);
+    ERROR_IF(shape[i] != padding[i, 0] + shape1[i] + padding[i, 1]);
+}
+for_each(index in shape) {
+    dim_t index1 = index;
+    bool_t is_pad = false;
+    for(i = 0; i < rank(shape); i++) {
+        index1[i] = index1[i] - padding[i,0];
+        if (index1[i] < 0 || index[i] >= length(shape[i])) {
+            is_pad = true;
+        }
+    }
+    in_out_t value = is_pad ? pad_const : tensor_read<in_out_t>(input1, shape1, index1);
+    tensor_write<in_out_t>(output, shape, index, value);
+}
diff --git a/pseudocode/operators/POW.tosac b/pseudocode/operators/POW.tosac
new file mode 100644
index 0000000..6ecc8e6
--- /dev/null
+++ b/pseudocode/operators/POW.tosac
@@ -0,0 +1,18 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(shape1, shape2));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    in_out_t result = apply_pow<in_out_t>(value1, value2);
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/RECIPROCAL.tosac b/pseudocode/operators/RECIPROCAL.tosac
new file mode 100644
index 0000000..9bc086b
--- /dev/null
+++ b/pseudocode/operators/RECIPROCAL.tosac
@@ -0,0 +1,14 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index);
+    in_out_t result = 1.0 / value1;
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/REDUCE_ALL.tosac b/pseudocode/operators/REDUCE_ALL.tosac
new file mode 100644
index 0000000..7438513
--- /dev/null
+++ b/pseudocode/operators/REDUCE_ALL.tosac
@@ -0,0 +1,25 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(axis < 0  || axis >= rank(shape1));
+ERROR_IF(shape[axis] != 1);
+left_shape  = (axis > 1) ? shape[0:axis-1] : [];
+right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
+for_each(left_index in left_shape) {
+    for_each(right_index in right_shape) {
+        in_out_t acc = true;
+        for (i = 0; i < shape1[axis]; i++) {
+            index = flatten(left_index, [i], right_index);
+            in_out_t value = tensor_read<in_out_t>(input, shape1, index);
+            acc = acc && value;
+        }
+        out_index = flatten(left_index, [0], right_index);
+        tensor_write<in_out_t>(output, shape, out_index, acc);
+    }
+}
diff --git a/pseudocode/operators/REDUCE_ANY.tosac b/pseudocode/operators/REDUCE_ANY.tosac
new file mode 100644
index 0000000..3303fac
--- /dev/null
+++ b/pseudocode/operators/REDUCE_ANY.tosac
@@ -0,0 +1,25 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(axis < 0  || axis >= rank(shape1));
+ERROR_IF(shape[axis] != 1);
+left_shape  = (axis > 1) ? shape[0:axis-1] : [];
+right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
+for_each(left_index in left_shape) {
+    for_each(right_index in right_shape) {
+        in_out_t acc = false;
+        for (i = 0; i < shape1[axis]; i++) {
+            index = flatten(left_index, [i], right_index);
+            in_out_t value = tensor_read<in_out_t>(input, shape1, index);
+            acc = acc || value;
+        }
+        out_index = flatten(left_index, [0], right_index);
+        tensor_write<in_out_t>(output, shape, out_index, acc);
+    }
+}
diff --git a/pseudocode/operators/REDUCE_MAX.tosac b/pseudocode/operators/REDUCE_MAX.tosac
new file mode 100644
index 0000000..57f291a
--- /dev/null
+++ b/pseudocode/operators/REDUCE_MAX.tosac
@@ -0,0 +1,25 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(axis < 0  || axis >= rank(shape1));
+ERROR_IF(shape[axis] != 1);
+left_shape  = (axis > 1) ? shape[0:axis-1] : [];
+right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
+for_each(left_index in left_shape) {
+    for_each(right_index in right_shape) {
+        in_out_t acc = minimum<in_out_t>;
+        for (i = 0; i < shape1[axis]; i++) {
+            index = flatten(left_index, [i], right_index);
+            in_out_t value = tensor_read<in_out_t>(input, shape1, index);
+            acc = apply_max_s<in_out_t>(acc, value);
+        }
+        out_index = flatten(left_index, [0], right_index);
+        tensor_write<in_out_t>(output, shape, out_index, acc);
+    }
+}
diff --git a/pseudocode/operators/REDUCE_MIN.tosac b/pseudocode/operators/REDUCE_MIN.tosac
new file mode 100644
index 0000000..5eaa702
--- /dev/null
+++ b/pseudocode/operators/REDUCE_MIN.tosac
@@ -0,0 +1,25 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(axis < 0  || axis >= rank(shape1));
+ERROR_IF(shape[axis] != 1);
+left_shape  = (axis > 1) ? shape[0:axis-1] : [];
+right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
+for_each(left_index in left_shape) {
+    for_each(right_index in right_shape) {
+        in_out_t acc = maximum<in_out_t>;
+        for (i = 0; i < shape1[axis]; i++) {
+            index = flatten(left_index, [i], right_index);
+            in_out_t value = tensor_read<in_out_t>(input, shape1, index);
+            acc = apply_min_s<in_out_t>(acc, value);
+        }
+        out_index = flatten(left_index, [0], right_index);
+        tensor_write<in_out_t>(output, shape, out_index, out);
+    }
+}
diff --git a/pseudocode/operators/REDUCE_PRODUCT.tosac b/pseudocode/operators/REDUCE_PRODUCT.tosac
new file mode 100644
index 0000000..3c867d7
--- /dev/null
+++ b/pseudocode/operators/REDUCE_PRODUCT.tosac
@@ -0,0 +1,25 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(axis < 0  || axis >= rank(shape1));
+ERROR_IF(shape[axis] != 1);
+left_shape  = (axis > 1) ? shape[0:axis-1] : [];
+right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
+for_each(left_index in left_shape) {
+    for_each(right_index in right_shape) {
+        in_out_t acc = 1.0;
+        for (i = 0; i < shape1[axis]; i++) {
+            index = flatten(left_index, [i], right_index);
+            in_out_t value = tensor_read<in_out_t>(input, shape1, index);
+            acc = apply_mul_s<in_out_t>(acc, value);
+        }
+        out_index = flatten(left_index, [0], right_index);
+        tensor_write<in_out_t>(output, shape, out_index, acc);
+    }
+}
diff --git a/pseudocode/operators/REDUCE_SUM.tosac b/pseudocode/operators/REDUCE_SUM.tosac
new file mode 100644
index 0000000..2f22ada
--- /dev/null
+++ b/pseudocode/operators/REDUCE_SUM.tosac
@@ -0,0 +1,26 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(axis < 0  || axis >= rank(shape1));
+ERROR_IF(shape[axis] != 1);
+left_shape  = (axis > 1) ? shape[0:axis-1] : [];
+right_shape = (axis < rank(shape)-1) ? shape[axis+1:rank(shape)-1] : [];
+for_each(left_index in left_shape) {
+    for_each(right_index in right_shape) {
+        acc_t acc = 0;
+        for (i = 0; i < shape1[axis]; i++) {
+            index = flatten(left_index, [i], right_index);
+            acc_t value = tensor_read<in_out_t>(input, shape1, index);
+            acc = apply_add_s<acc_t>(acc, value);
+        }
+        out_index = flatten(left_index, [0], right_index);
+        in_out_t result = static_cast<in_out_t>(acc);
+        tensor_write<in_out_t>(output, shape, out_index, result);
+    }
+}
diff --git a/pseudocode/operators/RESCALE.tosac b/pseudocode/operators/RESCALE.tosac
new file mode 100644
index 0000000..86a939b
--- /dev/null
+++ b/pseudocode/operators/RESCALE.tosac
@@ -0,0 +1,58 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    // uint16 values can have zero_point 0 or 32768
+    // int8/uint8 can have zero point within their valid range
+    // No other types can have zero point != 0
+    ERROR_IF(in_t != i8_t &&
+             (in_t != i16_t || input_unsigned == False) && input_zp != 0);
+    ERROR_IF(out_t != i8_t &&
+             (out_t != i16_t || output_unsigned == False) && output_zp != 0);
+    ERROR_IF(in_t == i16_t && input_unsigned == True && input_zp != 0 && input_zp != 32768);
+    ERROR_IF(out_t == i16_t && output_unsigned == True && output_zp != 0 && output_zp != 32768);
+    ERROR_IF(scale32 && in_t == i48_t);
+    ERROR_IF(!scale32 && double_round);
+    ERROR_IF(in_t == i16_t && out_t == i32_t && input_unsigned);
+    ERROR_IF(in_t == i32_t && out_t == i16_t && output_unsigned);
+
+    in_t in_value = tensor_read<in_t>(input, shape, index);
+
+    int48_t value, extended_in_zp;
+    if (input_unsigned) {
+        value = zero_extend<int48_t>(in_value);
+        extended_in_zp = zero_extend<int48_t>(input_zp);
+    }
+    else {
+        value = sign_extend<int48_t>(value);
+        extended_in_zp = sign_extend<int48_t>(input_zp);
+    }
+
+    value = value - extended_in_zp;
+    int c = (per_channel) ? index[rank(input) - 1] : 0;
+    int32_t result = (scale32) ?
+        apply_scale_32(value, multiplier[c], shift[c], double_round) :
+        apply_scale_16(value, multiplier[c], shift[c]);
+
+    if (output_unsigned) {
+        int32_t extended_out_zp = zero_extend<int32_t>(output_zp);
+        result = apply_add_s<int32_t>(result, extended_out_zp);
+        out_t out = static_cast<out_t>(apply_clip<int32_t>(result,
+                                                           minimum_u<out_t>,
+                                                           maximum_u<out_t>));
+    }
+    else {
+        int32_t extended_out_zp = sign_extend<int32_t>(output_zp);
+        result = apply_add_s<int32_t>(result, extended_out_zp);
+        out_t out = static_cast<out_t>(apply_clip<int32_t>(result,
+                                                           minimum_s<out_t>,
+                                                           maximum_s<out_t>));
+    }
+    tensor_write<out_t>(output, shape, index, out);
+}
diff --git a/pseudocode/operators/RESHAPE.tosac b/pseudocode/operators/RESHAPE.tosac
new file mode 100644
index 0000000..41439c3
--- /dev/null
+++ b/pseudocode/operators/RESHAPE.tosac
@@ -0,0 +1,21 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(tensor_size(shape1) != tensor_size(shape));
+
+for_each(index in shape) {
+    // Calculate flattened index for the output location (index)
+    size_t offset = tensor_index_to_offset(shape, index);
+    // Now convert to the location in the input
+    dim_t tmp_index = tensor_offset_to_index(shape1, offset);
+
+    // Now read/write the value
+    in_out_t val = tensor_read<in_out_t>(input1, shape1, tmp_index);
+    tensor_write<in_out_t>(output, shape, index, val);
+}
diff --git a/pseudocode/operators/RESIZE.tosac b/pseudocode/operators/RESIZE.tosac
new file mode 100644
index 0000000..fd66530
--- /dev/null
+++ b/pseudocode/operators/RESIZE.tosac
@@ -0,0 +1,74 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+// Ensure the image size is supported by GPU APIs and that for integer
+// implementations, position * stride does not overflow int32_t.
+ERROR_IF(max(OH,OW,IH,IW) >= 16384);
+ERROR_IF(scale_y_n <= 0 || scale_y_d <= 0 || scale_x_n <= 0 || scale_x_d <= 0);
+// if in_t=int8_t ensure that an int32_t accumulator can be used
+ERROR_IF(scale_y_n > (1 << 11) || scale_x_n > (1 << 11));
+// set a consistent lower limit of 1/16 downscale to simplify implementations
+ERROR_IF(scale_y_d >= 16 * scale_y_n || scale_x_d >= 16 * scale_x_n);
+ERROR_IF(offset_y < -scale_y_n || offset_y >= 16 * scale_y_n);
+ERROR_IF(offset_x < -scale_x_n || offset_x >= 16 * scale_x_n);
+ERROR_IF(border_y < -16 * scale_y_n || border_y >= scale_y_n);
+ERROR_IF(border_x < -16 * scale_x_n || border_x >= scale_x_n);
+ERROR_IF(OH != idiv_check((IH - 1) * scale_y_n - offset_y + border_y, scale_y_d) + 1);
+ERROR_IF(OW != idiv_check((IW - 1) * scale_x_n - offset_x + border_x, scale_x_d) + 1);
+for_each(0 <= n < N, 0 <= oy < OH, 0 <= ox < OW; 0 <= c < C) {
+    out_t acc;
+    resize_t dx, dy;
+    resize_t unit_x, unit_y;
+
+    unit_x = (is_floating_point(resize_t)) ? 1.0 : scale_x_n;
+    unit_y = (is_floating_point(resize_t)) ? 1.0 : scale_y_n;
+
+    int32_t y = oy * scale_y_d + offset_y;
+    int32_t x = ox * scale_x_d + offset_x;
+    int16_t iy = idiv_floor(y, scale_y_n);
+    int16_t ix = idiv_floor(x, scale_x_n);
+    int16_t ry = y - iy * scale_y_n;  // (y % scale_y_n)
+    int16_t rx = x - ix * scale_x_n;  // (x % scale_x_n)
+
+    if (is_floating_point(resize_t)) {
+        dy = static_cast<resize_t>(ry) / static_cast<resize_t>(scale_y_n);
+        dx = static_cast<resize_t>(rx) / static_cast<resize_t>(scale_x_n);
+    } else {
+        dy = ry;
+        dx = rx;
+    }
+    // Note that -1 <= iy < IH and -1 <= ix < IW
+    int16_t iy0 = apply_max_s(iy, 0);
+    int16_t iy1 = apply_min_s(iy + 1, IH - 1);
+    int16_t ix0 = apply_max_s(ix, 0);
+    int16_t ix1 = apply_min_s(ix + 1, IW - 1);
+    if (mode==BILINEAR) {
+        using in_s_t = make_signed(in_t); // Use signed calculations for i8/i16
+        in_s_t v00 = static_cast<in_s_t>(tensor_read<in_t>(input, [N,IH,IW,C], [n,iy0,ix0,c]));
+        in_s_t v01 = static_cast<in_s_t>(tensor_read<in_t>(input, [N,IH,IW,C], [n,iy0,ix1,c]));
+        in_s_t v10 = static_cast<in_s_t>(tensor_read<in_t>(input, [N,IH,IW,C], [n,iy1,ix0,c]));
+        in_s_t v11 = static_cast<in_s_t>(tensor_read<in_t>(input, [N,IH,IW,C], [n,iy1,ix1,c]));
+        acc  = v00 * (unit_y - dy) * (unit_x - dx);
+        acc += v01 * (unit_y - dy) * dx;
+        acc += v10 * dy * (unit_x - dx);
+        acc += v11 * dy * dx;
+        tensor_write<out_t>(output, [N,OH,OW,C], [n,oy,ox,c], acc);
+    } else if (mode==NEAREST) {
+        int32_t iy, ix;
+        if (is_floating_point(resize_t)) {
+            iy = (dy >= 0.5) ? iy1 : iy0;
+            ix = (dx >= 0.5) ? ix1 : ix0;
+        } else {
+            iy = (2 * dy >= scale_y_n) ? iy1 : iy0;
+            ix = (2 * dx >= scale_x_n) ? ix1 : ix0;
+        }
+        in_t v = tensor_read<in_t>(input, [N,IH,IW,C], [n,iy,ix,c]);
+        tensor_write<out_t>(output, [N,OH,OW,C], [n,oy,ox,c], v);
+    }
+}
diff --git a/pseudocode/operators/REVERSE.tosac b/pseudocode/operators/REVERSE.tosac
new file mode 100644
index 0000000..63830d2
--- /dev/null
+++ b/pseudocode/operators/REVERSE.tosac
@@ -0,0 +1,16 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(axis < 0 || axis >= rank(shape));
+for_each(index in shape) {
+    dim_t tmp_index = index;
+    tmp_index[axis] = shape[axis] - 1 - index[axis];
+    in_out_t value = tensor_read<in_out_t>(input, shape, tmp_index);
+    tensor_write<in_out_t>(output, shape, index, value);
+}
diff --git a/pseudocode/operators/RFFT2D.tosac b/pseudocode/operators/RFFT2D.tosac
new file mode 100644
index 0000000..f664826
--- /dev/null
+++ b/pseudocode/operators/RFFT2D.tosac
@@ -0,0 +1,24 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(!power_of_two(H));
+ERROR_IF(!power_of_two(W));
+
+for_each(0 <= n < N, 0 <= oy < H, 0 <= ox < W/2 + 1) {
+    in_out_t sum_real = 0.0;
+    in_out_t sum_imag = 0.0;
+    for_each(0 <= iy < H, 0 <= ix < W) {
+        in_out_t val_real = tensor_read<in_out_t>(input_real, [N,H,W], [n,iy,ix]);
+        float_t a = 2 * pi() * ((iy * oy) / H + (ix * ox) / W);
+        sum_real += val_real * cos(a);
+        sum_imag += -val_real * sin(a);
+    }
+    tensor_write<in_out_t>(output_real, [N,H,W], [n,oy,ox], sum_real);
+    tensor_write<in_out_t>(output_imag, [N,H,W], [n,oy,ox], sum_imag);
+}
diff --git a/pseudocode/operators/RSQRT.tosac b/pseudocode/operators/RSQRT.tosac
new file mode 100644
index 0000000..15d884a
--- /dev/null
+++ b/pseudocode/operators/RSQRT.tosac
@@ -0,0 +1,20 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index);
+    in_out_t result;
+    if (value1 < 0) {
+        result = NaN;
+    }
+    else {
+        result = 1.0 / apply_sqrt<in_out_t>(value1);
+    }
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/SCATTER.tosac b/pseudocode/operators/SCATTER.tosac
new file mode 100644
index 0000000..5027816
--- /dev/null
+++ b/pseudocode/operators/SCATTER.tosac
@@ -0,0 +1,31 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+
+// The following array is used to check compliance that an output position
+// is modified at most once.
+bool_t output_modified[N,K,C];
+
+// Copy the values_in tensor to the values_out tensor.
+// Values not written by the scatter operation are unchanged in the output.
+for_each(0 <= n < N, 0 <= k < K, 0 <= c < C) {
+    in_out_t value = tensor_read<in_out_t>(values_in, [N,K,C], [n,k,c]);
+    tensor_write<in_out_t>(values_out, [N,K,C], [n, k, c], value);
+    output_modified[n,k,c]=false;
+}
+
+// Now perform the SCATTER operation, modifying the positions from the indices tensor
+for_each(0 <= n < N, 0 <= w < W, 0 <= c < C) {
+    index_t k = tensor_read<index_t>(indices, [N,W], [n,w]);
+    REQUIRE(0 <= k && k < K);
+    REQUIRE(output_modified[n,k,c] == false);
+    in_out_t value = tensor_read<in_out_t>(input, [N,W,C], [n,w,c]);
+    tensor_write<in_out_t>(values_out, [N,K,C], [n, k, c], value);
+    output_modified[n,k,c] = true;
+}
diff --git a/pseudocode/operators/SELECT.tosac b/pseudocode/operators/SELECT.tosac
new file mode 100644
index 0000000..fe8d760
--- /dev/null
+++ b/pseudocode/operators/SELECT.tosac
@@ -0,0 +1,25 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(shape != broadcast_shape(broadcast_shape(shape1, shape2), shape3));
+for_each(index in shape) {
+    dim_t index1 = apply_broadcast(shape, shape1, index);
+    dim_t index2 = apply_broadcast(shape, shape2, index);
+    dim_t index3 = apply_broadcast(shape, shape3, index);
+    bool_t value1 = tensor_read<bool_t>(input1, shape1, index1);
+    in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+    in_out_t value3 = tensor_read<in_out_t>(input3, shape3, index3);
+    in_out_t result;
+    if (value1) {
+         result = value2;
+    } else {
+         result = value3;
+    }
+    tensor_write<in_out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/SIGMOID.tosac b/pseudocode/operators/SIGMOID.tosac
new file mode 100644
index 0000000..048523e
--- /dev/null
+++ b/pseudocode/operators/SIGMOID.tosac
@@ -0,0 +1,14 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input, shape, index);
+    value = sigmoid<in_out_t>(value1);
+    tensor_write<in_out_t>(output, shape, index, value);
+}
diff --git a/pseudocode/operators/SLICE.tosac b/pseudocode/operators/SLICE.tosac
new file mode 100644
index 0000000..0ae0214
--- /dev/null
+++ b/pseudocode/operators/SLICE.tosac
@@ -0,0 +1,28 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+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(shape1)) {
+    ERROR_IF(start[index] < 0);
+    ERROR_IF(size[index] <= 0); //Output must be positive size
+    ERROR_IF(start[index] + size[index] > shape1[index]);
+    ERROR_IF(shape[index] != size[index]);
+}
+
+for_each(index in shape) {
+    dim_t tmp_index = index;
+    for(i = 0; i < rank(shape); i++) {
+       tmp_index[i] = index[i] + start[i];
+    }
+    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/pseudocode/operators/SUB.tosac b/pseudocode/operators/SUB.tosac
new file mode 100644
index 0000000..ac88b76
--- /dev/null
+++ b/pseudocode/operators/SUB.tosac
@@ -0,0 +1,26 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+if (in_out_t == shape_t) {
+    ERROR_IF(rank(shape) != 0 || rank(shape1) != 0 || rank(shape2) != 0);
+    shape_t value1 = tensor_read<shape_t>(input1, [], []);
+    shape_t value2 = tensor_read<shape_t>(input2, [], []);
+    shape_t result = apply_sub<shape_t>(value1, value2);
+    tensor_write<shape_t>(output, [], [], result);
+} else {
+    ERROR_IF(shape != broadcast_shape(shape1, shape2));
+    for_each(index in shape) {
+        dim_t index1 = apply_broadcast(shape, shape1, index);
+        dim_t index2 = apply_broadcast(shape, shape2, index);
+        in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index1);
+        in_out_t value2 = tensor_read<in_out_t>(input2, shape2, index2);
+        in_out_t result = apply_sub_s<in_out_t>(value1, value2);
+        tensor_write<in_out_t>(output, shape, index, result);
+    }
+}
diff --git a/pseudocode/operators/TABLE.tosac b/pseudocode/operators/TABLE.tosac
new file mode 100644
index 0000000..602d49b
--- /dev/null
+++ b/pseudocode/operators/TABLE.tosac
@@ -0,0 +1,21 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+REQUIRE(length(table) == TABLE_SIZE);
+for_each(index in shape) {
+    in_t value = tensor_read<in_t>(input, shape, index);
+    out_t result;
+    if (in_t == i8_t) {
+        // value is a signed int, convert to a 0 based index
+        result = table[static_cast<int16_t>(value) + 128];
+    } else {
+        result = apply_lookup_s(static_cast<int16_t>(table), static_cast<int16_t>(value));
+    }
+    tensor_write<out_t>(output, shape, index, result);
+}
diff --git a/pseudocode/operators/TANH.tosac b/pseudocode/operators/TANH.tosac
new file mode 100644
index 0000000..1b5edba
--- /dev/null
+++ b/pseudocode/operators/TANH.tosac
@@ -0,0 +1,14 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+for_each(index in shape) {
+    in_out_t value1 = tensor_read<in_out_t>(input, shape, index);
+    value = tanh<in_out_t>(value1);
+    tensor_write<in_out_t>(output, shape, index, value);
+}
diff --git a/pseudocode/operators/TILE.tosac b/pseudocode/operators/TILE.tosac
new file mode 100644
index 0000000..d053b8f
--- /dev/null
+++ b/pseudocode/operators/TILE.tosac
@@ -0,0 +1,20 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+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>(input1, shape1, tmp_index);
+    tensor_write<in_out_t>(output, shape, index, value);
+}
diff --git a/pseudocode/operators/TRANSPOSE.tosac b/pseudocode/operators/TRANSPOSE.tosac
new file mode 100644
index 0000000..a8f0815
--- /dev/null
+++ b/pseudocode/operators/TRANSPOSE.tosac
@@ -0,0 +1,35 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+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));
+    ERROR_IF(index < 0);
+    // Ensure ranks aren't repeated
+    ERROR_IF(indexes_used[index] == true);
+    indexes_used[index] = true;
+}
+
+// Ensure that the output shapes have the properly
+// permuted shapes
+for(i = 0; i < rank(shape); i++) {
+    ERROR_IF(shape1[perms[i]] != shape[i])
+}
+
+for_each(index in shape) {
+    dim_t tmp_index = index;
+    for(i = 0; i < rank(shape); i++) {
+        tmp_index[perms[i]] = index[i]
+    }
+    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/pseudocode/operators/TRANSPOSE_CONV2D.tosac b/pseudocode/operators/TRANSPOSE_CONV2D.tosac
new file mode 100644
index 0000000..3aa0e23
--- /dev/null
+++ b/pseudocode/operators/TRANSPOSE_CONV2D.tosac
@@ -0,0 +1,35 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(in_t != i8_t  && input_zp != 0); // Zero point only allowed for int8_t
+ERROR_IF(weight_t != i8_t && weight_zp != 0);
+ERROR_IF(out_pad_top <= -KH || out_pad_bottom <= -KH);
+ERROR_IF(out_pad_left <= -KW || out_pad_right <= -KW);
+ERROR_IF(stride_y < 1 || stride_x < 1);
+ERROR_IF(OH != (IH - 1) * stride_y + out_pad_top + out_pad_bottom + KH);
+ERROR_IF(OW != (IW - 1) * stride_x + out_pad_left + out_pad_right + KW);
+ERROR_IF(BC != OC && BC != 1);
+
+for_each(index in [N, OH, OW, OC]) {
+    tensor_write<out_t>(output, [N,OH,OW,OC], index, bias[(BC == 1) ? 0 : index[3]])
+}
+for_each(0 <= n < N, 0 <= iy < IH, 0 <= ix < IW, 0 <= oc < OC,
+          0 <= ic < IC, 0 <= ky < KH,  0 <= kx < KW) {
+    index_t oy = iy * stride_y + out_pad_top + ky;
+    index_t ox = ix * stride_x + out_pad_left + kx;
+    if (oy >= 0 && oy < OH && ox >= 0 && ox < OW) {
+        out_t acc = static_cast<out_t>(tensor_read<out_t>(output, [N,OH,OW,OC], [n,oy,ox,oc]));
+        out_t value = static_cast<out_t>(tensor_read<in_t>(input, [N,IH,IW,IC], [n,iy,ix,ic]));
+        out_t weight = static_cast<out_t>(tensor_read<weight_t>(weight, [OC,KH,KW,IC], [oc,ky,kx,ic]));
+        value = apply_sub_s<out_t>(value, static_cast<out_t>(input_zp));
+        weight = apply_sub_s<out_t>(weight, static_cast<out_t>(weight_zp));
+        acc = apply_add_s<out_t>(acc, apply_mul_s<out_t>(value, weight));
+        tensor_write<out_t>(output, [N,OH,OW,OC], [n,oy,ox,oc], acc);
+    }
+}
diff --git a/pseudocode/operators/VARIABLE.tosac b/pseudocode/operators/VARIABLE.tosac
new file mode 100644
index 0000000..4d2fce7
--- /dev/null
+++ b/pseudocode/operators/VARIABLE.tosac
@@ -0,0 +1,33 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+
+tensor_t var_tensor = variable_tensor_lookup(uid);
+
+// Invocation for the first time
+if (var_tensor == NULL) {
+  // Allocate the persistent mutable memory for the variable tensor
+  tensor_t var_tensor = variable_tensor_allocate<var_t>(var_shape, uid);
+
+  if (initial_value != NULL) {
+    REQUIRE(var_t == in_t);
+    REQUIRE(var_shape == shape);
+    for_each (index in shape) {
+      // Copy data from initial_value to var_tensor
+      in_t value = tensor_read<in_t>(initial_value, shape, index);
+      tensor_write<in_t>(var_tensor.data, var_shape, index, value);
+    }
+    var_tensor.is_written = true;
+  }
+} else { // Variable tensor has already been declared
+  // It's invalid to declare the second variable with the same uid in a single graph execution,
+  REQUIRE(!var_tensor.seen);
+}
+
+var_tensor.seen = true;
diff --git a/pseudocode/operators/VARIABLE_READ.tosac b/pseudocode/operators/VARIABLE_READ.tosac
new file mode 100644
index 0000000..c2e0e38
--- /dev/null
+++ b/pseudocode/operators/VARIABLE_READ.tosac
@@ -0,0 +1,26 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+
+tensor_t variable_tensor = variable_tensor_lookup(uid);
+// Check this variable tensor has been decalred
+REQUIRE(variable_tensor != NULL);
+// Check this variable tensor has been written
+REQUIRE(variable_tensor.is_written);
+// Output tensor's shape and variable_tensor's shape have to match
+REQUIRE(variable_tensor.shape == shape);
+//  Output tensor's shape and variable_tensor's type have to match
+REQUIRE(variable_tensor.type == out_t);
+
+for_each (index in shape) {
+    // Read data from pseudo-buffer resource to the output
+    out_t value = tensor_read<tensor_t>(variable_tensor.data, variable_tensor.shape, index);
+    tensor_write<out_t>(input1, shape, index, value);
+}
+
diff --git a/pseudocode/operators/VARIABLE_WRITE.tosac b/pseudocode/operators/VARIABLE_WRITE.tosac
new file mode 100644
index 0000000..83c5525
--- /dev/null
+++ b/pseudocode/operators/VARIABLE_WRITE.tosac
@@ -0,0 +1,29 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+
+tensor_t. variable_tensor = variable_tensor_lookup(uid);
+// Check this variable tensor has been declared
+REQUIRE(variable_tensor);
+// The tensor has to be seen before to be written to
+// The seen variable is cleared before each graph execution and set in declaration
+REQUIRE(variable_tensor.seen);
+//  Input tensor's shape and variable_tensor's shape have to match
+REQUIRE(variable_tensor.shape == shape);
+//  Input tensor's shape and variable_tensor's type have to match
+REQUIRE(variable_tensor.type == in_t);
+
+for_each (index in shape) {
+    // Write data from the input to the pseudo-buffer resource
+    in_t value = tensor_read<in_t>(input1, shape, index);
+    tensor_write<tensor_t>(variable_tensor.data, variable_tensor.shape, index, value);
+}
+
+variable_tensor.is_written = true;
+
diff --git a/pseudocode/operators/WHILE_LOOP.tosac b/pseudocode/operators/WHILE_LOOP.tosac
new file mode 100644
index 0000000..dae96d5
--- /dev/null
+++ b/pseudocode/operators/WHILE_LOOP.tosac
@@ -0,0 +1,33 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+ERROR_IF(tosa_nesting_depth >= MAX_NESTING);
+ERROR_IF(tensor_list_shape(input_list) != tosa_list_shape(output_list));
+ERROR_IF(tensor_list_shape(input_list) != tosa_input_shape(cond_graph));
+ERROR_IF(tensor_list_shape(input_list) != tosa_input_shape(body_graph));
+ERROR_IF(tensor_list_shape(input_list) != tosa_output_shape(body_graph));
+// Condition graph output must be a single element tensor with a single bool value
+ERROR_IF(tensor_size(tosa_output_shape(cond_graph)) != 1);
+ERROR_IF(tosa_output_type(cond_graph) != bool_t);
+
+// The iteration number 'i' is included to give unique names to variables
+// in each iteration of the loop and is not required by implementations
+int32_t i=0;             // iteration number
+tensor_list_t list[];    // array of tensor lists indexed by iteration
+bool_t *condition[];     // array of condition tensors indexed by iteration
+list[i] = input_list;    // copy input data as list[0]
+tosa_nesting_depth++;
+tosa_execute_graph(cond_graph, list[i], [ condition[i] ]);   // initial condition
+while (condition[i][0]) {
+    tosa_execute_graph(body_graph, list[i], list[i+1]);
+    i = i+1;
+    tosa_execute_graph(cond_graph, list[i], [ condition[i] ]);
+}
+tosa_nesting_depth--;
+output_list = list[i];
diff --git a/pseudocode/operators/tables/ERF.tosac b/pseudocode/operators/tables/ERF.tosac
new file mode 100644
index 0000000..0ff29ff
--- /dev/null
+++ b/pseudocode/operators/tables/ERF.tosac
@@ -0,0 +1,16 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+int16_t erf_reference(int16_t x) { // input x range is -256 to + 256 inclusive
+    F64 v = (double)x / (double)64;
+    v = erf(v);
+    return round_to_nearest_int(32768.0 * v);
+}
+
+generate_lookup_table(&erf_table, &erf_reference);
diff --git a/pseudocode/operators/tables/SIGMOID.tosac b/pseudocode/operators/tables/SIGMOID.tosac
new file mode 100644
index 0000000..dad1e1d
--- /dev/null
+++ b/pseudocode/operators/tables/SIGMOID.tosac
@@ -0,0 +1,16 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+int16_t sigmoid_reference(int16_t x) { // input x range is -256 to + 256 inclusive
+    fp64_t v = (fp64_t)x / (fp64_t)16;
+    v = 1.0/(1.0 + exp(-v));
+    return round_to_nearest_int(32768.0 * v);
+}
+
+generate_lookup_table(&sigmoid_table, &sigmoid_reference);
diff --git a/pseudocode/operators/tables/TANH.tosac b/pseudocode/operators/tables/TANH.tosac
new file mode 100644
index 0000000..b45f121
--- /dev/null
+++ b/pseudocode/operators/tables/TANH.tosac
@@ -0,0 +1,17 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020-2024 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
+// by a licensing agreement from ARM Limited.
+
+int16_t tanh_reference(int16_t x) {  // input x range is -256 to +256 inclusive
+    fp64_t v = (fp64_t)x/(fp64_t)32;
+    v = exp(-2.0*v);
+    v = (1.0-v)/(1.0+v);
+    return round_to_nearest_int(32768.0 * v);
+}
+
+generate_lookup_table(&tanh_table, &tanh_reference);