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-rw-r--r--chapters/ewise_binary.adoc151
1 files changed, 58 insertions, 93 deletions
diff --git a/chapters/ewise_binary.adoc b/chapters/ewise_binary.adoc
index 876ab4b..864cf5b 100644
--- a/chapters/ewise_binary.adoc
+++ b/chapters/ewise_binary.adoc
@@ -18,22 +18,14 @@ 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);
- }
+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<in_out_t>(value1, value2);
+ tensor_write<in_out_t>(output, shape, index, result);
}
----
@@ -54,16 +46,15 @@ for_each(index in shape) {
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));
+ REQUIRE((in_out_t == int32_t && 0 <= value2 && value2 <= 31) ||
+ (in_out_t == int16_t && 0 <= value2 && value2 <= 15) ||
+ (in_out_t == int8_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) {
+ in_out_t result = value1 >> value2;
+ if (round == true && value2 > 0 && (value1 >> (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>);
+ result = apply_clip<in_out_t>(result, minimum<in_out_t>, maximum<in_out_t>);
tensor_write<in_out_t>(output, shape, index, result);
}
----
@@ -140,27 +131,18 @@ 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, [], []);
+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);
- 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);
- }
+ // This catches the case where we divide minimum<in_out_t> by -1
+ // which is not representable in two's complement
+ REQUIRE((int64_t)value1 / value2 <= maximum<in_out_t>);
+ in_out_t result = value1 / value2;
+ tensor_write<in_out_t>(output, shape, index, result);
}
----
@@ -220,9 +202,8 @@ for_each(index in shape) {
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);
+ REQUIRE(0 <= value2 && value2 <= 31);
+ in_out_t result = (in_out_t)((unsigned in_out_t)value1 >> value2);
tensor_write<in_out_t>(output, shape, index, result);
}
----
@@ -282,7 +263,7 @@ for_each(index in shape) {
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);
+ in_out_t result = apply_max(value1, value2);
tensor_write<in_out_t>(output, shape, index, result);
}
----
@@ -302,7 +283,7 @@ for_each(index in shape) {
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);
+ in_out_t result = apply_min(value1, value2);
tensor_write<in_out_t>(output, shape, index, result);
}
----
@@ -316,33 +297,25 @@ 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);
+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 == int32_t && shift > 0) {
+ int64_t product = (int64_t)value1 * (int64_t)value2;
+ int64_t round = (int64_t)1 << (shift-1);
+ product = (product + round) >> shift;
+ REQUIRE(product >= minimum<int32_t> && product <= maximum<int32_t>)
+ result = product;
+ } else {
+ result = value1 * value2; // low 32-bits of result for int32_t
}
+ tensor_write<out_t>(output, shape, index, result);
}
----
@@ -375,22 +348,14 @@ 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);
- }
+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<in_out_t>(value1, value2);
+ tensor_write<in_out_t>(output, shape, index, result);
}
----
@@ -418,11 +383,11 @@ 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) {
+ if (in_t == int8_t) {
// value is a signed int, convert to a 0 based index
- result = table[static_cast<int16_t>(value) + 128];
+ result = table[value + 128];
} else {
- result = apply_lookup_s(static_cast<int16_t>(table), static_cast<int16_t>(value));
+ result = apply_lookup(table, value);
}
tensor_write<out_t>(output, shape, index, result);
}
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-28 20:11:22 +0000