diff options
Diffstat (limited to 'chapters/ewise_binary.adoc')
| -rw-r--r-- | chapters/ewise_binary.adoc | 339 |
1 files changed, 17 insertions, 322 deletions
diff --git a/chapters/ewise_binary.adoc b/chapters/ewise_binary.adoc index 27efb44..dcd44b4 100644 --- a/chapters/ewise_binary.adoc +++ b/chapters/ewise_binary.adoc @@ -14,15 +14,7 @@ Elementwise addition of input1 and input2. Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/ADD.adoc[] *Operation Function:* @@ -38,32 +30,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|signed 32|int32_t -|MI, MT|fp16|fp16_t -|MI, MT|bf16|bf16_t -|MI, MT|fp32|fp32_t -|=== - ==== ARITHMETIC_RIGHT_SHIFT Elementwise arithmetic right shift of input1 by the amount specified in input2. Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Attribute|bool_t|round|-|If true then the shift is rounded -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/ARITHMETIC_RIGHT_SHIFT.adoc[] *Operation Function:* @@ -89,30 +61,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|signed 8|int8_t -|Any|signed 16|int16_t -|Any|signed 32|int32_t -|=== - ==== BITWISE_AND Elementwise bitwise AND of input1 and input2. Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor of same type as the input tensors, with broadcast shape if necessary -|=== +include::{generated}/operators/BITWISE_AND.adoc[] *Operation Function:* @@ -128,30 +82,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|signed 8|int8_t -|Any|signed 16|int16_t -|Any|signed 32|int32_t -|=== - ==== BITWISE_OR Elementwise bitwise OR of input1 and input2. Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/BITWISE_OR.adoc[] *Operation Function:* @@ -167,30 +103,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|signed 8|int8_t -|Any|signed 16|int16_t -|Any|signed 32|int32_t -|=== - ==== BITWISE_XOR Elementwise bitwise XOR of input1 and input2. Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/BITWISE_XOR.adoc[] *Operation Function:* @@ -206,16 +124,6 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|signed 8|int8_t -|Any|signed 16|int16_t -|Any|signed 32|int32_t -|=== - ==== INTDIV Elementwise integer divide of input1 by input2. @@ -224,15 +132,7 @@ Expected use is for operations on non-scaled integers. Floating point divide should use RECIPROCAL and MUL. Quantized integer divide should use TABLE (for 1/x) and MUL. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/INTDIV.adoc[] *Operation Function:* @@ -252,27 +152,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* -|=== -|Profile|Mode|in_out_t - -|Any|signed 32|int32_t -|=== - ==== LOGICAL_AND Elementwise logical AND of input1 and input2. Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/LOGICAL_AND.adoc[] *Operation Function:* @@ -288,28 +173,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|Bool|bool_t -|=== - ==== LOGICAL_LEFT_SHIFT Elementwise left shift of input1 and input2. Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/LOGICAL_LEFT_SHIFT.adoc[] *Operation Function:* @@ -326,30 +195,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|signed 8|int8_t -|Any|signed 16|int16_t -|Any|signed 32|int32_t -|=== - ==== LOGICAL_RIGHT_SHIFT Elementwise logical right shift of input1 by the amount specified in input2. Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/LOGICAL_RIGHT_SHIFT.adoc[] *Operation Function:* @@ -366,30 +217,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|signed 8|int8_t -|Any|signed 16|int16_t -|Any|signed 32|int32_t -|=== - ==== LOGICAL_OR Elementwise logical OR of input1 and input2. Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/LOGICAL_OR.adoc[] *Operation Function:* @@ -405,28 +238,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|Bool|bool_t -|=== - ==== LOGICAL_XOR Elementwise logical XOR of input1 and input2. Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor of same type as the input tensors, with broadcast shape if necessary -|=== +include::{generated}/operators/LOGICAL_XOR.adoc[] *Operation Function:* @@ -442,28 +259,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|Bool|bool_t -|=== - ==== MAXIMUM Elementwise max of input1 and input2. Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/MAXIMUM.adoc[] *Operation Function:* @@ -479,31 +280,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|signed 32|int32_t -|MI, MT|fp16|fp16_t -|MI, MT|bf16|bf16_t -|MI, MT|fp32|fp32_t -|=== - ==== MINIMUM Elementwise minimum of input1 and input2. Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/MINIMUM.adoc[] *Operation Function:* @@ -519,32 +301,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|signed 32|int32_t -|MI, MT|fp16|fp16_t -|MI, MT|bf16|bf16_t -|MI, MT|fp32|fp32_t -|=== - ==== MUL Elementwise multiplication (Hadamard product) of input1 and input2. Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_t*|input1|shape1|Input tensor -|Input|in_t*|input2|shape2|Input tensor with the same rank as input1 -|Input (MT profile) Attribute (BI/MI profiles)|uint6_t|shift|-|Result right shift (int32_t data type only) -|Output|out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/MUL.adoc[] *Operation Function:* @@ -570,32 +332,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* -|=== -|Profile|Mode|in_t|out_t - -|Any|signed 8|int8_t|int32_t -|Any|signed 16|int16_t|int32_t -|Any|signed 32|int32_t|int32_t -|MI, MT|fp16|fp16_t|fp16_t -|MI, MT|bf16|bf16_t|bf16_t -|MI, MT|fp32|fp32_t|fp32_t -|=== - ==== POW Elementwise input1 value raised to the power of input2. Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor from 1 to 4 dims -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor of same type as the input tensors, with broadcast shape if necessary -|=== +include::{generated}/operators/POW.adoc[] *Operation Function:* @@ -611,30 +353,12 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|MI, MT|fp16|fp16_t -|MI, MT|bf16|bf16_t -|MI, MT|fp32|fp32_t -|=== - ==== SUB Elementwise subtraction of input1 and input2. Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_out_t*|input1|shape1|Input tensor -|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary -|=== +include::{generated}/operators/SUB.adoc[] *Operation Function:* @@ -650,17 +374,6 @@ for_each(index in shape) { } ---- -*Supported Data Types:* - -|=== -|Profile|Mode|in_out_t - -|Any|signed 32|int32_t -|MI, MT|fp16|fp16_t -|MI, MT|bf16|bf16_t -|MI, MT|fp32|fp32_t -|=== - ==== TABLE Table lookup operation. @@ -677,15 +390,7 @@ An int16_t to int16_t table lookup can be constructed in TOSA as follows: * Use the TABLE operator to produce a fixed point 16.7 interpolated result * Use RESCALE (in_t=int32_t, out_t=int16_t, scale=1<<14, shift=21) to scale the output to int16_t range (or alternate scale as required) -*Arguments:* - -|=== -|Argument|Type|Name|Shape|Description - -|Input|in_t*|Input|shape|Input tensor -|Input (MT profile) Attribute (BI/MI profiles)|table_t*|table|[TABLE_SIZE]|Lookup table tensor -|Output|out_t*|output|shape|Output tensor -|=== +include::{generated}/operators/TABLE.adoc[] *Operation Function:* @@ -704,13 +409,3 @@ for_each(index in shape) { tensor_write<out_t>(output, shape, index, result); } ---- - -*Supported Data Types:* - -|=== -|Profile|Mode|in_t|table_t|TABLE_SIZE|out_t - -|Any|signed 8|int8_t|int8_t|256|int8_t -|Any|signed 16|int16_t|int16_t|513|int32_t -|=== - |