diff options
Diffstat (limited to 'chapters/ewise_unary.adoc')
| -rw-r--r-- | chapters/ewise_unary.adoc | 140 |
1 files changed, 70 insertions, 70 deletions
diff --git a/chapters/ewise_unary.adoc b/chapters/ewise_unary.adoc index 633b8ac..326cc3c 100644 --- a/chapters/ewise_unary.adoc +++ b/chapters/ewise_unary.adoc @@ -18,8 +18,8 @@ Elementwise absolute value operation |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape|Input tensor -|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Input|in_out_t*|input1|shape|Input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* @@ -27,17 +27,17 @@ Elementwise absolute value operation [source,c++] ---- for_each(index in shape) { - in_t value1 = tensor_read<in_t>(input1, shape, index); + in_out_t value1 = tensor_read<in_out_t>(input1, shape, index); if (value1 < 0) - value1 = apply_sub<in_t>(0, value1); - tensor_write<in_t>(output, shape, index, value1); + value1 = apply_sub<in_out_t>(0, value1); + tensor_write<in_out_t>(output, shape, index, value1); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|signed 32|int32_t |MI, MT|floating-point|float_t @@ -52,8 +52,8 @@ Elementwise bitwise NOT of input tensor. |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape|Input tensor -|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Input|in_out_t*|input1|shape|Input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* @@ -61,16 +61,16 @@ Elementwise bitwise NOT of input tensor. [source,c++] ---- for_each(index in shape) { - in_t value1 = tensor_read<in_t>(input1, shape, index); - in_t result = ~value1; - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|signed 8|int8_t |Any|signed 16|int16_t @@ -86,8 +86,8 @@ Elementwise ceiling operation |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape|Input tensor -|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Input|in_out_t*|input1|shape|Input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* @@ -95,16 +95,16 @@ Elementwise ceiling operation [source,c++] ---- for_each(index in shape) { - in_t value1 = tensor_read<in_t>(input1, shape, index); - in_t result = apply_ceil<in_t>(value1); - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |MI, MT|floating-point|float_t |=== @@ -118,8 +118,8 @@ Elementwise count leading zeros operation |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape|Input tensor -|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Input|in_out_t*|input1|shape|Input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* @@ -127,15 +127,15 @@ Elementwise count leading zeros operation [source,c++] ---- for_each(index in shape) { - in_t value1 = tensor_read<in_t>(input1, shape, index); - in_t result = count_leading_zeros(value1); - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|signed 32|int32_t |=== @@ -149,8 +149,8 @@ Elementwise e to the x operation |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape|Input tensor -|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Input|in_out_t*|input1|shape|Input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* @@ -158,16 +158,16 @@ Elementwise e to the x operation [source,c++] ---- for_each(index in shape) { - in_t value1 = tensor_read<in_t>(input1, shape, index); - in_t result = apply_exp<in_t>(value1); - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |MI, MT|floating-point|float_t |=== @@ -181,8 +181,8 @@ Elementwise floor operation |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape|Input tensor -|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Input|in_out_t*|input1|shape|Input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* @@ -190,16 +190,16 @@ Elementwise floor operation [source,c++] ---- for_each(index in shape) { - in_t value1 = tensor_read<in_t>(input1, shape, index); - in_t result = apply_floor<in_t>(value1); - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |MI, MT|floating-point|float_t |=== @@ -213,8 +213,8 @@ Elementwise natural logarithm operation |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape|Input tensor -|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Input|in_out_t*|input1|shape|Input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* @@ -222,16 +222,16 @@ Elementwise natural logarithm operation [source,c++] ---- for_each(index in shape) { - in_t value1 = tensor_read<in_t>(input1, shape, index); - in_t result = apply_log<in_t>(value1); - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |MI, MT|floating-point|float_t |=== @@ -245,8 +245,8 @@ Elementwise logical NOT of input. |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape|Input tensor -|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Input|in_out_t*|input1|shape|Input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* @@ -254,16 +254,16 @@ Elementwise logical NOT of input. [source,c++] ---- for_each(index in shape) { - in_t value1 = tensor_read<in_t>(input1, shape1, index); - in_t result = !value1; - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|bool|bool_t |=== @@ -277,31 +277,31 @@ Elementwise negation operation |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape|Input tensor -|Attribute|in_t|input1_zp|-|Input 1 zero point. Must be zero for non-int8 types. -|Attribute|in_t|output_zp|-|Output zero point. Must be zero for non-int8 types. -|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Input|in_out_t*|input1|shape|Input tensor +|Attribute|in_out_t|input1_zp|-|Input 1 zero point. Must be zero for non-int8 types. +|Attribute|in_out_t|output_zp|-|Output zero point. Must be zero for non-int8 types. +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* [source,c++] ---- -ERROR_IF(in_t != int8_t && input1_zp != 0) // Zero point only for int8_t -ERROR_IF(in_t != int8_t && output_zp != 0) // Zero point only for int8_t +ERROR_IF(in_out_t != int8_t && input1_zp != 0) // Zero point only for int8_t +ERROR_IF(in_out_t != int8_t && output_zp != 0) // Zero point only for int8_t for_each(index in shape) { - in_t value1 = tensor_read<in_t>(input1, shape, index); + in_out_t value1 = tensor_read<in_out_t>(input1, shape, index); acc_t value = (acc_t)value1 - input1_zp; value = apply_sub<acc_t>(0, value); - in_t result = (in_t)apply_clip<acc_t>(value + output_zp, minimum<in_t>, maximum<in_t>); - tensor_write<in_t>(output, shape, index, result); + in_out_t result = (in_out_t)apply_clip<acc_t>(value + output_zp, minimum<in_out_t>, maximum<in_out_t>); + tensor_write<in_out_t>(output, shape, index, result); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t|acc_t +|Profile|Mode|in_out_t|acc_t |Any|signed 8|int8_t|int32_t |Any|signed 16|int16_t|int32_t @@ -318,8 +318,8 @@ Elementwise reciprocal operation. For integer operation, a TABLE should be used |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape|Input tensor -|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Input|in_out_t*|input1|shape|Input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* @@ -327,16 +327,16 @@ Elementwise reciprocal operation. For integer operation, a TABLE should be used [source,c++] ---- for_each(index in shape) { - in_t value1 = tensor_read<in_t>(input1, shape1, index); - in_t result = 1.0 / value1; - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |MI, MT|floating-point|float_t |=== @@ -350,8 +350,8 @@ Elementwise reciprocal square root operation. For integer operation, a TABLE sho |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape|Input tensor -|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Input|in_out_t*|input1|shape|Input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* @@ -359,16 +359,16 @@ Elementwise reciprocal square root operation. For integer operation, a TABLE sho [source,c++] ---- for_each(index in shape) { - in_t value1 = tensor_read<in_t>(input1, shape1, index); - in_t result = 1.0 / apply_sqrt<in_t>(value1); - tensor_write<in_t>(output, shape, index, result); + in_out_t value1 = tensor_read<in_out_t>(input1, shape1, index); + in_out_t result = 1.0 / apply_sqrt<in_out_t>(value1); + tensor_write<in_out_t>(output, shape, index, result); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |MI, MT|floating-point|float_t |=== |