diff options
Diffstat (limited to 'chapters/ewise_binary.adoc')
| -rw-r--r-- | chapters/ewise_binary.adoc | 252 |
1 files changed, 126 insertions, 126 deletions
diff --git a/chapters/ewise_binary.adoc b/chapters/ewise_binary.adoc index c624437..aa1c86c 100644 --- a/chapters/ewise_binary.adoc +++ b/chapters/ewise_binary.adoc @@ -19,9 +19,9 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match |=== |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 -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -31,17 +31,17 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); - in_t result = apply_add<in_t>(value1, value2); - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|signed 32|int32_t |MI, MT|floating-point|float_t @@ -57,10 +57,10 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match |=== |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|in_out_t*|input1|shape1|Input tensor +|Input|in_out_t*|input2|shape2|Input tensor with the same rank as input1 |Input|bool_t|round|-|If true then the shift is rounded -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|Output|in_out_t*|output|shape|Output tensor with broadcast shape if necessary |=== *Operation Function:* @@ -70,27 +70,27 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); + 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_t == int32_t && 0 <= value2 && value2 <= 31) || - (in_t == int16_t && 0 <= value2 && value2 <= 15) || - (in_t == int8_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_t result = value1 >> value2; + in_out_t result = value1 >> value2; if (round == true && value2 > 0 && (value1 >> (value2 - 1)) & 1 != 0) { result = result + 1; } - result = apply_clip<in_t>(result, minimum<in_t>, maximum<in_t>); - tensor_write<in_t>(output, shape, index, result); + result = apply_clip<in_out_t>(result, minimum<in_out_t>, maximum<in_out_t>); + 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 @@ -107,9 +107,9 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. |=== |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 -|Output|in_t*|output|shape|Output tensor of same type as the input tensors, with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -119,17 +119,17 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); - in_t result = value1 & value2; - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|signed 8|int8_t |Any|signed 16|int16_t @@ -146,9 +146,9 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. |=== |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 -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -158,17 +158,17 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); - in_t result = value1 | value2; - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|signed 8|int8_t |Any|signed 16|int16_t @@ -185,9 +185,9 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. |=== |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 -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -197,17 +197,17 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); - in_t result = value1 ^ value2; - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|signed 8|int8_t |Any|signed 16|int16_t @@ -227,9 +227,9 @@ Quantized integer divide should use TABLE (for 1/x) and MUL. |=== |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 -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -239,20 +239,20 @@ Quantized integer divide should use TABLE (for 1/x) and MUL. for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); + 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_t> by -1 + // 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_t>); - in_t result = value1 / value2; - tensor_write<in_t>(output, shape, index, result); + REQUIRE((int64_t)value1 / value2 <= maximum<in_out_t>); + in_out_t result = value1 / value2; + 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 |=== @@ -267,9 +267,9 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match |=== |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 -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -279,17 +279,17 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); - in_t result = value1 && value2; - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|Bool|bool_t |=== @@ -304,9 +304,9 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match |=== |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 -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -316,18 +316,18 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); + 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_t result = value1 << value2; - tensor_write<in_t>(output, shape, index, result); + in_out_t result = value1 << value2; + 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 @@ -344,9 +344,9 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match |=== |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 -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -356,18 +356,18 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); + 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_t result = (in_t)((unsigned in_t)value1 >> value2); - tensor_write<in_t>(output, shape, index, result); + in_out_t result = (in_out_t)((unsigned in_out_t)value1 >> value2); + 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 @@ -384,9 +384,9 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. |=== |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 -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -396,17 +396,17 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); - in_t result = value1 || value2; - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|Bool|bool_t |=== @@ -421,9 +421,9 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. |=== |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 -|Output|in_t*|output|shape|Output tensor of same type as the input tensors, with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -433,17 +433,17 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); - in_t result = value1 != value2; - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|Bool|bool_t |=== @@ -458,9 +458,9 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match |=== |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 -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -470,17 +470,17 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); - in_t result = apply_max(value1, value2); - tensor_write<in_t>(output, shape, index, result); + 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(value1, value2); + 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 |MI, MT|floating-point|float_t @@ -496,9 +496,9 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match |=== |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 -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -508,17 +508,17 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); - in_t result = apply_min(value1, value2); - tensor_write<in_t>(output, shape, index, result); + 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(value1, value2); + 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 |MI, MT|floating-point|float_t @@ -579,9 +579,9 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape1|Input tensor from 1 to 4 dims -|Input|in_t*|input2|shape2|Input tensor with the same rank as input1 -|Output|in_t*|output|shape|Output tensor of same type as the input tensors, with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -591,17 +591,17 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); - in_t result = apply_pow<in_t>(value1, value2); - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |MI, MT|floating-point|float_t |=== @@ -616,9 +616,9 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. |=== |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 -|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary +|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 |=== *Operation Function:* @@ -628,17 +628,17 @@ Axis of size 1 will be broadcast as necessary. Rank of input tensors must match. for_each(index in shape) { index1 = apply_broadcast(shape, shape1, index); 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); - in_t result = apply_sub<in_t>(value1, value2); - tensor_write<in_t>(output, shape, index, result); + 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); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|signed 32|int32_t |MI, MT|floating-point|float_t |