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//
// This confidential and proprietary software may be used only as
// authorised by a licensing agreement from ARM Limited
// (C) COPYRIGHT 2020-2022 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.
=== Type Conversion
==== CAST
Casts a tensor from one data type to another.
include::{generated}/operators/CAST.adoc[]
*Operation Function:*
[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(in);
} else {
out = truncate(in);
}
tensor_write<out_t>(output, shape, index, out)
}
----
==== RESCALE
Rescale quantized values into a new domain. This function scales by factor: multiplier * 2^-shift^.
include::{generated}/operators/RESCALE.adoc[]
*Operation Function:*
[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 != int8_t &&
in_t != uint8_t &&
in_t != uint16_t && input_zp != 0);
ERROR_IF(out_t != int8_t &&
out_t != uint8_t &&
out_t != uint16_t && output_zp != 0);
ERROR_IF(in_t == uint16_t && (input_zp != 0 || input_zp != 32768));
ERROR_IF(out_t == uint16_t && (output_zp != 0 || output_zp != 32768));
ERROR_IF(scale32 && in_t == int48_t);
ERROR_IF(!scale32 && double_round);
int48_t value = tensor_read<in_t>(input, shape, index);
value = value - input_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]);
result = (out_t)apply_clip<int32_t>(result + output_zp, minimum<out_t>, maximum<out_t>);
tensor_write<out_t>(output, shape, index, result);
}
----
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