//
// This confidential and proprietary software may be used only as
// authorised by a licensing agreement from ARM Limited
// (C) COPYRIGHT 2020-2023 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[]

[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<out_t>(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[]

[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 != i8_t &&
             (in_t != i16_t || input_unsigned == False) && input_zp != 0);
    ERROR_IF(out_t != i8_t &&
             (out_t != i16_t || output_unsigned == False) && output_zp != 0);
    ERROR_IF(in_t == i16_t && input_unsigned == True && input_zp != 0 && input_zp != 32768);
    ERROR_IF(out_t == i16_t && output_unsigned == True && output_zp != 0 && output_zp != 32768);
    ERROR_IF(scale32 && in_t == i48_t);
    ERROR_IF(!scale32 && double_round);
    ERROR_IF(in_t == i16_t && out_t == i32_t && input_unsigned);
    ERROR_IF(in_t == i32_t && out_t == i16_t && output_unsigned);

    in_t in_value = tensor_read<in_t>(input, shape, index);

    int48_t value, extended_in_zp;
    if (input_unsigned) {
        value = zero_extend<int48_t>(in_value);
        extended_in_zp = zero_extend<int48_t>(input_zp);
    }
    else {
        value = sign_extend<int48_t>(value);
        extended_in_zp = sign_extend<int48_t>(input_zp);
    }

    value = value - extended_in_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]);

    if (output_unsigned) {
        int32_t extended_out_zp = zero_extend<int32_t>(output_zp);
        result = apply_add_s<int32_t>(result, extended_out_zp);
        out_t out = static_cast<out_t>(apply_clip<int32_t>(result,
                                                           minimum_u<out_t>,
                                                           maximum_u<out_t>));
    }
    else {
        int32_t extended_out_zp = sign_extend<int32_t>(output_zp);
        result = apply_add_s<int32_t>(result, extended_out_zp);
        out_t out = static_cast<out_t>(apply_clip<int32_t>(result,
                                                           minimum_s<out_t>,
                                                           maximum_s<out_t>));
    }
    tensor_write<out_t>(output, shape, index, out);
}
----
