| // |
| // 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[] |
| |
| [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[] |
| |
| [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 = apply_add<int32_t>(result, output_zp); |
| out_t out = (out_t)apply_clip<int32_t>(result, minimum<out_t>, maximum<out_t>); |
| tensor_write<out_t>(output, shape, index, out); |
| } |
| ---- |