use log::trace;
use runmat_accelerate_api::{GpuTensorHandle, HostTensorView};
use runmat_builtins::{CharArray, IntValue, Tensor, Value};
use runmat_macros::runtime_builtin;
use crate::builtins::common::{
gpu_helpers,
spec::{
BroadcastSemantics, BuiltinFusionSpec, BuiltinGpuSpec, ConstantStrategy, GpuOpKind,
ReductionNaN, ResidencyPolicy, ScalarType, ShapeRequirements,
},
tensor,
};
use crate::builtins::math::type_resolvers::numeric_unary_type;
use crate::{build_runtime_error, BuiltinResult, RuntimeError};
const BUILTIN_NAME: &str = "uint16";
const UINT16_MAX_F64: f64 = u16::MAX as f64;
#[runmat_macros::register_gpu_spec(builtin_path = "crate::builtins::math::elementwise::uint16")]
pub const GPU_SPEC: BuiltinGpuSpec = BuiltinGpuSpec {
name: "uint16",
op_kind: GpuOpKind::Elementwise,
supported_precisions: &[ScalarType::F32, ScalarType::F64],
broadcast: BroadcastSemantics::Matlab,
provider_hooks: &[],
constant_strategy: ConstantStrategy::InlineLiteral,
residency: ResidencyPolicy::NewHandle,
nan_mode: ReductionNaN::Include,
two_pass_threshold: None,
workgroup_size: None,
accepts_nan_mode: false,
notes: "No provider-native uint16 hook yet; gpuArray inputs gather to host for saturating conversion and are then re-uploaded when possible.",
};
#[runmat_macros::register_fusion_spec(builtin_path = "crate::builtins::math::elementwise::uint16")]
pub const FUSION_SPEC: BuiltinFusionSpec = BuiltinFusionSpec {
name: "uint16",
shape: ShapeRequirements::BroadcastCompatible,
constant_strategy: ConstantStrategy::InlineLiteral,
elementwise: None,
reduction: None,
emits_nan: false,
notes:
"Runs outside fusion today because integer storage remains host-represented in f64 buffers.",
};
fn builtin_error(message: impl Into<String>) -> RuntimeError {
build_runtime_error(message)
.with_builtin(BUILTIN_NAME)
.build()
}
fn conversion_error(type_name: &str) -> RuntimeError {
builtin_error(format!(
"uint16: conversion to uint16 from {type_name} is not possible"
))
}
#[runtime_builtin(
name = "uint16",
category = "math/elementwise",
summary = "Convert scalars, arrays, and gpuArray values to uint16 using MATLAB saturating rounding.",
keywords = "uint16,cast,integer,conversion,gpuArray",
accel = "unary",
type_resolver(numeric_unary_type),
builtin_path = "crate::builtins::math::elementwise::uint16"
)]
async fn uint16_builtin(value: Value, rest: Vec<Value>) -> BuiltinResult<Value> {
if !rest.is_empty() {
return Err(builtin_error("uint16: too many input arguments"));
}
match value {
Value::Num(n) => Ok(Value::Int(IntValue::U16(cast_scalar_to_uint16(n)))),
Value::Int(i) => Ok(Value::Int(IntValue::U16(cast_scalar_to_uint16(i.to_f64())))),
Value::Bool(flag) => Ok(Value::Int(IntValue::U16(if flag { 1 } else { 0 }))),
Value::Tensor(tensor) => Ok(uint16_value_from_tensor(uint16_tensor_to_host(tensor))),
Value::LogicalArray(array) => {
let tensor = tensor::logical_to_tensor(&array)
.map_err(|e| builtin_error(format!("uint16: {e}")))?;
Ok(uint16_value_from_tensor(uint16_tensor_to_host(tensor)))
}
Value::CharArray(chars) => uint16_from_char_array(chars),
Value::GpuTensor(handle) => uint16_from_gpu(handle).await,
Value::Complex(_, _) | Value::ComplexTensor(_) => Err(conversion_error("complex")),
Value::String(_) | Value::StringArray(_) => Err(conversion_error("string")),
Value::Cell(_) => Err(conversion_error("cell")),
Value::Struct(_) => Err(conversion_error("struct")),
Value::Object(obj) => Err(conversion_error(&obj.class_name)),
Value::HandleObject(handle) => Err(conversion_error(&handle.class_name)),
Value::Listener(_) => Err(conversion_error("event.listener")),
Value::FunctionHandle(_) | Value::Closure(_) => Err(conversion_error("function_handle")),
Value::ClassRef(_) => Err(conversion_error("meta.class")),
Value::MException(_) => Err(conversion_error("MException")),
Value::OutputList(_) => Err(conversion_error("OutputList")),
}
}
fn uint16_from_char_array(chars: CharArray) -> BuiltinResult<Value> {
let data: Vec<f64> = chars
.data
.iter()
.map(|&ch| cast_scalar_to_uint16(ch as u32 as f64) as f64)
.collect();
let tensor = Tensor::new(data, vec![chars.rows, chars.cols])
.map_err(|e| builtin_error(format!("uint16: {e}")))?;
Ok(uint16_value_from_tensor(tensor))
}
async fn uint16_from_gpu(handle: GpuTensorHandle) -> BuiltinResult<Value> {
let converted = uint16_tensor_to_host(gpu_helpers::gather_tensor_async(&handle).await?);
if let Some(provider) = runmat_accelerate_api::provider_for_handle(&handle) {
let _ = provider.free(&handle);
let view = HostTensorView {
data: &converted.data,
shape: &converted.shape,
};
match provider.upload(&view) {
Ok(new_handle) => return Ok(Value::GpuTensor(new_handle)),
Err(err) => trace!("uint16: provider upload failed after gather ({err})"),
}
}
Ok(uint16_value_from_tensor(converted))
}
fn uint16_tensor_to_host(mut tensor: Tensor) -> Tensor {
for value in &mut tensor.data {
*value = cast_scalar_to_uint16(*value) as f64;
}
tensor
}
fn uint16_value_from_tensor(tensor: Tensor) -> Value {
if tensor.data.len() == 1 {
Value::Int(IntValue::U16(cast_scalar_to_uint16(tensor.data[0])))
} else {
Value::Tensor(tensor)
}
}
fn cast_scalar_to_uint16(value: f64) -> u16 {
if value.is_nan() {
return 0;
}
if value.is_infinite() {
return if value.is_sign_negative() {
0
} else {
u16::MAX
};
}
value.round().clamp(0.0, UINT16_MAX_F64) as u16
}
#[cfg(test)]
pub(crate) mod tests {
use super::*;
use crate::builtins::common::test_support;
use futures::executor::block_on;
use runmat_accelerate_api::HostTensorView;
use runmat_builtins::{ResolveContext, Type};
fn uint16_builtin(value: Value, rest: Vec<Value>) -> BuiltinResult<Value> {
block_on(super::uint16_builtin(value, rest))
}
#[test]
fn uint16_type_preserves_tensor_shape() {
let out = numeric_unary_type(
&[Type::Tensor {
shape: Some(vec![Some(2), Some(3)]),
}],
&ResolveContext::new(Vec::new()),
);
assert_eq!(
out,
Type::Tensor {
shape: Some(vec![Some(2), Some(3)])
}
);
}
#[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
#[test]
fn uint16_scalar_saturates_and_rounds() {
assert_eq!(
uint16_builtin(Value::Num(3.5), Vec::new()).expect("uint16"),
Value::Int(IntValue::U16(4))
);
assert_eq!(
uint16_builtin(Value::Num(-1.0), Vec::new()).expect("uint16"),
Value::Int(IntValue::U16(0))
);
assert_eq!(
uint16_builtin(Value::Num(f64::INFINITY), Vec::new()).expect("uint16"),
Value::Int(IntValue::U16(u16::MAX))
);
assert_eq!(
uint16_builtin(Value::Num(f64::NAN), Vec::new()).expect("uint16"),
Value::Int(IntValue::U16(0))
);
}
#[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
#[test]
fn uint16_tensor_preserves_shape() {
let tensor = Tensor::new(vec![-2.0, 2.49, 2.5, 70000.0], vec![2, 2]).unwrap();
let result = uint16_builtin(Value::Tensor(tensor), Vec::new()).expect("uint16");
match result {
Value::Tensor(out) => {
assert_eq!(out.shape, vec![2, 2]);
assert_eq!(out.data, vec![0.0, 2.0, 3.0, u16::MAX as f64]);
}
other => panic!("expected tensor, got {other:?}"),
}
}
#[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
#[test]
fn uint16_char_array_produces_codes() {
let chars = CharArray::new_row("Az");
let result = uint16_builtin(Value::CharArray(chars), Vec::new()).expect("uint16");
match result {
Value::Tensor(t) => {
assert_eq!(t.shape, vec![1, 2]);
assert_eq!(t.data, vec![65.0, 122.0]);
}
other => panic!("expected tensor, got {other:?}"),
}
}
#[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
#[test]
fn uint16_errors_on_string_input() {
let err = uint16_builtin(Value::String("hello".to_string()), Vec::new())
.expect_err("expected error");
assert!(err.message().contains("uint16"));
assert!(err.message().contains("string"));
}
#[cfg_attr(target_arch = "wasm32", wasm_bindgen_test::wasm_bindgen_test)]
#[test]
fn uint16_gpu_roundtrip() {
test_support::with_test_provider(|provider| {
let tensor = Tensor::new(vec![-3.0, 4.4, 70000.0], vec![3, 1]).unwrap();
let view = HostTensorView {
data: &tensor.data,
shape: &tensor.shape,
};
let handle = provider.upload(&view).expect("upload");
let result = uint16_builtin(Value::GpuTensor(handle), Vec::new()).expect("uint16");
match result {
Value::GpuTensor(handle) => {
let gathered = test_support::gather(Value::GpuTensor(handle)).expect("gather");
assert_eq!(gathered.shape, vec![3, 1]);
assert_eq!(gathered.data, vec![0.0, 4.0, u16::MAX as f64]);
}
other => panic!("expected gpu tensor, got {other:?}"),
}
});
}
}