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use std::ops::Deref;
use std::sync::Arc;
use model::{eval_order_for_nodes, Model, Node, TVec};
use ops::Value;
use tensor::Tensor;
use Result;
#[derive(Debug, Clone)]
pub struct RawSimplePlan {
pub model: Model,
pub input_ids: Vec<usize>,
pub output_ids: Vec<usize>,
pub order: Vec<usize>,
}
impl RawSimplePlan {
pub fn new(
model: &Model,
inputs: &[impl AsRef<str>],
outputs: &[impl AsRef<str>],
) -> Result<RawSimplePlan> {
let input_ids: Vec<usize> = inputs
.iter()
.map(|n| Ok(model.node_by_name(n.as_ref())?.id))
.collect::<Result<_>>()?;
let output_ids: Vec<usize> = outputs
.iter()
.map(|n| Ok(model.node_by_name(n.as_ref())?.id))
.collect::<Result<_>>()?;
let order = eval_order_for_nodes(&model.nodes(), &*output_ids)?;
Ok(RawSimplePlan {
model: model.clone(),
order,
input_ids,
output_ids,
})
}
}
#[derive(Debug, Clone)]
pub struct SimplePlan(Arc<RawSimplePlan>);
impl Deref for SimplePlan {
type Target = RawSimplePlan;
fn deref(&self) -> &RawSimplePlan {
&self.0
}
}
impl SimplePlan {
pub fn new(
model: &Model,
inputs: &[impl AsRef<str>],
outputs: &[impl AsRef<str>],
) -> Result<SimplePlan> {
Ok(SimplePlan(Arc::new(RawSimplePlan::new(
model, inputs, outputs,
)?)))
}
pub fn run(&self, inputs: TVec<Tensor>) -> Result<Vec<TVec<Tensor>>> {
let mut state = SimpleState::new(&self)?;
state.set_inputs(inputs)?;
for &n in &self.order {
if state.values[n].is_none() {
state.compute_one(n)?;
}
}
state.take_outputs()
}
pub fn state(&self) -> Result<SimpleState> {
SimpleState::new(self)
}
}
#[derive(Clone, Debug)]
pub struct SimpleState {
plan: SimplePlan,
pub values: Vec<Option<TVec<Value>>>,
}
impl SimpleState {
pub fn new(plan: &SimplePlan) -> Result<SimpleState> {
Ok(SimpleState {
plan: plan.clone(),
values: vec![None; plan.model.nodes.len()],
})
}
pub fn reset(&mut self) -> Result<()> {
self.values.iter_mut().for_each(|s| *s = None);
Ok(())
}
pub fn set_inputs(&mut self, inputs: TVec<Tensor>) -> Result<()> {
let SimpleState {
ref plan,
ref mut values,
} = self;
inputs
.into_iter()
.zip(plan.input_ids.iter())
.for_each(|(t, &id)| values[id] = Some(tvec![t.into()]));
Ok(())
}
pub fn set_input(&mut self, input: usize, t: Tensor) -> Result<()> {
let id = self.plan.input_ids[input];
self.values[id] = Some(tvec![t.into()]);
Ok(())
}
pub fn take_outputs(&mut self) -> Result<Vec<TVec<Tensor>>> {
let mut v = vec![];
for &id in &self.plan.output_ids {
v.push(
self.values[id]
.take()
.ok_or("Value is not computed")?
.into_iter()
.map(Value::into_tensor)
.collect(),
)
}
Ok(v)
}
pub fn set_values(&mut self, id: usize, values: TVec<Tensor>) -> Result<()> {
self.values[id] = Some(values.into_iter().map(|t| t.into()).collect());
Ok(())
}
pub fn set_value(&mut self, id: usize, value: Tensor) -> Result<()> {
self.set_values(id, tvec!(value))
}
pub fn compute_one(&mut self, node: usize) -> Result<()> {
let node: &Node = &self.plan.model.nodes[node];
let mut inputs: TVec<Value> = tvec![];
for i in &node.inputs {
let prec_node = &self.model().nodes[i.node];
let prec = self.values[i.node].as_ref().ok_or(format!(
"Computing {}, precursor {} not done:",
node.name, prec_node.name
))?;
inputs.push(prec[i.slot].clone().into())
}
let values = node.op.eval(inputs)?;
self.values[node.id] = Some(values);
Ok(())
}
pub fn compute_recursively(&mut self, node: usize) -> Result<()> {
let precs: Vec<usize> = self.plan.model.nodes[node]
.inputs
.iter()
.map(|i| i.node)
.collect();
for i in precs.into_iter() {
if self.values[i].is_none() {
self.compute_recursively(i)?
}
}
let mut inputs: TVec<Value> = tvec![];
let node: &Node = &self.plan.model.nodes[node];
for i in &node.inputs {
inputs.push(self.values[i.node].as_ref().unwrap()[i.slot].clone().into())
}
let values = node.op.eval(inputs)?;
self.values[node.id] = Some(values);
Ok(())
}
pub fn take_by_name(&mut self, name: &str) -> Result<TVec<Tensor>> {
let id = self.model().node_by_name(name)?.id;
Self::take(self, id)
}
pub fn take(&mut self, id: usize) -> Result<TVec<Tensor>> {
Ok(self.values[id]
.take()
.ok_or("Value is not computed")?
.into_iter()
.map(Value::into_tensor)
.collect())
}
pub fn model(&self) -> &Model {
&self.plan.model
}
}