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ONNX: Add Floor and Ceil (#2235)

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This commit is contained in:
mokulus
2024-06-02 21:45:20 +02:00
committed by GitHub
parent 1ec3b2cc18
commit 03344d3c19
2 changed files with 162 additions and 0 deletions
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10
candle-onnx/src/eval.rs
View File

@ -877,6 +877,16 @@ pub fn simple_eval(
let output = input.relu()?; let output = input.relu()?;
values.insert(node.output[0].clone(), output); values.insert(node.output[0].clone(), output);
} }
"Ceil" => {
let input = get(&node.input[0])?;
let output = input.ceil()?;
values.insert(node.output[0].clone(), output);
}
"Floor" => {
let input = get(&node.input[0])?;
let output = input.floor()?;
values.insert(node.output[0].clone(), output);
}
// https://github.com/onnx/onnx/blob/main/docs/Operators.md#Constant // https://github.com/onnx/onnx/blob/main/docs/Operators.md#Constant
"Constant" => { "Constant" => {
let value = match node.attribute.iter().find(|attr| attr.name == "value") { let value = match node.attribute.iter().find(|attr| attr.name == "value") {

152
candle-onnx/tests/ops.rs
View File

@ -2556,3 +2556,155 @@ fn test_where() -> Result<()> {
Ok(()) Ok(())
} }
#[test]
fn test_floor() -> Result<()> {
let manual_graph = create_model_proto_with_graph(Some(GraphProto {
node: vec![NodeProto {
op_type: "Floor".to_string(),
domain: "".to_string(),
attribute: vec![],
input: vec![INPUT_X.to_string()],
output: vec![OUTPUT_Z.to_string()],
name: "".to_string(),
doc_string: "".to_string(),
}],
name: "".to_string(),
initializer: vec![],
input: vec![ValueInfoProto {
name: INPUT_X.to_string(),
doc_string: "".to_string(),
r#type: None,
}],
output: vec![ValueInfoProto {
name: OUTPUT_Z.to_string(),
doc_string: "".to_string(),
r#type: None,
}],
value_info: vec![],
doc_string: "".to_string(),
sparse_initializer: vec![],
quantization_annotation: vec![],
}));
let x = Tensor::from_vec(
// some values taken from https://numpy.org/doc/stable/reference/generated/numpy.floor.html
vec![
f64::NAN,
f64::INFINITY,
f64::NEG_INFINITY,
-1.7,
-1.5,
-0.2,
0.2,
1.5,
1.7,
2.0,
],
&[10],
&Device::Cpu,
)?;
let mut inputs: HashMap<String, Tensor> = HashMap::new();
inputs.insert(INPUT_X.to_string(), x);
let eval = candle_onnx::simple_eval(&manual_graph, inputs)?;
assert_eq!(eval.len(), 1);
let z = eval.get(OUTPUT_Z).expect("Output 'z' not found");
let results = z.to_vec1::<f64>()?;
assert!(results[0].is_nan());
assert_eq!(
results[1..],
vec![
f64::INFINITY,
f64::NEG_INFINITY,
-2.,
-2.,
-1.,
0.,
1.,
1.,
2.
]
);
Ok(())
}
#[test]
fn test_ceil() -> Result<()> {
let manual_graph = create_model_proto_with_graph(Some(GraphProto {
node: vec![NodeProto {
op_type: "Ceil".to_string(),
domain: "".to_string(),
attribute: vec![],
input: vec![INPUT_X.to_string()],
output: vec![OUTPUT_Z.to_string()],
name: "".to_string(),
doc_string: "".to_string(),
}],
name: "".to_string(),
initializer: vec![],
input: vec![ValueInfoProto {
name: INPUT_X.to_string(),
doc_string: "".to_string(),
r#type: None,
}],
output: vec![ValueInfoProto {
name: OUTPUT_Z.to_string(),
doc_string: "".to_string(),
r#type: None,
}],
value_info: vec![],
doc_string: "".to_string(),
sparse_initializer: vec![],
quantization_annotation: vec![],
}));
let x = Tensor::from_vec(
// some values taken from https://numpy.org/doc/stable/reference/generated/numpy.ceil.html
vec![
f64::NAN,
f64::INFINITY,
f64::NEG_INFINITY,
-1.7,
-1.5,
-0.2,
0.2,
1.5,
1.7,
2.0,
],
&[10],
&Device::Cpu,
)?;
let mut inputs: HashMap<String, Tensor> = HashMap::new();
inputs.insert(INPUT_X.to_string(), x);
let eval = candle_onnx::simple_eval(&manual_graph, inputs)?;
assert_eq!(eval.len(), 1);
let z = eval.get(OUTPUT_Z).expect("Output 'z' not found");
let results = z.to_vec1::<f64>()?;
assert!(results[0].is_nan());
assert_eq!(
results[1..],
vec![
f64::INFINITY,
f64::NEG_INFINITY,
-1.,
-1.,
-0.,
1.,
2.,
2.,
2.
]
);
Ok(())
}