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Pyo3 and numpy update #958

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Merged
merged 1 commit into from
Mar 18, 2022
Merged

Pyo3 and numpy update #958

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4 changes: 2 additions & 2 deletions pymoose/Cargo.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -17,10 +17,10 @@ crate-type = ["cdylib"]
[dependencies]
anyhow = "~1.0"
approx = "~0.5"
numpy = "~0.14"
numpy = "~0.16"
ndarray = "~0.15"
moose = { path = "../moose" }
pyo3 = "~0.14"
pyo3 = "~0.16"
rmp-serde = "~1.0"
serde = { version = "~1.0", features = ["derive"] }

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53 changes: 37 additions & 16 deletions pymoose/src/bindings.rs
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Expand Up @@ -23,16 +23,16 @@ fn create_computation_graph_from_py_bytes(computation: Vec<u8>) -> Computation {

fn pyobj_to_value(py: Python, obj: PyObject) -> PyResult<Value> {
let obj_ref = obj.as_ref(py);
if obj_ref.is_instance::<PyString>()? {
if obj_ref.is_instance_of::<PyString>()? {
let string_value: String = obj.extract(py)?;
Ok(Value::HostString(Box::new(HostString(
string_value,
HostPlacement::from("fake"),
))))
} else if obj_ref.is_instance::<PyFloat>()? {
} else if obj_ref.is_instance_of::<PyFloat>()? {
let float_value: f64 = obj.extract(py)?;
Ok(Value::Float64(Box::new(float_value)))
} else if obj_ref.is_instance::<PyArrayDyn<f32>>()? {
} else if obj_ref.is_instance_of::<PyArrayDyn<f32>>()? {
// NOTE: this passes for any inner dtype, since python's isinstance will
// only do a shallow typecheck. inside the pyobj_tensor_to_value we do further
// introspection on the array & its dtype to map to the correct kind of Value
Expand Down Expand Up @@ -65,19 +65,40 @@ fn pyobj_tensor_to_host_bit_tensor(py: Python, obj: &PyObject) -> HostBitTensor
fn pyobj_tensor_to_value(py: Python, obj: &PyObject) -> Result<Value, anyhow::Error> {
let dtype_obj = obj.getattr(py, "dtype")?;
let dtype: &PyArrayDescr = dtype_obj.cast_as(py).unwrap();
let np_dtype = dtype.get_datatype().unwrap();
match np_dtype {
numpy::DataType::Float32 => Ok(Value::from(pyobj_tensor_to_host_tensor::<f32>(py, obj))),
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This enum was removed as a result of this comment: PyO3/rust-numpy#256 (comment)

Not much of a conversation and/or migration guide. I think I followed the suggested path though, judging by the comments and the changes in that PR.

numpy::DataType::Float64 => Ok(Value::from(pyobj_tensor_to_host_tensor::<f64>(py, obj))),
numpy::DataType::Int8 => Ok(Value::from(pyobj_tensor_to_host_tensor::<i8>(py, obj))),
numpy::DataType::Int16 => Ok(Value::from(pyobj_tensor_to_host_tensor::<i16>(py, obj))),
numpy::DataType::Int32 => Ok(Value::from(pyobj_tensor_to_host_tensor::<i32>(py, obj))),
numpy::DataType::Int64 => Ok(Value::from(pyobj_tensor_to_host_tensor::<i64>(py, obj))),
numpy::DataType::Uint8 => Ok(Value::from(pyobj_tensor_to_host_tensor::<u8>(py, obj))),
numpy::DataType::Uint16 => Ok(Value::from(pyobj_tensor_to_host_tensor::<u16>(py, obj))),
numpy::DataType::Uint32 => Ok(Value::from(pyobj_tensor_to_host_tensor::<u32>(py, obj))),
numpy::DataType::Uint64 => Ok(Value::from(pyobj_tensor_to_host_tensor::<u64>(py, obj))),
numpy::DataType::Bool => Ok(Value::from(pyobj_tensor_to_host_bit_tensor(py, obj))),
match dtype {
dt if dt.is_equiv_to(numpy::dtype::<f32>(py)) => {
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Alternatively we can use obj.is_instance_of::<PyArrayDyn<f32>> syntax, but I think this one is a bit better.

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fwiw I also thought is_equiv_to was the right approach, so happy to go with this 👍

Ok(Value::from(pyobj_tensor_to_host_tensor::<f32>(py, obj)))
}
dt if dt.is_equiv_to(numpy::dtype::<f64>(py)) => {
Ok(Value::from(pyobj_tensor_to_host_tensor::<f64>(py, obj)))
}
dt if dt.is_equiv_to(numpy::dtype::<i8>(py)) => {
Ok(Value::from(pyobj_tensor_to_host_tensor::<i8>(py, obj)))
}
dt if dt.is_equiv_to(numpy::dtype::<i16>(py)) => {
Ok(Value::from(pyobj_tensor_to_host_tensor::<i16>(py, obj)))
}
dt if dt.is_equiv_to(numpy::dtype::<i32>(py)) => {
Ok(Value::from(pyobj_tensor_to_host_tensor::<i32>(py, obj)))
}
dt if dt.is_equiv_to(numpy::dtype::<i64>(py)) => {
Ok(Value::from(pyobj_tensor_to_host_tensor::<i64>(py, obj)))
}
dt if dt.is_equiv_to(numpy::dtype::<u8>(py)) => {
Ok(Value::from(pyobj_tensor_to_host_tensor::<u8>(py, obj)))
}
dt if dt.is_equiv_to(numpy::dtype::<u16>(py)) => {
Ok(Value::from(pyobj_tensor_to_host_tensor::<u16>(py, obj)))
}
dt if dt.is_equiv_to(numpy::dtype::<u32>(py)) => {
Ok(Value::from(pyobj_tensor_to_host_tensor::<u32>(py, obj)))
}
dt if dt.is_equiv_to(numpy::dtype::<u64>(py)) => {
Ok(Value::from(pyobj_tensor_to_host_tensor::<u64>(py, obj)))
}
dt if dt.is_equiv_to(numpy::dtype::<bool>(py)) => {
Ok(Value::from(pyobj_tensor_to_host_bit_tensor(py, obj)))
}
otherwise => Err(anyhow::Error::msg(format!(
"Unsupported numpy datatype {:?}",
otherwise
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