[BUG]: pybind11::format_descriptor<float16_t>::format() throws RuntimeError: NumPy type info missing for Dh but should return e

[dastrobu]

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What version (or hash if on master) of pybind11 are you using?

2.11.1

Problem description

when constructing a buffer format for a dtype float16 array, I get:

RuntimeError: NumPy type info missing for Dh. Here is a full function to reproduce:

std::string float16_format() {
  return pybind11::format_descriptor<float16_t>::format();
}

float16_t is defined as typedef __fp16 float16_t in arm_fp16.h running on MacOS.

According to the python buffer protocol specs float16 should be represented as 'e'.

Numpy and tensor flow are following this convention:

>>> memoryview(np.ones(3, dtype=np.float16)).format
'e'
>>> memoryview(tf.ones(3, dtype=tf.float16)).format
'e'

Reproducible example code

std::string float16_format() {
  return pybind11::format_descriptor<float16_t>::format();
}

Is this a regression? Put the last known working version here if it is.

Not a regression

[dastrobu]

relates to #1908

[swillisart]

Hello! Yes, it's true half floats are not currently available. You can see extra information here: #4627
and a workaround from the issue here: #1776

None of the core devs have responded to the discussion but I'm still very interested in bringing support of the half-float type from OpenEXR / Imath directly. The question is how they want to proceed with it.