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

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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

Start at pybind11::format_descriptor<float16_t>::format() and trace the NumPy type-info lookup for the reported Dh type. Compare the expected Python buffer format for float16 with the existing mappings, then add or update a regression test showing that the format is e.