ct.convert(convert_to="mlprogram", compute_precision=ct.precision.FLOAT16) have precision problem for some models

[daikankan]

🐞Describing the bug

• I have checked my cases, and found for some models, ct.convert(convert_to="mlprogram", compute_precision=ct.precision.FLOAT16) have big problem of precision, while ct.convert(convert_to="mlprogram", compute_precision=ct.precision.FLOAT32) is correct. also ct.convert(convert_to="neuralnetwork") along with quantization_utils.quantize_weights(model_ct, nbits=16) is correct.

Stack Trace

To Reproduce

• sorry cannot provide model now

System environment (please complete the following information):

• coremltools version: 8.3.0
• OS (e.g. MacOS version or Linux type): MacOS_14.5 (23F79)
• Any other relevant version information (e.g. PyTorch or TensorFlow version): pytorch_2.2.2

Additional context

• NeuralNetwork and MLprogram lead to very different results #2301
• Differences between neuralnetwork and mlprogram #2481
• and so on