How do I print the half-precision / bfloat16 values from in a (binary) file?

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04-10-2024

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Demystifying Half-Precision and bfloat16 Values in Binary Files

Have you ever stumbled upon a binary file filled with half-precision (FP16) or bfloat16 values, and found yourself wondering how to extract and display them? This is a common challenge faced by data scientists and engineers working with machine learning models, which often utilize these reduced-precision formats for memory efficiency and faster processing. Let's break down how to tackle this task.

Understanding the Problem:

Binary files store data in a compact, raw format, making it difficult for humans to interpret. Half-precision and bfloat16 are both 16-bit floating-point formats, offering a smaller size compared to the standard 32-bit single-precision (FP32). The challenge lies in converting these binary representations to their human-readable decimal equivalents.

Illustrative Example:

Imagine you have a binary file named "data.bin" containing a sequence of bfloat16 values. Here's a simplified example of how the data might look in a hex editor:

0x3F80 0x4000 0x3F00 0x4040 0x3F80

This represents five bfloat16 values, each occupying two bytes (hexadecimal pairs). Our goal is to transform this raw binary data into a readable format like:

1.0 2.0 1.5 2.5 1.0

Decoding the Mysteries:

1. Understanding the Format:

   • Both FP16 and bfloat16 use 16 bits to represent a floating-point number.
   • FP16 follows the IEEE 754 standard, allocating 1 bit for the sign, 5 bits for the exponent, and 10 bits for the mantissa.
   • bfloat16 prioritizes the exponent (8 bits) over the mantissa (7 bits), sacrificing precision for a wider range of values.

2. Leveraging Libraries:

   • Libraries like NumPy in Python provide powerful tools for handling binary data and performing conversions.
   • NumPy's fromfile() function allows you to read binary data directly into a NumPy array, making it easy to work with.

Python Code Example (bfloat16):

import numpy as np

# Open the binary file
with open("data.bin", "rb") as f:
    # Read the file into a NumPy array (dtype=np.float16)
    data = np.fromfile(f, dtype=np.float16)

# Convert the array to bfloat16 using NumPy's casting 
data_bfloat16 = data.astype(np.float16)

# Print the values
print(data_bfloat16) 

Explanation:

1. The code reads the binary file into a NumPy array using np.fromfile().
2. The dtype=np.float16 specifies that the binary data represents half-precision values.
3. We then cast the array to bfloat16 using astype(np.float16) to ensure accurate representation.
4. Finally, the code prints the converted bfloat16 values, resulting in the desired output.

Additional Notes:

• For FP16 values, the code remains similar, but you'll need to find a library or function specifically designed to handle FP16 conversion.
• The accuracy of the printed values depends on the precision of the conversion process and the limitations of the underlying data type.

Conclusion:

By understanding the format and leveraging appropriate libraries like NumPy, you can easily extract and print half-precision or bfloat16 values from binary files. This empowers you to explore and analyze data stored in these compact formats, further accelerating your machine learning and data analysis workflows.