How to feed .h5 files in tf.data pipeline in tensorflow model

Question

I\'m trying to optimize the input pipeline for .h5 data with tf.data. But I encountered a TypeError: expected str, bytes or os.PathLike object, not Tensor. I did a

Answer 1

Here is an example of how you can wrap the function with the help of py_func. Do note that this is deprecated in TF V2. You can follow the documentation for further details.

def parse_function_wrapper(filename):
   # Assuming your data and labels are float32
   # Your input is parse_function, who arg is filename, and you get X and y as output
   # whose datatypes are indicated by the tuple argument  
   features, labels = tf.py_func(
       parse_function, [filename], (tf.float32, tf.float32)) 
   return features, labels

# Create dataset of filenames.
dataset = tf.data.Dataset.from_tensor_slices(flist)
dataset = dataset.shuffle(len(flist))
dataset = dataset.map(parse_function_wrapper)