You can use tf.py_func to wrap load_audio_file().
import tensorflow as tf
tf.enable_eager_execution()
def load_audio_file(file_path):
# you should decode bytes type to string type
print("file_path: ",bytes.decode(file_path),type(bytes.decode(file_path)))
return file_path
train_dataset = tf.data.Dataset.list_files('clean_4s_val/*.wav')
train_dataset = train_dataset.map(lambda x: tf.py_func(load_audio_file, [x], [tf.string]))
for one_element in train_dataset:
print(one_element)
file_path: clean_4s_val/1.wav <class 'str'>
(<tf.Tensor: id=32, shape=(), dtype=string, numpy=b'clean_4s_val/1.wav'>,)
file_path: clean_4s_val/3.wav <class 'str'>
(<tf.Tensor: id=34, shape=(), dtype=string, numpy=b'clean_4s_val/3.wav'>,)
file_path: clean_4s_val/2.wav <class 'str'>
(<tf.Tensor: id=36, shape=(), dtype=string, numpy=b'clean_4s_val/2.wav'>,)
UPDATE for TF 2
The above solution will not work with TF 2 (tested with 2.2.0), even when replacing tf.py_func with tf.py_function, giving
InvalidArgumentError: TypeError: descriptor 'decode' requires a 'bytes' object but received a 'tensorflow.python.framework.ops.EagerTensor'
To make it work in TF 2, make the following changes:
- Remove
tf.enable_eager_execution()(eager is enabled by default in TF 2, which you can verify withtf.executing_eagerly()returningTrue) - Replace
tf.py_funcwithtf.py_function - Replace all in-function references of
file_pathwithfile_path.numpy()