Convert Tensorflow String to Python String

How to convert a string tensor to a python string in Tensorflow?

tf.train.string_input_producer() return a queue, not a string. You have to use Graph operation, which get string tensor from this queue and read file from disk. For example you can use chain of operation:

image = tf.image.decode_jpeg(tf.read_file(filename_queue.dequeue()))

if you have jpeg files.

In TensorFlow 1.2 there is new structure Dataset for creating input pipeline. I think it is good idea to use Dataset instead queues.

Convert Tensorflow strings.split output to an Int

a_id is a tensor of UTF-8 string bytes, not integer bytes. That's why you keep getting the wrong integer.

Use python decode() and encode() to translate between string bytes and python strings.

In your case, to get the string version of byte_id, do byte_id.decode()

how to get string value out of tf.tensor which dtype is string

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 with tf.executing_eagerly() returning True)
• Replace tf.py_func with tf.py_function
• Replace all in-function references of file_path with file_path.numpy()

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