TypeError: only integer scalar arrays can be converted to a scalar index

Question

I am trying a simple demo code of tensorflow from github link.
I'm currently using python version 3.5.2

Z:\downloads\tensorflow_demo-master\tensorflow_demo-master>py Python
3.5.2 (v3.5.2:4def2a2901a5, Jun 25 2016, 22:18:55) [MSC v.1900 64 bit (AMD64)] on win32<br> Type "help", "copyright", "credits" or "license" for more information.

I ran into this error when I tried board.py in command-line. I have installed all the dependencies that are required for this to run.

def _read32(bytestream):
    dt = numpy.dtype(numpy.uint32).newbyteorder('>')
    return numpy.frombuffer(bytestream.read(4), dtype=dt)

def extract_images(filename):
    """Extract the images into a 4D uint8 numpy array [index, y, x, depth]."""
    print('Extracting', filename)
    with gzip.open(filename) as bytestream:
        magic = _read32(bytestream)
        if magic != 2051:
            raise ValueError(
                'Invalid magic number %d in MNIST image file: %s' %
                (magic, filename))
        num_images = _read32(bytestream)
        rows = _read32(bytestream)
        cols = _read32(bytestream)
        buf = bytestream.read(rows * cols * num_images)
        data = numpy.frombuffer(buf, dtype=numpy.uint8)
        data = data.reshape(num_images, rows, cols, 1)
    return data

Z:\downloads\tensorflow_demo-master\tensorflow_demo-master>py board.py
Extracting  Z:/downloads/MNIST dataset\train-images-idx3-ubyte.gz
Traceback (most recent call last):  
File "board.py", line 3, in <module>
    mnist = input_data.read_data_sets(r'Z:/downloads/MNIST dataset', one_hot=True)  
File "Z:\downloads\tensorflow_demo-master\tensorflow_demo-master\input_data.py", line 150, in read_data_sets
    train_images = extract_images(local_file) 
File "Z:\downloads\tensorflow_demo-master\tensorflow_demo-master\input_data.py", line 40, in extract_images
    buf = bytestream.read(rows * cols * num_images) 
File "C:\Users\surak\AppData\Local\Programs\Python\Python35\lib\gzip.py", line 274, in read
    return self._buffer.read(size)
TypeError: only integer scalar arrays can be converted to a scalar index

Enterovirus

Answer 1

you can modify the function:

def _read32(bytestream):
    dt = numpy.dtype(numpy.uint32).newbyteorder('>')
    return numpy.frombuffer(bytestream.read(4), dtype=dt)

new version:

def _read32(bytestream):
    dt = numpy.dtype(numpy.uint32).newbyteorder('>')
    return numpy.frombuffer(bytestream.read(4), dtype=dt)[0]

add [0] in the end.

This appears to be an issue with the latest version of Numpy. A recent change made it an error to treat a single-element array as a scalar for the purposes of indexing.

Newfangled

python 3.5.2 here. add [0] failed, but from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_sets('MNIST_data', one_hot=True) succeeded – Trepang

Answer 2

The code link you have provided uses a separate file named input_data.py to download data from MNIST using the following two lines in board.py

import input_data 
mnist = input_data.read_data_sets("/tmp/data/",one_hot=True)

Since MNIST data is so frequently used for demonstration purposes, Tensorflow provides a way to automatically download it.

Replace the above two lines in board.py with the following two lines and the error will disappear.

from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)

Antenatal

This worked for me but then got this error: w_h = tf.histogram_summary("weights", W) AttributeError: module 'tensorflow' has no attribute 'histogram_summary' – Shandishandie

having the same issue here. – Hibernal

That's because api has changed in newest version. Now histogram summary has been moved to tf.summary.histogram. – Antenatal

you are right. Both tf.histogram_summary on the line 32 need to be changed. However, now I am stuck at line 40: AttributeError: 'module' object has no attribute 'scalar_summary' – Hibernal

@Hibernal tf.summary.scalar - all summaries moved to summary module – Antenatal

Answer 3

This file is likely corrupt:

Z:/downloads/MNIST dataset\train-images-idx3-ubyte.gz

Let's analyze the error you posted.

This, indicates that code is currently working with the file in question:

Extracting  Z:/downloads/MNIST dataset\train-images-idx3-ubyte.gz

Traceback indicates that a stack trace follows:

Traceback (most recent call last):

This, indicates that you read your data sets from 'Z:/downloads/MNIST dataset':

File "board.py", line 3, in <module>
    mnist = input_data.read_data_sets(r'Z:/downloads/MNIST dataset', one_hot=True)

This, indicates that the code is extracting images:

File "Z:\downloads\tensorflow_demo-master\tensorflow_demo-master\input_data.py", line 150, in read_data_sets
    train_images = extract_images(local_file)

This, indicates that the code is expected to read rows * cols * num_images bytes:

File "Z:\downloads\tensorflow_demo-master\tensorflow_demo-master\input_data.py", line 40, in extract_images
    buf = bytestream.read(rows * cols * num_images)

This is the line that errors:

File "C:\Users\surak\AppData\Local\Programs\Python\Python35\lib\gzip.py", line 274, in read
    return self._buffer.read(size)
TypeError: only integer scalar arrays can be converted to a scalar index

I expect size is the problematic value and was calculated on the previous line of the stacktrace.

I can see at least two ways to proceed.

1. Delete the offending file and see if the problem goes away. This would allow you to verify that the file is somehow corrupt.

2. Use a debugger to step into the code and then inspect the values used to calculate the offending variable. Use the knowledge gained to proceed from there.

Vicentevicepresident