I'm trying to use tf.contrib.training.stratified_sample in Tensorflow to balance classes. I made a quick example below to test it, drawing samples from two unbalanced classes in a balanced way and verifying it, but I'm getting an error.
import tensorflow as tf
from tensorflow.python.framework import ops
from tensorflow.python.framework import dtypes
batch_size = 10
data = ['a']*9990+['b']*10
labels = [1]*9990+[0]*10
data_tensor = ops.convert_to_tensor(data, dtype=dtypes.string)
label_tensor = ops.convert_to_tensor(labels)
target_probs = [0.5,0.5]
data_batch, label_batch = tf.contrib.training.stratified_sample(
data_tensor, label_tensor, target_probs, batch_size,
queue_capacity=2*batch_size)
with tf.Session() as sess:
d,l = sess.run(data_batch,label_batch)
print('percentage "a" = %.3f' % (np.sum(l)/len(l)))
The error I'm getting is:
Traceback (most recent call last):
File "/home/jason/code/scrap.py", line 56, in <module>
test_stratified_sample()
File "/home/jason/code/scrap.py", line 47, in test_stratified_sample
queue_capacity=2*batch_size)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/contrib/training/python/training/sampling_ops.py", line 191, in stratified_sample
with ops.name_scope(name, 'stratified_sample', tensors + [labels]):
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/math_ops.py", line 829, in binary_op_wrapper
y = ops.convert_to_tensor(y, dtype=x.dtype.base_dtype, name="y")
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py", line 676, in convert_to_tensor
as_ref=False) File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py", line 741, in internal_convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/constant_op.py", line 113, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/constant_op.py", line 102, in constant
tensor_util.make_tensor_proto(value, dtype=dtype, shape=shape, verify_shape=verify_shape))
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/tensor_util.py", line 374, in make_tensor_proto
_AssertCompatible(values, dtype)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/tensor_util.py", line 302, in _AssertCompatible
(dtype.name, repr(mismatch), type(mismatch).__name__)) TypeError: Expected string, got list containing Tensors of type '_Message' instead.
The error doesn't explain what I'm doing wrong. I also tried putting the raw data and labels in (without converting to a tensor), as well as tried using tf.train.slice_input_producer to create an initial queue of the data and label tensors.
Has anyone gotten stratified_sample to work? I haven't been able to find any examples.