Comments (4)
I did the following change, and some how it worked for me.
first, add this import command in "udc_predict.py"
from tensorflow.contrib.learn.python.learn.estimators import *
change the following line from
estimator._targets_info = tf.contrib.learn.estimators.tensor_signature.TensorSignature(tf.constant(0, shape=[1,1]))
to
estimator._targets_info = tensor_signature.TensorSignature(tf.constant(0, shape=[1,1]))
Also at the bottom, change the print command from
print("{}: {:g}".format(r, prob[0,0]))
to
print("{}: {:g}".format(r, next(prob)[0]))
Hope it helps. I am using Tensorflow Version 1.8, Python 3.6.5
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i cannot find any useful solution _ORZ
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having the similar issue in google colab? tf 2.0
feature_columns = tf.contrib.learn.infer_real_valued_columns_from_input_fn
module 'tensorflow' has no attribute 'contrib'
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- the error is in function 'create_model_fn' in udc_model.py,
move "batch_size = targets.get_shape().as_list()[0]" after "if mode == tf.contrib.learn.ModeKeys.EVAL:" can fix this problem.
the reason is when in PREDICT mode, model_fn deal the param 'targets' as None.
- "prob = estimator.predict(input_fn=input_fn, as_iterable=False)" in cdc_predict.py,
the param 'as_iterable' default value is True, change to False,
the next line "prob[0,0]" can execute correct.
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