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ValueError: Tried to convert 'x' to a tensor and failed. Error: Cannot create a tensor proto whose content is larger than 2GB. #4

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lxyzler opened this issue Aug 22, 2019 · 4 comments
Open

ValueError: Tried to convert 'x' to a tensor and failed. Error: Cannot create a tensor proto whose content is larger than 2GB. #4

lxyzler opened this issue Aug 22, 2019 · 4 comments

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@lxyzler
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lxyzler commented Aug 22, 2019 •
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Traceback (most recent call last):
File "train.py", line 95, in
training_model.fit_generator(train_generator, steps_per_epoch=int(train_generator.nb_samples / train_generator.batch_size), epochs=cfg.nb_epochs, verbose=1, workers=cfg.nb_workers, use_multiprocessing=True, callbacks=callbacks)
File "/home/sherry/.local/lib/python3.6/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/home/sherry/.local/lib/python3.6/site-packages/keras/engine/training.py", line 1418, in fit_generator
initial_epoch=initial_epoch)
File "/home/sherry/.local/lib/python3.6/site-packages/keras/engine/training_generator.py", line 223, in fit_generator
callbacks.on_batch_end(batch_index, batch_logs)
File "/home/sherry/.local/lib/python3.6/site-packages/keras/callbacks.py", line 115, in on_batch_end
callback.on_batch_end(batch, logs)
File "/home/sherry/CRNN-master/utils.py", line 130, in on_batch_end
accuracy, correct_char_predictions = self.evaluate()
File "/home/sherry/CRNN-master/utils.py", line 162, in evaluate
ctc_decode = K.ctc_decode(y_pred[:, 2:, :], input_length=np.ones(shape[0])*shape[1])[0][0]
File "/home/sherry/.local/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py", line 4289, in ctc_decode
y_pred = tf.log(tf.transpose(y_pred, perm=[1, 0, 2]) + epsilon())
File "/usr/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 1420, in transpose
ret = transpose_fn(a, perm, name=name)
File "/usr/anaconda3/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 8927, in transpose
"Transpose", x=x, perm=perm, name=name)
File "/usr/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 528, in _apply_op_helper
(input_name, err))

how to solve the problem?
@lxyzler lxyzler changed the title How to make the lexicon file? ValueError: Tried to convert 'x' to a tensor and failed. Error: Cannot create a tensor proto whose content is larger than 2GB. Aug 28, 2019
@janzd
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janzd commented Aug 29, 2019

What are the specs of the machine you use? Particularly the GPU.
And tell me your TF and Keras version too, please.

@lxyzler
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lxyzler commented Aug 29, 2019 via email

@janzd
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janzd commented Aug 30, 2019 •
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I haven't tested it with TF 1.12 and Keras version higher than 2.2, but I think it should work with those versions too.
How large is your input? This error indicates that it tried to initialize a variable larger than 2 GB, which doesn't work by default. https://stackoverflow.com/questions/51470991/create-a-tensor-proto-whose-content-is-larger-than-2gb

It uses Synth90k annotation. There is a file, let's call it annotation.txt, that contains paths to images and the IDs of the words in those images. Example:

img/wither.jpg 4
img/illager.jpg 1
img/ENDER.jpg 2
img/vindicator.jpg 5
img/PILLAGER.jpg 0
img/evoker.jpg 3

Then, you have a file lexicon.txt where all words (in your case sequences of Chinese characters) are stored. The above-mentioned IDs correspond to line numbers in this file (the first line is 0).

PILLAGER
illager
ENDER
evoker
wither
vindicator

If you'd rather use your format, which I like better than the Synth90k format actually, you'd have rewrite the data loading part of the code.

@lxyzler
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lxyzler commented Aug 31, 2019

I have rewrite the data_generator
File "/home/sherry/CRNN-master/utils.py", line 162, in evaluate
ctc_decode = K.ctc_decode(y_pred[:, 2:, :], input_length=np.ones(shape[0])*shape[1])[0][0]

I try the Synth90k,in this case,y_pred[:, 2:, :].shape is (5000, 48, 37)
if l use my dataset,the shape is (5000, 48, 5990),because l have 5990 Chinese characters
Does this cause problems?y_pred[:, 2:, :] can not be too large?

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@janzd @lxyzler