I got nothing after i've run disambiguating a sentence command

[talatccan]

Hi, im trying to convert project from python 2.x to python 3.x

Train and prediction commands are working without any problem now. Therewithal i get nothing when i run disambiguating a sentence command.

Here is the command i've run:

python train.py --command disambiguate --train_filepath data/train.merge.utf8 --test_filepath data/test.merge.utf8 --model_path ./models/ntd-nmd-20170619-06.epoch-32-val_acc-0.99507.hdf5 --label2ids_path ./models/ntd-nmd-20170619-06.epoch-32-val_acc-0.99507.hdf5.label2ids --run_name testing

Here is the output:

C:\Users\talat\PycharmProjects\TurkishMorp\lib\site-packages\h5py\__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from floattonp.floating
is deprecated. In future, it will be treated asnp.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
Using TensorFlow backend.
Tensor("sentences_word_root_input:0", shape=(?, 66, 24, 41), dtype=int32)
Tensor("char_embedding_layer/embedding_lookup:0", shape=(?, 64944, 100), dtype=float32)
lstm_layer_output_relu Tensor("activation_1/Relu:0", shape=(?, 1584, 200), dtype=float32)
lstm_layer_output_relu_reshaped Tensor("reshape_2/Reshape:0", shape=(?, 66, 24, 200), dtype=float32)
Tensor("tag_embedding_layer/embedding_lookup:0", shape=(?, 36432, 100), dtype=float32)
lstm_layer_output_relu Tensor("activation_2/Relu:0", shape=(?, 1584, 200), dtype=float32)
lstm_layer_output_relu_reshaped Tensor("reshape_4/Reshape:0", shape=(?, 66, 24, 200), dtype=float32)
char_lstm_layer_output Tensor("reshape_2/Reshape:0", shape=(?, 66, 24, 200), dtype=float32)
R_matrix Tensor("activation_3/Tanh:0", shape=(?, 66, 24, 200), dtype=float32)
Tensor("char_embedding_layer_1/embedding_lookup:0", shape=(?, 2706, 100), dtype=float32)
char_bi_lstm_outputs Tensor("time_distributed_3/Reshape_2:0", shape=(?, 66, 200), dtype=float32)
sentence_level_bi_lstm_outputs Tensor("bidirectional_4/add_16:0", shape=(?, ?, 200), dtype=float32)
sentence_level_bi_lstm_outputs_tanh Tensor("activation_4/Tanh:0", shape=(?, ?, 200), dtype=float32)
h Tensor("activation_4/Tanh:0", shape=(?, ?, 200), dtype=float32)
INPUTS TO LAMBDA: [<tf.Tensor 'activation_3/Tanh:0' shape=(?, 66, 24, 200) dtype=float32>, <tf.Tensor 'activation_4/Tanh:0' shape=(?, ?, 200) dtype=float32>]
p Tensor("p/truediv:0", shape=(?, 66, 24), dtype=float32)

Reading script from "tfeatures.scr"
0%>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>100%
0%>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>100%
0%>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>100%

***** LEXICON LOOK-UP *****

LOOKUP STATISTICS (success with different strategies):
strategy 0: 0 times (-1.#J %)
strategy 1: 0 times (-1.#J %)
strategy 2: 0 times (-1.#J %)
strategy 3: 0 times (-1.#J %)
not found: 0 times (-1.#J %)

corpus size: 0 words
execution time: 0 sec
speed: 0 words/sec

***** END OF LEXICON LOOK-UP *****

sentence with length 0? C:\Users\talat\AppData\Local\Temp\tmp0equejn5 []
file processed
sentence with length 0? C:\Users\talat\AppData\Local\Temp\tmp0equejn5 []
file processed`