Error when running inference on an audio file

[kausthubnaarayan]

E tensorflow/core/framework/op_segment.cc:53] Create kernel failed: Invalid argument: NodeDef mentions attr ‘identical_element_shapes’ not in Op<name=TensorArrayV3; signature=size:int32 -> handle:resource, flow:float; attr=dtype:type; attr=element_shape:shape,default=; attr=dynamic_size:bool,default=false; attr=clear_after_read:bool,default=true; attr=tensor_array_name:string,default=""; is_stateful=true>; NodeDef: bidirectional_rnn/bw/bw/TensorArray_1 = TensorArrayV3clear_after_read=true, dtype=DT_FLOAT, dynamic_size=false, element_shape=[?,750], identical_element_shapes=true, tensor_array_name=“bidirectional_rnn/bw/bw/dynamic_rnn/input_0”, _device="/job:localhost/replica:0/task:0/device:CPU:0". (Check whether your GraphDef-interpreting binary is up to date with your GraphDef-generating binary.).

please help

[kausthubnaarayan]

I have created my model by running this:

python -u DeepSpeech.py \ --train_files ../audo_files_sample/split_files/train-1.csv \ --dev_files ../audo_files_sample/split_files/dev-1.csv \ --test_files ../audo_files_sample/split_files/test-1.csv \ --train_batch_size 80 \ --dev_batch_size 80 \ --test_batch_size 40 \ --n_hidden 375 \ --epoch 33 \ --validation_step 1 \ --early_stop True \ --earlystop_nsteps 6 \ --estop_mean_thresh 0.1 \ --estop_std_thresh 0.1 \ --dropout_rate 0.22 \ --learning_rate 0.00095 \ --report_count 100 \ --use_seq_length False \ --export_dir ../new_model/ \ --decoder_library_path ../libctc_decoder_with_kenlm.so \ --alphabet_config_path ../new_model/alphabet.txt \ --lm_binary_path ../new_model/lm.binary \ --lm_trie_path ../new_model/trie

then when i try to run this:
deepspeech output_graph.pb ../testing_sampling/out.wav alphabet.txt

it gives me this error. Please help

[lissyx ((slow to reply) [NOT PROVIDING SUPPORT])]

Can you document the versions you used for all of that?

[kausthubnaarayan]

DeepSpeech: v0.1.1

I have created the lm.binary and trie by following the steps which is similar to this:

TUTORIAL : How I trained a specific french model to control my robot

Tutorial How to build your homemade deepspeech model from scratch Adapt links and params with your needs… For my robotic project, I needed to create a small monospeaker model, with nearly 1000 sentences orders (not just single word !) I recorded wav’s with a Respeaker Microphone Array : https://www.seeedstudio.com/ReSpeaker-Mic-Array-Far-field-w%2F-7-PDM-Microphones-p-2719.html Wav’s were recorder with the following params : mono / 16 bits / 16 k. The use of the google vad lib helped me t…

@lissyx Please let me know if you would need anyother info, which i may have missed.

This is my versions of other libraries which i have installed in a virtualenv:
absl-py==0.1.11
asn1crypto==0.24.0
backports.functools-lru-cache==1.5
backports.weakref==1.0.post1
bcrypt==3.1.4
beautifulsoup4==4.6.0
bleach==1.5.0
bs4==0.0.1
certifi==2018.1.18
cffi==1.11.5
chardet==3.0.4
cryptography==2.1.4
cycler==0.10.0
deepspeech==0.1.1
enum34==1.1.6
funcsigs==1.0.2
futures==3.2.0
html5lib==0.9999999
idna==2.6
ipaddress==1.0.19
kiwisolver==1.0.1
Markdown==2.6.11
matplotlib==2.2.0
mock==2.0.0
numpy==1.14.1
pandas==0.22.0
paramiko==2.4.0
pbr==3.1.1
progressbar2==3.36.0
protobuf==3.5.2
pyasn1==0.4.2
pycparser==2.18
PyNaCl==1.2.1
pyparsing==2.2.0
pysftp==0.2.9
python-dateutil==2.6.1
python-speech-features==0.6
python-utils==2.3.0
pytz==2018.3
pyxdg==0.26
requests==2.18.4
scipy==1.0.0
six==1.11.0
sox==1.3.2
subprocess32==3.2.7
tensorflow==1.5.0
tensorflow-tensorboard==1.5.1
urllib3==1.22
webrtcvad==2.0.10
Werkzeug==0.14.1

Thanks in advance

[lissyx ((slow to reply) [NOT PROVIDING SUPPORT])]

Can you try with native client from https://queue.taskcluster.net/v1/task/JccCd5JKTsqnucg_sknLnQ/runs/0/artifacts/public/native_client.tar.xz ?
Keep the same trained network, just update your client. I’m wondering if you are not hitting something because of training with v1.5.0 and running inference with earlier version: DeepSpeech v0.1.1 is r1.4-based.

[kausthubnaarayan]

@lissyx is this native client for mac os ?? it is giving me error.
Where can i find the binary for mac os ??

Thanks

[lissyx ((slow to reply) [NOT PROVIDING SUPPORT])]

That’s for Linux, but you can grab an OSX one at https://tools.taskcluster.net/groups/PrzjPY-ITSK6cn9x4yr3yg/tasks/U4tyZPPEQS6bZ5RHRyORFA/runs/0/artifacts

[kausthubnaarayan]

@lissyx which one from that above link do i download ?? because the previous link you had shared has the entire tar with all so files etc

[lissyx ((slow to reply) [NOT PROVIDING SUPPORT])]

pick public/native_client.tar.xz if you want the C++ client

[kausthubnaarayan]

@lissyx when i install this using this:

python util/taskcluster.py --arch osx --target .

it looks like it is downloading from:
https://index.taskcluster.net/v1/task/project.deepspeech.deepspeech.native_client.master.osx/artifacts/public/native_client.tar.xz

So this client is the older version having 1.4 is it ??

and which libraries version are you referring to here ??

Thanks

[lissyx ((slow to reply) [NOT PROVIDING SUPPORT])]

This command will download from latest master, use the link I gave you.

[kausthubnaarayan]

@lissyx nope still the same error.

But if i run this command on the prebuilt model which we get from this:
wget -O - https://github.com/mozilla/DeepSpeech/releases/download/v0.1.1/deepspeech-0.1.1-models.tar.gz | tar xvfz -

it works.

Only when i have built my own model i get this error.

[lissyx ((slow to reply) [NOT PROVIDING SUPPORT])]

Can you make sure you ran the C++ client ? I suspect you are still referring to the Python module. Can you precisely document your steps to run ?

‘identical_element_shapes is something that has been added recently, I think r1.5. That’s likely why you are running into that issue.

[kausthubnaarayan]

@lissyx Sorry for that miss from my side.
I used the c++ client now, but am getting this error:

Reading alphabet.txt ----5---10---15---20---25---30---35---40---45---50---55---60---65---70---75---80---85---90---95--100 libc++abi.dylib: terminating with uncaught exception of type lm::FormatLoadException: native_client/kenlm/lm/read_arpa.cc:65 in void lm::ReadARPACounts(util::FilePiece &, std::vector<uint64_t> &) threw FormatLoadException. first non-empty line was "a" not \data\. Byte: 218

[lissyx ((slow to reply) [NOT PROVIDING SUPPORT])]

Ok, that’s my fault, I forgot to tell you that WAV argument has been moved to the end :). So try: ./deepspeech output_graph.pb alphabet.txt ../testing_sampling/out.wav

[kausthubnaarayan]

@lissyx Thanks it works now.

Just curious as to what is this version you are talking about ?? is it deepspeech version ??
Also is c++ binary different in the way it works from the python one ??

[lissyx ((slow to reply) [NOT PROVIDING SUPPORT])]

No, the C++ binary mostly equivalent to what you have in Python. The version I’m referring to is the one that is embedded in the packages / tarball. It’s the TensorFlow version we used to build.

[kausthubnaarayan]

So the python project is built with 1.5 is it ??
But the native client is not updated for python ??

[lissyx ((slow to reply) [NOT PROVIDING SUPPORT])]

No, it’s about what has been released to PyPI/npm and what we have on TaskCluster. Latest version “released” is v0.1.1, based on r1.4. But newer binaries are available from TaskCluster. It will be updated on PyPI/NPM when we do a new release.

[kausthubnaarayan]

Got it. Thanks for patiently helping me out