experiments/STT
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Fix #3443: Link to upstream Dockerfile for lack of correct TensorFlow GPU deps doc.

Browse Source
This commit is contained in:
Alexandre Lissy 2020-11-27 12:14:02 +01:00
parent da31812173
commit c979e360da
3 changed files with 19 additions and 16 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

7
doc/TRAINING.rst
View File

@ -3,11 +3,14 @@
Training Your Own Model Training Your Own Model
======================= =======================
.. _cuda-training-deps:
Prerequisites for training a model Prerequisites for training a model
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
* `Python 3.6 <https://www.python.org/>`_ * `Python 3.6 <https://www.python.org/>`_
* Mac or Linux environment * Mac or Linux environment
* CUDA 10.0 / CuDNN v7.6 per `Dockerfile <https://hub.docker.com/layers/tensorflow/tensorflow/1.15.4-gpu-py3/images/sha256-a5255ae38bcce7c7610816c778244309f8b8d1576e2c0023c685c011392958d7?context=explore>`_.
Getting the training code Getting the training code
^^^^^^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^
@ -69,7 +72,7 @@ If you have a capable (NVIDIA, at least 8GB of VRAM) GPU, it is highly recommend
pip3 uninstall tensorflow pip3 uninstall tensorflow
pip3 install 'tensorflow-gpu==1.15.4' pip3 install 'tensorflow-gpu==1.15.4'
Please ensure you have the required :ref:`CUDA dependency <cuda-deps>`. Please ensure you have the required `CUDA dependency <https://www.tensorflow.org/install/source#gpu>`_ and/or :ref:`Prerequisites <cuda-training-deps>`.
It has been reported for some people failure at training: It has been reported for some people failure at training:
@ -78,7 +81,7 @@ It has been reported for some people failure at training:
tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above. tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[{{node tower_0/conv1d/Conv2D}}]] [[{{node tower_0/conv1d/Conv2D}}]]
Setting the ``TF_FORCE_GPU_ALLOW_GROWTH`` environment variable to ``true`` seems to help in such cases. This could also be due to an incorrect version of libcudnn. Double check your versions with the :ref:`TensorFlow 1.15 documentation <cuda-deps>`. Setting the ``TF_FORCE_GPU_ALLOW_GROWTH`` environment variable to ``true`` seems to help in such cases. This could also be due to an incorrect version of libcudnn. Double check your versions with the :ref:`TensorFlow 1.15 documentation <cuda-training-deps>`.
Basic Dockerfile for training Basic Dockerfile for training
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

14
doc/USING.rst
View File

@ -23,10 +23,10 @@ Running ``deepspeech`` might, see below, require some runtime dependencies to be
Please refer to your system's documentation on how to install these dependencies. Please refer to your system's documentation on how to install these dependencies.
.. _cuda-deps: .. _cuda-inference-deps:
CUDA dependency CUDA dependency (inference)
^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^^^
The GPU capable builds (Python, NodeJS, C++, etc) depend on CUDA 10.1 and CuDNN v7.6. The GPU capable builds (Python, NodeJS, C++, etc) depend on CUDA 10.1 and CuDNN v7.6.
@ -37,8 +37,8 @@ If you want to use the pre-trained English model for performing speech-to-text,
.. code-block:: bash .. code-block:: bash
wget https://github.com/mozilla/DeepSpeech/releases/download/v0.7.4/deepspeech-0.7.4-models.pbmm wget https://github.com/mozilla/DeepSpeech/releases/download/v0.9.1/deepspeech-0.9.1-models.pbmm
wget https://github.com/mozilla/DeepSpeech/releases/download/v0.7.4/deepspeech-0.7.4-models.scorer wget https://github.com/mozilla/DeepSpeech/releases/download/v0.9.1/deepspeech-0.9.1-models.scorer
There are several pre-trained model files available in official releases. Files ending in ``.pbmm`` are compatible with clients and language bindings built against the standard TensorFlow runtime. Usually these packages are simply called ``deepspeech``. These files are also compatible with CUDA enabled clients and language bindings. These packages are usually called ``deepspeech-gpu``. Files ending in ``.tflite`` are compatible with clients and language bindings built against the `TensorFlow Lite runtime <https://www.tensorflow.org/lite/>`_. These models are optimized for size and performance in low power devices. On desktop platforms, the compatible packages are called ``deepspeech-tflite``. On Android and Raspberry Pi, we only publish TensorFlow Lite enabled packages, and they are simply called ``deepspeech``. You can see a full list of supported platforms and which TensorFlow runtime is supported at :ref:`supported-platforms-inference`. There are several pre-trained model files available in official releases. Files ending in ``.pbmm`` are compatible with clients and language bindings built against the standard TensorFlow runtime. Usually these packages are simply called ``deepspeech``. These files are also compatible with CUDA enabled clients and language bindings. These packages are usually called ``deepspeech-gpu``. Files ending in ``.tflite`` are compatible with clients and language bindings built against the `TensorFlow Lite runtime <https://www.tensorflow.org/lite/>`_. These models are optimized for size and performance in low power devices. On desktop platforms, the compatible packages are called ``deepspeech-tflite``. On Android and Raspberry Pi, we only publish TensorFlow Lite enabled packages, and they are simply called ``deepspeech``. You can see a full list of supported platforms and which TensorFlow runtime is supported at :ref:`supported-platforms-inference`.
@ -136,7 +136,7 @@ Note: the following command assumes you `downloaded the pre-trained model <#gett
.. code-block:: bash .. code-block:: bash
deepspeech --model deepspeech-0.7.4-models.pbmm --scorer deepspeech-0.7.4-models.scorer --audio my_audio_file.wav deepspeech --model deepspeech-0.9.1-models.pbmm --scorer deepspeech-0.9.1-models.scorer --audio my_audio_file.wav
The ``--scorer`` argument is optional, and represents an external language model to be used when transcribing the audio. The ``--scorer`` argument is optional, and represents an external language model to be used when transcribing the audio.
@ -200,7 +200,7 @@ Note: the following command assumes you `downloaded the pre-trained model <#gett
.. code-block:: bash .. code-block:: bash
./deepspeech --model deepspeech-0.7.4-models.pbmm --scorer deepspeech-0.7.4-models.scorer --audio audio_input.wav ./deepspeech --model deepspeech-0.9.1-models.pbmm --scorer deepspeech-0.9.1-models.scorer --audio audio_input.wav
See the help output with ``./deepspeech -h`` for more details. See the help output with ``./deepspeech -h`` for more details.

14
doc/index.rst
View File

@ -20,15 +20,15 @@ To install and use DeepSpeech all you have to do is:
pip3 install deepspeech pip3 install deepspeech
# Download pre-trained English model files # Download pre-trained English model files
curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.4/deepspeech-0.7.4-models.pbmm curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.9.1/deepspeech-0.9.1-models.pbmm
curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.4/deepspeech-0.7.4-models.scorer curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.9.1/deepspeech-0.9.1-models.scorer
# Download example audio files # Download example audio files
curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.4/audio-0.7.4.tar.gz curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.9.1/audio-0.9.1.tar.gz
tar xvf audio-0.7.4.tar.gz tar xvf audio-0.9.1.tar.gz
# Transcribe an audio file # Transcribe an audio file
deepspeech --model deepspeech-0.7.4-models.pbmm --scorer deepspeech-0.7.4-models.scorer --audio audio/2830-3980-0043.wav deepspeech --model deepspeech-0.9.1-models.pbmm --scorer deepspeech-0.9.1-models.scorer --audio audio/2830-3980-0043.wav
A pre-trained English model is available for use and can be downloaded following the instructions in :ref:`the usage docs <usage-docs>`. For the latest release, including pre-trained models and checkpoints, `see the GitHub releases page <https://github.com/mozilla/DeepSpeech/releases/latest>`_. A pre-trained English model is available for use and can be downloaded following the instructions in :ref:`the usage docs <usage-docs>`. For the latest release, including pre-trained models and checkpoints, `see the GitHub releases page <https://github.com/mozilla/DeepSpeech/releases/latest>`_.
@ -44,9 +44,9 @@ Quicker inference can be performed using a supported NVIDIA GPU on Linux. See th
pip3 install deepspeech-gpu pip3 install deepspeech-gpu
# Transcribe an audio file. # Transcribe an audio file.
deepspeech --model deepspeech-0.7.4-models.pbmm --scorer deepspeech-0.7.4-models.scorer --audio audio/2830-3980-0043.wav deepspeech --model deepspeech-0.9.1-models.pbmm --scorer deepspeech-0.9.1-models.scorer --audio audio/2830-3980-0043.wav
Please ensure you have the required :ref:`CUDA dependencies <cuda-deps>`. Please ensure you have the required :ref:`CUDA dependencies <cuda-inference-deps>`.
See the output of ``deepspeech -h`` for more information on the use of ``deepspeech``. (If you experience problems running ``deepspeech``, please check :ref:`required runtime dependencies <runtime-deps>`). See the output of ``deepspeech -h`` for more information on the use of ``deepspeech``. (If you experience problems running ``deepspeech``, please check :ref:`required runtime dependencies <runtime-deps>`).