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# YouTube-8M Tensorflow Starter Code
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+ ** WARNING** : The project is under construction. You can use it, but you do so
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+ at your own risk.
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This repo contains starter code (written in TensorFlow 2.x) for training and
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evaluating machine learning models over the [ YouTube-8M] [ 1 ] dataset.
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This is the Tensorflow2 version of the original starter code:
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```
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The code can be run in different modes: ` train / train_and_eval / eval ` .
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- Run ` yt8m_train .py` and specify which mode you wish to execute.
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+ Run ` train .py` and specify which mode you wish to execute.
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Training is done using frame-level features with video-level labels,
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while inference can be done at segment-level.
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Setting ` segment_labels=True ` in your configuration forces
@@ -95,7 +98,7 @@ The following commands will train a model on Google Cloud over frame-level
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features.
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``` bash
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- python3 yt8m_train .py --mode=' train' \
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+ python3 train .py --mode=' train' \
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--experiment=' yt8m_experiment' \
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--model_dir=$MODEL_DIR \
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--config_file=$CONFIG_FILE
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as default.
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``` bash
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- python3 yt8m_train .py --mode=' train_and_eval' \
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+ python3 train .py --mode=' train_and_eval' \
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--experiment=' yt8m_experiment' \
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--model_dir=$MODEL_DIR \
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--config_file=$CONFIG_FILE \
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Running on evaluation mode loads saved checkpoint from specified path
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and runs inference task.
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``` bash
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- python3 yt8m_train .py --mode=' eval' \
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+ python3 train .py --mode=' eval' \
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--experiment=' yt8m_experiment' \
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--model_dir=$MODEL_DIR \
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--config_file=$CONFIG_FILE
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