keras data generator to tensorflow input
I am trying to train a deep learning model in a distributive way. I have built my model in Keras and now I need to transform my model to a tensorflow estimator in order for it to work. Since my dataset is already big enough and it will grow bigger as I collect more data, I used ImageDataGenerator followed by flow_from_directory. I specify that I want batches of size 32 with desired shape, which is (299, 299, 3). Therefore, the output are batches of (32, 299, 299, 3). Before, I just feed the objects to model.fit_generator and Keras takes care of the rest.
So far, I have converted my Keras model to a tensorflow estimator, but I can't figure out if I can use the object from the flow_from_directory to train the data using tf.train. I have already tried to write my own input_fn but I got confused. Your help is highly appreciated.
python tensorflow keras
asked Nov 19 '18 at 13:19
lambda93lambda93
112
add a comment |
I am trying to train a deep learning model in a distributive way. I have built my model in Keras and now I need to transform my model to a tensorflow estimator in order for it to work. Since my dataset is already big enough and it will grow bigger as I collect more data, I used ImageDataGenerator followed by flow_from_directory. I specify that I want batches of size 32 with desired shape, which is (299, 299, 3). Therefore, the output are batches of (32, 299, 299, 3). Before, I just feed the objects to model.fit_generator and Keras takes care of the rest.
So far, I have converted my Keras model to a tensorflow estimator, but I can't figure out if I can use the object from the flow_from_directory to train the data using tf.train. I have already tried to write my own input_fn but I got confused. Your help is highly appreciated.
python tensorflow keras
asked Nov 19 '18 at 13:19
lambda93lambda93
112
add a comment |
I am trying to train a deep learning model in a distributive way. I have built my model in Keras and now I need to transform my model to a tensorflow estimator in order for it to work. Since my dataset is already big enough and it will grow bigger as I collect more data, I used ImageDataGenerator followed by flow_from_directory. I specify that I want batches of size 32 with desired shape, which is (299, 299, 3). Therefore, the output are batches of (32, 299, 299, 3). Before, I just feed the objects to model.fit_generator and Keras takes care of the rest.
So far, I have converted my Keras model to a tensorflow estimator, but I can't figure out if I can use the object from the flow_from_directory to train the data using tf.train. I have already tried to write my own input_fn but I got confused. Your help is highly appreciated.
python tensorflow keras
asked Nov 19 '18 at 13:19
lambda93lambda93
112
I am trying to train a deep learning model in a distributive way. I have built my model in Keras and now I need to transform my model to a tensorflow estimator in order for it to work. Since my dataset is already big enough and it will grow bigger as I collect more data, I used ImageDataGenerator followed by flow_from_directory. I specify that I want batches of size 32 with desired shape, which is (299, 299, 3). Therefore, the output are batches of (32, 299, 299, 3). Before, I just feed the objects to model.fit_generator and Keras takes care of the rest.
So far, I have converted my Keras model to a tensorflow estimator, but I can't figure out if I can use the object from the flow_from_directory to train the data using tf.train. I have already tried to write my own input_fn but I got confused. Your help is highly appreciated.
python tensorflow keras
python tensorflow keras
asked Nov 19 '18 at 13:19
lambda93lambda93
112
asked Nov 19 '18 at 13:19
lambda93lambda93
112
asked Nov 19 '18 at 13:19
lambda93lambda93
112
asked Nov 19 '18 at 13:19
lambda93lambda93
112
asked Nov 19 '18 at 13:19
lambda93lambda93
112
112
add a comment |
add a comment |
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