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what use tensorflow estimator create multi-input

By : Anton Korhonen
Date : October 17 2020, 08:10 PM
hop of those help? Sorry my English is poor =。= , First, name input placeholders:
code :
input_image = keras.layers.Input(shape=(182, 182, 3),name='image')
input_anchor = keras.layers.Input(shape=(182, 182, 3),name='anchor')

def input_fn(data, epochs, batch_size):
    # Convert the inputs to a Dataset.
    dataset = tf.data.Dataset.from_tensor_slices(({'image':data[0],'anchor':data[1]}, data[2]))
    # Shuffle, repeat, and batch the examples.
    SHUFFLE_SIZE = 1000
    dataset = dataset.shuffle(SHUFFLE_SIZE).repeat(epochs).batch(batch_size)
    dataset = dataset.prefetch(2)
    # Return the dataset.
    return dataset
est_model.train(lambda :input_fn(train_data,EPOCHS,BATCH_SIZE))

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Tensorflow contrib.learn.Estimator multi-GPU

By : Brij Mohan Negi
Date : March 29 2020, 07:55 AM
help you fix your problem In order to use the contrib.learn.Estimator for multi-GPU training, I am attempting to specify GPU assignments in my model_fn. , Along with Estimator leaving contrib in Tensorflow 1.0 this is fixed.

TensorFlow estimator.predict() gives WARNING:tensorflow:Input graph does not contain a QueueRunner

By : Vairamani S
Date : March 29 2020, 07:55 AM
hop of those help? I hit this too, reading the thread https://github.com/tensorflow/tensorflow/issues/11621

Tensorflow Estimator API :How to get weights of each node of a trained model using estimator api of tensorflow

By : Jason w
Date : March 29 2020, 07:55 AM
Hope this helps Yes, it should be possible to do so. You can extract the trainable variables names with:
code :
train_var_names = [var.name for var in tf.trainable_variables()]
weights_0 = dnn_model.get_variable_value(train_var_names[0])

What is the difference between tf.estimator.Estimator and tf.contrib.learn.Estimator in TensorFlow

By : Elray
Date : March 29 2020, 07:55 AM
wish helps you I wondered the same and cannot give a definitive answer, but I have a few educated guesses that might help you:
It seems that tf.estimator.Estimator together with a model function that returns tf.estimator.EstimatorSpec is the most current one that is used in the newer examples and the one to be used in new code.

Multi GPU/Tower setup Tensorflow 1.2 Estimator

By : venkatajax
Date : March 29 2020, 07:55 AM
should help you out Actually you can implement multi GPU in model_fn function same as before.
You can find full code in here. It is support multi threading queue reader and multi GPU to very high speed training when using estimator.
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