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If the input is a Tensor then in Line 15 a TensorFlow Placeholder is created having data type as tf.float32 and shape of the tensor is [None, 224, 224, 3] i.e. [Batch Size, Height, Width, Channels]. None basically implies that the Batch Size is not fixed.

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Jul 11, 2020 · Understand How tf.get_variable() Initialize a Tensor When Initializer is None: A Beginner Guide – TensorFlow Tutorial; Get LSTM Cell Weights and Regularize LSTM in TensorFlow – TensorFlow Tutorial; Understand LSTM Weight and Bias Initialization When Initializer is None in TensorFlow – TensorFlow Tutorial

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get_weights() function returns a list of all weight tensors in the model, as Numpy arrays. to_json() returns a representation of the model as a JSON string. Note that the representation does not include the weights, only the architecture. save_weights(filepath) saves the weights of the model as a HDF5 file.

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Now all weights and variable data are quantized, and the model is significantly smaller compared to the original TensorFlow Lite model. However, to maintain compatibility with applications that traditionally use float model input and output tensors, the TensorFlow Lite Converter leaves the model input and output tensors in float:

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2. Working With Convolutional Neural Network. Before we start, it’ll be good to understand the working of a convolutional neural network. Basically, we will be working on the CIFAR 10 dataset, which is a dataset used for object recognition and consists of 60,000 32×32 images which contain one of the ten object classes including aeroplane, automobile, car, bird, dog, frog, horse, ship, and ...

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Aug 17, 2016 · The function also expects and returns tensors directly, so we do not need to convert to and from Python-lists anymore. Updated 2017-06-07: TensorFlow 1.0 moved recurrent cells into tf.contrib.rnn. From TensorFlow 1.2 on, recurrent cells reuse their weights, so that we need to create multiple separate GRUCells in the first code block. Moreover ...