What is Weak Crossentropy 2d in TF learn explain with example

This recipe explains what is Weak Crossentropy 2d in TF learn with example

Recipe Objective

This recipe explains what is Weak Crossentropy 2d.

Sentiment Analysis Project on eCommerce Product Reviews with Source Code

Step 1: Importing Libraries

We'll import tflearn, tensorflow as tf and tflearn.datasets.mnist as mnist.

import tflearn
import tensorflow as tf
import tflearn.datasets.mnist as mnist
from __future__ import division, print_function, absolute_import

Step 2: Building Model

We have combined TFLearn built-in ops with Tensorflow graph. We have built this using MNIST Dataset.
To create a multilayer perceptron we have used TFLearn PReLU activations ops.

with tf.Graph().as_default():

    x = tf.placeholder("float", [None, 392])
    y = tf.placeholder("float", [None, 5])

    u = tf.Variable(tf.random_normal([392, 128]))
    v = tf.Variable(tf.random_normal([128, 128]))
    w = tf.Variable(tf.random_normal([128, 5]))
    a = tf.Variable(tf.random_normal([128]))
    b = tf.Variable(tf.random_normal([128]))
    c = tf.Variable(tf.random_normal([5]))

    def net(X):
       X = tflearn.prelu(tf.add(tf.matmul(X, u), a))
       tflearn.summaries.monitor_activation(x)
       X = tflearn.prelu(tf.add(tf.matmul(X, v), b))
       tflearn.summaries.monitor_activation(x)
       X = tf.nn.softmax(tf.add(tf.matmul(X, w), c))
       return X

    my_net = net(x)

Step 3: Weak Crossentropy 2d

It's syntax is : tflearn.objectives.weak_cross_entropy_2d (y_pred, y_true, num_classes=None, epsilon=0.0001, head=None) where its arguments are y_pred, y_true, num_classes, epsilon and head.
By using weak softmax cross entropy loss it computes semantic segmentation.

wce = tflearn.weak_cross_entropy_2d (my_net, y, num_classes=None, epsilon=0.0001, head=None)

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