7fd49e352027b5e24d0f8ede917877e5d5ef945f,dataset/models/tf/vgg.py,VGG,_build,#VGG#,45

Before Change

        logits = tf.identity(net, name="predictions")
        pred_proba = tf.nn.softmax(logits, name="predicted_proba")
        pred_labels = tf.argmax(pred_proba, axis=-1, name="predicted_labels")
        true_labels = tf.argmax(inputs["labels"], axis=-1, name="true_labels")
        equality = tf.equal(pred_labels, true_labels)
        equality = tf.cast(equality, dtype=tf.float32)
        tf.reduce_mean(equality, name="accuracy")

After Change

        with tf.variable_scope("VGG"):
            x = self.input_block(dim, inputs["images"], **{**kwargs, **input_block_config})
            x = self.body(dim, x, arch, **{**kwargs, **body_config})
            output = self.head(dim, x, **{**kwargs, **head_config})

        logits = tf.identity(output, name="predictions")
        tf.nn.softmax(logits, name="predicted_proba")

Instances