keras-model-viewer
Version:
SVG-based viewer for Keras models
49 lines (38 loc) • 3.38 kB
HTML
<!DOCTYPE html>
<html>
<head>
<meta charset=utf-8>
<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1">
<meta name="description" content="SVG-based viewer for Keras models" />
<meta name="keywords" content="neural networks keras" />
<script type="text/javascript" src="../dist/keras-model-viewer.min.js"></script>
<title>neurals</title>
<head>
<body>
<div id="kerasmodel" class="model"></div>
<style type="text/css">
html,body {
width: 100%;
height: 100%;
margin: 0px;
padding: 0px;
overflow-y: hidden;
}
.model {
height: 100%;
}
</style>
<script type="text/javascript">
let kmodel = JSON.parse('{"keras_version": "1.0.7", "class_name": "Sequential", "config": [{"class_name": "Convolution2D", "config": {"bias": true, "batch_input_shape": [null, 28, 28, 1], "W_regularizer": null, "activity_regularizer": null, "trainable": true, "nb_row": 3, "subsample": [1, 1], "dim_ordering": "tf", "W_constraint": null, "init": "glorot_uniform", "b_constraint": null, "input_dtype": "float32", "nb_filter": 32, "name": "convolution2d_1", "b_regularizer": null, "activation": "linear", "nb_col": 3, "border_mode": "valid"}}, {"class_name": "Activation", "config": {"trainable": true, "activation": "relu", "name": "activation_1"}}, {"class_name": "Convolution2D", "config": {"bias": true, "W_regularizer": null, "activity_regularizer": null, "trainable": true, "nb_row": 3, "subsample": [1, 1], "dim_ordering": "tf", "W_constraint": null, "init": "glorot_uniform", "b_constraint": null, "nb_filter": 32, "name": "convolution2d_2", "b_regularizer": null, "activation": "linear", "nb_col": 3, "border_mode": "valid"}}, {"class_name": "Activation", "config": {"trainable": true, "activation": "relu", "name": "activation_2"}}, {"class_name": "MaxPooling2D", "config": {"trainable": true, "strides": [2, 2], "name": "maxpooling2d_1", "dim_ordering": "tf", "pool_size": [2, 2], "border_mode": "valid"}}, {"class_name": "Dropout", "config": {"trainable": true, "name": "dropout_1", "p": 0.25}}, {"class_name": "Flatten", "config": {"name": "flatten_1", "trainable": true}}, {"class_name": "Dense", "config": {"bias": true, "W_regularizer": null, "activity_regularizer": null, "b_regularizer": null, "trainable": true, "b_constraint": null, "input_dim": null, "init": "glorot_uniform", "W_constraint": null, "output_dim": 128, "activation": "linear", "name": "dense_1"}}, {"class_name": "Activation", "config": {"trainable": true, "activation": "relu", "name": "activation_3"}}, {"class_name": "Dropout", "config": {"trainable": true, "name": "dropout_2", "p": 0.5}}, {"class_name": "Dense", "config": {"bias": true, "W_regularizer": null, "activity_regularizer": null, "b_regularizer": null, "trainable": true, "b_constraint": null, "input_dim": null, "init": "glorot_uniform", "W_constraint": null, "output_dim": 10, "activation": "linear", "name": "dense_2"}}, {"class_name": "Activation", "config": {"trainable": true, "activation": "softmax", "name": "activation_4"}}]}')
this.model = new KerasModelViewer(kmodel, 'kerasmodel', {
"rankdir": "LR", // "LR" "UD"
"nodesep": 20,
"edgesep": 20,
"ranksep": 40,
"marginx": 0,
"marginy": 0
});
this.model.show();
</script>
</body>
</html>