* Print a text summary of the model's layers. * * The summary includes * - Name and type of all layers that comprise the model. * - Output

* Creates a `Dataset` with at most `count` initial elements from this * dataset. * * ```js * const a = tf.data.array([1, 2, 3, 4, 5, 6]).t

* Limits this stream to return at most `count` items. * * @param count The maximum number of items to provide from the stream. If * a negativ

* Computes tan of the input `tf.Tensor` element-wise, `tan(x)` * * ```js * const x = tf.tensor1d([0, Math.PI / 2, Math.PI * 3 / 4]); * * x.tan().

* Computes hyperbolic tangent of the input `tf.Tensor` element-wise: `tanh(x)` * * ```js * const x = tf.tensor1d([0, 1, -1, 70]); * * x.tanh().pr

* Creates a new tensor by applying sparse updates to individual * values or slices to the passed in tensor according to * indices. This operator is

create the keras mobilenet v2 model.

Test loading of model and its weights from buffers.