* Executes inference for the model for given input tensors in async * fashion, use this method when your model contains control flow ops. * @par

* Set the tensor at the index * @param elementIndex index of the tensor * @param tensor the tensor to be inserted into the list

* Returns the current number of items in the buffer.

* Constructs a `tf.SGDOptimizer` that uses stochastic gradient descent. * * ```js * // Fit a quadratic function by learning the coefficients

* Look up IOHandler for loading, given a URL-like string. * * @param url * @param loadOptions Optional, custom load options. * @returns Al

* Creates a surface on the visor * * Most methods in tfjs-vis that take a surface also take a SurfaceInfo * so you rarely need to call this m

* Force summary writer to send all buffered data to storage.

* Closes the visor. * * @doc {heading: 'Visor & Surfaces', subheading: 'Visor Methods'}

* Returns column names of the csv dataset. If `configuredColumnsOnly` is * true, return column names in `columnConfigs`. If `configuredColumnsOnly`

* Retrieve the element at the provided index * @param elementShape shape of the tensor * @param elementDtype dtype of the tensor * @param ele

* Releases the memory used by the weight tensors and resourceManager. * * @doc {heading: 'Models', subheading: 'Classes'}