@tensorflow/tfjs-layers/dist/keras_format/topology_config.d.ts

TensorFlow layers API in JavaScript

/**
 * @license
 * Copyright 2018 Google LLC
 *
 * Use of this source code is governed by an MIT-style
 * license that can be found in the LICENSE file or at
 * https://opensource.org/licenses/MIT.
 * =============================================================================
 */
/// <amd-module name="@tensorflow/tfjs-layers/dist/keras_format/topology_config" />
import { DataType } from '@tensorflow/tfjs-core';
import { Shape } from './common';
import { NodeConfig } from './node_config';
import { BaseSerialization, PyJson, PyJsonDict } from './types';
/** Constructor arguments for Layer. */
export interface LayerConfig extends PyJsonDict {
    input_shape?: Shape;
    batch_input_shape?: Shape;
    batch_size?: number;
    dtype?: DataType;
    name?: string;
    trainable?: boolean;
    input_dtype?: DataType;
}
/**
 * Converts a subtype of `LayerConfig` to a variant with restricted keys.
 *
 * This is a bit tricky because `keyof` obtains only local fields, not inherited
 * fields.  Thus, this type combines the keys from the `LayerConfig` supertype
 * with those of the specific subtype.
 *
 * See ./types.ts for an explanation of the PyJson type.
 */
export type JsonLayer<C extends LayerConfig> = C & LayerConfig & PyJson<Extract<keyof C, string> | Extract<keyof LayerConfig, string>>;
/**
 * A Keras JSON entry representing a layer.
 *
 * The Keras JSON convention is to provide the `class_name` (i.e., the layer
 * type) at the top level, and then to place the layer-specific configuration in
 * a `config` subtree.  These layer-specific configurations are provided by
 * subtypes of `LayerConfig`.  Thus, this `*Serialization` has a type parameter
 * giving the specific type of the wrapped `LayerConfig`.
 */
export interface BaseLayerSerialization<N extends string, C extends LayerConfig> extends BaseSerialization<N, JsonLayer<C>> {
    name: string;
    inbound_nodes?: NodeConfig[];
}