.. Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements. See the NOTICE file distributed with this work for additional information regarding copyright ownership. The ASF licenses this file to you under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at .. http://www.apache.org/licenses/LICENSE-2.0 .. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. NNVM Graph JSON Specification ============================= NNVM uses JSON for graph serialization. This allows NNVM graph to be exported to any backend either natively supported or by third-party without any dependency such as protobuf. Getting started --------------- A serialized NNVM graph in JSON format can be deserialized by any JSON parser. .. code:: python # python import json with open('model.json', 'r') as f: graph = json.loads(f.read()) print(graph.keys()) ``['nodes', 'arg_nodes', 'heads', 'node_row_ptr']`` Actually, the following keys are valid in JSON graph. +--------------------------------------+------------+-----------------------------------+ | Keys | Required | Description | +======================================+============+===================================+ | `nodes <#nodes>`__ | Yes | The nodes in graph. | +--------------------------------------+------------+-----------------------------------+ | `arg\_nodes <#arg_nodes>`__ | Yes | Indices of input nodes. | +--------------------------------------+------------+-----------------------------------+ | `heads <#heads>`__ | Yes | Indices of output nodes. | +--------------------------------------+------------+-----------------------------------+ | `node\_row\_ptr <#node_row_ptr>`__ | Optional | Depth first search row indices. | +--------------------------------------+------------+-----------------------------------+ | `attr <#attr>`__ | Optional | Additional information. | +--------------------------------------+------------+-----------------------------------+ nodes ----- Explained by the name itself, ``nodes`` are either placeholders or computational nodes in NNVM graph. The ``nodes`` are stored in list. .. code:: python nodes = graph['nodes'] print(len(nodes)) print(nodes[0]) print(nodes[3]) :: 53 {'inputs': [], 'name': 'data', 'op': 'null'} {'inputs': [[0, 0, 0], [1, 0, 0], [2, 0, 0]], 'attrs': {'channels': '64', 'padding': '(1, 1)', 'layout': 'NCHW', 'kernel_size': '[3, 3]', 'groups': '1', 'strides': '(1, 1)', 'use_bias': 'True', 'dilation': '(1, 1)'}, 'name': 'conv1_1', 'op': 'conv2d'} The following keys are valid in each node: +----------------+------------------+----------+ | Keys | Required | Descript | | | | ion | +================+==================+==========+ | op | Yes | The | | | | operator | | | | type | | | | name, | | | | 'null' | | | | is used | | | | if it's | | | | a | | | | placehol | | | | der/vari | | | | able/inp | | | | ut. | +----------------+------------------+----------+ | name | Yes | The | | | | given | | | | name of | | | | the | | | | node, | | | | defined | | | | by user | | | | composin | | | | g | | | | the | | | | network. | +----------------+------------------+----------+ | inputs | Yes | List of | | | | Entry | | | | of the | | | | input | | | | nodes, | | | | can be | | | | empty | | | | list []. | | | | Entry is | | | | a list | | | | of | | | | [nose\_i | | | | d, | | | | index, | | | | version] | +----------------+------------------+----------+ | attrs | Optional | Extra | | | | attribut | | | | es | | | | for the | | | | specific | | | | operator | | | | . | +----------------+------------------+----------+ | control\_deps | Optional | Control | | | | dependen | | | | cies, | | | | left | | | | blank | | | | unless | | | | specific | | | | ally | | | | used. | +----------------+------------------+----------+ ``attrs`` for operators is a dictionary. Key-value pair examples: +----------------+------------------+----------+----------+ | Keys | Value | Operator | Descript | | | | | ion | +================+==================+==========+==========+ | 'channels' | '64' | conv2d | Output | | | | | channels | | | | | for 2d | | | | | convolut | | | | | ion. | +----------------+------------------+----------+----------+ | 'kernel\_size' | '[3, 3]' | conv2d | Convolut | | | | | ion | | | | | filter | | | | | kernel | | | | | size in | | | | | (h, w), | | | | | list and | | | | | tuple | | | | | both | | | | | works. | +----------------+------------------+----------+----------+ | 'use\_bias' | '1' | conv2d | Whether | | | | | use bias | | | | | such | | | | | that | | | | | `y = w | | | | | * x + b` | | | | | . | +----------------+------------------+----------+----------+ .. note:: Tips for parsing key-value pair: * Both key and value are stored as strings. * Boolean values need extra attention, convert to int is recommended since `bool('0') == True` in python. * For a full list of operator attributes, please refer to the core operator `documentation <top.html>`__. arg\_nodes ---------- ``arg_nodes`` is a list of indices of nodes which is placeholder/variable/input to the graph. .. code:: python print(graph['arg_nodes']) :: [0, 1, 2, 6, 7, 11, 12, 15, 16, 20, 21, 24, 25, 29, 30, 33, 34, 39, 40, 44, 45, 49, 50] For example, ``nodes[3]`` is not in ``arg_nodes`` because it's an internal node. heads ----- ``heads`` is a list of entries as the outlet/output of the graph. .. code:: python print(graph['heads']) :: [[52, 0, 0]] This example indicating that there's only one output in the graph, with index 52. node\_row\_ptr -------------- ``node_row_ptr`` stores the history of forward path, so you can skip constructing the entire graph in inference tasks. attrs ----- ``attrs`` can contain version numbers or similar helpful informations.