| .. 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. |
