Merge branch 'master' of https://gitee.com/bnu_mixly/mixly3

boards/default_src/python_pyodide/others/loader.js

@@ -1,3 +1,6 @@
 import NavExt from './nav-ext';
+import * as tf from '@tensorflow/tfjs';
+import './tensorflow';
 
-NavExt.init();
+NavExt.init();
+window.tf = tf;

boards/default_src/python_pyodide/others/tensorflow.js

@@ -0,0 +1,58 @@
+import { Registry } from 'mixly';
+import * as tf from '@tensorflow/tfjs';
+
+
+const modelsValueRegistry = new Registry();
+const customFetch = function (path) {
+    let result = {
+        ok: false,
+        buffer: null,
+        json: function () {
+            const decoder = new TextDecoder('utf-8');
+            const jsonText = decoder.decode(this.buffer);
+            return JSON.parse(jsonText);
+        },
+        arrayBuffer: function () {
+            return this.buffer;
+        }
+    }
+    if (!modelsValueRegistry.hasKey(path)) {
+        return result;
+    }
+    result.ok = true;
+    result.buffer = modelsValueRegistry.getItem(path);
+    return result;
+};
+
+const tensorflow = {};
+tensorflow.modelsValue = {};
+
+tensorflow.loadGraphModel = async function (path) {
+    const model = await tf.loadGraphModel(path, {
+        fromTFHub: false,
+        fetchFunc: (...args) => {
+            return customFetch(args[0]);
+        }
+    });
+    return model;
+};
+
+tensorflow.loadLayersModel = async function (path) {
+    const model = await tf.loadLayersModel(path, {
+        fromTFHub: false,
+        fetchFunc: (...args) => {
+            return customFetch(args[0]);
+        }
+    });
+    return model;
+};
+
+tensorflow.setModelsValue = function (path, value) {
+    if (modelsValueRegistry.hasKey(path)) {
+        modelsValueRegistry.unregister(path);
+    }
+    modelsValueRegistry.register(path, value);
+    tensorflow.modelsValue[path] = value;
+};
+
+window.tensorflow = tensorflow;

boards/default_src/python_pyodide/package.json

@@ -20,6 +20,7 @@
     },
     "dependencies": {
         "@basthon/kernel-loader": "^0.62.21",
+        "@tensorflow/tfjs": "^4.22.0",
         "@zenfs/core": "^1.4.0",
         "@zenfs/dom": "^1.0.6",
         "idb-keyval": "^6.2.1",

boards/default_src/python_pyodide/whl/tensorflow-project/setup.py

@@ -0,0 +1,14 @@
+from setuptools import setup, find_packages
+
+setup(
+    name='tensorflow',
+    version='0.0.1',
+    packages=find_packages(),
+    install_requires=[],
+    author='Mixly Team',
+    author_email='',
+    description='适用于pyodide的tensorflowjs包',
+    classifiers=[
+        'Programming Language :: Python :: 3',
+    ]
+)

boards/default_src/python_pyodide/whl/tensorflow-project/tensorflow/__init__.py

@@ -0,0 +1,30 @@
+from pyodide.ffi import to_js, create_proxy
+import js
+import json
+import os
+
+
+def __cache_model(file_path):
+    data = json.load(open(file_path, 'r'))
+    f = open(file_path, 'rb')
+    js.tensorflow.setModelsValue(file_path, to_js(f.read()))
+    f.close()
+    folder_path = os.path.dirname(file_path)
+    for item in data['weightsManifest']:
+        for current_path in item['paths']:
+            bin_file_path = '{}/{}'.format(folder_path, current_path)
+            f = open(bin_file_path, 'rb')
+            js.tensorflow.setModelsValue(bin_file_path, to_js(f.read()))
+            f.close()
+
+
+async def load_graph_model(file_path):
+    __cache_model(file_path)
+    model = await js.tensorflow.loadGraphModel(file_path)
+    return model
+
+
+async def load_layers_model(file_path):
+    __cache_model(file_path)
+    model = await js.tensorflow.loadLayersModel(file_path)
+    return model

boards/default_src/python_pyodide/whl/tensorflow-project/tensorflow/layers/__init__.py

@@ -0,0 +1 @@
+from activation import *

boards/default_src/python_pyodide/whl/tensorflow-project/tensorflow/layers/activation.py

@@ -0,0 +1,37 @@
+import js
+
+
+def elu(*args, **kwargs):
+    '''
+    f(x) = alpha * (exp(x) - 1.) for x < 0, f(x) = x for x >= 0.
+    '''
+    js.tensorflow.layers.elu(*args, **kwargs)
+
+
+def leaky_relu(*args, **kwargs):
+    '''
+    f(x) = alpha * x for x < 0. f(x) = x for x >= 0.
+    '''
+    js.tensorflow.layers.leakyReLU(*args, **kwargs)
+
+
+def prelu(*args, **kwargs):
+    '''
+    f(x) = alpha * x for x < 0. f(x) = x for x >= 0.
+    '''
+    js.tensorflow.layers.prelu(*args, **kwargs)
+
+
+def relu(*args, **kwargs):
+    js.tensorflow.layers.relu(*args, **kwargs)
+
+
+def softmax(*args, **kwargs):
+    js.tensorflow.layers.softmax(*args, **kwargs)
+
+
+def thresholded_relu(*args, **kwargs):
+    '''
+    f(x) = x for x > theta, f(x) = 0 otherwise.
+    '''
+    js.tensorflow.layers.thresholdedReLU(*args, **kwargs)