feat(board): python_pyodide下添加对tensorflow的支持 (待完善)

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)