feat: sync all remaining python source board configurations

mixly/boards/default_src/python_pyodide/whl/sprite-project/setup.py

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

mixly/boards/default_src/python_pyodide/whl/sprite-project/sprite/__init__.py

@@ -0,0 +1,120 @@
+from js import window
+
+
+def createBackground(img):
+    return window.mixlySprite.createBackground(img)
+
+
+class Sprite:
+    def __init__(self, img, x, y, name=''):
+        self.vname = window.mixlySprite.createASprite(img, x, y, name)
+    
+    @property
+    def this(self):
+        return window.mixlySprite.sprites.__getattribute__(self.vname)
+
+    def show(self):
+        return self.this.show()
+
+    def hide(self):
+        return self.this.hide()
+        
+    def enlarge(self):
+        return self.this.enlarge()
+    
+    def enlargeTo(self, s):
+        return self.this.enlargeTo(s)
+        
+    def expandTo(self, s, time):
+        return self.this.expandTo(s, time)
+        
+    def move(self, step):
+        return self.this.move(step)
+        
+    def moveTo(self, x, y):
+        return self.this.moveTo(x, y)
+        
+    async def slideTo(self, x, y, time):
+        return await self.this.slideTo(x, y, time)
+        
+    def addX(self, step):
+        return self.this.addX(step)
+        
+    def addY(self, step):
+        return self.this.addY(step)
+    
+    def getX(self):
+        return self.this.getX()
+    
+    def getY(self):
+        return self.this.getY()
+    
+    def rotate(self, degree):
+        return self.this.rotate(degree)
+    
+    def rotateTo(self, degree):
+        return self.this.rotateTo(degree)
+    
+    def circleTo(self, degree):
+        return self.this.circleTo(degree)
+    
+    def hit(self, sprite2):
+        return self.this.hit(sprite2.this)
+    
+    def outOfScreen(self):
+        return self.this.outOfScreen()
+    
+    def mouseAction(self, calc):
+        return self.this.mouseAction(calc)
+    
+    def isClicked(self):
+        return self.this.isDown
+    
+    def setScale(self, h, w):
+        return self.this.setScale(h, w)
+    
+    def filterGray(self):
+        return self.this.filterGray()
+    
+    def filterBrighter(self):
+        return self.this.filterBrighter()
+    
+    def filterOrigin(self):
+        return self.this.filterOrigin()
+    
+
+class Text:
+    def __init__(self, text, x, y, name=''):
+        self.vname = window.mixlySprite.createText(text, x, y, name)
+    
+    @property
+    def this(self):
+        return window.mixlySprite.texts.__getattribute__(self.vname)
+    
+    def changeText(self, text):
+        return self.this.changeText(text)
+    
+    def show(self):
+        return self.this.show()
+    
+    def hide(self):
+        return self.this.hide()
+    
+
+def clearAllSprites():
+    return window.mixlySprite.clearAllSprites()
+    
+def repeat(calc):
+    return window.mixlySprite.repeat(calc)
+    
+def keyboardListener(calc):
+    return window.mixlySprite.keyboardListener(key, calc)
+    
+def isKeyboardHit(keyvalue):
+    return window.mixlySprite.isKeyboardHit(keyvalue)
+
+def getTime():
+    return window.mixlySprite.timer / 1000
+
+def clearTimer():
+    return window.mixlySprite.clearTimer()

mixly/boards/default_src/python_pyodide/whl/tensorflow-project/build/lib/tensorflow/__init__.py

@@ -0,0 +1,44 @@
+from pyodide.ffi import to_js, create_proxy
+import js
+import json
+import os
+from . import layers
+
+
+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
+
+def tensor(data):
+    return js.tf.tensor(to_js(data))
+
+def sequential():
+    return js.tf.sequential()
+
+async def load_model(name):
+    model = await js.tf.loadLayersModel(f"indexeddb://{name}")
+    return model
+
+async def prepare_qmyixtxi(imgTensor):
+    return await js.prepare_qmyixtxi(imgTensor)

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

@@ -0,0 +1,5 @@
+from .activation import *
+from .core import *
+
+from pyodide.ffi import to_js, create_proxy
+import js

mixly/boards/default_src/python_pyodide/whl/tensorflow-project/build/lib/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)

mixly/boards/default_src/python_pyodide/whl/tensorflow-project/build/lib/tensorflow/layers/core.py

@@ -0,0 +1,5 @@
+import js
+from pyodide.ffi import to_js
+
+def dense(units, input_shape=None):
+    return js.tf.layers.dense(units=units, inputShape=to_js(input_shape))

mixly/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',
+    ]
+)

mixly/boards/default_src/python_pyodide/whl/tensorflow-project/tensorflow.egg-info/PKG-INFO

@@ -0,0 +1,10 @@
+Metadata-Version: 2.4
+Name: tensorflow
+Version: 0.0.1
+Summary: 适用于pyodide的tensorflowjs包
+Author: Mixly Team
+Author-email: 
+Classifier: Programming Language :: Python :: 3
+Dynamic: author
+Dynamic: classifier
+Dynamic: summary

mixly/boards/default_src/python_pyodide/whl/tensorflow-project/tensorflow.egg-info/SOURCES.txt

@@ -0,0 +1,10 @@
+setup.py
+tensorflow/__init__.py
+tensorflow.egg-info/PKG-INFO
+tensorflow.egg-info/SOURCES.txt
+tensorflow.egg-info/dependency_links.txt
+tensorflow.egg-info/top_level.txt
+tensorflow/layers/__init__.py
+tensorflow/layers/activation.py
+tensorflow/layers/base.py
+tensorflow/layers/core.py

mixly/boards/default_src/python_pyodide/whl/tensorflow-project/tensorflow.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

mixly/boards/default_src/python_pyodide/whl/tensorflow-project/tensorflow.egg-info/top_level.txt

@@ -0,0 +1 @@
+tensorflow

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

@@ -0,0 +1,44 @@
+from pyodide.ffi import to_js, create_proxy
+import js
+import json
+import os
+from . import layers
+
+
+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
+
+def tensor(data):
+    return js.tf.tensor(to_js(data))
+
+def sequential():
+    return js.tf.sequential()
+
+async def load_model(name):
+    model = await js.tf.loadLayersModel(f"indexeddb://{name}")
+    return model
+
+async def prepare_qmyixtxi(imgTensor):
+    return await js.prepare_qmyixtxi(imgTensor)

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

@@ -0,0 +1,5 @@
+from .activation import *
+from .core import *
+
+from pyodide.ffi import to_js, create_proxy
+import js

mixly/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)

mixly/boards/default_src/python_pyodide/whl/tensorflow-project/tensorflow/layers/core.py

@@ -0,0 +1,5 @@
+import js
+from pyodide.ffi import to_js
+
+def dense(units, input_shape=None):
+    return js.tf.layers.dense(units=units, inputShape=to_js(input_shape))