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Pyodide里的Tensorflow目录

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可以跑通基本的训练、使用模型过程
This commit is contained in:
RXXXBNUer
2025-10-04 11:24:10 +08:00
parent 57b59e7d33
commit fe343c67ff
30 changed files with 1459 additions and 419 deletions
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32
common/msg/blockly/en.js
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@@ -4009,4 +4009,36 @@ En.MIXLY_TINY_WEB_DB_START_NUMBER = 'Start number';
En.MIXLY_TINY_WEB_DB_VARIABLE_NUMBER = 'Number of variables';
En.MIXLY_TINY_WEB_DB_SEARCH_VARS = 'Characters in variable names';
En.MIXLY_TENSORFLOW_INIT_TENSOR = 'Initialize tensor as';
En.MIXLY_TENSORFLOW_SEQUENTIAL = 'Initialize sequential model';
En.MIXLY_TENSORFLOW_INIT_LAYERS_DENSE_LAYER = 'Build dense layer';
En.MIXLY_TENSORFLOW_OUTPUT_DIMENSION = 'Output dimension';
En.MIXLY_TENSORFLOW_INPUT_SHAPE = 'Input shape';
En.MIXLY_TENSORFLOW_MODEL = 'Model';
En.MIXLY_TENSORFLOW_ADD_LAYER = 'Add layer';
En.MIXLY_TENSORFLOW_COMPILE_MODEL = 'Compile model';
En.MIXLY_TENSORFLOW_LOSS_FUNCTION_TYPE = 'Loss function type';
En.MIXLY_TENSORFLOW_MEAN_SQUARED_ERROR = 'Mean squared error';
En.MIXLY_TENSORFLOW_OPTIMIZER = 'Optimizer';
En.MIXLY_TENSORFLOW_SGD = 'Stochastic gradient descent';
En.MIXLY_TENSORFLOW_FIT_MODEL = 'Train model';
En.MIXLY_TENSORFLOW_FIT_INPUT_DATA = 'Input data';
En.MIXLY_TENSORFLOW_FIT_TARGET_DATA = 'Target data';
En.MIXLY_TENSORFLOW_FIT_EPOCHS = 'Training epochs';
En.MIXLY_TENSORFLOW_FIT_VERBOSE = 'Verbose level';
En.MIXLY_TENSORFLOW_FIT_RETURN_HISTORY = 'Return training history object';
En.MIXLY_TENSORFLOW_GET_LOSS_FROM_HISTORY = 'From training history object';
En.MIXLY_TENSORFLOW_GET_LOSS_FROM_HISTORY_2 = 'Get training loss values array';
En.MIXLY_TENSORFLOW_PREDICT = 'Use model for prediction';
En.MIXLY_TENSORFLOW_PREDICT_INPUT_DATA = 'Input data';
En.MIXLY_TENSORFLOW_PREDICT_RETURN_RESULT = 'Return prediction result tensor';
En.MIXLY_TENSORFLOW_GET_TENSOR_DATA = 'Get data from tensor';
En.MIXLY_TENSORFLOW_SAVE_MODEL = 'Save model';
En.MIXLY_TENSORFLOW_EXPORT_MODEL = 'Export model';
En.MIXLY_TENSORFLOW_SAVE_MODEL_NAME = 'Name';
En.MIXLY_TENSORFLOW_LOAD_MODEL = 'Use imported model';
En.MIXLY_TENSORFLOW_MODEL_NAME = 'Model name';
En.MIXLY_TENSORFLOW_PREPARE_PICTURE_TO_TENSOR = 'Preprocess image to tensor';
En.MIXLY_TENSORFLOW_PREPARE_PICTURE_READ_PICTURE = 'Read image';
})();

31
common/msg/blockly/zh-hans.js
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@@ -4168,4 +4168,35 @@ ZhHans.MIXLY_TINY_WEB_DB_START_NUMBER = '起始编号';
ZhHans.MIXLY_TINY_WEB_DB_VARIABLE_NUMBER = '变量个数';
ZhHans.MIXLY_TINY_WEB_DB_SEARCH_VARS = '变量名包含的字符';
ZhHans.MIXLY_TENSORFLOW_INIT_TENSOR = '初始化张量为';
ZhHans.MIXLY_TENSORFLOW_SEQUENTIAL = '初始化顺序模型';
ZhHans.MIXLY_TENSORFLOW_INIT_LAYERS_DENSE_LAYER = '构建全连接层';
ZhHans.MIXLY_TENSORFLOW_OUTPUT_DIMENSION = '输出维度';
ZhHans.MIXLY_TENSORFLOW_INPUT_SHAPE = '输入形状';
ZhHans.MIXLY_TENSORFLOW_MODEL = '模型';
ZhHans.MIXLY_TENSORFLOW_ADD_LAYER = '添加层';
ZhHans.MIXLY_TENSORFLOW_COMPILE_MODEL = '编译模型';
ZhHans.MIXLY_TENSORFLOW_LOSS_FUNCTION_TYPE = '损失函数类型';
ZhHans.MIXLY_TENSORFLOW_MEAN_SQUARED_ERROR = '均方误差';
ZhHans.MIXLY_TENSORFLOW_OPTIMIZER = '优化器';
ZhHans.MIXLY_TENSORFLOW_SGD = '随机梯度下降法';
ZhHans.MIXLY_TENSORFLOW_FIT_MODEL = '训练模型';
ZhHans.MIXLY_TENSORFLOW_FIT_INPUT_DATA = '输入数据';
ZhHans.MIXLY_TENSORFLOW_FIT_TARGET_DATA = '目标数据';
ZhHans.MIXLY_TENSORFLOW_FIT_EPOCHS = '训练迭代次数';
ZhHans.MIXLY_TENSORFLOW_FIT_VERBOSE = '日志输出级别';
ZhHans.MIXLY_TENSORFLOW_FIT_RETURN_HISTORY = '返回训练历史对象';
ZhHans.MIXLY_TENSORFLOW_GET_LOSS_FROM_HISTORY = '从训练历史对象';
ZhHans.MIXLY_TENSORFLOW_GET_LOSS_FROM_HISTORY_2 = '获取训练损失值数组';
ZhHans.MIXLY_TENSORFLOW_PREDICT = '使用模型预测';
ZhHans.MIXLY_TENSORFLOW_PREDICT_INPUT_DATA = '输入数据';
ZhHans.MIXLY_TENSORFLOW_PREDICT_RETURN_RESULT = '返回预测结果张量';
ZhHans.MIXLY_TENSORFLOW_GET_TENSOR_DATA = '获取张量中的数据';
ZhHans.MIXLY_TENSORFLOW_SAVE_MODEL = '保存模型';
ZhHans.MIXLY_TENSORFLOW_EXPORT_MODEL = '导出模型';
ZhHans.MIXLY_TENSORFLOW_SAVE_MODEL_NAME = '名称';
ZhHans.MIXLY_TENSORFLOW_LOAD_MODEL = '使用导入模型';
ZhHans.MIXLY_TENSORFLOW_MODEL_NAME = '模型名';
ZhHans.MIXLY_TENSORFLOW_PREPARE_PICTURE_TO_TENSOR = '预处理图像为张量';
ZhHans.MIXLY_TENSORFLOW_PREPARE_PICTURE_READ_PICTURE = '读入图像';
})();

31
common/msg/blockly/zh-hant.js
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@@ -4163,4 +4163,35 @@ ZhHant.MIXLY_TINY_WEB_DB_START_NUMBER = '起始編號';
ZhHant.MIXLY_TINY_WEB_DB_VARIABLE_NUMBER = '變數個數';
ZhHant.MIXLY_TINY_WEB_DB_SEARCH_VARS = '變數名稱包含的字元';
ZhHant.MIXLY_TENSORFLOW_INIT_TENSOR = '初始化張量為';
ZhHant.MIXLY_TENSORFLOW_SEQUENTIAL = '初始化順序模型';
ZhHant.MIXLY_TENSORFLOW_INIT_LAYERS_DENSE_LAYER = '構建全連接層';
ZhHant.MIXLY_TENSORFLOW_OUTPUT_DIMENSION = '輸出維度';
ZhHant.MIXLY_TENSORFLOW_INPUT_SHAPE = '輸入形狀';
ZhHant.MIXLY_TENSORFLOW_MODEL = '模型';
ZhHant.MIXLY_TENSORFLOW_ADD_LAYER = '添加層';
ZhHant.MIXLY_TENSORFLOW_COMPILE_MODEL = '編譯模型';
ZhHant.MIXLY_TENSORFLOW_LOSS_FUNCTION_TYPE = '損失函數類型';
ZhHant.MIXLY_TENSORFLOW_MEAN_SQUARED_ERROR = '均方誤差';
ZhHant.MIXLY_TENSORFLOW_OPTIMIZER = '優化器';
ZhHant.MIXLY_TENSORFLOW_SGD = '隨機梯度下降法';
ZhHant.MIXLY_TENSORFLOW_FIT_MODEL = '訓練模型';
ZhHant.MIXLY_TENSORFLOW_FIT_INPUT_DATA = '輸入數據';
ZhHant.MIXLY_TENSORFLOW_FIT_TARGET_DATA = '目標數據';
ZhHant.MIXLY_TENSORFLOW_FIT_EPOCHS = '訓練迭代次數';
ZhHant.MIXLY_TENSORFLOW_FIT_VERBOSE = '日誌輸出級別';
ZhHant.MIXLY_TENSORFLOW_FIT_RETURN_HISTORY = '返回訓練歷史對象';
ZhHant.MIXLY_TENSORFLOW_GET_LOSS_FROM_HISTORY = '從訓練歷史對象';
ZhHant.MIXLY_TENSORFLOW_GET_LOSS_FROM_HISTORY_2 = '獲取訓練損失值數組';
ZhHant.MIXLY_TENSORFLOW_PREDICT = '使用模型預測';
ZhHant.MIXLY_TENSORFLOW_PREDICT_INPUT_DATA = '輸入數據';
ZhHant.MIXLY_TENSORFLOW_PREDICT_RETURN_RESULT = '返回預測結果張量';
ZhHant.MIXLY_TENSORFLOW_GET_TENSOR_DATA = '獲取張量中的數據';
ZhHant.MIXLY_TENSORFLOW_SAVE_MODEL = '保存模型';
ZhHant.MIXLY_TENSORFLOW_EXPORT_MODEL = '導出模型';
ZhHant.MIXLY_TENSORFLOW_SAVE_MODEL_NAME = '名稱';
ZhHant.MIXLY_TENSORFLOW_LOAD_MODEL = '使用導入模型';
ZhHant.MIXLY_TENSORFLOW_MODEL_NAME = '模型名';
ZhHant.MIXLY_TENSORFLOW_PREPARE_PICTURE_TO_TENSOR = '預處理圖像為張量';
ZhHant.MIXLY_TENSORFLOW_PREPARE_PICTURE_READ_PICTURE = '讀入圖像';
})();