From ea1cac79da4a0236b82c7830ac7a44dd12a006e1 Mon Sep 17 00:00:00 2001
From: linjingming0103 <1023339599@qq.com>
Date: Sun, 21 Nov 2021 14:51:28 +0000
Subject: [PATCH] =?UTF-8?q?=E4=BD=9C=E4=B8=9A=E5=86=85=E5=AE=B9?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../Mycode"                                   | 219 ++++++++++++++++++
 .../data"                                     |  36 +++
 .../data_test"                                |   2 +
 .../lable"                                    |  36 +++
 .../lable_test"                               |   2 +
 5 files changed, 295 insertions(+)
 create mode 100644 "code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/Mycode"
 create mode 100644 "code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/data"
 create mode 100644 "code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/data_test"
 create mode 100644 "code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/lable"
 create mode 100644 "code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/lable_test"

diff --git "a/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/Mycode" "b/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/Mycode"
new file mode 100644
index 0000000..e73b825
--- /dev/null
+++ "b/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/Mycode"
@@ -0,0 +1,219 @@
+import numpy as np
+import mindspore as ms
+from mindspore import ops, nn
+import mindspore.dataset as ds
+import mindspore.common.initializer as init #库
+
+
+"""各函数定义"""
+def get_data():
+    ds_train = create_dataset()
+    file = open("data.txt", "r")
+    file2 = open("lable.txt", "r")
+    datas=[]
+    lables=[]
+    data = file.readlines()
+    for fields in data:
+        fields = fields.strip()
+        fields = fields.split(" ")
+        if fields!="":
+            fields = list(map(float,fields))
+            datas.append(fields)
+    lable = file2.readlines()
+    for fields in lable:
+        fields = fields.strip()
+        fields = fields.split(" ")
+        if fields!="":
+            fields = list(map(float,fields))
+            lables.append(fields)
+            
+    datas = np.array(datas,dtype=np.float32)
+    lables=np.array(lables,dtype=np.float32)
+        
+    for i in range(len(lables)): 
+        yield datas[i].astype(np.float32), lables[i].astype(np.float32)
+
+def get_data2():
+    """读取验证数据"""
+    file = open("data_test.txt", "r")
+    file2 = open("lable_test.txt", "r")
+    datas=[]
+    lables=[]
+    data = file.readlines()
+    for fields in data:
+        fields = fields.strip()
+        fields = fields.split(" ")
+        if fields!="":
+            fields = list(map(float,fields))
+            datas.append(fields)
+    lable = file2.readlines()
+    for fields in lable:
+        fields = fields.strip()
+        fields = fields.split(" ")
+        if fields!="":
+            fields = list(map(float,fields))
+            lables.append(fields)
+            
+    datas = np.array(datas,dtype=np.float32)
+    lables=np.array(lables,dtype=np.float32)
+        
+    for i in range(len(lables)): 
+        yield datas[i].astype(np.float32), lables[i].astype(np.float32)
+        
+def create_dataset(batch_size=12, repeat_size=1):
+    """定义数据集"""
+    input_data = ds.GeneratorDataset(list(get_data()), column_names=['data', 'label'])
+    input_data = input_data.batch(batch_size)
+    input_data = input_data.repeat(repeat_size)
+    return input_data
+
+def create_dataset_2(batch_size=1, repeat_size=1):
+    """验证数据集"""
+    input_data = ds.GeneratorDataset(list(get_data2()), column_names=['data', 'label'])
+    input_data = input_data.batch(batch_size)
+    input_data = input_data.repeat(repeat_size)
+    return input_data
+
+class MyNet(nn.Cell):
+    """定义网络"""
+    def __init__(self, input_size=15):
+        super(MyNet, self).__init__()
+        self.fc1 = nn.Dense(input_size, 120, weight_init=init.Normal(0.02))
+        self.fc2 = nn.Dense(120, 84, weight_init=init.Normal(0.02))
+        self.fc3 = nn.Dense(84, 20, weight_init=init.Normal(0.02))
+        self.fc4 = nn.Dense(20, 1, weight_init=init.Normal(0.02))
+        self.relu = nn.ReLU()
+
+    def construct(self, x):
+        x = self.relu(self.fc1(x))
+        x = self.relu(self.fc2(x))
+        x = self.relu(self.fc3(x))
+        x = self.fc4(x)
+        return x
+
+class MyL1Loss(nn.LossBase):
+    """定义损失"""
+    def __init__(self, reduction="mean"):
+        super(MyL1Loss, self).__init__(reduction)
+        self.abs = ops.Abs()
+        self.loss=nn.MSELoss()
+    
+    def construct(self, base, target):
+        x = self.abs(base - target)
+        return self.get_loss(x)
+
+
+class MyMomentum(nn.Optimizer):
+    """Momentum优化器"""
+    def __init__(self, params, learning_rate, momentum=0.9, use_nesterov=False):
+        super(MyMomentum, self).__init__(learning_rate, params)
+        self.moments = self.parameters.clone(prefix="moments", init="zeros")
+        self.momentum = momentum
+        self.opt = ops.ApplyMomentum(use_nesterov=use_nesterov)
+
+    def construct(self, gradients):
+        params = self.parameters
+        success = None
+        for param, mom, grad in zip(params, self.moments, gradients):
+            success = self.opt(param, mom, self.learning_rate, grad, self.momentum)
+        return success
+
+class MyWithLossCell(nn.Cell):
+    """定义损失网络"""
+    def __init__(self, backbone, loss_fn):
+        super(MyWithLossCell, self).__init__(auto_prefix=False)
+        self.backbone = backbone
+        self.loss_fn = loss_fn
+
+    def construct(self, data, label):
+        out = self.backbone(data)
+        return self.loss_fn(out, label)
+
+    def backbone_network(self):
+        return self.backbone
+
+class MyTrainStep(nn.TrainOneStepCell):
+    """定义训练流程"""
+    def __init__(self, network, optimizer):
+        """参数初始化"""
+        super(MyTrainStep, self).__init__(network, optimizer)
+        self.grad = ops.GradOperation(get_by_list=True)
+
+    def construct(self, data, label):
+        """构建训练过程"""
+        weights = self.weights
+        loss = self.network(data, label)
+        grads = self.grad(self.network, weights)(data, label)
+        return loss, self.optimizer(grads)
+
+
+"""搭建网络 训练 """
+ds_train = create_dataset()
+# 网络
+net = MyNet()
+# 损失函数
+loss_func = MyL1Loss()
+# 优化器
+opt = MyMomentum(net.trainable_params(), 0.1)
+# 构建损失网络
+net_with_criterion = MyWithLossCell(net, loss_func)
+# 构建训练网络
+train_net = MyTrainStep(net_with_criterion, opt)
+# 执行训练，每个epoch打印一次损失值
+epochs = 5000
+arr=[]
+for epoch in range(epochs):
+    for train_x, train_y in ds_train:
+        train_net(train_x, train_y)
+        loss_val = net_with_criterion(train_x, train_y)
+        print(loss_val)
+
+""" 模型评估部分"""
+class MyMAE(nn.Metric):
+    """定义metric"""
+    def __init__(self):
+        super(MyMAE, self).__init__()
+        self.clear()
+
+    def clear(self):
+        self.abs_error_sum = 0
+        self.samples_num = 0
+
+    def update(self, *inputs):
+        y_pred = inputs[0].asnumpy()
+        y = inputs[1].asnumpy()
+        error_abs = np.abs(y.reshape(y_pred.shape) - y_pred)
+        self.abs_error_sum += error_abs.sum()
+        self.samples_num += y.shape[0]
+
+    def eval(self):
+        return self.abs_error_sum / self.samples_num
+
+
+class MyWithEvalCell(nn.Cell):
+    """定义验证流程"""
+    def __init__(self, network):
+        super(MyWithEvalCell, self).__init__(auto_prefix=False)
+        self.network = network
+
+    def construct(self, data, label):
+        outputs = self.network(data)
+        return outputs, label
+
+""" 计算MAE"""
+# 获取验证数据
+ds_eval = create_dataset_2()
+# 定义评估网络
+eval_net = MyWithEvalCell(net)
+eval_net.set_train(False)
+# 定义评估指标
+mae = MyMAE()
+# 执行推理过程
+for eval_x, eval_y in ds_eval:
+    output, eval_y = eval_net(eval_x, eval_y)
+    mae.update(output, eval_y)
+
+mae_result = mae.eval()
+print("mae: ", mae_result)
+
+ms.save_checkpoint(net, "./MyNet.ckpt")
\ No newline at end of file
diff --git "a/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/data" "b/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/data"
new file mode 100644
index 0000000..fa77863
--- /dev/null
+++ "b/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/data"
@@ -0,0 +1,36 @@
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+-266.875 4737.225 279008.4 2087.5 277441.075 2758.925 24.975 497461.5385 36230.76923 0.194195932 0.103107395 0.071315742 67399.2 277004.825 2302.5
+-266.875 4543.4 281095.9 2087.5 280200 2758.925 25 590769.2308 93307.69231 0.181983344 -0.115118577 -0.218225973 59640.3 279690.7 2393.9
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\ No newline at end of file
diff --git "a/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/data_test" "b/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/data_test"
new file mode 100644
index 0000000..09c06a3
--- /dev/null
+++ "b/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/data_test"
@@ -0,0 +1,2 @@
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\ No newline at end of file
diff --git "a/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/lable" "b/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/lable"
new file mode 100644
index 0000000..f9d6050
--- /dev/null
+++ "b/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/lable"
@@ -0,0 +1,36 @@
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+477.6923077
\ No newline at end of file
diff --git "a/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/lable_test" "b/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/lable_test"
new file mode 100644
index 0000000..ca6d05b
--- /dev/null
+++ "b/code/2021_autumn/\346\236\227\351\235\231\351\270\243-\346\267\261\345\272\246\345\255\246\344\271\240\345\234\250\347\205\244\347\202\255\345\273\272\346\250\241\347\232\204\345\272\224\347\224\250/lable_test"
@@ -0,0 +1,2 @@
+653.25
+618.9583333
\ No newline at end of file
-- 
Gitee