diff --git a/.idea/.gitignore b/.idea/.gitignore
new file mode 100644
index 0000000..26d3352
--- /dev/null
+++ b/.idea/.gitignore
@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml
diff --git a/.idea/ML.iml b/.idea/ML.iml
new file mode 100644
index 0000000..d0876a7
--- /dev/null
+++ b/.idea/ML.iml
@@ -0,0 +1,8 @@
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml
new file mode 100644
index 0000000..105ce2d
--- /dev/null
+++ b/.idea/inspectionProfiles/profiles_settings.xml
@@ -0,0 +1,6 @@
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
new file mode 100644
index 0000000..f0e9c8a
--- /dev/null
+++ b/.idea/misc.xml
@@ -0,0 +1,4 @@
+
+
+
+
\ No newline at end of file
diff --git a/.idea/modules.xml b/.idea/modules.xml
new file mode 100644
index 0000000..f7d5bab
--- /dev/null
+++ b/.idea/modules.xml
@@ -0,0 +1,8 @@
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/.idea/vcs.xml b/.idea/vcs.xml
new file mode 100644
index 0000000..94a25f7
--- /dev/null
+++ b/.idea/vcs.xml
@@ -0,0 +1,6 @@
+
+
+
+
+
+
\ No newline at end of file
diff --git a/main.py b/main.py
new file mode 100644
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--- /dev/null
+++ b/main.py
@@ -0,0 +1,61 @@
+import os
+
+import tensorflow as tf
+from tensorflow import keras
+import matplotlib.pyplot as plt
+
+print(tf.version.VERSION)
+
+(train_images, train_labels), (test_images, test_labels) = tf.keras.datasets.mnist.load_data()
+
+plt.imshow(train_images[0])
+
+train_labels = train_labels[:1000]
+test_labels = test_labels[:1000]
+
+train_images = train_images[:1000].reshape(-1, 28 * 28) / 255.0
+test_images = test_images[:1000].reshape(-1, 28 * 28) / 255.0
+
+# 定义一个简单的序列模型
+def create_model():
+ model = tf.keras.models.Sequential([
+ keras.layers.Dense(512, activation='relu', input_shape=(784,)),
+ keras.layers.Dropout(0.2),
+ keras.layers.Dense(10)
+ ])
+
+ model.compile(optimizer='adam',
+ loss=tf.losses.SparseCategoricalCrossentropy(from_logits=True),
+ metrics=['accuracy'])
+
+ return model
+
+# 创建一个基本的模型实例
+model = create_model()
+
+# 显示模型的结构
+model.summary()
+
+checkpoint_path = "training_1/cp.ckpt"
+checkpoint_dir = os.path.dirname(checkpoint_path)
+
+# 创建一个保存模型权重的回调
+cp_callback = tf.keras.callbacks.ModelCheckpoint(filepath=checkpoint_path,
+ save_weights_only=True,
+ verbose=1)
+
+# 使用新的回调训练模型
+model.fit(train_images,
+ train_labels,
+ epochs=10,
+ batch_size=8,
+ validation_data=(test_images,test_labels),
+ callbacks=[cp_callback]) # 通过回调训练
+
+# 这可能会生成与保存优化程序状态相关的警告。
+# 这些警告（以及整个笔记本中的类似警告）
+# 是防止过时使用，可以忽略。
+
+results = model.evaluate(test_images, test_labels, verbose=2)
+
+print(results)
\ No newline at end of file
diff --git a/training_1/checkpoint b/training_1/checkpoint
new file mode 100644
index 0000000..c4fa61d
--- /dev/null
+++ b/training_1/checkpoint
@@ -0,0 +1,2 @@
+model_checkpoint_path: "cp.ckpt"
+all_model_checkpoint_paths: "cp.ckpt"
diff --git a/training_1/cp.ckpt.data-00000-of-00001 b/training_1/cp.ckpt.data-00000-of-00001
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diff --git a/training_1/cp.ckpt.index b/training_1/cp.ckpt.index
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