First

Assignment1/as1.py

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+import os
+from time import time
+
+import matplotlib.pyplot as plt
+import numpy as np
+import tensorflow as tf
+from icecream import ic
+from tensorflow import keras
+
+
+# os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
+
+global_random_seed = 3884
+np.random.seed(global_random_seed)
+
+
+def gene_test_data(num_points: int, low_val=-1, high_val=1):
+    return np.linspace(low_val, high_val, num_points)
+
+
+def get_network(input_dim, output_dim, width, depth):
+    # Random weight
+    initializer = keras.initializers.RandomUniform(
+        minval=-1., maxval=1., seed=global_random_seed)
+    # initializer = keras.initializers.Constant(1)
+
+    # different activation functions
+    activation_func = keras.activations.tanh
+    # activation_func = tf.math.sin
+
+    hidden_layers = [keras.layers.InputLayer(input_shape=[input_dim, ])]
+    hidden_layers += [keras.layers.Dense(width, activation=activation_func,
+                                         kernel_initializer=initializer, bias_initializer=initializer) for _ in range(depth-1)]
+    hidden_layers.append(keras.layers.Dense(
+        output_dim, kernel_initializer=initializer))
+    model = keras.Sequential(hidden_layers)
+    return model
+
+
+def predict(input):
+    result = []
+    for model in all_models:
+        temp = model.predict(input)
+        result.append(temp)
+    return result
+
+
+model_5 = get_network(1, 1, 5, 15)
+model_10 = get_network(1, 1, 10, 15)
+model_20 = get_network(1, 1, 20, 15)
+model_40 = get_network(1, 1, 40, 15)
+all_models = [model_5, model_10, model_20, model_40]
+
+if __name__ == '__main__':
+    st_time = time()
+    test_data = gene_test_data(100)
+
+    result = predict(test_data)
+    ic(np.shape(result))
+    print(time()-st_time)
+    # result = list(zip(*result))
+    ic(np.shape(result))
+    result_fft = []
+    for i in range(len(result)):
+        result_fft.append(list(np.fft.fft(result[i], axis=0)))
+
+    ic(np.shape(result_fft))
+
+    fig, ((p1, p2, p3, p4), (p5, p6, p7, p8)) = plt.subplots(2, 4)
+    pics = [p1, p2, p3, p4, p5, p6, p7, p8]
+    for i in range(len(result)):
+        pics[i].scatter(range(len(result[i])), list(result[i]), s=1.5, c='r')
+        pics[i+4].scatter(range(len(result_fft[i])),
+                          list(result_fft[i]), s=0.5, c='b')
+        pics[i].set(adjustable='box', aspect=1.0/pics[i].get_data_ratio())
+        pics[i+4].set(adjustable='box', aspect=1.0/pics[i+4].get_data_ratio())
+    plt.show()

Assignment2/.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml
+# Editor-based HTTP Client requests
+/httpRequests/

Assignment2/.idea/Assignment2.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="jdk" jdkName="Python 3.8 (tf)" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

Assignment2/.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

Assignment2/.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (tf)" project-jdk-type="Python SDK" />
+</project>

Assignment2/.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/Assignment2.iml" filepath="$PROJECT_DIR$/.idea/Assignment2.iml" />
+    </modules>
+  </component>
+</project>