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skyer9hunkim
skyer9
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hunkim
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modify list indentation style. (hunkim#128)
1 parent 8f59ee8 commit a01716d

10 files changed

+116
-28
lines changed

‎lab-04-2-multi_variable_matmul_linear_regression.py

+10-3
Original file line numberDiff line numberDiff line change
@@ -2,9 +2,16 @@
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import tensorflow as tf
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tf.set_random_seed(777) # for reproducibility
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5-
x_data = [[73., 80., 75.], [93., 88., 93.],
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[89., 91., 90.], [96., 98., 100.], [73., 66., 70.]]
7-
y_data = [[152.], [185.], [180.], [196.], [142.]]
5+
x_data = [[73., 80., 75.],
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[93., 88., 93.],
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[89., 91., 90.],
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[96., 98., 100.],
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[73., 66., 70.]]
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y_data = [[152.],
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[185.],
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[180.],
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[196.],
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[142.]]
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# placeholders for a tensor that will be always fed.

‎lab-05-1-logistic_regression.py

+12-2
Original file line numberDiff line numberDiff line change
@@ -2,8 +2,18 @@
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import tensorflow as tf
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tf.set_random_seed(777) # for reproducibility
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5-
x_data = [[1, 2], [2, 3], [3, 1], [4, 3], [5, 3], [6, 2]]
6-
y_data = [[0], [0], [0], [1], [1], [1]]
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x_data = [[1, 2],
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[2, 3],
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[3, 1],
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[4, 3],
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[5, 3],
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[6, 2]]
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y_data = [[0],
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[0],
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[0],
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[1],
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[1],
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[1]]
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# placeholders for a tensor that will be always fed.
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X = tf.placeholder(tf.float32, shape=[None, 2])

‎lab-06-1-softmax_classifier.py

+16-4
Original file line numberDiff line numberDiff line change
@@ -2,10 +2,22 @@
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import tensorflow as tf
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tf.set_random_seed(777) # for reproducibility
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5-
x_data = [[1, 2, 1, 1], [2, 1, 3, 2], [3, 1, 3, 4], [4, 1, 5, 5],
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[1, 7, 5, 5], [1, 2, 5, 6], [1, 6, 6, 6], [1, 7, 7, 7]]
7-
y_data = [[0, 0, 1], [0, 0, 1], [0, 0, 1], [0, 1, 0],
8-
[0, 1, 0], [0, 1, 0], [1, 0, 0], [1, 0, 0]]
5+
x_data = [[1, 2, 1, 1],
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[2, 1, 3, 2],
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[3, 1, 3, 4],
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[4, 1, 5, 5],
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[1, 7, 5, 5],
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[1, 2, 5, 6],
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[1, 6, 6, 6],
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[1, 7, 7, 7]]
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y_data = [[0, 0, 1],
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[0, 0, 1],
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[0, 0, 1],
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[0, 1, 0],
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[0, 1, 0],
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[0, 1, 0],
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[1, 0, 0],
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[1, 0, 0]]
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X = tf.placeholder("float", [None, 4])
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Y = tf.placeholder("float", [None, 3])

‎lab-07-1-learning_rate_and_evaluation.py

+22-6
Original file line numberDiff line numberDiff line change
@@ -2,15 +2,31 @@
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import tensorflow as tf
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tf.set_random_seed(777) # for reproducibility
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5-
x_data = [[1, 2, 1], [1, 3, 2], [1, 3, 4], [1, 5, 5],
6-
[1, 7, 5], [1, 2, 5], [1, 6, 6], [1, 7, 7]]
7-
y_data = [[0, 0, 1], [0, 0, 1], [0, 0, 1], [0, 1, 0],
8-
[0, 1, 0], [0, 1, 0], [1, 0, 0], [1, 0, 0]]
5+
x_data = [[1, 2, 1],
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[1, 3, 2],
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[1, 3, 4],
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[1, 5, 5],
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[1, 7, 5],
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[1, 2, 5],
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[1, 6, 6],
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[1, 7, 7]]
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y_data = [[0, 0, 1],
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[0, 0, 1],
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[0, 0, 1],
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[0, 1, 0],
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[0, 1, 0],
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[0, 1, 0],
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[1, 0, 0],
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[1, 0, 0]]
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# Evaluation our model using this test dataset
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x_test = [[2, 1, 1], [3, 1, 2], [3, 3, 4]]
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y_test = [[0, 0, 1], [0, 0, 1], [0, 0, 1]]
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x_test = [[2, 1, 1],
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[3, 1, 2],
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[3, 3, 4]]
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y_test = [[0, 0, 1],
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[0, 0, 1],
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[0, 0, 1]]
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X = tf.placeholder("float", [None, 3])
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Y = tf.placeholder("float", [None, 3])

‎lab-09-1-xor.py

+10-2
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@@ -4,8 +4,16 @@
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import numpy as np
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tf.set_random_seed(777) # for reproducibility
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7-
x_data = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
8-
y_data = np.array([[0], [1], [1], [0]], dtype=np.float32)
7+
x_data = [[0, 0],
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[0, 1],
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[1, 0],
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[1, 1]]
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y_data = [[0],
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[1],
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[1],
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[0]]
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x_data = np.array(x_data, dtype=np.float32)
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y_data = np.array(y_data, dtype=np.float32)
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X = tf.placeholder(tf.float32, [None, 2])
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Y = tf.placeholder(tf.float32, [None, 1])

‎lab-09-2-xor-nn.py

+10-2
Original file line numberDiff line numberDiff line change
@@ -4,8 +4,16 @@
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import numpy as np
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tf.set_random_seed(777) # for reproducibility
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7-
x_data = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
8-
y_data = np.array([[0], [1], [1], [0]], dtype=np.float32)
7+
x_data = [[0, 0],
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[0, 1],
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[1, 0],
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[1, 1]]
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y_data = [[0],
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[1],
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[1],
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[0]]
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x_data = np.array(x_data, dtype=np.float32)
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y_data = np.array(y_data, dtype=np.float32)
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X = tf.placeholder(tf.float32, [None, 2])
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Y = tf.placeholder(tf.float32, [None, 1])

‎lab-09-3-xor-nn-wide-deep.py

+10-2
Original file line numberDiff line numberDiff line change
@@ -4,8 +4,16 @@
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import numpy as np
55
tf.set_random_seed(777) # for reproducibility
66

7-
x_data = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
8-
y_data = np.array([[0], [1], [1], [0]], dtype=np.float32)
7+
x_data = [[0, 0],
8+
[0, 1],
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[1, 0],
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[1, 1]]
11+
y_data = [[0],
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[1],
13+
[1],
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[0]]
15+
x_data = np.array(x_data, dtype=np.float32)
16+
y_data = np.array(y_data, dtype=np.float32)
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1018
X = tf.placeholder(tf.float32, [None, 2])
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Y = tf.placeholder(tf.float32, [None, 1])

‎lab-09-4-xor_tensorboard.py

+10-2
Original file line numberDiff line numberDiff line change
@@ -4,8 +4,16 @@
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import numpy as np
55
tf.set_random_seed(777) # for reproducibility
66

7-
x_data = np.array([[0, 0], [0, 1], [1, 0], [1, 1]], dtype=np.float32)
8-
y_data = np.array([[0], [1], [1], [0]], dtype=np.float32)
7+
x_data = [[0, 0],
8+
[0, 1],
9+
[1, 0],
10+
[1, 1]]
11+
y_data = [[0],
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[1],
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[1],
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[0]]
15+
x_data = np.array(x_data, dtype=np.float32)
16+
y_data = np.array(y_data, dtype=np.float32)
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X = tf.placeholder(tf.float32, [None, 2], name='x-input')
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Y = tf.placeholder(tf.float32, [None, 1], name='y-input')

‎lab-09-5-linear_back_prop.py

+6-2
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@@ -6,8 +6,12 @@
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tf.set_random_seed(777) # reproducibility
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# tf Graph Input
9-
x_data = [[1.], [2.], [3.]]
10-
y_data = [[1.], [2.], [3.]]
9+
x_data = [[1.],
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[2.],
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[3.]]
12+
y_data = [[1.],
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[2.],
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[3.]]
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# placeholders for a tensor that will be always fed.

‎lab-09-6-multi-linear_back_prop.py

+10-3
Original file line numberDiff line numberDiff line change
@@ -6,9 +6,16 @@
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tf.set_random_seed(777) # reproducibility
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88
# tf Graph Input
9-
x_data = [[73., 80., 75.], [93., 88., 93.],
10-
[89., 91., 90.], [96., 98., 100.], [73., 66., 70.]]
11-
y_data = [[152.], [185.], [180.], [196.], [142.]]
9+
x_data = [[73., 80., 75.],
10+
[93., 88., 93.],
11+
[89., 91., 90.],
12+
[96., 98., 100.],
13+
[73., 66., 70.]]
14+
y_data = [[152.],
15+
[185.],
16+
[180.],
17+
[196.],
18+
[142.]]
1219

1320
# placeholders for a tensor that will be always fed.
1421
X = tf.placeholder(tf.float32, shape=[None, 3])

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