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ML/TensorFlow/Basics/tutorial2-tensorbasics.py

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+import os
+
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
+
+import tensorflow as tf
+
+# Initialization
+x = tf.constant(4, shape=(1, 1), dtype=tf.float32)
+print(x)
+
+x = tf.constant([[1, 2, 3], [4, 5, 6]], shape=(2, 3))
+print(x)
+
+x = tf.eye(3)
+print(x)
+
+x = tf.ones((4, 3))
+print(x)
+
+x = tf.zeros((3, 2, 5))
+print(x)
+
+x = tf.random.uniform((2, 2), minval=0, maxval=1)
+print(x)
+
+x = tf.random.normal((3, 3), mean=0, stddev=1)
+print(tf.cast(x, dtype=tf.float64))
+# tf.float (16,32,64), tf.int (8, 16, 32, 64), tf.bool
+
+x = tf.range(9)
+x = tf.range(start=0, limit=10, delta=2)
+print(x)
+
+# Math
+x = tf.constant([1, 2, 3])
+y = tf.constant([9, 8, 7])
+
+z = tf.add(x, y)
+z = x + y
+
+z = tf.subtract(x, y)
+z = x - y
+
+z = tf.divide(x, y)
+z = x / y
+
+z = tf.multiply(x, y)
+z = x * y
+
+z = tf.tensordot(x, y, axes=1)
+
+z = x ** 5
+
+x = tf.random.normal((2, 3))
+y = tf.random.normal((3, 2))
+z = tf.matmul(x, y)
+z = x @ y
+
+x = tf.random.normal((2, 2))
+
+# Indexing
+x = tf.constant([0, 1, 1, 2, 3, 1, 2, 3])
+print(x[:])
+print(x[1:])
+print(x[1:3])
+print(x[::2])
+print(x[::-1])
+
+indices = tf.constant([0, 3])
+x_indices = tf.gather(x, indices)
+
+x = tf.constant([[1, 2], [3, 4], [5, 6]])
+
+print(x[0, :])
+print(x[0:2, :])
+
+# Reshaping
+x = tf.range(9)
+
+x = tf.reshape(x, (3, 3))
+
+x = tf.transpose(x, perm=[1, 0])