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https://github.com/aladdinpersson/Machine-Learning-Collection.git
synced 2026-02-21 11:18:01 +00:00
83 lines
1.2 KiB
Python
83 lines
1.2 KiB
Python
import os
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os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"
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import tensorflow as tf
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# Initialization
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x = tf.constant(4, shape=(1, 1), dtype=tf.float32)
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print(x)
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x = tf.constant([[1, 2, 3], [4, 5, 6]], shape=(2, 3))
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print(x)
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x = tf.eye(3)
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print(x)
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x = tf.ones((4, 3))
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print(x)
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x = tf.zeros((3, 2, 5))
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print(x)
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x = tf.random.uniform((2, 2), minval=0, maxval=1)
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print(x)
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x = tf.random.normal((3, 3), mean=0, stddev=1)
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print(tf.cast(x, dtype=tf.float64))
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# tf.float (16,32,64), tf.int (8, 16, 32, 64), tf.bool
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x = tf.range(9)
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x = tf.range(start=0, limit=10, delta=2)
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print(x)
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# Math
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x = tf.constant([1, 2, 3])
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y = tf.constant([9, 8, 7])
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z = tf.add(x, y)
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z = x + y
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z = tf.subtract(x, y)
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z = x - y
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z = tf.divide(x, y)
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z = x / y
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z = tf.multiply(x, y)
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z = x * y
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z = tf.tensordot(x, y, axes=1)
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z = x ** 5
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x = tf.random.normal((2, 3))
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y = tf.random.normal((3, 2))
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z = tf.matmul(x, y)
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z = x @ y
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x = tf.random.normal((2, 2))
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# Indexing
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x = tf.constant([0, 1, 1, 2, 3, 1, 2, 3])
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print(x[:])
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print(x[1:])
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print(x[1:3])
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print(x[::2])
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print(x[::-1])
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indices = tf.constant([0, 3])
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x_indices = tf.gather(x, indices)
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x = tf.constant([[1, 2], [3, 4], [5, 6]])
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print(x[0, :])
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print(x[0:2, :])
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# Reshaping
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x = tf.range(9)
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x = tf.reshape(x, (3, 3))
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x = tf.transpose(x, perm=[1, 0])
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