【TensorFlow】筆記：基礎(chǔ)知識(shí)-變量

import tensorflow as tfmy_tensor = tf.constant([[1.0, 2.0], [3.0, 4.0]])my_variable = tf.Variable(my_tensor)

bool_variable = tf.Variable([False, False, False, True])complex_variable = tf.Variable([5 + 4j, 6 + 1j])

print("Shape: ",my_variable.shape)print("DType: ",my_variable.dtype)print("As NumPy: ", my_variable.numpy)
# outputShape:  (2, 2)DType:  'float32'>As NumPy:  'Variable:0' shape=(2, 2) dtype=float32, numpy=array([[1., 2.],       [3., 4.]], dtype=float32)>>

print("A variable:",my_variable)print("\nViewed as a tensor:", tf.convert_to_tensor(my_variable))print("\nIndex of highest value:", tf.argmax(my_variable))
# This creates a new tensor; it does not reshape the variable.print("\nCopying and reshaping: ", tf.reshape(my_variable, ([1,4]))
# outputA variable: 'Variable:0' shape=(2, 2) dtype=float32, numpy=array([[1., 2.],       [3., 4.]], dtype=float32)>
Viewed as a tensor: tf.Tensor([[1. 2.] [3. 4.]], shape=(2, 2), dtype=float32)
Index of highest value: tf.Tensor([1 1], shape=(2,), dtype=int64)
Copying and reshaping:  tf.Tensor([[1. 2. 3. 4.]], shape=(1, 4), dtype=float32)