tf.convert_to_tensor  |  TensorFlow v2.16.1 (original) (raw)

tf.convert_to_tensor

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Converts the given value to a Tensor.

tf.convert_to_tensor(
    value, dtype=None, dtype_hint=None, name=None
) -> tf.Tensor

Used in the notebooks

This function converts Python objects of various types to Tensorobjects. It accepts Tensor objects, numpy arrays, Python lists, and Python scalars.

For example:

import numpy as np def my_func(arg): arg = tf.convert_to_tensor(arg, dtype=tf.float32) return arg

# The following calls are equivalent. `` value_1 = my_func(tf.constant([[1.0, 2.0], [3.0, 4.0]])) print(value_1) tf.Tensor( [[1. 2.] [3. 4.]], shape=(2, 2), dtype=float32) value_2 = my_func([[1.0, 2.0], [3.0, 4.0]]) print(value_2) tf.Tensor( [[1. 2.] [3. 4.]], shape=(2, 2), dtype=float32) value_3 = my_func(np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)) print(value_3) tf.Tensor( [[1. 2.] [3. 4.]], shape=(2, 2), dtype=float32)

This function can be useful when composing a new operation in Python (such as my_func in the example above). All standard Python op constructors apply this function to each of their Tensor-valued inputs, which allows those ops to accept numpy arrays, Python lists, and scalars in addition to Tensor objects.