TensorFlow is open-source python library designed by Google to develop Machine Learning models and deep learning neural networks.
bitcast() is method in tensorflow library which is used to bitcast a tensor from one type to another type. It doesn’t copy the data.
Syntax:
tf.bitcast(
input, type, name
)
Arguments:
1. input: It is the Tensor and the allowed type for this tensor are
bfloat16, half, float32, float64, int64, int32, uint8, uint16, uint32,
uint64, int8, int16, complex64, complex128, qint8, quint8, qint16, quint16, qint32.
2. type: It defines the dtype in which input need to be bitcasted.
3. name: It is an optional argument. It is used to give a name to operation.
Return: It returns a tensor of type type.
Note: bitcast can’t be used to cast real dtype to complex dtype. It will raise InvalidArgumentError.
Example 1:
Python3
# importing the libraryimport tensorflow# initializing the constant tensor of dtype uint32a = tensorflow.constant(0xffffffff, dtype=tensorflow.uint32)# Checking the initialized tensorprint('a:',a)# bitcasting to dtype uint8b = tensorflow.bitcast(a, tensorflow.uint8)# Checking the bitcasted tensorprint('b:',b) |
Output:
a: tf.Tensor(4294967295, shape=(), dtype=uint32) b: tf.Tensor([255 255 255 255], shape=(4,), dtype=uint8)
Example 2:
This example tries to bitcast a real dtype to complex dtype
Python3
# importing the libraryimport tensorflow# initializing the constant tensor of dtype uint32a = tensorflow.constant(0xffffffff, dtype=tensorflow.uint32)# Checking the initialized tensorprint('a:',a)# bitcasting to dtype complex128b = tensorflow.bitcast(a, tensorflow.complex128) |
Output:
