Cast#
Outputs the given input tensor to the output tensor. The input is transformed from one precision to another.
All conversions between supported data types are allowed.
Attributes#
toType
The DataType of the output tensor.
Inputs#
input: tensor of type T1
.
Outputs#
output: tensor of type T2
.
Data Types#
T1: bool
, uint8
, int8
, int32
, int64
, float16
, bfloat16
, float32
T2: bool
, uint8
, int8
, int32
, int64
, float16
, bfloat16
, float32
Shape Information#
input and output are tensors with a shape of \([a_0,...,a_n]\)
Examples#
Cast
in1 = network.add_input("input1", dtype=trt.float32, shape=(1, 1, 3, 3))
layer = network.add_cast(in1, trt.int32)
network.mark_output(layer.get_output(0))
inputs[in1.name] = np.array(
[
[
[
[1.2, 2.3, 3.4],
[4.5, 5.6, 6.7],
[7.8, 8.9, 9.1],
]
]
]
)
outputs[layer.get_output(0).name] = layer.get_output(0).shape
expected[layer.get_output(0).name] = np.array(
[
[
[
[1.0, 2.0, 3.0],
[4.0, 5.0, 6.0],
[7.0, 8.0, 9.0],
]
]
]
)
C++ API#
For more information about the C++ ICastLayer operator, refer to the C++ ICastLayer documentation.
Python API#
For more information about the Python ICastLayer operator, refer to the Python ICastLayer documentation.