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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
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"""
Permute(2, 1, 0) op.
Swap the dimension of dim0 and dim2 of input 3d tensor.
"""
from typing import List
from aitemplate import backend
from aitemplate.backend import registry
from aitemplate.compiler.base import IntVar, Operator, Tensor
# pylint: disable=C0103,W0221
[docs]class permute210(Operator):
"""
Permutes the input 3d tensor from (B, N, M) to (M, N, B).
Args:
input (Tensor[B, N, M]): the source tensor with 3 dimensions
Returns:
output (Tensor[M, N, B]): the destination tensor
Example:
.. highlight:: python
.. code-block:: python
X = Tensor(shape=[2, 384, 262], name="X", is_input=True)
Y = ops.permute210()(X)
y_shape = [d._attrs["values"][0] for d in Y.shape()]
print(y_shape)
Outs:
[262, 384, 2]
"""
def __init__(self):
super().__init__()
self._attrs["op"] = "permute210"
def _infer_shapes(self, x: Tensor) -> List[IntVar]:
"""Infers shapes for permute210.
Parameters
----------
x : Tensor
Returns
------
List[IntVar]
Inferred output 3d tensor with input shape.
Because its a permute210 operation,
Out.d0=In.d2, Out.d2=In.d0.
"""
x_shape = x._attrs["shape"]
return [x_shape[2], x_shape[1], x_shape[0]]
def __call__(self, x: Tensor) -> Tensor:
"""
Return the output tensor of permute210
Parameters
----------
x : Tensor
Returns
-------
Tensor
Generate output tensors of function calls.
In permute210, its a 3d tensor with d2,d1,d0 of
input Tensor.
"""
self._attrs["inputs"] = [x]
self._set_depth()
output_shape = self._infer_shapes(x)
output = Tensor(output_shape, src_ops={self})
output._attrs["dtype"] = x.dtype()
self._attrs["outputs"] = [output]
return output
[docs] def gen_function(self) -> str:
"""
Generate function body
Returns
-------
str
The function body string
"""
target = backend.target.Target.current()
template_path = target.template_path()
func_key = "{target}.{op}.gen_function".format(
target=target.name(), op=self._attrs["op"]
)
func = registry.get(func_key)
return func(
self._attrs,
template_path,
)