# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# 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
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
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"""
permute(0, 2, 1) op
"""
from typing import List
from aitemplate import backend
from aitemplate.backend import registry
from aitemplate.compiler.base import IntVar, Operator, Tensor
from aitemplate.compiler.tensor_accessor import TensorAccessor
# pylint: disable=C0103,W0221
[docs]class permute021(Operator):
"""
Permutes the input tensor from (B1, B2, ..., Bn, N, M) to (B1, B2, ..., Bn, M, N).
Args:
input (Tensor[B1, B2, ..., Bn, N, M]): the source tensor with 3 dimensions
Returns:
output (Tensor[B1, B2, ..., Bn, M, N]): the destination tensor
Example:
.. highlight:: python
.. code-block:: python
X = Tensor(shape=[2, 384, 262], name="X", is_input=True)
Y = ops.permute021()(X)
y_shape = [d._attrs["values"][0] for d in Y.shape()]
print(y_shape)
Outs:
[2, 262, 384]
"""
def __init__(self):
super().__init__()
self._attrs["op"] = "permute021"
def _infer_shapes(self, x: Tensor) -> List[IntVar]:
"""Infers shapes for permute021."""
x_shape = x._attrs["shape"]
return x_shape[:-2] + [x_shape[-1], x_shape[-2]]
def __call__(self, x: Tensor) -> Tensor:
assert len(x.shape()) > 2, "The input tensor must have at least 3 dimensions"
self._attrs["inputs"] = [x]
self._attrs["input_accessors"] = [TensorAccessor(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:
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,
)