# Copyright 2022-2023 XProbe Inc.
# derived from copyright 1999-2021 Alibaba Group Holding Ltd.
#
# 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.
from ... import opcodes as OperandDef
from ...serialization.serializables import Int32Field, KeyField
from ..array_utils import as_same_device, device
from ..core import TensorOrder
from ..datasource import tensor as astensor
from ..operands import TensorHasInput, TensorOperandMixin
from ..utils import reverse_order, validate_axis
def _swap(it, axis1, axis2):
new_it = list(it)
new_it[axis1], new_it[axis2] = it[axis2], it[axis1]
return tuple(new_it)
class TensorSwapAxes(TensorHasInput, TensorOperandMixin):
_op_type_ = OperandDef.SWAPAXES
_input = KeyField("input")
_axis1 = Int32Field("axis1")
_axis2 = Int32Field("axis2")
def __init__(self, axis1=None, axis2=None, **kw):
super().__init__(_axis1=axis1, _axis2=axis2, create_view=True, **kw)
@property
def axis1(self):
return self._axis1
@property
def axis2(self):
return self._axis2
def __call__(self, a):
axis1, axis2 = self._axis1, self._axis2
if (axis1 == 0 and axis2 == a.ndim - 1) or (axis1 == a.ndim - 1 and axis2 == 0):
tensor_order = reverse_order(a.order)
else:
tensor_order = TensorOrder.C_ORDER
shape = _swap(a.shape, self.axis1, self.axis2)
return self.new_tensor([a], shape, order=tensor_order)
def _set_inputs(self, inputs):
super()._set_inputs(inputs)
self._input = self._inputs[0]
def on_output_modify(self, new_output):
op = TensorSwapAxes(
axis1=self._axis2,
axis2=self._axis1,
dtype=new_output.dtype,
sparse=new_output.issparse(),
)
return op(new_output)
def on_input_modify(self, new_input):
op = self.copy().reset_key()
return op(new_input)
@classmethod
def tile(cls, op):
axis1, axis2 = op.axis1, op.axis2
in_tensor = op.inputs[0]
out_tensor = op.outputs[0]
out_chunks = []
for c in in_tensor.chunks:
chunk_shape = _swap(c.shape, axis1, axis2)
chunk_idx = _swap(c.index, axis1, axis2)
chunk_op = op.copy().reset_key()
out_chunk = chunk_op.new_chunk(
[c], shape=chunk_shape, index=chunk_idx, order=out_tensor.order
)
out_chunks.append(out_chunk)
new_op = op.copy()
nsplits = _swap(in_tensor.nsplits, axis1, axis2)
return new_op.new_tensors(
[in_tensor],
out_tensor.shape,
order=out_tensor.order,
chunks=out_chunks,
nsplits=nsplits,
)
@classmethod
def execute(cls, ctx, op):
(x,), device_id, xp = as_same_device(
[ctx[c.key] for c in op.inputs], device=op.device, ret_extra=True
)
axis1, axis2 = op.axis1, op.axis2
with device(device_id):
ctx[op.outputs[0].key] = xp.swapaxes(x, axis1, axis2)
[docs]def swapaxes(a, axis1, axis2):
"""
Interchange two axes of a tensor.
Parameters
----------
a : array_like
Input tensor.
axis1 : int
First axis.
axis2 : int
Second axis.
Returns
-------
a_swapped : Tensor
If `a` is a Tensor, then a view of `a` is
returned; otherwise a new tensor is created.
Examples
--------
>>> import mars.tensor as mt
>>> x = mt.array([[1,2,3]])
>>> mt.swapaxes(x,0,1).execute()
array([[1],
[2],
[3]])
>>> x = mt.array([[[0,1],[2,3]],[[4,5],[6,7]]])
>>> x.execute()
array([[[0, 1],
[2, 3]],
[[4, 5],
[6, 7]]])
>>> mt.swapaxes(x,0,2).execute()
array([[[0, 4],
[2, 6]],
[[1, 5],
[3, 7]]])
"""
a = astensor(a)
axis1 = validate_axis(a.ndim, axis1)
axis2 = validate_axis(a.ndim, axis2)
if axis1 == axis2:
return a
op = TensorSwapAxes(axis1, axis2, dtype=a.dtype, sparse=a.issparse())
return op(a)