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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
# 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 maxframe import opcodes
from maxframe.serialization.serializables import Int32Field
from maxframe.tensor.core import TensorOrder
from maxframe.tensor.datasource import tensor as astensor
from maxframe.tensor.operators import TensorHasInput, TensorOperatorMixin
from maxframe.tensor.utils import reverse_order, validate_axis
class TensorSwapAxes(TensorHasInput, TensorOperatorMixin):
_op_type_ = opcodes.SWAPAXES
axis1 = Int32Field("axis1")
axis2 = Int32Field("axis2")
def __init__(self, **kw):
super().__init__(create_view=True, **kw)
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 = self._swap(a.shape, self.axis1, self.axis2)
return self.new_tensor([a], shape, order=tensor_order)
@staticmethod
def _swap(it, axis1, axis2):
new_it = list(it)
new_it[axis1], new_it[axis2] = it[axis2], it[axis1]
return tuple(new_it)
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)
[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 maxframe.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=axis1, axis2=axis2, dtype=a.dtype, sparse=a.issparse())
return op(a)