#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright 1999-2020 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. import numpy as np from ... import opcodes as OperandDef from ...serialize import ValueType, KeyField, ListField from ..operands import TensorHasInput, TensorOperandMixin from ..datasource import tensor as astensor from ..array_utils import as_same_device, device from ..utils import reverse_order from ..core import TensorOrder def _reorder(x, axes): if x is None: return return type(x)(np.array(x)[list(axes)].tolist()) class TensorTranspose(TensorHasInput, TensorOperandMixin): _op_type_ = OperandDef.TRANSPOSE _input = KeyField('input') _axes = ListField('axes', ValueType.int32) def __init__(self, axes=None, dtype=None, sparse=False, **kw): super().__init__(_axes=axes, _dtype=dtype, _sparse=sparse, # transpose will create a view _create_view=True, **kw) @property def axes(self): return getattr(self, '_axes', None) def __call__(self, a): shape = tuple(s if np.isnan(s) else int(s) for s in _reorder(a.shape, self._axes)) if self._axes == list(reversed(range(a.ndim))): # order reversed tensor_order = reverse_order(a.order) else: tensor_order = TensorOrder.C_ORDER 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 = self.copy().reset_key() 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): tensor = op.outputs[0] out_chunks = [] for c in op.inputs[0].chunks: chunk_op = op.copy().reset_key() chunk_shape = tuple(s if np.isnan(s) else int(s) for s in _reorder(c.shape, op.axes)) chunk_idx = _reorder(c.index, op.axes) out_chunk = chunk_op.new_chunk([c], shape=chunk_shape, index=chunk_idx, order=tensor.order) out_chunks.append(out_chunk) new_op = op.copy() nsplits = _reorder(op.inputs[0].nsplits, op.axes) return new_op.new_tensors(op.inputs, op.outputs[0].shape, order=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) axes = op.axes with device(device_id): ctx[op.outputs[0].key] = xp.transpose(x, axes or None) [docs]def transpose(a, axes=None): """ Permute the dimensions of a tensor. Parameters ---------- a : array_like Input tensor. axes : list of ints, optional By default, reverse the dimensions, otherwise permute the axes according to the values given. Returns ------- p : Tensor `a` with its axes permuted. A view is returned whenever possible. See Also -------- moveaxis argsort Notes ----- Use `transpose(a, argsort(axes))` to invert the transposition of tensors when using the `axes` keyword argument. Transposing a 1-D array returns an unchanged view of the original tensor. Examples -------- >>> import mars.tensor as mt >>> x = mt.arange(4).reshape((2,2)) >>> x.execute() array([[0, 1], [2, 3]]) >>> mt.transpose(x).execute() array([[0, 2], [1, 3]]) >>> x = mt.ones((1, 2, 3)) >>> mt.transpose(x, (1, 0, 2)).shape (2, 1, 3) """ a = astensor(a) if axes: if len(axes) != a.ndim: raise ValueError("axes don't match tensor") axes = axes or list(range(a.ndim))[::-1] op = TensorTranspose(axes, dtype=a.dtype, sparse=a.issparse()) return op(a)