m53297601
/
Paddle
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Merge pull request #11174 from kuke/argsort_dev

Browse Source 
Add the argsort operator
analysis/code-clean
Yibing Liu 7 years ago committed by GitHub
parent 66c91911cf 9386ac0a40
commit 5f79c7fbb6
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
7 changed files with 445 additions and 0 deletions
Show Stats Download Patch File Download Diff File

8
doc/fluid/api/layers.rst
Unescape View File

@ -1468,6 +1468,14 @@ argmax
.. autofunction:: paddle.fluid.layers.argmax .. autofunction:: paddle.fluid.layers.argmax
:noindex: :noindex:
.. _api_fluid_layers_argsort:
argsort
-------
.. autofunction:: paddle.fluid.layers.argsort
:noindex:
.. _api_fluid_layers_ones: .. _api_fluid_layers_ones:
ones ones

87
paddle/fluid/operators/argsort_op.cc
Unescape View File

@ -0,0 +1,87 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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. */
#include "paddle/fluid/operators/argsort_op.h"
namespace paddle {
namespace operators {
class ArgsortOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext *ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("X"),
"Input(X) of ArgsortOp should not be null.");
PADDLE_ENFORCE(ctx->HasOutput("Out"),
"Output(Out) of ArgsortOp should not be null.");
PADDLE_ENFORCE(ctx->HasOutput("Indices"),
"Output(Indices) of ArgsortOp should not be null.");
auto in_dims = ctx->GetInputDim("X");
int axis = ctx->Attrs().Get<int>("axis");
auto num_dims = in_dims.size();
PADDLE_ENFORCE(axis < num_dims,
"Attr(axis) %d of ArgsortOp is out of bounds for Input(X)'s "
"rank %d.",
axis, num_dims);
PADDLE_ENFORCE(axis >= -num_dims,
"Attr(axis) %d of ArgsortOp must be not less than "
"-rank(Input(X)) (%d).",
axis, num_dims);
ctx->SetOutputDim("Out", in_dims);
ctx->SetOutputDim("Indices", in_dims);
ctx->ShareLoD("X", "Out");
ctx->ShareLoD("X", "Indices");
}
};
class ArgsortOpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
AddInput("X", "(Tensor) The input of Argsort op.");
AddOutput("Out",
"(Tensor) The sorted tensor of Argsort op, with the same "
"shape as Input(X).");
AddOutput("Indices",
"(Tensor) The indices of a tensor giving the sorted order, with "
"the same shape as Input(X).");
AddComment(R"DOC(
Argsort operator
Performs sorting on the input tensor along the given axis and outputs two
tensors, Output(Out) and Output(Indices). They reserve the same shape
with Input(X), and Output(Out) represents the sorted tensor while
Output(Indices) gives the sorted order along the given axis Attr(axis).
)DOC");
AddAttr<int>("axis",
"(int, default -1) The axis along which to sort the tensor. "
"When axis < 0, the actual axis will be the |axis|'th "
"counting backwards. Default -1, the last dimension.")
.SetDefault(-1);
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(argsort, ops::ArgsortOp, ops::ArgsortOpMaker,
paddle::framework::EmptyGradOpMaker);
REGISTER_OP_CPU_KERNEL(argsort,
ops::ArgsortKernel<paddle::platform::CPUPlace, float>,
ops::ArgsortKernel<paddle::platform::CPUPlace, double>);

151
paddle/fluid/operators/argsort_op.cu
Unescape View File

@ -0,0 +1,151 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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. */
#include <thrust/execution_policy.h>
#include <thrust/sort.h>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/argsort_op.h"
#include "paddle/fluid/platform/assert.h"
#include "paddle/fluid/platform/cuda_device_function.h"
#include "paddle/fluid/platform/cuda_primitives.h"
namespace paddle {
namespace operators {
using Tensor = framework::Tensor;
using platform::PADDLE_CUDA_NUM_THREADS;
const int kMaxRank = 9; // The max rank of a tensor allowed in Fluid
__global__ void ComputeTargetIdx(const int64_t* in_dims, int dims_size,
int axis, int64_t n, int64_t* trg_idx,
int64_t* med_ids) {
int64_t index = threadIdx.x + blockDim.x * blockIdx.x;
if (index < n) {
int64_t shape_out_axis[kMaxRank - 1] = {0};
int64_t dims_out_axis[kMaxRank - 1] = {0};
int64_t tmp = index;
int64_t pos_in_axis = 0;
int64_t i = dims_size - 2;
int64_t dim_axis = 0;
for (int64_t j = dims_size - 1; j >= 0; --j) {
int64_t dim = in_dims[j];
if (j != axis) {
shape_out_axis[i] = tmp % dim;
dims_out_axis[i] = dim;
i--;
} else {
dim_axis = dim;
pos_in_axis = tmp % dim_axis;
}
tmp /= dim;
}
int64_t group = (dims_size > 1) ? shape_out_axis[0] : 0;
for (int64_t j = 0; j < dims_size - 2; ++j) {
group = group * dims_out_axis[j + 1] + shape_out_axis[j + 1];
}
int64_t traget_idx = group * dim_axis + pos_in_axis;
trg_idx[index] = traget_idx;
med_ids[traget_idx] = pos_in_axis;
}
}
template <typename T>
__global__ void PermuteInData(const T* in, const int64_t* trg_idx, int64_t n,
T* med_out) {
int index = threadIdx.x + blockDim.x * blockIdx.x;
if (index < n) {
med_out[trg_idx[index]] = in[index];
}
}
template <typename T>
__global__ void Sort(int64_t axis_dim, int64_t groups, T* med_out,
int64_t* med_ids) {
int index = threadIdx.x + blockDim.x * blockIdx.x;
if (index < groups) {
thrust::sort_by_key(thrust::device, med_out + index * axis_dim,
med_out + axis_dim * (1 + index),
med_ids + index * axis_dim);
}
}
template <typename T>
__global__ void PermuteMediateData(const T* med_out, const int64_t* med_ids,
const int64_t* trg_idx, int64_t n, T* out,
int64_t* indices) {
int index = threadIdx.x + blockDim.x * blockIdx.x;
if (index < n) {
out[index] = med_out[trg_idx[index]];
indices[index] = med_ids[trg_idx[index]];
}
}
template <typename T>
class ArgsortOpCUDAKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
auto* input = ctx.Input<Tensor>("X");
auto* output = ctx.Output<Tensor>("Out");
auto* indices = ctx.Output<Tensor>("Indices");
int axis = ctx.Attr<int>("axis");
auto in_dims = input->dims();
axis = (axis < 0) ? (in_dims.size() + axis) : axis;
const T* in_data = input->data<T>();
T* out_data = output->mutable_data<T>(ctx.GetPlace());
int64_t* ids_data = indices->mutable_data<int64_t>(ctx.GetPlace());
int64_t numel = input->numel();
int64_t groups = numel / in_dims[axis];
std::vector<int64_t> in_dims_vec = vectorize(in_dims);
thrust::device_vector<int64_t> in_dims_dev(in_dims_vec.begin(),
in_dims_vec.end());
int64_t* in_dims_data = thrust::raw_pointer_cast(in_dims_dev.data());
// Mediate tensor for sorting data and indices
Tensor mediate_output, mediate_indices;
T* med_out_data =
mediate_output.mutable_data<T>(input->dims(), ctx.GetPlace());
int64_t* med_ids_data =
mediate_indices.mutable_data<int64_t>(in_dims, ctx.GetPlace());
// Target index of each element along the given axis in the mediate tensors
Tensor trg_idx_t;
int64_t* trg_idx = trg_idx_t.mutable_data<int64_t>(in_dims, ctx.GetPlace());
auto stream = ctx.cuda_device_context().stream();
const int num_threads = PADDLE_CUDA_NUM_THREADS;
ComputeTargetIdx<<<(numel - 1) / num_threads + 1, num_threads, 0, stream>>>(
in_dims_data, in_dims.size(), axis, numel, trg_idx, med_ids_data);
PermuteInData<<<(numel - 1) / num_threads + 1, num_threads, 0, stream>>>(
in_data, trg_idx, numel, med_out_data);
Sort<<<(groups - 1) / num_threads + 1, num_threads, 0, stream>>>(
in_dims[axis], groups, med_out_data, med_ids_data);
PermuteMediateData<<<(numel - 1) / num_threads + 1, num_threads, 0,
stream>>>(med_out_data, med_ids_data, trg_idx, numel,
out_data, ids_data);
}
};
} // namespace operators
} // namespace paddle
REGISTER_OP_CUDA_KERNEL(argsort, paddle::operators::ArgsortOpCUDAKernel<float>,
paddle::operators::ArgsortOpCUDAKernel<double>);

81
paddle/fluid/operators/argsort_op.h
Unescape View File

@ -0,0 +1,81 @@
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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. */
#pragma once
#include <algorithm>
#include <utility>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
namespace paddle {
namespace operators {
template <typename DeviceContext, typename T>
class ArgsortKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& ctx) const override {
auto* input = ctx.Input<framework::Tensor>("X");
auto* output = ctx.Output<framework::Tensor>("Out");
auto* indices = ctx.Output<framework::Tensor>("Indices");
int axis = ctx.Attr<int>("axis");
auto in_dims = input->dims();
axis = (axis < 0) ? (in_dims.size() + axis) : axis;
const T* in_data = input->data<T>();
T* out_data = output->mutable_data<T>(ctx.GetPlace());
int64_t* ids_data = indices->mutable_data<int64_t>(ctx.GetPlace());
int64_t groups = input->numel() / in_dims[axis];
int64_t stride = (axis == in_dims.size() - 1)
? 1
: framework::product(framework::slice_ddim(
in_dims, axis + 1, in_dims.size()));
for (int64_t i = 0; i < groups; ++i) {
int64_t idx = i;
std::vector<int64_t> shape_vec(in_dims.size(), 0);
for (int64_t dim = in_dims.size() - 1; dim >= 0; --dim) {
if (dim != axis) {
shape_vec[dim] = idx % in_dims[dim];
idx /= in_dims[dim];
}
}
int64_t start_index = shape_vec[0];
for (int64_t dim = 0; dim < in_dims.size() - 1; ++dim) {
start_index = start_index * in_dims[dim + 1] + shape_vec[dim + 1];
}
std::vector<int64_t> org_index_vec(in_dims[axis], start_index);
for (int64_t j = 1; j < in_dims[axis]; ++j) {
org_index_vec[j] += j * stride;
}
std::sort(org_index_vec.begin(), org_index_vec.end(),
[in_data](const int64_t v1, const int64_t v2) {
return in_data[v1] < in_data[v2];
});
for (size_t j = 0; j < org_index_vec.size(); ++j) {
int64_t index = start_index + j * stride;
out_data[index] = in_data[org_index_vec[j]];
ids_data[index] = (org_index_vec[j] - start_index) / stride;
}
}
}
};
} // namespace operators
} // namespace paddle

53
python/paddle/fluid/layers/tensor.py
Unescape View File

@ -33,6 +33,7 @@ __all__ = [
'fill_constant', 'fill_constant',
'argmin', 'argmin',
'argmax', 'argmax',
'argsort',
'ones', 'ones',
'zeros', 'zeros',
'reverse', 'reverse',
@ -444,6 +445,58 @@ def argmax(x, axis=0):
return out return out
def argsort(input, axis=-1, name=None):
"""
Performs sorting on the input Variable along the given axis, and outputs
sorted data Varibale and its corresponding index Variable with the same
shape as :attr:`input`.
.. code-block:: text
For example, the given axis is -1 and the input Variable
input = [[0.15849551, 0.45865775, 0.8563702 ],
[0.12070083, 0.28766365, 0.18776911]],
after argsort, the sorted Vairable becomes
out = [[0.15849551, 0.45865775, 0.8563702 ],
[0.12070083, 0.18776911, 0.28766365]],
and the sorted indices along the given axis turn outs to be
indices = [[0, 1, 2],
[0, 2, 1]]
Args:
input(Variable): The input Variable for sorting.
axis(int): The axis along which to sort the input Variable. When
:attr:`axis` < 0, the actual axis will be :attr:`axis` +
rank(:attr:`input`). Default -1, the last dimension.
name(str|None): (optional) A name for this layer. If set None, the
layer will be named automatically.
Returns:
tuple: A tuple of sorted data Variable and the sorted indices.
Examples:
.. code-block:: python
input = fluid.layers.data(data=[2, 3])
out, indices = fluid.layers.argsort(input, axis=0)
"""
helper = LayerHelper("argsort", **locals())
out = helper.create_tmp_variable(dtype=input.dtype, stop_gradient=True)
ids = helper.create_tmp_variable(VarDesc.VarType.INT64, stop_gradient=True)
helper.append_op(
type='argsort',
inputs={'X': input},
outputs={'Out': out,
'Indices': ids},
attrs={'axis': axis})
return out, ids
def ones(shape, dtype, force_cpu=False): def ones(shape, dtype, force_cpu=False):
""" """
**ones** **ones**

56
python/paddle/fluid/tests/unittests/test_argsort_op.py
Unescape View File

@ -0,0 +1,56 @@
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# 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 unittest
import numpy as np
from op_test import OpTest
class TestArgsortOp(OpTest):
def setUp(self):
self.init_axis()
x = np.random.random((2, 3, 4, 5, 10)).astype("float32")
if self.axis < 0:
self.axis = self.axis + len(x.shape)
self.indices = np.argsort(x, kind='quicksort', axis=self.axis)
self.out = np.sort(x, kind='quicksort', axis=self.axis)
self.op_type = "argsort"
self.inputs = {'X': x}
self.attrs = {'axis': self.axis}
self.outputs = {'Indices': self.indices, 'Out': self.out}
def init_axis(self):
self.axis = -1
def test_check_output(self):
self.check_output()
class TestArgsortOpAxis0(TestArgsortOp):
def init_axis(self):
self.axis = 0
class TestArgsortOpAxis1(TestArgsortOp):
def init_axis(self):
self.axis = 1
class TestArgsortOpAxisNeg2(TestArgsortOp):
def init_axis(self):
self.axis = -2
if __name__ == "__main__":
unittest.main()

9
python/paddle/fluid/tests/unittests/test_layers.py
Unescape View File

@ -419,6 +419,15 @@ class TestBook(unittest.TestCase):
self.assertIsNotNone(iou) self.assertIsNotNone(iou)
print(str(program)) print(str(program))
def test_argsort(self):
program = Program()
with program_guard(program):
data = layers.data(name='x', shape=[2, 3, 3], dtype="float32")
out, ids = layers.argsort(input=data, axis=1)
self.assertIsNotNone(out)
self.assertIsNotNone(ids)
print(str(program))
if __name__ == '__main__': if __name__ == '__main__':
unittest.main() unittest.main()

Write Preview
Loading…
Cancel
Save