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Added batch dims in gather (#435) 

Signed-off-by: Chen Xin <jack.chen@verisilicon.com>

Co-authored-by: Chen Xin <jack.chen@verisilicon.com>
This commit is contained in:
chxin66 2022-07-19 12:33:09 +08:00 committed by GitHub
parent f52cb852d6
commit 9f331ed5ec
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GPG Key ID: 4AEE18F83AFDEB23
4 changed files with 85 additions and 5 deletions
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3
include/tim/vx/ops/gather.h
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@ -37,12 +37,13 @@ namespace ops {
class Gather : public DirectMapOp {
public:
Gather(Graph* Graph, int axis);
Gather(Graph* Graph, int axis, int batch_dims = 0);
std::shared_ptr<Operation> Clone(std::shared_ptr<Graph>& graph) const override;
protected:
int axis_;
int batch_dims_;
};
} // namespace ops

3
src/tim/transform/ops/gather_layout_inference.h
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@ -41,7 +41,8 @@ class GatherLayoutInfer : public OpLayoutInfer {
ReverseInputsPermuteVector();
auto gather = context_->infer_graph_->CreateOperation<vx::ops::Gather>(
op_->impl()->node()->nn_param.gather.axis);
op_->impl()->node()->nn_param.gather.axis,
op_->impl()->node()->nn_param.gather.batch_dims);
int32_t output_rank = -1;
for (const auto& i_src : op_->impl()->InputsTensor()) {
(*gather).BindInput(context_->GetMapedTensor(i_src));

7
src/tim/vx/ops/gather.cc
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@ -30,13 +30,14 @@ namespace tim {
namespace vx {
namespace ops {
Gather::Gather(Graph* graph, int axis)
: DirectMapOp(graph, VSI_NN_OP_GATHER), axis_(axis) {
Gather::Gather(Graph* graph, int axis, int batch_dims)
: DirectMapOp(graph, VSI_NN_OP_GATHER), axis_(axis), batch_dims_(batch_dims) {
this->impl()->node()->nn_param.gather.axis = axis_;
this->impl()->node()->nn_param.gather.batch_dims = batch_dims_;
}
std::shared_ptr<Operation> Gather::Clone(std::shared_ptr<Graph>& graph) const {
return graph->CreateOperation<Gather>(this->axis_);
return graph->CreateOperation<Gather>(this->axis_, this->batch_dims_);
}
} // namespace ops

77
src/tim/vx/ops/gather_test.cc Normal file
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@ -0,0 +1,77 @@
/****************************************************************************
*
* Copyright (c) 2022 Vivante Corporation
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and associated documentation files (the "Software"),
* to deal in the Software without restriction, including without limitation
* the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
* DEALINGS IN THE SOFTWARE.
*
*****************************************************************************/
#include "tim/vx/context.h"
#include "tim/vx/graph.h"
#include "tim/vx/ops/gather.h"
#include <iostream>
#include "gtest/gtest.h"
#include "test_utils.h"
TEST(Gather, shape_5_3_2_2_int32_axis_1_batchdims_1) {
auto ctx = tim::vx::Context::Create();
auto graph = ctx->CreateGraph();
tim::vx::ShapeType in_shape({5, 3, 2, 2});
tim::vx::ShapeType indices_shape({2, 2, 2});
tim::vx::ShapeType out_shape({5, 2, 2, 2, 2});
tim::vx::TensorSpec input_spec(tim::vx::DataType::INT8, in_shape,
tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec indices_spec(tim::vx::DataType::INT32, indices_shape,
tim::vx::TensorAttribute::INPUT);
tim::vx::TensorSpec output_spec(tim::vx::DataType::INT8, out_shape,
tim::vx::TensorAttribute::OUTPUT);
auto input_tensor = graph->CreateTensor(input_spec);
auto indices_tensor = graph->CreateTensor(indices_spec);
auto output_tensor = graph->CreateTensor(output_spec);
std::vector<int8_t> in_data = {
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44,
45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
};
//The index value greater than rank-1 is regarded as rank-1
std::vector<int32_t> indices = {1, 0, 0, 1, 1, 0, 0, 1};
std::vector<int8_t> golden = {
5, 6, 7, 8, 9, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 5,
6, 7, 8, 9, 20, 21, 22, 23, 24, 15, 16, 17, 18, 19, 15, 16,
17, 18, 19, 20, 21, 22, 23, 24, 35, 36, 37, 38, 39, 30, 31, 32,
33, 34, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 50, 51, 52, 53,
54, 45, 46, 47, 48, 49, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54};
EXPECT_TRUE(
input_tensor->CopyDataToTensor(in_data.data(), in_data.size()));
EXPECT_TRUE(
indices_tensor->CopyDataToTensor(indices.data(), indices.size() * 4));
auto op = graph->CreateOperation<tim::vx::ops::Gather>(1,1);
(*op).BindInputs({input_tensor, indices_tensor}).BindOutputs({output_tensor});
EXPECT_TRUE(graph->Compile());
EXPECT_TRUE(graph->Run());
std::vector<int8_t> output(golden.size());
EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
EXPECT_EQ(golden, output);
}