MNN/test/expr/GatherTest.cpp

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- build: - unify schema building in core and converter; - add more build script for android; - add linux build script for python; - ops impl: - add floor mod support in binary; - use eltwise impl in add/max/sub/mul binary for optimization; - remove fake double support in cast; - fix 5d support for concat; - add adjX and adjY support for batch matmul; - optimize conv2d back prop filter; - add pad mode support for conv3d; - fix bug in conv2d & conv depthwise with very small feature map; - optimize binary without broacast; - add data types support for gather; - add gather ND support; - use uint8 data type in gather v2; - add transpose support for matmul; - add matrix band part; - add dim != 4 support for padding, reshape & tensor convert; - add pad type support for pool3d; - make ops based on TensorFlow Lite quantization optional; - add all & any support for reduction; - use type in parameter as output type in reduction; - add int support for unary; - add variable weight support for conv2d; - fix conv2d depthwise weights initialization; - fix type support for transpose; - fix grad outputs count for reduce grad and reshape grad; - fix priorbox & detection output; - fix metal softmax error; - python: - add runSessionWithCallBackInfo interface; - add max nodes limit (1400) for visualization tool; - fix save error in python3; - align default dim; - convert: - add extra design for optimization; - add more post converting optimizers; - add caffe v1 weights blob support; - add cast, unary, conv transpose support for onnx model; - optimize batchnorm, conv with variable weights, prelu, reshape, slice, upsample for onnx model; - add cos/sin/atan/tan support for unary for tensorflow model; - add any/all support for reduction for tensorflow model; - add elu, conv3d, pool3d support for tensorflow model; - optimize argmax, batchnorm, concat, batch to space, conv with variable weights, prelu, slice for tensorflow model; - others: - fix size computer lock; - fix thread pool deadlock; - add express & parameters in express; - rewrite blitter chooser without static map; - add tests for expr;
2019-10-29 13:37:26 +08:00
//
// GatherTest.cpp
// MNNTests
//
// Created by MNN on 2019/09/17.
// Copyright © 2018, Alibaba Group Holding Limited
//
/*
Test Case From https://www.tensorflow.org/api_docs/cc/class/tensorflow/ops/gather-nd
*/
2019-12-27 22:16:57 +08:00
#include <MNN/expr/ExprCreator.hpp>
- build: - unify schema building in core and converter; - add more build script for android; - add linux build script for python; - ops impl: - add floor mod support in binary; - use eltwise impl in add/max/sub/mul binary for optimization; - remove fake double support in cast; - fix 5d support for concat; - add adjX and adjY support for batch matmul; - optimize conv2d back prop filter; - add pad mode support for conv3d; - fix bug in conv2d & conv depthwise with very small feature map; - optimize binary without broacast; - add data types support for gather; - add gather ND support; - use uint8 data type in gather v2; - add transpose support for matmul; - add matrix band part; - add dim != 4 support for padding, reshape & tensor convert; - add pad type support for pool3d; - make ops based on TensorFlow Lite quantization optional; - add all & any support for reduction; - use type in parameter as output type in reduction; - add int support for unary; - add variable weight support for conv2d; - fix conv2d depthwise weights initialization; - fix type support for transpose; - fix grad outputs count for reduce grad and reshape grad; - fix priorbox & detection output; - fix metal softmax error; - python: - add runSessionWithCallBackInfo interface; - add max nodes limit (1400) for visualization tool; - fix save error in python3; - align default dim; - convert: - add extra design for optimization; - add more post converting optimizers; - add caffe v1 weights blob support; - add cast, unary, conv transpose support for onnx model; - optimize batchnorm, conv with variable weights, prelu, reshape, slice, upsample for onnx model; - add cos/sin/atan/tan support for unary for tensorflow model; - add any/all support for reduction for tensorflow model; - add elu, conv3d, pool3d support for tensorflow model; - optimize argmax, batchnorm, concat, batch to space, conv with variable weights, prelu, slice for tensorflow model; - others: - fix size computer lock; - fix thread pool deadlock; - add express & parameters in express; - rewrite blitter chooser without static map; - add tests for expr;
2019-10-29 13:37:26 +08:00
#include "MNNTestSuite.h"
#include "MNN_generated.h"
using namespace MNN::Express;
class GatherTest : public MNNTestCase {
public:
virtual bool run() {
std::unique_ptr<MNN::OpT> gatherOp(new MNN::OpT);
gatherOp->type = MNN::OpType_GatherND;
auto parameter = _Input({2, 2}, NHWC, halide_type_of<int32_t>());
auto indice = _Input({2, 2}, NHWC, halide_type_of<int32_t>());
auto y = Variable::create(Expr::create(gatherOp.get(), {parameter, indice}));
{
parameter->resize({2, 2});
auto ptr = parameter->writeMap<int32_t>();
ptr[0] = 7;
ptr[1] = 2;
ptr[2] = 4;
ptr[3] = 6;
}
{
auto indicePtr = indice->writeMap<int32_t>();
indicePtr[0] = 0;
indicePtr[1] = 0;
indicePtr[2] = 1;
indicePtr[3] = 1;
auto size = y->getInfo()->size;
if (size != 2) {
return false;
}
auto yPtr = y->readMap<int32_t>();
if (yPtr[0] != 7 || yPtr[1] != 6) {
return false;
}
}
{
indice->resize({2, 1});
auto indicePtr = indice->writeMap<int32_t>();
indicePtr[0] = 1;
indicePtr[1] = 0;
auto size = y->getInfo()->size;
if (4 != size) {
return false;
}
auto yPtr = y->readMap<int32_t>();
if (yPtr[0] != 4 || yPtr[1] != 6 || yPtr[2] != 7 || yPtr[3] != 2) {
return false;
}
}
{
indice->resize({1, 1});
auto indicePtr = indice->writeMap<int32_t>();
indicePtr[0] = 1;
parameter->resize({2, 2, 2});
auto parameterPtr = parameter->writeMap<int32_t>();
for (int i=0; i<parameter->getInfo()->size; ++i) {
parameterPtr[i] = i;
}
auto size = y->getInfo()->size;
if (4 != size) {
return false;
}
auto yPtr = y->readMap<int32_t>();
for (int i=0; i<size; ++i) {
if (yPtr[i] != 4 + i) {
return false;
}
}
}
return true;
}
};
MNNTestSuiteRegister(GatherTest, "expr/Gather");