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fuse adaptive pool dynamic output size, implement ncnn adaptive pooling dynamic outsize #5043

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merged 7 commits into from
Sep 20, 2023
Merged

fuse adaptive pool dynamic output size, implement ncnn adaptive pooling dynamic outsize #5043

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apply code-format changes
nihui Sep 19, 2023
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fuse adaptive pool dynamic output size, implement ncnn adaptive pooli…
nihui Sep 19, 2023
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nihui Sep 19, 2023
0f55c5f
Merge branch 'adaptive-pooling-2' of github.com:nihui/ncnn into adapt…
nihui Sep 19, 2023
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nihui Sep 20, 2023
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nihui Sep 20, 2023
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nihui Sep 20, 2023
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39 changes: 24 additions & 15 deletions src/layer/pooling.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -104,7 +104,16 @@ int Pooling::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) c

if (adaptive_pooling)
{
top_blob.create(out_w, out_h, channels, elemsize, opt.blob_allocator);
int _out_w = out_w == -233 ? w : out_w;
int _out_h = out_h == -233 ? h : out_h;

if (_out_w == w && _out_h == h)
{
top_blob = bottom_blob;
return 0;
}

top_blob.create(_out_w, _out_h, channels, elemsize, opt.blob_allocator);
if (top_blob.empty())
return -100;

Expand All @@ -116,18 +125,18 @@ int Pooling::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) c
const float* inptr = bottom_blob.channel(q);
float* outptr = top_blob.channel(q);

for (int i = 0; i < out_h; i++)
for (int i = 0; i < _out_h; i++)
{
// floor div
const int ih0 = h * i / out_h;
const int ih0 = h * i / _out_h;
// ceil div
const int ih1 = (h * (i + 1) + out_h - 1) / out_h;
for (int j = 0; j < out_w; j++)
const int ih1 = (h * (i + 1) + _out_h - 1) / _out_h;
for (int j = 0; j < _out_w; j++)
{
// floor div
const int iw0 = w * j / out_w;
const int iw0 = w * j / _out_w;
// ceil div
const int iw1 = (w * (j + 1) + out_w - 1) / out_w;
const int iw1 = (w * (j + 1) + _out_w - 1) / _out_w;

float max = inptr[ih0 * w + iw0];
for (int ih = ih0; ih < ih1; ih++)
Expand All @@ -140,7 +149,7 @@ int Pooling::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) c

outptr[j] = max;
}
outptr += out_w;
outptr += _out_w;
}
}
}
Expand All @@ -152,19 +161,19 @@ int Pooling::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) c
const float* inptr = bottom_blob.channel(q);
float* outptr = top_blob.channel(q);

for (int i = 0; i < out_h; i++)
for (int i = 0; i < _out_h; i++)
{
// floor div
const int ih0 = h * i / out_h;
const int ih0 = h * i / _out_h;
// ceil div
const int ih1 = (h * (i + 1) + out_h - 1) / out_h;
const int ih1 = (h * (i + 1) + _out_h - 1) / _out_h;
const int hk = ih1 - ih0;
for (int j = 0; j < out_w; j++)
for (int j = 0; j < _out_w; j++)
{
// floor div
const int iw0 = w * j / out_w;
const int iw0 = w * j / _out_w;
// ceil div
const int iw1 = (w * (j + 1) + out_w - 1) / out_w;
const int iw1 = (w * (j + 1) + _out_w - 1) / _out_w;
const int wk = iw1 - iw0;

float sum = 0;
Expand All @@ -179,7 +188,7 @@ int Pooling::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt) c
outptr[j] = sum / hk / wk;
}

outptr += out_w;
outptr += _out_w;
}
}
}
Expand Down
52 changes: 31 additions & 21 deletions src/layer/pooling3d.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -108,7 +108,17 @@ int Pooling3D::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt)

if (adaptive_pooling)
{
top_blob.create(out_w, out_h, out_d, channels, elemsize, opt.blob_allocator);
int _out_w = out_w == -233 ? w : out_w;
int _out_h = out_h == -233 ? h : out_h;
int _out_d = out_d == -233 ? d : out_d;

if (_out_w == w && _out_h == h && _out_d == d)
{
top_blob = bottom_blob;
return 0;
}

top_blob.create(_out_w, _out_h, _out_d, channels, elemsize, opt.blob_allocator);
if (top_blob.empty())
return -100;

Expand All @@ -120,24 +130,24 @@ int Pooling3D::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt)
const float* inptr = bottom_blob.channel(q);
float* outptr = top_blob.channel(q);

for (int z = 0; z < out_d; z++)
for (int z = 0; z < _out_d; z++)
{
// floor div
const int id0 = d * z / out_d;
const int id0 = d * z / _out_d;
// ceil div
const int id1 = (d * (z + 1) + out_d - 1) / out_d;
for (int i = 0; i < out_h; i++)
const int id1 = (d * (z + 1) + _out_d - 1) / _out_d;
for (int i = 0; i < _out_h; i++)
{
// floor div
const int ih0 = h * i / out_h;
const int ih0 = h * i / _out_h;
// ceil div
const int ih1 = (h * (i + 1) + out_h - 1) / out_h;
for (int j = 0; j < out_w; j++)
const int ih1 = (h * (i + 1) + _out_h - 1) / _out_h;
for (int j = 0; j < _out_w; j++)
{
// floor div
const int iw0 = w * j / out_w;
const int iw0 = w * j / _out_w;
// ceil div
const int iw1 = (w * (j + 1) + out_w - 1) / out_w;
const int iw1 = (w * (j + 1) + _out_w - 1) / _out_w;

float max_value = inptr[id0 * w * h + ih0 * w + iw0];

Expand All @@ -155,7 +165,7 @@ int Pooling3D::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt)
outptr[j] = max_value;
}

outptr += out_w;
outptr += _out_w;
}
}
}
Expand All @@ -168,26 +178,26 @@ int Pooling3D::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt)
const float* inptr = bottom_blob.channel(q);
float* outptr = top_blob.channel(q);

for (int z = 0; z < out_d; z++)
for (int z = 0; z < _out_d; z++)
{
// floor div
const int id0 = d * z / out_d;
const int id0 = d * z / _out_d;
// ceil div
const int id1 = (d * (z + 1) + out_d - 1) / out_d;
const int id1 = (d * (z + 1) + _out_d - 1) / _out_d;
int dk = id1 - id0;
for (int i = 0; i < out_h; i++)
for (int i = 0; i < _out_h; i++)
{
// floor div
const int ih0 = h * i / out_h;
const int ih0 = h * i / _out_h;
// ceil div
const int ih1 = (h * (i + 1) + out_h - 1) / out_h;
const int ih1 = (h * (i + 1) + _out_h - 1) / _out_h;
int hk = ih1 - ih0;
for (int j = 0; j < out_w; j++)
for (int j = 0; j < _out_w; j++)
{
// floor div
const int iw0 = w * j / out_w;
const int iw0 = w * j / _out_w;
// ceil div
const int iw1 = (w * (j + 1) + out_w - 1) / out_w;
const int iw1 = (w * (j + 1) + _out_w - 1) / _out_w;
int wk = iw1 - iw0;

float sum = 0;
Expand All @@ -205,7 +215,7 @@ int Pooling3D::forward(const Mat& bottom_blob, Mat& top_blob, const Option& opt)
outptr[j] = sum / hk / wk / dk;
}

outptr += out_w;
outptr += _out_w;
}
}
}
Expand Down
22 changes: 20 additions & 2 deletions src/layer/vulkan/pooling_vulkan.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -403,7 +403,16 @@ int Pooling_vulkan::forward(const VkMat& bottom_blob, VkMat& top_blob, VkCompute

if (adaptive_pooling)
{
top_blob.create(out_w, out_h, channels, elemsize, elempack, opt.blob_vkallocator);
int _out_w = out_w == -233 ? w : out_w;
int _out_h = out_h == -233 ? h : out_h;

if (_out_w == w && _out_h == h)
{
top_blob = bottom_blob;
return 0;
}

top_blob.create(_out_w, _out_h, channels, elemsize, elempack, opt.blob_vkallocator);
if (top_blob.empty())
return -100;

Expand Down Expand Up @@ -610,7 +619,16 @@ int Pooling_vulkan::forward(const VkImageMat& bottom_blob, VkImageMat& top_blob,

if (adaptive_pooling)
{
top_blob.create(out_w, out_h, channels, elemsize, elempack, opt.blob_vkallocator);
int _out_w = out_w == -233 ? w : out_w;
int _out_h = out_h == -233 ? h : out_h;

if (_out_w == w && _out_h == h)
{
top_blob = bottom_blob;
return 0;
}

top_blob.create(_out_w, _out_h, channels, elemsize, elempack, opt.blob_vkallocator);
if (top_blob.empty())
return -100;

Expand Down
1 change: 1 addition & 0 deletions tools/pnnx/src/CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -302,6 +302,7 @@ set(pnnx_pass_level3_SRCS
pass_level3/expand_quantization_modules.cpp
pass_level3/fuse_opnto1_tensors.cpp
pass_level3/fuse_op1ton_unpack.cpp
pass_level3/fuse_dynamic_adaptive_pool.cpp
pass_level3/fuse_einsum_operands.cpp
pass_level3/fuse_expression.cpp
pass_level3/fuse_index_expression.cpp
Expand Down
54 changes: 52 additions & 2 deletions tools/pnnx/src/ir.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -291,6 +291,13 @@ Parameter::Parameter(const torch::jit::Node* value_node)
type = 5;
for (const auto& x : value_node->inputs())
{
if (!x->node()->hasAttribute(torch::jit::attr::value))
{
fprintf(stderr, "no attribute value in int list\n");
ai.push_back(0);
continue;
}

ai.push_back((int)x->node()->i(torch::jit::attr::value));
}
break;
Expand All @@ -300,6 +307,13 @@ Parameter::Parameter(const torch::jit::Node* value_node)
type = 6;
for (const auto& x : value_node->inputs())
{
if (!x->node()->hasAttribute(torch::jit::attr::value))
{
fprintf(stderr, "no attribute value in float list\n");
af.push_back(0.f);
continue;
}

af.push_back((float)x->node()->f(torch::jit::attr::value));
}
break;
Expand All @@ -309,6 +323,13 @@ Parameter::Parameter(const torch::jit::Node* value_node)
type = 7;
for (const auto& x : value_node->inputs())
{
if (!x->node()->hasAttribute(torch::jit::attr::value))
{
fprintf(stderr, "no attribute value in string list\n");
as.push_back("");
continue;
}

as.push_back(x->node()->s(torch::jit::attr::value));
}
break;
Expand All @@ -319,6 +340,13 @@ Parameter::Parameter(const torch::jit::Node* value_node)
type = 11;
for (const auto& x : value_node->inputs())
{
if (!x->node()->hasAttribute(torch::jit::attr::value))
{
fprintf(stderr, "no attribute value in complex list\n");
ac.push_back(std::complex<float>(0.f, 0.f));
continue;
}

ac.push_back(std::complex<float>(x->node()->c(torch::jit::attr::value)));
}
break;
Expand Down Expand Up @@ -1629,7 +1657,18 @@ int Graph::python(const std::string& pypath, const std::string& pnnxbinpath)
fprintf(pyfp, "(");
for (size_t i = 0; i < param.ai.size(); i++)
{
fprintf(pyfp, "%d", param.ai[i]);
if ((op->type == "nn.AdaptiveAvgPool2d"
|| op->type == "nn.AdaptiveAvgPool3d"
|| op->type == "nn.AdaptiveMaxPool2d"
|| op->type == "nn.AdaptiveMaxPool3d")
&& it.first == "output_size" && param.ai[i] == 0)
{
fprintf(pyfp, "None");
}
else
{
fprintf(pyfp, "%d", param.ai[i]);
}
if (i + 1 != param.ai.size() || param.ai.size() == 1)
fprintf(pyfp, ",");
}
Expand Down Expand Up @@ -2299,7 +2338,18 @@ int Graph::python(const std::string& pypath, const std::string& pnnxbinpath)
fprintf(pyfp, "(");
for (size_t i = 0; i < param.ai.size(); i++)
{
fprintf(pyfp, "%d", param.ai[i]);
if ((op->type == "F.adaptive_avg_pool2d"
|| op->type == "F.adaptive_avg_pool3d"
|| op->type == "F.adaptive_max_pool2d"
|| op->type == "F.adaptive_max_pool3d")
&& it.first == "output_size" && param.ai[i] == 0)
{
fprintf(pyfp, "None");
}
else
{
fprintf(pyfp, "%d", param.ai[i]);
}
if (i + 1 != param.ai.size() || param.ai.size() == 1)
fprintf(pyfp, ",");
}
Expand Down
6 changes: 3 additions & 3 deletions tools/pnnx/src/pass_level2.cpp
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -50,9 +50,9 @@ bool GraphRewriterPass::match(const std::map<std::string, Parameter>& captured_p
return match(captured_params);
}

bool GraphRewriterPass::match(const std::map<std::string, const Operator*>& /*matched_operators*/) const
bool GraphRewriterPass::match(const std::map<std::string, const Operator*>& /*matched_operators*/, const std::map<std::string, Parameter>& captured_params, const std::map<std::string, Attribute>& captured_attrs) const
{
return true;
return match(captured_params, captured_attrs);
}

void GraphRewriterPass::write(Operator* op, const std::map<std::string, Parameter>& captured_params) const
Expand Down Expand Up @@ -893,7 +893,7 @@ void pnnx_graph_rewrite(Graph& graph, const GraphRewriterPass* pass, int& opinde
break;
}

if (matched && (!pass->match(captured_params, captured_attrs) || !pass->match(matched_operators)))
if (matched && !pass->match(matched_operators, captured_params, captured_attrs))
{
matched_operators.clear();
matched_inputs.clear();
Expand Down
2 changes: 1 addition & 1 deletion tools/pnnx/src/pass_level2.h
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,7 @@ class GraphRewriterPass

virtual bool match(const std::map<std::string, Parameter>& captured_params, const std::map<std::string, Attribute>& captured_attrs) const;

virtual bool match(const std::map<std::string, const Operator*>& matched_operators) const;
virtual bool match(const std::map<std::string, const Operator*>& matched_operators, const std::map<std::string, Parameter>& captured_params, const std::map<std::string, Attribute>& captured_attrs) const;

virtual void write(Operator* op, const std::map<std::string, Parameter>& captured_params) const;

Expand Down
3 changes: 3 additions & 0 deletions tools/pnnx/src/pass_level3.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@
#include "pass_level3/expand_quantization_modules.h"
#include "pass_level3/fuse_opnto1_tensors.h"
#include "pass_level3/fuse_op1ton_unpack.h"
#include "pass_level3/fuse_dynamic_adaptive_pool.h"
#include "pass_level3/fuse_einsum_operands.h"
#include "pass_level3/fuse_expression.h"
#include "pass_level3/fuse_index_expression.h"
Expand Down Expand Up @@ -52,6 +53,8 @@ void pass_level3(Graph& g, const std::set<std::string>& foldable_constants, cons

fuse_rnn_unpack(g);

fuse_dynamic_adaptive_pool(g);

expand_quantization_modules(g);

eliminate_tuple_pair(g);
Expand Down
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