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Unverified Commit 98ade977 authored by kahmed10's avatar kahmed10 Committed by GitHub
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Nd deconv cpu (#565) 



* initial progress

* formatting

* check existing tests

* formatting

* change for loop to transform

* formatting

* add tests

* formatting

* remove comment

* add more tests

* update gpu miopen calls

* formatting

* initial progress

* add cpu impl and tests

* formatting

* add NOLINT

* add 3d test

* formatting

* add more op_shape tests

* fix error msg

* fix bounds

* formatting

* fix algorithm

* formatting

* pin numpy version
Co-authored-by: default avatarmvermeulen <5479696+mvermeulen@users.noreply.github.com>
parent dced4d4b
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Showing with 185 additions and 32 deletions
Dockerfile
View file @ 98ade977
...@@ -59,7 +59,7 @@ ENV LC_ALL=C.UTF-8 ...@@ -59,7 +59,7 @@ ENV LC_ALL=C.UTF-8
ENV LANG=C.UTF-8 ENV LANG=C.UTF-8
# Install cget # Install cget
RUN pip3 install cget && pip3 install numpy RUN pip3 install cget && pip3 install numpy==1.18.5
# Install rclone # Install rclone
RUN pip install https://github.com/pfultz2/rclone/archive/master.tar.gz RUN pip install https://github.com/pfultz2/rclone/archive/master.tar.gz
......
src/targets/cpu/lowering.cpp
View file @ 98ade977
...@@ -26,6 +26,7 @@ ...@@ -26,6 +26,7 @@
#include <migraphx/cpu/gemm.hpp> #include <migraphx/cpu/gemm.hpp>
#include <unordered_map> #include <unordered_map>
#include <utility> #include <utility>
#include <iostream>
namespace migraphx { namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS { inline namespace MIGRAPHX_INLINE_NS {
...@@ -275,41 +276,69 @@ struct cpu_deconvolution ...@@ -275,41 +276,69 @@ struct cpu_deconvolution
std::fill(output.begin(), output.end(), type{0}); std::fill(output.begin(), output.end(), type{0});
auto out_lens = output_shape.lens(); auto in_lens = input.get_shape().lens();
auto out_h = out_lens[2]; auto in_n = in_lens[0];
auto out_w = out_lens[3]; auto in_c = in_lens[1];
auto in = input.get_shape().lens();
auto in_n = in[0];
auto in_c = in[1];
auto in_h = in[2];
auto in_w = in[3];
auto wei = weights.get_shape().lens(); auto wei = weights.get_shape().lens();
auto wei_n = wei[0]; auto wei_n = wei[0];
auto wei_c = wei[1]; auto wei_c = wei[1];
auto wei_h = wei[2];
auto wei_w = wei[3];
par_dfor(in_n, wei_c)([&](std::size_t o, std::size_t k) { auto out_lens = output_shape.lens();
auto kdims = op.kdims();
dfor(in_c, in_h, in_w, wei_h, wei_w)( std::vector<std::size_t> win_size{in_c};
[&](std::size_t w, std::size_t i, std::size_t j, std::size_t x, std::size_t y) { std::copy(in_lens.begin() + 2, in_lens.end(), std::back_inserter(win_size));
const int start_x = i * op.stride[0] - op.padding[0]; std::copy(wei.begin() + 2, wei.end(), std::back_inserter(win_size));
const int start_y = j * op.stride[1] - op.padding[1]; shape win_shape{output_shape.type(), win_size};
const int out_x = start_x + x * op.dilation[0];
const int out_y = start_y + y * op.dilation[1];
const auto group_id = w / (wei_n / op.group); par_dfor(in_n, wei_c)([&](int o, int k) {
const auto in_ch = group_id * wei_c + k;
shape_for_each(win_shape, [&](auto idx_win) {
const int w = idx_win[0];
auto input_dims_start = idx_win.begin() + 1;
auto wei_dims_start = idx_win.begin() + kdims + 1;
std::vector<std::ptrdiff_t> win_start;
for(std::size_t n = 0; n < kdims; ++n)
{
win_start.push_back(std::ptrdiff_t(*(input_dims_start + n) * op.stride[n]) -
std::ptrdiff_t(op.padding[n]));
}
const int group_id = w / (wei_n / op.group);
const int in_ch = group_id * wei_c + k;
std::vector<std::ptrdiff_t> idx_out{o, in_ch};
for(size_t n = 0; n < kdims; n++)
{
idx_out.push_back(win_start[n] + *(wei_dims_start + n) * op.dilation[n]);
}
std::vector<std::ptrdiff_t> idx_wei{w, k};
std::copy(wei_dims_start, idx_win.end(), std::back_inserter(idx_wei));
std::vector<std::ptrdiff_t> idx_in{o, w};
std::copy(input_dims_start, wei_dims_start, std::back_inserter(idx_in));
if(out_x >= 0 && out_x < out_h && out_y >= 0 && out_y < out_w) if(std::all_of(
idx_out.begin() + 2, idx_out.end(), [&](auto ii) { return ii >= 0; }) and
std::equal(idx_out.begin() + 2,
idx_out.end(),
out_lens.begin() + 2,
out_lens.end(),
std::less<std::ptrdiff_t>{}))
{ {
output(o, in_ch, out_x, out_y) += output(idx_out.begin(), idx_out.end()) +=
input(o, w, i, j) * weights(w, k, x, y); input(idx_in.begin(), idx_in.end()) *
weights(idx_wei.begin(), idx_wei.end());
} }
}); });
}); });
}); });
return result; return result;
} }
...@@ -493,7 +522,7 @@ struct cpu_pad ...@@ -493,7 +522,7 @@ struct cpu_pad
return migraphx::reflect(self.op, f); return migraphx::reflect(self.op, f);
} }
std::string name() const { return "cpu::contiguous"; } std::string name() const { return "cpu::pad"; }
shape compute_shape(const std::vector<shape>& inputs) const { return op.compute_shape(inputs); } shape compute_shape(const std::vector<shape>& inputs) const { return op.compute_shape(inputs); }
argument compute(context&, const shape& output_shape, std::vector<argument> args) const argument compute(context&, const shape& output_shape, std::vector<argument> args) const
{ {
......
test/cpu_ops_test.cpp
View file @ 98ade977
...@@ -2193,6 +2193,71 @@ TEST_CASE(deconv_test) ...@@ -2193,6 +2193,71 @@ TEST_CASE(deconv_test)
EXPECT(migraphx::verify_range(results_vector, gold)); EXPECT(migraphx::verify_range(results_vector, gold));
} }
TEST_CASE(deconv_1d_test)
{
migraphx::shape s{migraphx::shape::float_type, {1, 1, 3}};
std::vector<float> x_data{0, 0.5, 1};
std::vector<float> w_data{0.5, 0.5, 0.5};
std::vector<float> gold{0, 0.25, 0.75, 0.75, 0.5};
migraphx::program p;
auto x = p.add_literal(migraphx::literal{s, x_data});
auto w = p.add_literal(migraphx::literal{s, w_data});
p.add_instruction(migraphx::op::deconvolution{{0}, {1}, {1}}, x, w);
p.compile(migraphx::cpu::target{});
auto result = p.eval({}).back();
std::vector<float> results_vector;
result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
EXPECT(migraphx::verify_range(results_vector, gold));
}
TEST_CASE(deconv_3d_test)
{
migraphx::shape s_1{migraphx::shape::float_type, {1, 1, 1, 2, 3}};
migraphx::shape s_2{migraphx::shape::float_type, {1, 1, 3, 2, 3}};
std::vector<float> x_data{0.8471, -0.4195, -2.2749, 1.2491, 0.1722, 0.3246};
std::vector<float> w_data{0.6478,
-0.1985,
0.0633,
-0.3479,
2.7056,
-0.1440,
-1.1229,
-0.7507,
-1.3151,
0.8884,
-0.1859,
-0.3407,
-1.1544,
-1.5893,
1.6265,
-1.4624,
0.3812,
-1.5378};
std::vector<float> gold{0.5488, -0.4399, -1.3369, 0.4251, -0.1439, 0.5145, 2.3015, -0.2104,
-6.1482, 0.3482, -0.4346, 3.3197, 0.1731, 0.8533, -0.0467, -0.9512,
-0.1649, 1.7553, 2.2594, 2.9917, -0.6500, -1.6612, -4.3680, 0.0957,
0.3482, 1.1097, -0.0792, -0.1692, -0.1190, -0.1106, -0.9779, -0.8621,
4.6707, 2.9332, -3.7001, -2.6808, -1.2476, 3.2475, -0.4578, 4.0263,
-1.8267, 0.2243, -2.3299, -0.1411, -0.4991};
migraphx::program p;
auto x = p.add_literal(migraphx::literal{s_1, x_data});
auto w = p.add_literal(migraphx::literal{s_2, w_data});
p.add_instruction(migraphx::op::deconvolution{{0, 0, 0}, {1, 1, 1}, {1, 1, 1}}, x, w);
p.compile(migraphx::cpu::target{});
auto result = p.eval({}).back();
std::vector<float> results_vector;
result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
EXPECT(migraphx::verify_range(results_vector, gold));
}
TEST_CASE(transpose_test) TEST_CASE(transpose_test)
{ {
migraphx::shape a_shape{migraphx::shape::float_type, {1, 2, 2, 3}}; migraphx::shape a_shape{migraphx::shape::float_type, {1, 2, 2, 3}};
......
test/gpu/ops_test.cpp
View file @ 98ade977
...@@ -755,6 +755,62 @@ struct test_group_conv : verify_program<test_group_conv> ...@@ -755,6 +755,62 @@ struct test_group_conv : verify_program<test_group_conv>
} }
}; };
struct test_deconv : verify_program<test_deconv>
{
migraphx::program create_program() const
{
migraphx::program p;
auto input =
p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 1, 3, 3}});
auto weights =
p.add_parameter("w", migraphx::shape{migraphx::shape::float_type, {1, 1, 3, 3}});
p.add_instruction(migraphx::op::deconvolution{}, input, weights);
return p;
}
};
struct test_deconv_2x3 : verify_program<test_deconv_2x3>
{
migraphx::program create_program() const
{
migraphx::program p;
auto input =
p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 3, 6, 7}});
auto weights =
p.add_parameter("w", migraphx::shape{migraphx::shape::float_type, {3, 4, 3, 3}});
p.add_instruction(migraphx::op::deconvolution{{1, 1}, {2, 3}, {1, 1}}, input, weights);
return p;
}
};
struct test_deconv_1d : verify_program<test_deconv_1d>
{
migraphx::program create_program() const
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 1, 3}});
auto weights =
p.add_parameter("w", migraphx::shape{migraphx::shape::float_type, {1, 1, 3}});
p.add_instruction(migraphx::op::deconvolution{{0}, {1}, {1}}, input, weights);
return p;
}
};
struct test_deconv_3d : verify_program<test_deconv_3d>
{
migraphx::program create_program() const
{
migraphx::program p;
auto input =
p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {1, 1, 3, 3, 3}});
auto weights =
p.add_parameter("w", migraphx::shape{migraphx::shape::float_type, {1, 1, 3, 3, 3}});
p.add_instruction(
migraphx::op::deconvolution{{0, 0, 0}, {1, 1, 1}, {1, 1, 1}}, input, weights);
return p;
}
};
struct test_conv_relu : verify_program<test_conv_relu> struct test_conv_relu : verify_program<test_conv_relu>
{ {
migraphx::program create_program() const migraphx::program create_program() const
......
test/op_shape_test.cpp
View file @ 98ade977
...@@ -69,6 +69,7 @@ TEST_CASE(convolution_shape) ...@@ -69,6 +69,7 @@ TEST_CASE(convolution_shape)
migraphx::shape weights{migraphx::shape::float_type, {4, 3, 3, 3}}; migraphx::shape weights{migraphx::shape::float_type, {4, 3, 3, 3}};
expect_shape(output, migraphx::op::convolution{}, input, weights); expect_shape(output, migraphx::op::convolution{}, input, weights);
throws_shape(migraphx::op::convolution{}, input); throws_shape(migraphx::op::convolution{}, input);
throws_shape(migraphx::op::convolution{{0}, {1}, {1}}, input);
migraphx::shape input2{migraphx::shape::float_type, {3, 3}}; migraphx::shape input2{migraphx::shape::float_type, {3, 3}};
migraphx::shape weights2{migraphx::shape::float_type, {3, 3}}; migraphx::shape weights2{migraphx::shape::float_type, {3, 3}};
...@@ -98,6 +99,7 @@ TEST_CASE(deconvolution_shape) ...@@ -98,6 +99,7 @@ TEST_CASE(deconvolution_shape)
migraphx::shape weights{migraphx::shape::float_type, {4, 3, 3, 3}}; migraphx::shape weights{migraphx::shape::float_type, {4, 3, 3, 3}};
expect_shape(output, migraphx::op::deconvolution{}, input, weights); expect_shape(output, migraphx::op::deconvolution{}, input, weights);
throws_shape(migraphx::op::deconvolution{}, input); throws_shape(migraphx::op::deconvolution{}, input);
throws_shape(migraphx::op::deconvolution{{0}, {1}, {1}}, input);
migraphx::shape input_1d{migraphx::shape::float_type, {4, 4, 1}}; migraphx::shape input_1d{migraphx::shape::float_type, {4, 4, 1}};
migraphx::shape output_1d{migraphx::shape::float_type, {4, 3, 3}}; migraphx::shape output_1d{migraphx::shape::float_type, {4, 3, 3}};
...@@ -121,6 +123,7 @@ TEST_CASE(quant_convolution_shape) ...@@ -121,6 +123,7 @@ TEST_CASE(quant_convolution_shape)
expect_shape(output, migraphx::op::quant_convolution{}, input, weights); expect_shape(output, migraphx::op::quant_convolution{}, input, weights);
throws_shape(migraphx::op::quant_convolution{}, input); throws_shape(migraphx::op::quant_convolution{}, input);
throws_shape(migraphx::op::quant_convolution{{0}, {1, 1}, {1, 1}}, input, weights); throws_shape(migraphx::op::quant_convolution{{0}, {1, 1}, {1, 1}}, input, weights);
throws_shape(migraphx::op::quant_convolution{{0}, {1}, {1}}, input, weights);
migraphx::shape input2{migraphx::shape::int32_type, {3, 3}}; migraphx::shape input2{migraphx::shape::int32_type, {3, 3}};
migraphx::shape weights2{migraphx::shape::float_type, {3, 3}}; migraphx::shape weights2{migraphx::shape::float_type, {3, 3}};
......
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