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Common forward convolution utility refactor. (#141)

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* Convolution ND

* Code unification across dimensions for generating tensor descriptors.
* Example
* Instances

* Move convnd f32 instance file to comply with repo structure.

* Conv 1D tensor layouts.

* Formatting and use ReferenceConv

* Reference ConvFwd supporting 1D and 2D convolution.

* Debug printing TensorLayout name.

* Conv fwd 1D instance f32

* Refactor conv ND example.

Needed to support various conv dimensio.

Needed to support various conv dimensions

* Rename conv nd example director to prevent conflicts.

* Refactor some common utility to single file.

Plus some tests.

* Refactor GetHostTensorDescriptor + UT.

* Add 1D test case.

* Test reference convolution 1d/2d

* Remove some leftovers.

* Fix convolution example error for 1D

* Refactor test check errors utility function.

* Test Conv2D Fwd XDL

* More UT for 1D case.

* Parameterize input & weight initializers.

* Rename example to prevent conflicts.

* Split convnd instance into separate files for 1d/2d

* Address review comments.

* Fix data type for flops/gbytes calculations.

* Assign example number 11.

* 3D cases for convolution utility functions.

* 3D reference convolution.

* Add support for 3D convolution.

* Check for inputs bigger than  2GB.

* Formatting

* Support for bf16/f16/f32/i8 - conv instances + UT.

* Use check_err from test_util.hpp.

* Split convnd test into separate files for each dim.

* Fix data generation and use proper instances.

* Formatting

* Skip tensor initialization if not necessary.

* Fix CMakefiles.

* Remove redundant conv2d_fwd test.

* Lower problem size for conv3D UT.

* 3D case for convnd example.

* Remove leftovers after merge.

* Add Conv Specialization string to GetTypeString

* Skip instance causing numerical errors.

* Small fixes.

* Remove redundant includes.

* Fix namespace name error.

* Script for automatic testing and logging convolution fwd UTs

* Comment out numactl cmd.

* Refine weights initalization and relax rtol for fp16

* Move test_util.hpp to check_err.hpp

* Refine weights initalization and relax rtol for fp16

* Refactor common part of test conv utils.

* Move utility function to single common place.

* Add additional common functions to utility.

* Refactor convnd_fwd_xdl examples.

* Remove redundant files.
* Unify structure.

* Add constructor to ConvParams.

* And add input parameters validation.

* Modify conv examples to use single utility file.

* Remove check_error from host_tensor.hpp

* Get rid of check_indices function.

* Remove bf16_to_f32 function overload for scalars.

* Fix namespace.

* Add half_float::half for check_err.

* Fix conv params size in UT.

* Fix weights initialization for int8.

* Fix weights initialization for int8.

* Add type_convert when store output in ref conv 1D.

* Get back old conv2d_fwd_xdl operation.

* Silence conv debug print.

* format

* clean

* clean

* Fix merge.

* Fix namespace for check_err

* Formatting.

* Fix merge artifacts.

* Remove deleted header.

* Fix some includes and use ck::utils::check_err.

* Remove unused check_indices restored by previous merge.

* Fix namespaces after merge.

* Fix compilation error.

* Small fixes.

* Use common functions.
* Fix filename
* Fix namespaces.

* Fix merge artifact - retrieve removed by accident fun.

* Fix ConvForwardSpecialization.

* Adhere to coding style rules.

* Fix merge artifacts.

Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
This commit is contained in:
Adam Osewski
2022-04-05 22:16:59 +02:00
committed by GitHub
parent 6717168c18
commit abf4bdb9a9
75 changed files with 2278 additions and 2518 deletions
Download Patch File Download Diff File Expand all files Collapse all files

27
profiler/include/profile_convnd_bwd_data_impl.hpp
View File

@@ -1,7 +1,7 @@
#pragma once
#include "config.hpp"
#include "device.hpp"
#include "conv_utils.hpp"
#include "conv_fwd_util.hpp"
#include "host_tensor.hpp"
#include "host_tensor_generator.hpp"
#include "tensor_layout.hpp"
@@ -68,13 +68,13 @@ HostTensorDescriptor get_input_host_tensor_descriptor(const std::vector<std::siz
switch(num_dim_spatial)
{
case 3: {
return ck::conv_util::GetHostTensorDescriptor(dims, InLayout{});
return ck::utils::conv::get_host_tensor_descriptor(dims, InLayout{});
}
case 2: {
return ck::conv_util::GetHostTensorDescriptor(dims, InLayout{});
return ck::utils::conv::get_host_tensor_descriptor(dims, InLayout{});
}
case 1: {
return ck::conv_util::GetHostTensorDescriptor(dims, InLayout{});
return ck::utils::conv::get_host_tensor_descriptor(dims, InLayout{});
}
default: {
throw std::runtime_error("Unsupported number of spatial dimensions provided!");
@@ -90,13 +90,13 @@ HostTensorDescriptor get_filters_host_tensor_descriptor(const std::vector<std::s
switch(num_dim_spatial)
{
case 3: {
return ck::conv_util::GetHostTensorDescriptor(dims, WeiLayout{});
return ck::utils::conv::get_host_tensor_descriptor(dims, WeiLayout{});
}
case 2: {
return ck::conv_util::GetHostTensorDescriptor(dims, WeiLayout{});
return ck::utils::conv::get_host_tensor_descriptor(dims, WeiLayout{});
}
case 1: {
return ck::conv_util::GetHostTensorDescriptor(dims, WeiLayout{});
return ck::utils::conv::get_host_tensor_descriptor(dims, WeiLayout{});
}
default: {
throw std::runtime_error("Unsupported number of spatial dimensions provided!");
@@ -112,13 +112,13 @@ HostTensorDescriptor get_output_host_ensor_descriptor(const std::vector<std::siz
switch(num_dim_spatial)
{
case 3: {
return ck::conv_util::GetHostTensorDescriptor(dims, OutLayout{});
return ck::utils::conv::get_host_tensor_descriptor(dims, OutLayout{});
}
case 2: {
return ck::conv_util::GetHostTensorDescriptor(dims, OutLayout{});
return ck::utils::conv::get_host_tensor_descriptor(dims, OutLayout{});
}
case 1: {
return ck::conv_util::GetHostTensorDescriptor(dims, OutLayout{});
return ck::utils::conv::get_host_tensor_descriptor(dims, OutLayout{});
}
default: {
throw std::runtime_error("Unsupported number of spatial dimensions provided!");
@@ -413,9 +413,10 @@ bool profile_convnd_bwd_data_impl(int do_verification,
float ave_time = invoker_ptr->Run(argument_ptr.get(), nrepeat);
std::size_t flop =
ck::conv_util::GetFlops(N, C, K, filter_spatial_lengths, output_spatial_lengths);
std::size_t num_btype = ck::conv_util::GetBtype<InDataType, WeiDataType, OutDataType>(
N, C, K, input_spatial_lengths, filter_spatial_lengths, output_spatial_lengths);
ck::utils::conv::get_flops(N, C, K, filter_spatial_lengths, output_spatial_lengths);
std::size_t num_btype =
ck::utils::conv::get_btype<InDataType, WeiDataType, OutDataType>(
N, C, K, input_spatial_lengths, filter_spatial_lengths, output_spatial_lengths);
float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
float gb_per_sec = num_btype / 1.E6 / ave_time;