Common forward convolution utility refactor. (#141)

* 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 t...

Common forward convolution utility refactor. (#141)
* 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 t...
abf4bdb9 · Adam Osewski · GitHub · 6717168c · abf4bdb9 · abf4bdb9
Unverified Commit abf4bdb9 authored Apr 05, 2022 by Adam Osewski Committed by GitHub Apr 05, 2022
14 changed files
--- a/test/convnd_fwd/conv1d_fwd.cpp
+++ b/test/convnd_fwd/conv1d_fwd.cpp
@@ -5,10 +5,11 @@

 #include "data_type.hpp"
 #include "element_wise_operation.hpp"
-#include "conv_test_util.hpp"
+#include "conv_fwd_util.hpp"
+#include "conv_util.hpp"
 #include "host_tensor.hpp"
 #include "tensor_layout.hpp"
-#include "test_util.hpp"
+#include "check_err.hpp"

 // Forward declarations for conv instances.

@@ -34,10 +35,10 @@ void add_device_conv1d_fwd_xdl_nwc_kxc_nwk_int8_instances(std::vector<DeviceConv

 namespace {

-bool TestConv1DNWC()
+bool test_conv1D_nwc()
 {
    bool res{true};
-    ck::conv_util::ConvParams params;
+    ck::utils::conv::ConvParams params;
    params.num_dim_spatial        = 1;
    params.N                      = 2;
    params.K                      = 16;
@@ -49,30 +50,31 @@ bool TestConv1DNWC()
    params.input_left_pads        = std::vector<ck::index_t>{1};
    params.input_right_pads       = std::vector<ck::index_t>{1};

-    auto host_tensors            = test::conv::GetHostTensors<float,
-                                                   float,
-                                                   float,
-                                                   ck::tensor_layout::convolution::NWC,
-                                                   ck::tensor_layout::convolution::KXC,
-                                                   ck::tensor_layout::convolution::NWK>(params);
+    auto host_tensors =
+        ck::utils::conv::get_host_tensors<float,
+                                          float,
+                                          float,
+                                          ck::tensor_layout::convolution::NWC,
+                                          ck::tensor_layout::convolution::KXC,
+                                          ck::tensor_layout::convolution::NWK>(params);
    const Tensor<float>& input   = std::get<0>(host_tensors);
    const Tensor<float>& weights = std::get<1>(host_tensors);
    Tensor<float>& host_output   = std::get<2>(host_tensors);
    Tensor<float>& device_output = std::get<3>(host_tensors);

-    test::conv::RunReferenceConv<1>(params, input, weights, host_output);
+    ck::utils::conv::run_reference_convolution_forward<1>(params, input, weights, host_output);
    test::conv::RunConv<1>(params, input, weights, device_output);
    res = res &&
-          test::check_err(
+          ck::utils::check_err(
              device_output.mData, host_output.mData, "Error: incorrect results!", 1e-5f, 1e-4f);

    return res;
 }

 template <typename T>
-bool TestConv1DNWCInstances(const std::vector<DeviceConvFwdNoOpPtr>& conv_ptrs)
+bool test_conv1d_nwc_instances(const std::vector<DeviceConvFwdNoOpPtr>& conv_ptrs)
 {
-    ck::conv_util::ConvParams params;
+    ck::utils::conv::ConvParams params;
    params.num_dim_spatial        = 1;
    params.filter_spatial_lengths = std::vector<ck::index_t>{3};
    params.input_spatial_lengths  = std::vector<ck::index_t>{71};
@@ -81,51 +83,52 @@ bool TestConv1DNWCInstances(const std::vector<DeviceConvFwdNoOpPtr>& conv_ptrs)
    params.input_left_pads        = std::vector<ck::index_t>{1};
    params.input_right_pads       = std::vector<ck::index_t>{1};

-    auto host_tensors        = test::conv::GetHostTensors<T,
-                                                   T,
-                                                   T,
-                                                   ck::tensor_layout::convolution::NWC,
-                                                   ck::tensor_layout::convolution::KXC,
-                                                   ck::tensor_layout::convolution::NWK>(params);
+    auto host_tensors =
+        ck::utils::conv::get_host_tensors<T,
+                                          T,
+                                          T,
+                                          ck::tensor_layout::convolution::NWC,
+                                          ck::tensor_layout::convolution::KXC,
+                                          ck::tensor_layout::convolution::NWK>(params);
    const Tensor<T>& input   = std::get<0>(host_tensors);
    const Tensor<T>& weights = std::get<1>(host_tensors);
    Tensor<T>& host_output   = std::get<2>(host_tensors);
    Tensor<T>& device_output = std::get<3>(host_tensors);

-    test::conv::RunReferenceConv<1>(params, input, weights, host_output);
-    return test::conv::RunConvInstances<1>(
+    ck::utils::conv::run_reference_convolution_forward<1>(params, input, weights, host_output);
+    return ck::utils::conv::run_convolution_forward_instances<1>(
        params, conv_ptrs, input, weights, device_output, host_output);
 }
-bool TestConv1DNWCBF16Instances()
+bool test_conv1d_nwc_bf16_instances()
 {
    std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
    ck::tensor_operation::device::device_conv1d_fwd_instance::
        add_device_conv1d_fwd_xdl_nwc_kxc_nwk_bf16_instances(conv_ptrs);
-    return TestConv1DNWCInstances<ck::bhalf_t>(conv_ptrs);
+    return test_conv1d_nwc_instances<ck::bhalf_t>(conv_ptrs);
 }

-bool TestConv1DNWCF16Instances()
+bool test_conv1d_nwc_f16_instances()
 {
    std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
    ck::tensor_operation::device::device_conv1d_fwd_instance::
        add_device_conv1d_fwd_xdl_nwc_kxc_nwk_f16_instances(conv_ptrs);
-    return TestConv1DNWCInstances<ck::half_t>(conv_ptrs);
+    return test_conv1d_nwc_instances<ck::half_t>(conv_ptrs);
 }

-bool TestConv1DNWCF32Instances()
+bool test_conv1d_nwc_f32_instances()
 {
    std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
    ck::tensor_operation::device::device_conv1d_fwd_instance::
        add_device_conv1d_fwd_xdl_nwc_kxc_nwk_f32_instances(conv_ptrs);
-    return TestConv1DNWCInstances<float>(conv_ptrs);
+    return test_conv1d_nwc_instances<float>(conv_ptrs);
 }

-bool TestConv1DNWCInt8Instances()
+bool test_conv1d_nwc_int8_instances()
 {
    std::vector<DeviceConvFwdNoOpPtr> conv_ptrs;
    ck::tensor_operation::device::device_conv1d_fwd_instance::
        add_device_conv1d_fwd_xdl_nwc_kxc_nwk_int8_instances(conv_ptrs);
-    return TestConv1DNWCInstances<int8_t>(conv_ptrs);
+    return test_conv1d_nwc_instances<int8_t>(conv_ptrs);
 }

 } // anonymous namespace
@@ -133,18 +136,20 @@ bool TestConv1DNWCInt8Instances()
 int main()
 {
    bool res{true};
-    res = TestConv1DNWC();
-    std::cout << "TestConv1DNWC ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
+    res = test_conv1D_nwc();
+    std::cout << "test_conv1D_nwc ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;

-    res = TestConv1DNWCBF16Instances();
+    res = test_conv1d_nwc_bf16_instances();
    std::cout << "\nTestConv1DNWCBF16Instances ..... " << (res ? "SUCCESS" : "FAILURE")
              << std::endl;
-    res = TestConv1DNWCF16Instances();
-    std::cout << "\nTestConv1DNWCF16Instances ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
-    res = TestConv1DNWCF32Instances();
-    std::cout << "\nTestConv1DNWCF32Instances ..... " << (res ? "SUCCESS" : "FAILURE") << std::endl;
-    res = TestConv1DNWCInt8Instances();
-    std::cout << "\nTestConv1DNWCInt8Instances ..... " << (res ? "SUCCESS" : "FAILURE")
+    res = test_conv1d_nwc_f16_instances();
+    std::cout << "\ntest_conv1d_nwc_f16_instances ..... " << (res ? "SUCCESS" : "FAILURE")
+              << std::endl;
+    res = test_conv1d_nwc_f32_instances();
+    std::cout << "\ntest_conv1d_nwc_f32_instances ..... " << (res ? "SUCCESS" : "FAILURE")
+              << std::endl;
+    res = test_conv1d_nwc_int8_instances();
+    std::cout << "\ntes_tconv1_dnw_cint_8instances ..... " << (res ? "SUCCESS" : "FAILURE")
              << std::endl;

    return res ? 0 : 1;

--- a/test/convnd_fwd/conv2d_fwd.cpp
+++ b/test/convnd_fwd/conv2d_fwd.cpp
--- a/test/convnd_fwd/conv3d_fwd.cpp
+++ b/test/convnd_fwd/conv3d_fwd.cpp
--- a/test/convnd_fwd/conv_util.hpp
+++ b/test/convnd_fwd/conv_util.hpp
--- a/test/gemm/gemm_bf16.cpp
+++ b/test/gemm/gemm_bf16.cpp
@@ -19,7 +19,6 @@
 #include "element_wise_operation.hpp"
 #include "reference_gemm.hpp"
 #include "gemm_specialization.hpp"
-#include "test_util.hpp"

 using PassThrough = ck::tensor_operation::element_wise::PassThrough;


--- a/test/gemm/gemm_fp32.cpp
+++ b/test/gemm/gemm_fp32.cpp
@@ -19,7 +19,6 @@
 #include "element_wise_operation.hpp"
 #include "reference_gemm.hpp"
 #include "gemm_specialization.hpp"
-#include "test_util.hpp"

 using PassThrough = ck::tensor_operation::element_wise::PassThrough;


--- a/test/gemm/gemm_int8.cpp
+++ b/test/gemm/gemm_int8.cpp
@@ -19,7 +19,6 @@
 #include "element_wise_operation.hpp"
 #include "reference_gemm.hpp"
 #include "gemm_specialization.hpp"
-#include "test_util.hpp"

 using PassThrough = ck::tensor_operation::element_wise::PassThrough;


--- a/test/gemm/gemm_util.hpp
+++ b/test/gemm/gemm_util.hpp
--- a/test/grouped_gemm/grouped_gemm_fp16.cpp
+++ b/test/grouped_gemm/grouped_gemm_fp16.cpp
--- a/test/include/conv_test_util.hpp
+++ b/test/include/conv_test_util.hpp
--- a/test/magic_number_division/magic_number_division.cpp
+++ b/test/magic_number_division/magic_number_division.cpp
--- a/test/reduce/reduce_no_index.cpp
+++ b/test/reduce/reduce_no_index.cpp
--- a/test/reduce/reduce_with_index.cpp
+++ b/test/reduce/reduce_with_index.cpp
--- a/test/reference_conv_fwd/reference_conv_fwd.cpp
+++ b/test/reference_conv_fwd/reference_conv_fwd.cpp