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Commit 8f41bd8e authored by Jun Liu's avatar Jun Liu
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Merge branch 'develop' into amd-develop

parents 7f65ac05 d7f05fb9
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library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mnn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mnn_instance.cpp
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary! // setting Don't use this hack unless absolutely necessary!
...@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mn ...@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mn
F32, F32,
PassThrough, PassThrough,
PassThrough, PassThrough,
Scale>; Scale,
2>;
void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mnn_instance( void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_compute_f32_mnn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2, std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
......
library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance.cpp
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary! // setting Don't use this hack unless absolutely necessary!
...@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance = ...@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance =
F64, F64,
PassThrough, PassThrough,
PassThrough, PassThrough,
Scale>; Scale,
2>;
void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance( void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_kkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2, std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
......
library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance.cpp
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary! // setting Don't use this hack unless absolutely necessary!
...@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance = ...@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance =
F64, F64,
PassThrough, PassThrough,
PassThrough, PassThrough,
Scale>; Scale,
2>;
void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance( void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_knn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2, std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
......
library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance.cpp
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary! // setting Don't use this hack unless absolutely necessary!
...@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance = ...@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance =
F64, F64,
PassThrough, PassThrough,
PassThrough, PassThrough,
Scale>; Scale,
2>;
void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance( void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2, std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
......
library/src/tensor_operation_instance/gpu/contraction_scale/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance.cpp → library/src/tensor_operation_instance/gpu/contraction_scale/2D/device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance.cpp
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT // SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved. // Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default // This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary! // setting Don't use this hack unless absolutely necessary!
...@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance = ...@@ -31,7 +31,8 @@ using device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance =
F64, F64,
PassThrough, PassThrough,
PassThrough, PassThrough,
Scale>; Scale,
2>;
void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance( void add_device_contraction_scale_m2_n2_k2_xdl_c_shuffle_f64_f64_f64_mnn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<2, std::vector<std::unique_ptr<DeviceContractionMultipleD<2,
......
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_kkn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// k/k/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_kkn_instance =
device_contraction_kk_instance<BF16,
BF16,
F32,
BF16,
Empty_Tuple,
BF16,
F32,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_kkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
BF16,
BF16,
Empty_Tuple,
BF16,
PassThrough,
PassThrough,
Scale,
F32>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_kkn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_knn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// k/n/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_knn_instance =
device_contraction_kn_instance<BF16,
BF16,
F32,
BF16,
Empty_Tuple,
BF16,
F32,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_knn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
BF16,
BF16,
Empty_Tuple,
BF16,
PassThrough,
PassThrough,
Scale,
F32>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_knn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mkn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// m/k/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mkn_instance =
device_contraction_mk_instance<BF16,
BF16,
F32,
BF16,
Empty_Tuple,
BF16,
F32,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
BF16,
BF16,
Empty_Tuple,
BF16,
PassThrough,
PassThrough,
Scale,
F32>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mkn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mnn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// m/n/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mnn_instance =
device_contraction_mn_instance<BF16,
BF16,
F32,
BF16,
Empty_Tuple,
BF16,
F32,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mnn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
BF16,
BF16,
Empty_Tuple,
BF16,
PassThrough,
PassThrough,
Scale,
F32>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_bf16_bf16_bf16_compute_f32_mnn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_kkn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// k/k/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_kkn_instance =
device_contraction_kk_instance<F16,
F16,
F32,
F16,
Empty_Tuple,
F16,
F32,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_kkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
F16,
F16,
Empty_Tuple,
F16,
PassThrough,
PassThrough,
Scale,
F32>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_kkn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_knn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// k/n/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_knn_instance =
device_contraction_kn_instance<F16,
F16,
F32,
F16,
Empty_Tuple,
F16,
F32,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_knn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
F16,
F16,
Empty_Tuple,
F16,
PassThrough,
PassThrough,
Scale,
F32>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_knn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mkn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// m/k/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mkn_instance =
device_contraction_mk_instance<F16,
F16,
F32,
F16,
Empty_Tuple,
F16,
F32,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
F16,
F16,
Empty_Tuple,
F16,
PassThrough,
PassThrough,
Scale,
F32>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mkn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mnn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// m/n/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mnn_instance =
device_contraction_mn_instance<F16,
F16,
F32,
F16,
Empty_Tuple,
F16,
F32,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mnn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
F16,
F16,
Empty_Tuple,
F16,
PassThrough,
PassThrough,
Scale,
F32>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f16_f16_f16_compute_f32_mnn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_kkn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// k/k/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_kkn_instance =
device_contraction_kk_instance<F32,
F32,
F32,
F32,
Empty_Tuple,
F32,
BF16,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_kkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
F32,
F32,
Empty_Tuple,
F32,
PassThrough,
PassThrough,
Scale,
BF16>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_kkn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_knn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// k/n/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_knn_instance =
device_contraction_kn_instance<F32,
F32,
F32,
F32,
Empty_Tuple,
F32,
BF16,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_knn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
F32,
F32,
Empty_Tuple,
F32,
PassThrough,
PassThrough,
Scale,
BF16>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_knn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_mkn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// m/k/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_mkn_instance =
device_contraction_mk_instance<F32,
F32,
F32,
F32,
Empty_Tuple,
F32,
BF16,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_mkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
F32,
F32,
Empty_Tuple,
F32,
PassThrough,
PassThrough,
Scale,
BF16>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_mkn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_mnn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// m/n/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_mnn_instance =
device_contraction_mn_instance<F32,
F32,
F32,
F32,
Empty_Tuple,
F32,
BF16,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_mnn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
F32,
F32,
Empty_Tuple,
F32,
PassThrough,
PassThrough,
Scale,
BF16>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_bf16_mnn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_kkn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// k/k/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_kkn_instance =
device_contraction_kk_instance<F32,
F32,
F32,
F32,
Empty_Tuple,
F32,
F16,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_kkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
F32,
F32,
Empty_Tuple,
F32,
PassThrough,
PassThrough,
Scale,
F16>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_kkn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_knn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// k/n/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_knn_instance =
device_contraction_kn_instance<F32,
F32,
F32,
F32,
Empty_Tuple,
F32,
F16,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_knn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
F32,
F32,
Empty_Tuple,
F32,
PassThrough,
PassThrough,
Scale,
F16>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_knn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
library/src/tensor_operation_instance/gpu/contraction_scale/6D/device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_mkn_instance.cpp 0 → 100644
View file @ 8f41bd8e
// SPDX-License-Identifier: MIT
// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
// This (ifndef) is a hack to use customized behavior for buffer load rather than using default
// setting Don't use this hack unless absolutely necessary!
// FIXME: make the behavior of buffer load a configurable (template) parameter of each device op
#define CK_EXPERIMENTAL_USE_BUFFER_LOAD_OOB_CHECK_OFFSET_TRICK 1
#include <cstdlib>
#include "ck/ck.hpp"
#include "ck/tensor_operation/gpu/device/device_contraction_multiple_d.hpp"
#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
#include "ck/library/tensor_operation_instance/gpu/contraction/device_contraction_instance.hpp"
#include "ck/library/tensor_operation_instance/add_device_operation_instance.hpp"
namespace ck {
namespace tensor_operation {
namespace device {
namespace instance {
// A[m0, m1, k0, k1] * B[n0, n1, k0, k1] + D[m0, m1, n0, n1] = E[m0, m1, n0, n1]
// m/k/n/n are the fast changing dimension for A/B/D/E
using device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_mkn_instance =
device_contraction_mk_instance<F32,
F32,
F32,
F32,
Empty_Tuple,
F32,
F16,
PassThrough,
PassThrough,
Scale,
6>;
void add_device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_mkn_instance(
std::vector<std::unique_ptr<DeviceContractionMultipleD<6,
6,
6,
F32,
F32,
Empty_Tuple,
F32,
PassThrough,
PassThrough,
Scale,
F16>>>& instances)
{
add_device_operation_instances(
instances,
device_contraction_scale_m6_n6_k6_xdl_c_shuffle_f32_f32_f32_compute_f16_mkn_instance{});
}
} // namespace instance
} // namespace device
} // namespace tensor_operation
} // namespace ck
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