mirror of
https://github.com/ggml-org/llama.cpp.git
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ggml-zdnn: fix pr comments
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
This commit is contained in:
Aaron Teo
@@ -1,38 +1,36 @@
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if (GGML_ZDNN)
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if (DEFINED ZDNN_ROOT)
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if (DEFINED ZDNN_ROOT)
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message(STATUS "zdnn: using ZDNN_ROOT override: ${ZDNN_ROOT}")
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message(STATUS "zdnn: using ZDNN_ROOT override: ${ZDNN_ROOT}")
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set(ZDNN_HINT "${ZDNN_ROOT}")
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set(ZDNN_HINT "${ZDNN_ROOT}")
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else()
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else()
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set(ZDNN_HINT "")
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set(ZDNN_HINT "")
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endif()
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endif()
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find_path(ZDNN_INCLUDE
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find_path(ZDNN_INCLUDE
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NAMES zdnn.h
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NAMES zdnn.h
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HINTS ${ZDNN_HINT} /usr /usr/local
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HINTS ${ZDNN_HINT} /usr /usr/local
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PATH_SUFFIXES include)
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PATH_SUFFIXES include)
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if (ZDNN_INCLUDE)
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if (ZDNN_INCLUDE)
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message(STATUS "zdnn: found include: ${ZDNN_INCLUDE}")
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message(STATUS "zdnn: found include: ${ZDNN_INCLUDE}")
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else()
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else()
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message(FATAL_ERROR "zdnn: include directory not found, please set ZDNN_ROOT to the proper path if necessary")
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message(FATAL_ERROR "zdnn: include directory not found, please set ZDNN_ROOT to the proper path if necessary")
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endif()
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endif()
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find_library(ZDNN_LIB
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find_library(ZDNN_LIB
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NAMES zdnn
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NAMES zdnn
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HINTS ${ZDNN_HINT} /usr /usr/local
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HINTS ${ZDNN_HINT} /usr /usr/local
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PATH_SUFFIXES lib lib64)
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PATH_SUFFIXES lib lib64)
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if (ZDNN_LIB)
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if (ZDNN_LIB)
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message(STATUS "zdnn: found library: ${ZDNN_LIB}")
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message(STATUS "zdnn: found library: ${ZDNN_LIB}")
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else()
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else()
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message(FATAL_ERROR "zdnn: library not found, please set ZDNN_ROOT to the proper path if necessary")
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message(FATAL_ERROR "zdnn: library not found, please set ZDNN_ROOT to the proper path if necessary")
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endif()
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file(GLOB GGML_SOURCES_ZDNN "*.c" "*.cpp")
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file(GLOB GGML_HEADERS_ZDNN "*.h" "*.hpp")
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ggml_add_backend_library(ggml-zdnn ${GGML_HEADERS_ZDNN} ${GGML_SOURCES_ZDNN})
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target_link_libraries(ggml-zdnn PRIVATE ${ZDNN_LIB})
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target_include_directories(ggml-zdnn PRIVATE ${ZDNN_INCLUDE})
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target_link_directories(ggml-zdnn PRIVATE ${ZDNN_LIB})
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target_compile_definitions(ggml-zdnn PRIVATE GGML_ZDNN GGML_USE_ZDNN)
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endif()
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endif()
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file(GLOB GGML_SOURCES_ZDNN "*.c" "*.cpp")
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file(GLOB GGML_HEADERS_ZDNN "*.h" "*.hpp")
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ggml_add_backend_library(ggml-zdnn ${GGML_HEADERS_ZDNN} ${GGML_SOURCES_ZDNN})
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target_link_libraries(ggml-zdnn PRIVATE ${ZDNN_LIB})
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target_include_directories(ggml-zdnn PRIVATE ${ZDNN_INCLUDE})
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target_link_directories(ggml-zdnn PRIVATE ${ZDNN_LIB})
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target_compile_definitions(ggml-zdnn PRIVATE GGML_ZDNN GGML_USE_ZDNN)
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@@ -287,8 +287,6 @@ static bool ggml_zdnn_supports_op(const ggml_backend_zdnn_device_context * ctx_d
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default:
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default:
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return false;
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return false;
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}
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}
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GGML_UNUSED(ctx_dev);
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}
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}
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////////////////////////////////////////////////////////////////////////////////
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////////////////////////////////////////////////////////////////////////////////
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@@ -1,660 +0,0 @@
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// SPDX-License-Identifier: Apache-2.0
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/*
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* Copyright IBM Corp. 2021, 2024
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef ZDNN_ZDNN_H_
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#define ZDNN_ZDNN_H_
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#include <inttypes.h>
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#include <stdbool.h>
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#include <stddef.h>
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#include <stdint.h>
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#ifdef __cplusplus
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extern "C" {
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#endif
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// -----------------------------------------------------------------------------
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// NOTE:
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// Ensure that symbols in zdnn.h and zdnn.map are in sync!
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// Please also have a look at zdnn.map how to add, update or remove a symbol.
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// -----------------------------------------------------------------------------
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// -----------------------------------------------------------------------------
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// Initializer and global variables
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// -----------------------------------------------------------------------------
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void zdnn_init();
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// -----------------------------------------------------------------------------
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// zDNN Status
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// -----------------------------------------------------------------------------
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// -----------------------------------------------------------------------------
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// NOTE:
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// Update status.c and zdnn_private.h after any status modification!
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// -----------------------------------------------------------------------------
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// Status categories
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#define ZDNN_WARNING 0x00020000
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#define ZDNN_PARAMETER_ERROR 0x00040000
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#define ZDNN_DATA_ERROR 0x00100000
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#define ZDNN_HW_ERROR 0x000c0000
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// clang-format off
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typedef enum zdnn_status {
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// ----------------------------------------------------------------
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ZDNN_OK = 0x00000000, // Success.
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// ----------------------------------------------------------------
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ZDNN_ELEMENT_RANGE_VIOLATION = ZDNN_WARNING + 0x0001, // zAIU operation resulted in data that was out of the normal range.
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// ----------------------------------------------------------------
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ZDNN_INVALID_SHAPE = ZDNN_PARAMETER_ERROR + 0x0001, // Invalid shape information in one (or more) of the input/output tensor(s).
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ZDNN_INVALID_LAYOUT, // Invalid layout information in one (or more) of the input/output tensor(s).
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ZDNN_INVALID_TYPE, // Invalid type information in one (or more) of the input/output tensor(s).
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ZDNN_INVALID_FORMAT, // Invalid format information in one (or more) of the input/output tensor(s).
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ZDNN_INVALID_DIRECTION, // Invalid RNN direction.
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ZDNN_INVALID_CONCAT_INFO, // Invalid concatenation info.
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ZDNN_INVALID_STRIDE_PADDING, // Invalid padding type parameter for current strides
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ZDNN_INVALID_STRIDES, // Invalid stride height or width parameter.
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ZDNN_MISALIGNED_PARMBLOCK, // NNPA parameter block is not on double word boundary.
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ZDNN_INVALID_CLIPPING_VALUE, // Invalid clipping for the specified operation.
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ZDNN_INVALID_ADJUSTMENT_FACTOR, // Invalid adjustment for the specified operation.
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ZDNN_INVALID_EPSILON, // Invalid epsilon for the specified operation.
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ZDNN_INVALID_TRANSFORM_TYPE, // Invalid transformation type
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ZDNN_INVALID_BETA, // Invalid beta value for the specified operation.
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ZDNN_INVALID_GAMMA, // Invalid gamma value for the specified operation.
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ZDNN_INVALID_BESSEL_CORRECTION, // Invalid bessel correction value for the specified operation.
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ZDNN_INVALID_SCALE, // Invalid scale value for the specified operation.
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ZDNN_INVALID_OFFSET, // Invalid offset value for the specified operation.
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// ----------------------------------------------------------------
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ZDNN_ALLOCATION_FAILURE = ZDNN_DATA_ERROR + 0x0001, // Can not allocate storage.
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ZDNN_INVALID_BUFFER, // Buffer address is NULL or not on 4K-byte boundary, or insufficient buffer size.
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ZDNN_CONVERT_FAILURE, // Floating point data conversion failure.
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ZDNN_INVALID_STATE, // Invalid zTensor state.
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ZDNN_UNSUPPORTED_AIU_EXCEPTION, // zAIU operation returned an unexpected exception.
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// ----------------------------------------------------------------
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ZDNN_UNSUPPORTED_PARMBLOCK = ZDNN_HW_ERROR + 0x0001, // NNPA parameter block format is not supported by the model.
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ZDNN_UNAVAILABLE_FUNCTION, // Specified NNPA function is not defined or installed on the machine.
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ZDNN_UNSUPPORTED_FORMAT = ZDNN_HW_ERROR + 0x0010, // Specified tensor data layout format is not supported.
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ZDNN_UNSUPPORTED_TYPE, // Specified tensor data type is not supported.
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ZDNN_EXCEEDS_MDIS, // Tensor dimension exceeds maximum dimension index size (MDIS).
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ZDNN_EXCEEDS_MTS, // Total number of elements in tensor exceeds maximum tensor size. (MTS).
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ZDNN_MISALIGNED_TENSOR, // Tensor address is not on 4K-byte boundary.
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ZDNN_MISALIGNED_SAVEAREA, // Function specific save area address is not on 4K-byte boundary.
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// ----------------------------------------------------------------
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// Function specific response code (F00x)
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ZDNN_FUNC_RC_F000 = ZDNN_HW_ERROR + 0xF000, // Function specific response code (F000).
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ZDNN_FUNC_RC_F001, // Function specific response code (F001).
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ZDNN_FUNC_RC_F002, // Function specific response code (F002).
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ZDNN_FUNC_RC_F003, // Function specific response code (F003).
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ZDNN_FUNC_RC_F004, // Function specific response code (F004).
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ZDNN_FUNC_RC_F005, // Function specific response code (F005).
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ZDNN_FUNC_RC_F006, // Function specific response code (F006).
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ZDNN_FUNC_RC_F007, // Function specific response code (F007).
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ZDNN_FUNC_RC_F008, // Function specific response code (F008).
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ZDNN_FUNC_RC_F009, // Function specific response code (F009).
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// ----------------------------------------------------------------
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} zdnn_status;
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// clang-format on
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// -----------------------------------------------------------------------------
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// NNPA hardware defined values as described in
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// z/Architecture - Principles of Operation
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// -----------------------------------------------------------------------------
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typedef enum nnpa_function_code {
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NNPA_QAF = 0,
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NNPA_ADD = 16,
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NNPA_SUB = 17,
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NNPA_MUL = 18,
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NNPA_DIV = 19,
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NNPA_MIN = 20,
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NNPA_MAX = 21,
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NNPA_LOG = 32,
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NNPA_EXP = 33,
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NNPA_SQRT = 34,
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NNPA_INVSQRT = 35,
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// reserved = 48
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NNPA_RELU = 49,
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NNPA_TANH = 50,
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NNPA_SIGMOID = 51,
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NNPA_SOFTMAX = 52,
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NNPA_GELU = 53,
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NNPA_BATCHNORMALIZATION = 64,
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NNPA_MOMENTS = 65,
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NNPA_LAYERNORM = 66,
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NNPA_NORM = 67,
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NNPA_MAXPOOL2D = 80,
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NNPA_AVGPOOL2D = 81,
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NNPA_LSTMACT = 96,
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NNPA_GRUACT = 97,
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NNPA_CONVOLUTION = 112,
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NNPA_MATMUL_OP = 113,
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NNPA_MATMUL_OP_BCAST23 = 114,
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NNPA_MATMUL_OP_BCAST1 = 115,
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NNPA_TRANSFORM = 240,
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NNPA_REDUCE = 241
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} nnpa_function_code;
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typedef enum nnpa_parmblk_format {
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NNPA_PARMBLKFORMAT_0 = 0,
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NNPA_PARMBLKFORMAT_1 = 1,
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} nnpa_parmblk_format;
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typedef enum nnpa_data_type {
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NNPA_DATATYPE_1 = 0,
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NNPA_32_BIT_BINARY_FP_SHORT = 6,
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NNPA_8_BIT_BINARY_INT = 8,
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NNPA_32_BIT_BINARY_INT = 10
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} nnpa_data_type;
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typedef enum nnpa_layout_format {
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NNPA_LAYOUTFMT_4DFEATURE = 0,
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NNPA_LAYOUTFMT_4DKERNEL = 1,
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NNPA_LAYOUTFMT_4DWEIGHTS = 2,
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NNPA_LAYOUTFMT_4DGENERIC = 31
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} nnpa_layout_format;
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typedef enum nnpa_bfp_format {
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// 0 is reversed
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NNPA_BFPFMT_TINY = 1,
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NNPA_BFPFMT_SHORT = 2
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} nnpa_bfp_format;
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// NNPA_SOFTMAX, NNPA_REDUCE, and NNPA_TRANSFORM require 8K work area
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#define ZDNN_SOFTMAX_SAVEAREA_SIZE 8 * 1024
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#define ZDNN_8K_SAVEAREA_SIZE 8 * 1024
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// NNPA Hardware defined values for Function Specific Parameters
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typedef enum nnpa_matmul_operations {
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NNPA_MATMUL_OP_ADDITION = 0,
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NNPA_MATMUL_OP_COMP_HIGH = 1,
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NNPA_MATMUL_OP_COMP_NOT_LOW = 2,
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NNPA_MATMUL_OP_COMP_EQUAL = 3,
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NNPA_MATMUL_OP_COMP_NOT_EQUAL = 4,
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NNPA_MATMUL_OP_COMP_NOT_HIGH = 5,
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NNPA_MATMUL_OP_COMP_LOW = 6,
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} nnpa_matmul_operations;
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typedef enum nnpa_matmul_bcast_operations {
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NNPA_MATMUL_BCAST_OP_ADDITION = 0,
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NNPA_MATMUL_BCAST_OP_COMP_HIGH = 1,
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NNPA_MATMUL_BCAST_OP_COMP_NOT_LOW = 2,
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NNPA_MATMUL_BCAST_OP_COMP_EQUAL = 3,
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NNPA_MATMUL_BCAST_OP_COMP_NOT_EQUAL = 4,
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NNPA_MATMUL_BCAST_OP_COMP_NOT_HIGH = 5,
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NNPA_MATMUL_BCAST_OP_COMP_LOW = 6
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} nnpa_matmul_bcast_operations;
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typedef enum nnpa_softmax_act {
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NNPA_SOFTMAX_NONE = 0,
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NNPA_SOFTMAX_LOG = 1
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} nnpa_softmax_act;
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typedef enum nnpa_reduce_operations {
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NNPA_REDUCE_OP_MINIMUM = 0,
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NNPA_REDUCE_OP_MINIMUM_IDX = 1,
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NNPA_REDUCE_OP_MAXIMUM = 2,
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NNPA_REDUCE_OP_MAXIMUM_IDX = 3
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} nnpa_reduce_operations;
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// -----------------------------------------------------------------------------
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// zdnn_query_*() bit-field enums
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// -----------------------------------------------------------------------------
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// pos is counting from left to right
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#define MSB_BITMASK(field_size, pos) 1u << ((field_size - 1) - pos)
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typedef enum zdnn_query_datatypes {
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QUERY_DATATYPE_INTERNAL1 = MSB_BITMASK(16, NNPA_DATATYPE_1),
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QUERY_DATATYPE_BINARY_FP32 = MSB_BITMASK(16, NNPA_32_BIT_BINARY_FP_SHORT),
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QUERY_DATATYPE_BINARY_INT8 = MSB_BITMASK(16, NNPA_8_BIT_BINARY_INT),
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QUERY_DATATYPE_BINARY_INT32 = MSB_BITMASK(16, NNPA_32_BIT_BINARY_INT)
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} zdnn_query_datatypes;
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typedef enum zdnn_query_layoutfmts {
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QUERY_LAYOUTFMT_4DFEATURE = MSB_BITMASK(32, NNPA_LAYOUTFMT_4DFEATURE),
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QUERY_LAYOUTFMT_4DKERNEL = MSB_BITMASK(32, NNPA_LAYOUTFMT_4DKERNEL),
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QUERY_LAYOUTFMT_4DWEIGHTS = MSB_BITMASK(32, NNPA_LAYOUTFMT_4DWEIGHTS),
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QUERY_LAYOUTFMT_4DGENERIC = MSB_BITMASK(32, NNPA_LAYOUTFMT_4DGENERIC)
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} zdnn_query_layoutfmts;
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typedef enum zdnn_query_bfpfmts {
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QUERY_BFPFMT_TINY = MSB_BITMASK(16, NNPA_BFPFMT_TINY),
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QUERY_BFPFMT_SHORT = MSB_BITMASK(16, NNPA_BFPFMT_SHORT)
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} zdnn_query_bfpfmts;
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// -----------------------------------------------------------------------------
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// ZDNN enums
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// -----------------------------------------------------------------------------
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typedef enum zdnn_data_types {
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ZDNN_DLFLOAT16 = NNPA_DATATYPE_1, // 16-bit deep learning format
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ZDNN_BINARY_FP32 =
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NNPA_32_BIT_BINARY_FP_SHORT, // 32-bit binary-floating-point format
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ZDNN_BINARY_INT8 =
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NNPA_8_BIT_BINARY_INT, // 8-bit signed or unsigned binary integer
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ZDNN_BINARY_INT32 =
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NNPA_32_BIT_BINARY_INT, // 32-bit signed or unsigned binary integer
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INT8 = 251, // 8-bit signed or unsigned binary integer format
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|
||||||
INT32 = 252, // 32-bit signed or unsigned binary integer format
|
|
||||||
BFLOAT = 253, // Brain floating point format
|
|
||||||
FP16 = 254, // 16-bit IEEE-754 floating point format
|
|
||||||
FP32 = 255, // 32-bit IEEE-754 floating point format
|
|
||||||
} zdnn_data_types;
|
|
||||||
|
|
||||||
typedef enum zdnn_data_layouts {
|
|
||||||
ZDNN_1D, // 1d tensor
|
|
||||||
ZDNN_2D, // 2d tensor
|
|
||||||
ZDNN_2DS, // represents special 2D tensors required by LSTM/GRU
|
|
||||||
ZDNN_3D, // 3d tensor
|
|
||||||
ZDNN_3DS, // represents special 3D tensors required by
|
|
||||||
// LSTM/GRU/Softmax/Matmul
|
|
||||||
ZDNN_ZRH, // represents (update, reset, hidden) used by GRU
|
|
||||||
ZDNN_4D, // 4d tensor
|
|
||||||
ZDNN_4DS, // represents special 4D tensors required by LSTM/GRU output
|
|
||||||
ZDNN_NHWC, // 4d feature tensor in NHWC
|
|
||||||
ZDNN_NCHW, // 4d feature tensor in NCHW
|
|
||||||
ZDNN_FICO, // represents (forget, input, cell, output) used by LSTM
|
|
||||||
ZDNN_HWCK, // 4d kernel CNN tensor
|
|
||||||
ZDNN_BIDIR_ZRH, // ZRH variant to work with bidirectional LSTM/GRU output
|
|
||||||
ZDNN_BIDIR_FICO // FICO variant to work with bidirectional LSTM/GRU output
|
|
||||||
} zdnn_data_layouts;
|
|
||||||
|
|
||||||
typedef enum zdnn_data_formats {
|
|
||||||
ZDNN_FORMAT_4DFEATURE =
|
|
||||||
NNPA_LAYOUTFMT_4DFEATURE, // tensor in zAIU data layout format 0
|
|
||||||
ZDNN_FORMAT_4DKERNEL =
|
|
||||||
NNPA_LAYOUTFMT_4DKERNEL, // tensor in zAIU data layout format 1
|
|
||||||
ZDNN_FORMAT_4DWEIGHTS =
|
|
||||||
NNPA_LAYOUTFMT_4DWEIGHTS, // tensor in zAIU data layout format 2
|
|
||||||
ZDNN_FORMAT_4DGENERIC =
|
|
||||||
NNPA_LAYOUTFMT_4DGENERIC, // tensor in zAIU data layout 31
|
|
||||||
} zdnn_data_formats;
|
|
||||||
|
|
||||||
typedef enum zdnn_quantized_transform_types {
|
|
||||||
QUANTIZED_DLFLOAT16 = 0, // quantized dlfloat16
|
|
||||||
QUANTIZED_INT8 = 1, // quantized int8
|
|
||||||
QUANTIZED_WEIGHTS_INT8 = 2 // quantized weights
|
|
||||||
} zdnn_quantized_transform_types;
|
|
||||||
|
|
||||||
// Supported padding types for use in pooling functions
|
|
||||||
typedef enum zdnn_pool_padding {
|
|
||||||
VALID_PADDING = 0,
|
|
||||||
SAME_PADDING = 1
|
|
||||||
} zdnn_pool_padding;
|
|
||||||
|
|
||||||
// Support operations for use in matmul functions
|
|
||||||
typedef enum zdnn_matmul_ops {
|
|
||||||
MATMUL_OP_ADDITION = NNPA_MATMUL_OP_ADDITION,
|
|
||||||
MATMUL_OP_GREATER = NNPA_MATMUL_OP_COMP_HIGH,
|
|
||||||
MATMUL_OP_GREATER_EQUAL = NNPA_MATMUL_OP_COMP_NOT_LOW,
|
|
||||||
MATMUL_OP_EQUAL = NNPA_MATMUL_OP_COMP_EQUAL,
|
|
||||||
MATMUL_OP_NOT_EQUAL = NNPA_MATMUL_OP_COMP_NOT_EQUAL,
|
|
||||||
MATMUL_OP_LESSER_EQUAL = NNPA_MATMUL_OP_COMP_NOT_HIGH,
|
|
||||||
MATMUL_OP_LESSER = NNPA_MATMUL_OP_COMP_LOW
|
|
||||||
} zdnn_matmul_ops;
|
|
||||||
|
|
||||||
// Support operations for use in matmul function
|
|
||||||
typedef enum zdnn_matmul_bcast_ops {
|
|
||||||
MATMUL_BCAST_OP_ADDITION = NNPA_MATMUL_BCAST_OP_ADDITION,
|
|
||||||
MATMUL_BCAST_OP_GREATER = NNPA_MATMUL_BCAST_OP_COMP_HIGH,
|
|
||||||
MATMUL_BCAST_OP_GREATER_EQUAL = NNPA_MATMUL_BCAST_OP_COMP_NOT_LOW,
|
|
||||||
MATMUL_BCAST_OP_EQUAL = NNPA_MATMUL_BCAST_OP_COMP_EQUAL,
|
|
||||||
MATMUL_BCAST_OP_NOT_EQUAL = NNPA_MATMUL_BCAST_OP_COMP_NOT_EQUAL,
|
|
||||||
MATMUL_BCAST_OP_LESSER_EQUAL = NNPA_MATMUL_BCAST_OP_COMP_NOT_HIGH,
|
|
||||||
MATMUL_BCAST_OP_LESSER = NNPA_MATMUL_BCAST_OP_COMP_LOW
|
|
||||||
|
|
||||||
} zdnn_matmul_bcast_ops;
|
|
||||||
|
|
||||||
typedef enum zdnn_softmax_act {
|
|
||||||
SOFTMAX_ACT_NONE = NNPA_SOFTMAX_NONE,
|
|
||||||
SOFTMAX_ACT_LOG = NNPA_SOFTMAX_LOG
|
|
||||||
} zdnn_softmax_act;
|
|
||||||
|
|
||||||
typedef enum zdnn_conv2d_act {
|
|
||||||
CONV2D_ACT_NONE,
|
|
||||||
CONV2D_ACT_RELU
|
|
||||||
} zdnn_conv2d_act;
|
|
||||||
|
|
||||||
// Support operations for use in reduce functions
|
|
||||||
typedef enum zdnn_reduce_ops {
|
|
||||||
REDUCE_OP_MINIMUM = NNPA_REDUCE_OP_MINIMUM,
|
|
||||||
REDUCE_OP_MINIMUM_IDX = NNPA_REDUCE_OP_MINIMUM_IDX,
|
|
||||||
REDUCE_OP_MAXIMUM = NNPA_REDUCE_OP_MAXIMUM,
|
|
||||||
REDUCE_OP_MAXIMUM_IDX = NNPA_REDUCE_OP_MAXIMUM_IDX
|
|
||||||
} zdnn_reduce_ops;
|
|
||||||
|
|
||||||
typedef enum zdnn_moments_bessel {
|
|
||||||
MOMENTS_BESSEL_POPULATION,
|
|
||||||
MOMENTS_BESSEL_SAMPLE,
|
|
||||||
} zdnn_moments_bessel;
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// Structs
|
|
||||||
// ----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
// describes general pre-transformed or transformed information (e.g. shape) of
|
|
||||||
// a tensor
|
|
||||||
typedef struct zdnn_tensor_desc {
|
|
||||||
zdnn_data_layouts layout; // data layout
|
|
||||||
zdnn_data_formats format; // internal use only
|
|
||||||
zdnn_data_types type; // data type
|
|
||||||
uint32_t dim4; // number of elements in outermost dimension
|
|
||||||
uint32_t dim3; // ... outer dimension
|
|
||||||
uint32_t dim2; // ... inner dimension
|
|
||||||
uint32_t dim1; // number of elements in innermost dimension
|
|
||||||
} zdnn_tensor_desc;
|
|
||||||
|
|
||||||
// struct for describing a ztensor
|
|
||||||
typedef struct zdnn_ztensor {
|
|
||||||
zdnn_tensor_desc
|
|
||||||
*pre_transformed_desc; // tensor's shape information before transformation
|
|
||||||
zdnn_tensor_desc *transformed_desc; // transformed tensor's shape information
|
|
||||||
uint64_t buffer_size; // tensor size in bytes
|
|
||||||
void *buffer; // pointer to the tensor in memory
|
|
||||||
bool is_transformed; // indicator if data in buffer has been transformed
|
|
||||||
char reserved[3]; // not currently used, should contain zeros.
|
|
||||||
float rec_scale; // the scale factor for quantization, stored as reciprocal
|
|
||||||
float offset; // the offset for quantization
|
|
||||||
char reserved2[20]; // not currently used, should contain zeros.
|
|
||||||
} zdnn_ztensor;
|
|
||||||
|
|
||||||
#define ZDNN_VERSION "1.2.0"
|
|
||||||
#define ZDNN_VERNUM 0x010200 // 0x[major][minor][patch]
|
|
||||||
#define ZDNN_VER_MAJOR 1
|
|
||||||
#define ZDNN_VER_MINOR 2
|
|
||||||
#define ZDNN_VER_PATCH 0
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// External Tensor Functions
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
// Concatenation information is encoded into a 32-bit word:
|
|
||||||
// [RNN_TYPE: 8][PREV_LAYER_TYPE: 8][USAGE: 8][8]
|
|
||||||
|
|
||||||
typedef uint32_t zdnn_concat_info;
|
|
||||||
|
|
||||||
#define BITSHIFT_RNN_TYPE 24
|
|
||||||
#define BITSHIFT_PREV_LAYER 16
|
|
||||||
#define BITSHIFT_USAGE 8
|
|
||||||
|
|
||||||
#define RNN_TYPE_LSTM (0 << BITSHIFT_RNN_TYPE)
|
|
||||||
#define RNN_TYPE_GRU (1 << BITSHIFT_RNN_TYPE)
|
|
||||||
|
|
||||||
#define PREV_LAYER_UNI (0 << BITSHIFT_PREV_LAYER)
|
|
||||||
#define PREV_LAYER_NONE PREV_LAYER_UNI
|
|
||||||
#define PREV_LAYER_BIDIR (1 << BITSHIFT_PREV_LAYER)
|
|
||||||
|
|
||||||
#define USAGE_WEIGHTS (0 << BITSHIFT_USAGE)
|
|
||||||
#define USAGE_HIDDEN_WEIGHTS (1 << BITSHIFT_USAGE)
|
|
||||||
#define USAGE_BIASES (2 << BITSHIFT_USAGE)
|
|
||||||
#define USAGE_HIDDEN_BIASES (3 << BITSHIFT_USAGE)
|
|
||||||
|
|
||||||
#define CONCAT_RNN_TYPE(info) (info & (0xFFu << BITSHIFT_RNN_TYPE))
|
|
||||||
#define CONCAT_PREV_LAYER(info) (info & (0xFFu << BITSHIFT_PREV_LAYER))
|
|
||||||
#define CONCAT_USAGE(info) (info & (0xFFu << BITSHIFT_USAGE))
|
|
||||||
|
|
||||||
void zdnn_init_pre_transformed_desc(zdnn_data_layouts layout,
|
|
||||||
zdnn_data_types type,
|
|
||||||
zdnn_tensor_desc *pre_tfrmd_desc, ...);
|
|
||||||
|
|
||||||
zdnn_status
|
|
||||||
zdnn_generate_transformed_desc(const zdnn_tensor_desc *pre_tfrmd_desc,
|
|
||||||
zdnn_tensor_desc *tfrmd_desc);
|
|
||||||
|
|
||||||
zdnn_status zdnn_generate_quantized_transformed_desc(
|
|
||||||
const zdnn_tensor_desc *pre_tfrmd_desc,
|
|
||||||
zdnn_quantized_transform_types transform_type,
|
|
||||||
zdnn_tensor_desc *tfrmd_desc);
|
|
||||||
|
|
||||||
zdnn_status zdnn_generate_transformed_desc_concatenated(
|
|
||||||
const zdnn_tensor_desc *pre_tfrmd_desc, zdnn_concat_info info,
|
|
||||||
zdnn_tensor_desc *tfrmd_desc);
|
|
||||||
|
|
||||||
zdnn_status zdnn_allochelper_ztensor(zdnn_ztensor *ztensor);
|
|
||||||
zdnn_status zdnn_free_ztensor_buffer(const zdnn_ztensor *ztensor);
|
|
||||||
|
|
||||||
void zdnn_init_ztensor(zdnn_tensor_desc *pre_tfrmd_desc,
|
|
||||||
zdnn_tensor_desc *tfrmd_desc, zdnn_ztensor *output);
|
|
||||||
|
|
||||||
void zdnn_init_quantized_ztensor(zdnn_tensor_desc *pre_tfrmd_desc,
|
|
||||||
zdnn_tensor_desc *tfrmd_desc, float scale,
|
|
||||||
float offset, zdnn_ztensor *output);
|
|
||||||
|
|
||||||
zdnn_status zdnn_init_ztensor_with_malloc(zdnn_tensor_desc *pre_tfrmd_desc,
|
|
||||||
zdnn_tensor_desc *tfrmd_desc,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
|
|
||||||
zdnn_status zdnn_init_quantized_ztensor_with_malloc(
|
|
||||||
zdnn_tensor_desc *pre_tfrmd_desc, zdnn_tensor_desc *tfrmd_desc, float scale,
|
|
||||||
float offset, zdnn_ztensor *output);
|
|
||||||
|
|
||||||
bool zdnn_is_quantized_ztensor(zdnn_ztensor *ztensor);
|
|
||||||
|
|
||||||
void zdnn_reset_ztensor(zdnn_ztensor *ztensor);
|
|
||||||
|
|
||||||
uint64_t zdnn_getsize_ztensor(const zdnn_tensor_desc *tfrmd_desc);
|
|
||||||
|
|
||||||
zdnn_status zdnn_getrange_ztensor(const zdnn_ztensor *ztensor, float *min,
|
|
||||||
float *max);
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// External Query Functions
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
bool zdnn_is_nnpa_installed();
|
|
||||||
bool zdnn_is_nnpa_function_installed(int count, ...);
|
|
||||||
bool zdnn_is_nnpa_parmblk_fmt_installed(int count, ...);
|
|
||||||
bool zdnn_is_nnpa_datatype_installed(uint16_t types_bitmask);
|
|
||||||
bool zdnn_is_nnpa_layout_fmt_installed(uint32_t layout_bitmask);
|
|
||||||
bool zdnn_is_nnpa_conversion_installed(nnpa_data_type type,
|
|
||||||
uint16_t format_bitmask);
|
|
||||||
|
|
||||||
uint32_t zdnn_get_nnpa_max_dim_idx_size();
|
|
||||||
uint32_t zdnn_get_max_for_dim(uint8_t dimension);
|
|
||||||
uint64_t zdnn_get_nnpa_max_tensor_size();
|
|
||||||
|
|
||||||
zdnn_status zdnn_refresh_nnpa_query_result();
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// Versioning Functions
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
bool zdnn_is_version_runnable(uint32_t ver_num);
|
|
||||||
uint32_t zdnn_get_max_runnable_version();
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// External Elementwise Operations
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
zdnn_status zdnn_add(const zdnn_ztensor *input_a, const zdnn_ztensor *input_b,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_sub(const zdnn_ztensor *input_a, const zdnn_ztensor *input_b,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_mul(const zdnn_ztensor *input_a, const zdnn_ztensor *input_b,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_div(const zdnn_ztensor *input_a, const zdnn_ztensor *input_b,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_min(const zdnn_ztensor *input_a, const zdnn_ztensor *input_b,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_max(const zdnn_ztensor *input_a, const zdnn_ztensor *input_b,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
|
|
||||||
zdnn_status zdnn_log(const zdnn_ztensor *input, zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_exp(const zdnn_ztensor *input, zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_sqrt(const zdnn_ztensor *input, zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_invsqrt(const zdnn_ztensor *input, float epsilon,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// External Activation Operations
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
zdnn_status zdnn_relu(const zdnn_ztensor *input, const void *clipping_value,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_leaky_relu(const zdnn_ztensor *input,
|
|
||||||
const void *clipping_value, float adjustment_factor,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_tanh(const zdnn_ztensor *input, zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_sigmoid(const zdnn_ztensor *input, zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_softmax(const zdnn_ztensor *input, void *save_area,
|
|
||||||
zdnn_softmax_act act_func, zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_softmax_mask(const zdnn_ztensor *input, void *save_area,
|
|
||||||
zdnn_softmax_act act_func, uint32_t softmax_mask,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_gelu(const zdnn_ztensor *input, zdnn_ztensor *output);
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// Recurrent Neural Network (RNN) Operations
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
typedef enum lstm_gru_direction { FWD, BWD, BIDIR } lstm_gru_direction;
|
|
||||||
|
|
||||||
zdnn_status zdnn_lstm(const zdnn_ztensor *input, const zdnn_ztensor *h0,
|
|
||||||
const zdnn_ztensor *c0, const zdnn_ztensor *weights,
|
|
||||||
const zdnn_ztensor *biases,
|
|
||||||
const zdnn_ztensor *hidden_weights,
|
|
||||||
const zdnn_ztensor *hidden_biases,
|
|
||||||
lstm_gru_direction direction, void *work_area,
|
|
||||||
zdnn_ztensor *hn_output, zdnn_ztensor *cf_output);
|
|
||||||
zdnn_status zdnn_gru(const zdnn_ztensor *input, const zdnn_ztensor *h0,
|
|
||||||
const zdnn_ztensor *weights, const zdnn_ztensor *biases,
|
|
||||||
const zdnn_ztensor *hidden_weights,
|
|
||||||
const zdnn_ztensor *hidden_biases,
|
|
||||||
lstm_gru_direction direction, void *work_area,
|
|
||||||
zdnn_ztensor *hn_output);
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// Matrix Multiplication Operations
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
zdnn_status zdnn_matmul_op(const zdnn_ztensor *input_a,
|
|
||||||
const zdnn_ztensor *input_b,
|
|
||||||
const zdnn_ztensor *input_c, zdnn_matmul_ops op_type,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_matmul_bcast_op(const zdnn_ztensor *input_a,
|
|
||||||
const zdnn_ztensor *input_b,
|
|
||||||
const zdnn_ztensor *input_c,
|
|
||||||
zdnn_matmul_bcast_ops op_type,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_matmul_transpose_op(const zdnn_ztensor *input_a,
|
|
||||||
const zdnn_ztensor *input_b,
|
|
||||||
const zdnn_ztensor *input_c,
|
|
||||||
bool transpose_a, bool transpose_b,
|
|
||||||
zdnn_matmul_ops op_type,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_quantized_matmul_op(
|
|
||||||
const zdnn_ztensor *input_a, const zdnn_ztensor *input_b,
|
|
||||||
const zdnn_ztensor *input_c, zdnn_matmul_ops op_type, const int8_t clip_min,
|
|
||||||
const int8_t clip_max, const bool disable_clipping, const bool dequantize,
|
|
||||||
const bool pre_computed, void *work_area, zdnn_ztensor *output);
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// External Norm Operations
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
zdnn_status zdnn_batchnorm(const zdnn_ztensor *input_a,
|
|
||||||
const zdnn_ztensor *input_b,
|
|
||||||
const zdnn_ztensor *input_c, zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_norm(const zdnn_ztensor *input_a, const zdnn_ztensor *input_b,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_moments(const zdnn_ztensor *input,
|
|
||||||
zdnn_moments_bessel bessel_correction_type,
|
|
||||||
zdnn_ztensor *output_a, zdnn_ztensor *output_b);
|
|
||||||
zdnn_status zdnn_layernorm(const zdnn_ztensor *input_a,
|
|
||||||
const zdnn_ztensor *input_b,
|
|
||||||
const zdnn_ztensor *input_c, const float beta_value,
|
|
||||||
const float gamma_value, const float epsilon_value,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
zdnn_status zdnn_meanreduce2d(const zdnn_ztensor *input, zdnn_ztensor *output);
|
|
||||||
|
|
||||||
zdnn_status zdnn_reduce(const zdnn_ztensor *input, void *save_area,
|
|
||||||
zdnn_reduce_ops op_type, zdnn_ztensor *output);
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// External Pool Operations
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
zdnn_status zdnn_avgpool2d(const zdnn_ztensor *input,
|
|
||||||
zdnn_pool_padding padding_type,
|
|
||||||
uint32_t kernel_height, uint32_t kernel_width,
|
|
||||||
uint32_t stride_height, uint32_t stride_width,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
|
|
||||||
zdnn_status zdnn_maxpool2d(const zdnn_ztensor *input,
|
|
||||||
zdnn_pool_padding padding_type,
|
|
||||||
uint32_t kernel_height, uint32_t kernel_width,
|
|
||||||
uint32_t stride_height, uint32_t stride_width,
|
|
||||||
zdnn_ztensor *output);
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// External Convolution Operations
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
zdnn_status zdnn_conv2d(const zdnn_ztensor *input, const zdnn_ztensor *kernel,
|
|
||||||
const zdnn_ztensor *bias,
|
|
||||||
zdnn_pool_padding padding_type, uint32_t stride_height,
|
|
||||||
uint32_t stride_width, zdnn_conv2d_act act_func,
|
|
||||||
const void *clipping_value, zdnn_ztensor *output);
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// External Tensor Transform Operations
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
zdnn_status zdnn_transform_ztensor(zdnn_ztensor *ztensor, ...);
|
|
||||||
|
|
||||||
zdnn_status zdnn_transform_ztensor_with_saturation(zdnn_ztensor *ztensor, ...);
|
|
||||||
|
|
||||||
zdnn_status zdnn_transform_quantized_ztensor(zdnn_ztensor *ztensor,
|
|
||||||
bool saturation_control,
|
|
||||||
int8_t clip_min, int8_t clip_max,
|
|
||||||
const void *data);
|
|
||||||
|
|
||||||
zdnn_status zdnn_transform_origtensor(const zdnn_ztensor *ztensor,
|
|
||||||
void *out_buf);
|
|
||||||
|
|
||||||
zdnn_status zdnn_reshape_ztensor(const zdnn_ztensor *src, zdnn_ztensor *dest);
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// External Version Related Functions
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
char *zdnn_get_library_version_str();
|
|
||||||
uint32_t zdnn_get_library_version();
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// zDNN Status Related Functions
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
const char *zdnn_get_status_message(zdnn_status status);
|
|
||||||
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
// zDNN Data Type Limit Functions
|
|
||||||
// -----------------------------------------------------------------------------
|
|
||||||
|
|
||||||
zdnn_status zdnn_get_max_limit(zdnn_data_types transformed_type,
|
|
||||||
zdnn_data_types pre_transformed_type,
|
|
||||||
void *limit);
|
|
||||||
zdnn_status zdnn_get_min_limit(zdnn_data_types transformed_type,
|
|
||||||
zdnn_data_types pre_transformed_type,
|
|
||||||
void *limit);
|
|
||||||
#ifdef __cplusplus
|
|
||||||
}
|
|
||||||
#endif /* __cplusplus */
|
|
||||||
|
|
||||||
#endif /* ZDNN_ZDNN_H_ */
|
|
||||||
Reference in New Issue
Block a user