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104 lines
4.1 KiB
C++
104 lines
4.1 KiB
C++
// Copyright (c) Advanced Micro Devices, Inc., or its affiliates.
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// SPDX-License-Identifier: MIT
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#pragma once
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#include <hipdnn_frontend/Types.hpp>
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#include <hipdnn_frontend/attributes/BlockScaleQuantizeAttributes.hpp>
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#include <hipdnn_frontend/detail/DescriptorUnpackHelpers.hpp>
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#include <memory>
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#include <unordered_map>
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namespace hipdnn_frontend::detail
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{
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/// Unpacks a block scale quantize operation from a backend operation descriptor.
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/// Populates the BlockScaleQuantizeAttributes with tensors (using tensorMap for sharing)
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/// and block scale quantize parameters.
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[[nodiscard]] inline Error unpackBlockScaleQuantizeOperation(
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hipdnnBackendDescriptor_t opDesc,
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std::unordered_map<int64_t, std::shared_ptr<graph::TensorAttributes>>& tensorMap,
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graph::BlockScaleQuantizeAttributes& attributes)
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{
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// Unpack X (input) tensor
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std::shared_ptr<graph::TensorAttributes> xTensor;
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HIPDNN_CHECK_ERROR(unpackAndRegisterTensor(opDesc,
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HIPDNN_ATTR_OPERATION_BLOCK_SCALE_QUANTIZE_XDESC,
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tensorMap,
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xTensor,
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"block_scale_quantize X tensor"));
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attributes.set_x(xTensor);
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// Unpack Y (output) tensor
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std::shared_ptr<graph::TensorAttributes> yTensor;
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HIPDNN_CHECK_ERROR(unpackAndRegisterTensor(opDesc,
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HIPDNN_ATTR_OPERATION_BLOCK_SCALE_QUANTIZE_YDESC,
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tensorMap,
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yTensor,
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"block_scale_quantize Y tensor"));
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attributes.set_y(yTensor);
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// Unpack Scale tensor
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std::shared_ptr<graph::TensorAttributes> scaleTensor;
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HIPDNN_CHECK_ERROR(
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unpackAndRegisterTensor(opDesc,
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HIPDNN_ATTR_OPERATION_BLOCK_SCALE_QUANTIZE_SCALE_DESC,
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tensorMap,
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scaleTensor,
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"block_scale_quantize Scale tensor"));
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attributes.set_scale(scaleTensor);
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// Unpack block_size (INT32)
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int32_t blockSize = 0;
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HIPDNN_CHECK_ERROR(
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getDescriptorAttrScalar(opDesc,
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HIPDNN_ATTR_OPERATION_BLOCK_SCALE_QUANTIZE_BLOCK_SIZE,
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HIPDNN_TYPE_INT32,
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blockSize,
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"block_scale_quantize block_size"));
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attributes.set_block_size(blockSize);
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// Unpack optional axis (INT64)
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std::optional<int64_t> axis;
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HIPDNN_CHECK_ERROR(
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getDescriptorAttrOptionalScalar(opDesc,
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HIPDNN_ATTR_OPERATION_BLOCK_SCALE_QUANTIZE_AXIS_EXT,
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HIPDNN_TYPE_INT64,
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axis,
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"block_scale_quantize axis"));
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if(axis.has_value())
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{
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attributes.set_axis(axis.value());
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}
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// Unpack transpose (BOOLEAN)
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bool transpose = false;
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HIPDNN_CHECK_ERROR(
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getDescriptorAttrScalar(opDesc,
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HIPDNN_ATTR_OPERATION_BLOCK_SCALE_QUANTIZE_TRANSPOSE_EXT,
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HIPDNN_TYPE_BOOLEAN,
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transpose,
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"block_scale_quantize transpose"));
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attributes.set_transpose(transpose);
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// Unpack compute data type
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auto [dt, dtErr] = unpackGraphDataType(opDesc,
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HIPDNN_ATTR_OPERATION_BLOCK_SCALE_QUANTIZE_MATH_PREC,
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"block_scale_quantize compute data type");
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if(dtErr.is_bad())
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{
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return dtErr;
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}
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attributes.set_compute_data_type(dt);
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// Unpack operation name
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std::string opName;
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HIPDNN_CHECK_ERROR(
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getDescriptorAttrString(opDesc, HIPDNN_ATTR_OPERATION_NAME_EXT, opName, "operation name"));
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attributes.set_name(opName);
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return {};
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}
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} // namespace hipdnn_frontend::detail
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