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Merge pull request #1112 from InfiniTensor/issue/1031_T1-1-50
【比赛2025秋】T1-1-50
2 parents 9db1b6c + f9e6f1f commit 6e88052

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‎include/infinicore/ops/logcumsumexp.hpp‎

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#pragma once
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#include "../device.hpp"
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#include "common/op.hpp"
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namespace infinicore::op {
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class LogCumSumExp {
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public:
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using schema = void (*)(Tensor, Tensor, int, bool, bool);
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static void execute(Tensor y, Tensor x, int axis, bool exclusive, bool reverse);
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static common::OpDispatcher<schema> &dispatcher();
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};
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Tensor logcumsumexp(Tensor x, int axis, bool exclusive = false, bool reverse = false);
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void logcumsumexp_(Tensor y, Tensor x, int axis, bool exclusive = false, bool reverse = false);
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} // namespace infinicore::op

‎include/infinicore/ops/logical_and.hpp‎

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#pragma once
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#include "../device.hpp"
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#include "common/op.hpp"
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namespace infinicore::op {
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class LogicalAnd {
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public:
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// LogicalAnd 是二元操作，schema 通常定义为 (Output, Input1, Input2)
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using schema = void (*)(Tensor, Tensor, Tensor);
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static void execute(Tensor output, Tensor input1, Tensor input2);
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static common::OpDispatcher<schema> &dispatcher();
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};
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Tensor logical_and(Tensor input1, Tensor input2);
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void logical_and_(Tensor output, Tensor input1, Tensor input2);
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} // namespace infinicore::op

‎include/infinicore/ops/logical_not.hpp‎

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#pragma once
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#include "../device.hpp"
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#include "common/op.hpp"
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namespace infinicore::op {
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class LogicalNot {
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public:
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// LogicalNot 是一元操作，schema 定义为 (Output, Input)
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using schema = void (*)(Tensor, Tensor);
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static void execute(Tensor output, Tensor input);
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static common::OpDispatcher<schema> &dispatcher();
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};
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// 构造新 Tensor 返回结果
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Tensor logical_not(Tensor input);
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// 将结果写入指定的 output Tensor
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void logical_not_(Tensor output, Tensor input);
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} // namespace infinicore::op

‎include/infinicore/ops/unfold.hpp‎

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#pragma once
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#include "../device.hpp"
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#include "common/op.hpp"
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#include <vector>
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namespace infinicore::op {
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class Unfold {
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public:
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// schema: output, input, kernel_sizes, dilations, paddings, strides
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using schema = void (*)(Tensor, Tensor, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &, const std::vector<int64_t> &);
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static void execute(Tensor output, Tensor input,
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const std::vector<int64_t> &kernel_sizes,
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const std::vector<int64_t> &dilations,
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const std::vector<int64_t> &paddings,
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const std::vector<int64_t> &strides);
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static common::OpDispatcher<schema> &dispatcher();
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};
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// Functional API
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Tensor unfold(Tensor input,
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std::vector<int64_t> kernel_sizes,
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std::vector<int64_t> dilations,
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std::vector<int64_t> paddings,
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std::vector<int64_t> strides);
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void unfold_(Tensor output, Tensor input,
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std::vector<int64_t> kernel_sizes,
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std::vector<int64_t> dilations,
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std::vector<int64_t> paddings,
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std::vector<int64_t> strides);
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} // namespace infinicore::op

‎include/infinicore/ops/vander.hpp‎

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#pragma once
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#include "../device.hpp"
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#include "common/op.hpp"
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namespace infinicore::op {
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class Vander {
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public:
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// schema: output, input, N, increasing
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using schema = void (*)(Tensor, Tensor, int64_t, bool);
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static void execute(Tensor output, Tensor input, int64_t N, bool increasing);
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static common::OpDispatcher<schema> &dispatcher();
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};
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// N defaults to 0 (implying N = input.size(0), i.e., a square matrix)
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Tensor vander(Tensor input, int64_t N = 0, bool increasing = false);
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void vander_(Tensor output, Tensor input, int64_t N, bool increasing);
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} // namespace infinicore::op

‎include/infiniop.h‎

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#include "infiniop/ops/log_softmax.h"
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#include "infiniop/ops/logaddexp.h"
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#include "infiniop/ops/logaddexp2.h"
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#include "infiniop/ops/logcumsumexp.h"
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#include "infiniop/ops/lp_norm.h"
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#include "infiniop/ops/masked_select.h"
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#include "infiniop/ops/mul.h"
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#include "infiniop/ops/topksoftmax.h"
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#include "infiniop/ops/triplet_margin_loss.h"
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#include "infiniop/ops/triplet_margin_with_distance_loss.h"
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#include "infiniop/ops/unfold.h"
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#include "infiniop/ops/upsample_bilinear.h"
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#include "infiniop/ops/upsample_nearest.h"
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#include "infiniop/ops/vander.h"
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#include "infiniop/ops/var.h"
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#include "infiniop/ops/var_mean.h"
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#include "infiniop/ops/zeros.h"

‎include/infiniop/ops/logcumsumexp.h‎

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#ifndef __INFINIOP_LOGCUMSUMEXP_API_H__
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#define __INFINIOP_LOGCUMSUMEXP_API_H__
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#include "../operator_descriptor.h"
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typedef struct InfiniopDescriptor *infiniopLogCumSumExpDescriptor_t;
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__INFINI_C __export infiniStatus_t infiniopCreateLogCumSumExpDescriptor(infiniopHandle_t handle,
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infiniopLogCumSumExpDescriptor_t *desc_ptr,
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infiniopTensorDescriptor_t y,
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infiniopTensorDescriptor_t x,
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int axis,
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int exclusive,
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int reverse);
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/* 获取执行 LogCumSumExp 所需的临时空间大小 */
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__INFINI_C __export infiniStatus_t infiniopGetLogCumSumExpWorkspaceSize(infiniopLogCumSumExpDescriptor_t desc,
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size_t *size);
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__INFINI_C __export infiniStatus_t infiniopLogCumSumExp(infiniopLogCumSumExpDescriptor_t desc,
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void *workspace,
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size_t workspace_size,
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void *y,
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const void *x,
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void *stream);
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/* 销毁描述符 */
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__INFINI_C __export infiniStatus_t infiniopDestroyLogCumSumExpDescriptor(infiniopLogCumSumExpDescriptor_t desc);
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#endif

‎include/infiniop/ops/unfold.h‎

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#ifndef __INFINIOP_UNFOLD_API_H__
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#define __INFINIOP_UNFOLD_API_H__
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#include "../operator_descriptor.h"
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typedef struct InfiniopDescriptor *infiniopUnfoldDescriptor_t;
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__INFINI_C __export infiniStatus_t infiniopCreateUnfoldDescriptor(infiniopHandle_t handle,
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infiniopUnfoldDescriptor_t *desc_ptr,
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infiniopTensorDescriptor_t output,
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infiniopTensorDescriptor_t input,
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const int *kernel_sizes,
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const int *strides,
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const int *paddings,
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const int *dilations);
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// 获取 Unfold 工作区大小
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__INFINI_C __export infiniStatus_t infiniopGetUnfoldWorkspaceSize(infiniopUnfoldDescriptor_t desc, size_t *size);
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__INFINI_C __export infiniStatus_t infiniopUnfold(infiniopUnfoldDescriptor_t desc,
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void *workspace,
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size_t workspace_size,
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void *output,
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const void *input,
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void *stream);
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__INFINI_C __export infiniStatus_t infiniopDestroyUnfoldDescriptor(infiniopUnfoldDescriptor_t desc);
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#endif // __INFINIOP_UNFOLD_API_H__

‎include/infiniop/ops/vander.h‎

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#ifndef __INFINIOP_VANDER_API_H__
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#define __INFINIOP_VANDER_API_H__
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#include "../operator_descriptor.h"
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typedef struct InfiniopDescriptor *infiniopVanderDescriptor_t;
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__INFINI_C __export infiniStatus_t infiniopCreateVanderDescriptor(infiniopHandle_t handle,
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infiniopVanderDescriptor_t *desc_ptr,
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infiniopTensorDescriptor_t output,
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infiniopTensorDescriptor_t input,
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int N,
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int increasing);
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__INFINI_C __export infiniStatus_t infiniopGetVanderWorkspaceSize(infiniopVanderDescriptor_t desc, size_t *size);
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__INFINI_C __export infiniStatus_t infiniopVander(infiniopVanderDescriptor_t desc,
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void *workspace,
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size_t workspace_size,
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void *output,
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const void *input,
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void *stream);
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__INFINI_C __export infiniStatus_t infiniopDestroyVanderDescriptor(infiniopVanderDescriptor_t desc);
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#endif // __INFINIOP_VANDER_API_H__

‎python/infinicore/__init__.py‎

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from infinicore.ops.lerp import lerp
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from infinicore.ops.logaddexp import logaddexp
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from infinicore.ops.logaddexp2 import logaddexp2
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from infinicore.ops.logcumsumexp import logcumsumexp
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from infinicore.ops.logical_and import logical_and
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from infinicore.ops.logical_not import logical_not
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from infinicore.ops.masked_select import masked_select
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from infinicore.ops.matmul import matmul
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from infinicore.ops.mha_kvcache import mha_kvcache
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from infinicore.ops.tan import tan
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from infinicore.ops.topk import topk
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from infinicore.ops.unsqueeze import unsqueeze
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from infinicore.ops.vander import vander
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from infinicore.ops.var import var
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from infinicore.ops.var_mean import var_mean
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from infinicore.tensor import (
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"float_power",
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"flipud",
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"scatter",
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"logcumsumexp",
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"logical_not",
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"logical_and",
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"vander",
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"paged_caching",
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"paged_attention",
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"paged_attention_prefill",

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