#pragma once
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// @generated by aten/src/ATen/gen.py
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#include <c10/core/TensorOptions.h>
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#include <c10/core/Scalar.h>
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#include <c10/core/QScheme.h>
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#include <c10/core/MemoryFormat.h>
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#include <c10/util/ArrayRef.h>
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#include <c10/util/intrusive_ptr.h>
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#include <torch/csrc/WindowsTorchApiMacro.h>
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#include <ATen/Dimname.h>
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#include <ATen/core/EnableNamedTensor.h>
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namespace c10 {
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struct Storage;
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}
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namespace at {
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class Tensor;
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using TensorList = ArrayRef<Tensor>;
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class Context;
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struct Generator;
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struct Quantizer;
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// This is temporary typedef to enable Quantizer in aten native function API
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// we'll remove them when we are actually exposing Quantizer class
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// to frontend
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using ConstQuantizerPtr = const c10::intrusive_ptr<Quantizer>&;
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#ifdef USE_STATIC_DISPATCH
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namespace MkldnnCPUType {
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Tensor add(const Tensor & self, const Tensor & other, Scalar alpha);
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Tensor & add_(Tensor & self, const Tensor & other, Scalar alpha);
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Tensor & add_out(Tensor & out, const Tensor & self, const Tensor & other, Scalar alpha);
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Tensor empty(IntArrayRef size, const TensorOptions & options, c10::optional<MemoryFormat> memory_format);
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Tensor mkldnn_linear(const Tensor & input, const Tensor & weight, const Tensor & bias);
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Tensor mkldnn_max_pool2d(const Tensor & self, IntArrayRef kernel_size, IntArrayRef stride, IntArrayRef padding, IntArrayRef dilation, bool ceil_mode);
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Tensor mul(const Tensor & self, const Tensor & other);
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Tensor & mul_(Tensor & self, const Tensor & other);
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Tensor & mul_out(Tensor & out, const Tensor & self, const Tensor & other);
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std::tuple<Tensor,Tensor,Tensor> native_batch_norm(const Tensor & input, const Tensor & weight, const Tensor & bias, const Tensor & running_mean, const Tensor & running_var, bool training, double momentum, double eps);
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Tensor _mkldnn_reshape(const Tensor & self, IntArrayRef shape);
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Tensor relu(const Tensor & self);
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Tensor & relu_(Tensor & self);
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Tensor sigmoid(const Tensor & self);
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Tensor & sigmoid_(Tensor & self);
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Tensor _softmax(const Tensor & self, int64_t dim, bool half_to_float);
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Tensor _mkldnn_transpose(const Tensor & self, int64_t dim0, int64_t dim1);
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Tensor & _mkldnn_transpose_(Tensor & self, int64_t dim0, int64_t dim1);
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Tensor clone(const Tensor & self);
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Tensor & zero_(Tensor & self);
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Tensor to_dense(const Tensor & self);
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Tensor mkldnn_reorder_conv2d_weight(const Tensor & self, IntArrayRef padding, IntArrayRef stride, IntArrayRef dilation, int64_t groups);
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Tensor view(const Tensor & self, IntArrayRef size);
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Tensor & adaptive_avg_pool2d_out(Tensor & out, const Tensor & self, IntArrayRef output_size);
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Tensor mkldnn_adaptive_avg_pool2d(const Tensor & self, IntArrayRef output_size);
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Tensor & avg_pool2d_out(Tensor & out, const Tensor & self, IntArrayRef kernel_size, IntArrayRef stride, IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional<int64_t> divisor_override);
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Tensor avg_pool2d(const Tensor & self, IntArrayRef kernel_size, IntArrayRef stride, IntArrayRef padding, bool ceil_mode, bool count_include_pad, c10::optional<int64_t> divisor_override);
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}
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#endif
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} // namespace at
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