#pragma once

#include <torch/csrc/jit/tensorexpr/operators/misc.h>
#include <torch/csrc/jit/tensorexpr/tensor.h>

namespace torch::jit::tensorexpr {

// An API to compute 2D depthwise convolutions with bias.
TORCH_API Tensor conv2d_depthwise(
    BufHandle input,
    BufHandle weight,
    BufHandle bias,
    int stride,
    int pad,
    int groups);

// An API to compute 2D depthwise convolutions without bias.
TORCH_API Tensor conv2d_depthwise(
    BufHandle input,
    BufHandle weight,
    int stride,
    int pad,
    int groups);

TORCH_API Tensor conv2d_depthwise(
    BufHandle input,
    BufHandle weight,
    BufHandle bias,
    ExprHandle N,
    ExprHandle C,
    ExprHandle H,
    ExprHandle W,
    ExprHandle K,
    ExprHandle CperG,
    ExprHandle R,
    ExprHandle S,
    ExprHandle stride,
    ExprHandle pad,
    ExprHandle groups);

TORCH_API Tensor conv2d_depthwise(
    BufHandle input,
    BufHandle weight,
    ExprHandle N,
    ExprHandle C,
    ExprHandle H,
    ExprHandle W,
    ExprHandle K,
    ExprHandle CperG,
    ExprHandle R,
    ExprHandle S,
    ExprHandle stride,
    ExprHandle pad,
    ExprHandle groups);

bool conv2dIsSupported(
    const TensorInfo& input,
    const TensorInfo& weight,
    const TensorInfo& bias,
    const std::vector<int64_t>& stride,
    const std::vector<int64_t>& pad,
    const std::vector<int64_t>& dilation,
    int64_t groups);
bool mkldnnPrepackedConvIsSupported(
    const TensorInfo& input,
    const TensorInfo& weight,
    const std::vector<int64_t>& stride,
    const std::vector<int64_t>& pad,
    const std::vector<int64_t>& dilation,
    int64_t groups);
Tensor computeConv2d(
    const std::vector<ArgValue>& inputs,
    const std::vector<ExprHandle>& outputShape,
    const std::vector<ExprHandle>& outputStrides,
    const std::optional<ScalarType>& outputType,
    at::Device device);
Tensor computeConv1d(
    const std::vector<ArgValue>& inputs,
    const std::vector<ExprHandle>& outputShape,
    const std::vector<ExprHandle>& outputStrides,
    const std::optional<ScalarType>& outputType,
    at::Device device);
Tensor computePrepackedConv2dClampRun(
    const std::vector<ArgValue>& inputs,
    const std::vector<ExprHandle>& outputShape,
    const std::vector<ExprHandle>& outputStrides,
    const std::optional<ScalarType>& outputType,
    at::Device device);
Tensor computePrepackedLinearClampRun(
    const std::vector<ArgValue>& inputs,
    const std::vector<ExprHandle>& outputShape,
    const std::vector<ExprHandle>& outputStrides,
    const std::optional<ScalarType>& outputType,
    at::Device device);
Tensor computeMkldnnPrepackedConvRun(
    const std::vector<ArgValue>& inputs,
    const std::vector<ExprHandle>& outputShape,
    const std::vector<ExprHandle>& outputStrides,
    const std::optional<ScalarType>& outputType,
    at::Device device);
} // namespace torch::jit::tensorexpr
