#include "mlir/Dialect/Tensor/IR/Tensor.h"

#include "src/Accelerators/PIM/Common/IR/TensorSliceUtils.hpp"

using namespace mlir;

namespace onnx_mlir {

Value extractAxisSlice(
  PatternRewriter& rewriter, Location loc, Value source, int64_t axis, int64_t offset, int64_t size) {
  auto sourceType = cast<RankedTensorType>(source.getType());
  SmallVector<int64_t> resultShape(sourceType.getShape());
  resultShape[axis] = size;
  auto resultType = RankedTensorType::get(resultShape, sourceType.getElementType(), sourceType.getEncoding());

  SmallVector<OpFoldResult> offsets = getZeroOffsets(rewriter, sourceType.getRank());
  SmallVector<OpFoldResult> sizes = getStaticSizes(rewriter, sourceType.getShape());
  offsets[axis] = rewriter.getIndexAttr(offset);
  sizes[axis] = rewriter.getIndexAttr(size);
  return tensor::ExtractSliceOp::create(
           rewriter, loc, resultType, source, offsets, sizes, getUnitStrides(rewriter, sourceType.getRank()))
    .getResult();
}

Value extractStaticSliceOrIdentity(RewriterBase& rewriter,
                                   Location loc,
                                   Value source,
                                   RankedTensorType resultType,
                                   ArrayRef<OpFoldResult> offsets,
                                   ArrayRef<OpFoldResult> sizes,
                                   ArrayRef<OpFoldResult> strides) {
  auto sourceType = cast<RankedTensorType>(source.getType());
  size_t rank = static_cast<size_t>(sourceType.getRank());

  bool isIdentitySlice =
    sourceType == resultType && sourceType.hasStaticShape() && offsets.size() == rank && sizes.size() == rank
    && strides.size() == rank;
  if (isIdentitySlice) {
    ArrayRef<int64_t> sourceShape = sourceType.getShape();
    for (auto [dim, offset, size, stride] : llvm::zip_equal(sourceShape, offsets, sizes, strides)) {
      std::optional<int64_t> staticOffset = mlir::getConstantIntValue(offset);
      std::optional<int64_t> staticSize = mlir::getConstantIntValue(size);
      std::optional<int64_t> staticStride = mlir::getConstantIntValue(stride);
      if (!staticOffset || !staticSize || !staticStride || *staticOffset != 0 || *staticSize != dim
          || *staticStride != 1) {
        isIdentitySlice = false;
        break;
      }
    }
  }

  if (isIdentitySlice)
    return source;

  return tensor::ExtractSliceOp::create(rewriter, loc, resultType, source, offsets, sizes, strides).getResult();
}

Value insertStaticSlice(
  PatternRewriter& rewriter, Location loc, Value source, Value dest, ArrayRef<OpFoldResult> offsets) {
  auto sourceType = cast<RankedTensorType>(source.getType());
  return tensor::InsertSliceOp::create(rewriter,
                                       loc,
                                       source,
                                       dest,
                                       offsets,
                                       getStaticSizes(rewriter, sourceType.getShape()),
                                       getUnitStrides(rewriter, sourceType.getRank()))
    .getResult();
}

} // namespace onnx_mlir