message: feat(//core/conversion/converters/impl): added support for trilinear3d op
diff: @@ -163,13 +163,45 @@ auto interpolate_registrations TRTORCH_UNUSED = RegisterNodeConversionPatterns()
  auto layer_output = ctx->AssociateValueAndTensor(n->outputs()[0], resize_layer->getOutput(0));
  LOG_DEBUG("Output tensor shape: " << layer_output->getDimensions());
  } else {
  - TRTORCH_THROW_ERROR("Unable to convert node: " << util::node_info(n) << "\nScale factor parameter for upsample_linear1d not supported yet.");
  + TRTORCH_THROW_ERROR("Unable to convert node: " << util::node_info(n) << "\nScale factor parameter for upsample_bilinear2d not supported yet.");
  }
  return true;
  }
  - });
  + }).pattern({
  + "aten::upsample_trilinear3d(Tensor self, int[3] output_size, bool align_corners, float? scales_d=None, float? scales_h=None, float? scales_w=None) -> (Tensor)",
  + [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
  + auto in = args[0].ITensor();
  + auto in_shape = util::toVec(in->getDimensions());
  +
  + bool align_corners = args[2].IValue()->to<bool>();
  + // Case 1: user uses output size and not scales_d, scales_h, scales_w
  + if (!args[1].IValue()->isNone() && args[3].IValue()->isNone() && args[4].IValue()->isNone() && args[5].IValue()->isNone()) {
  + auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
  +
  + TRTORCH_ASSERT(out_size.size() == 3, "aten::upsample_trilinear3d input Tensor and output size dimension mismatch");
  +
  + auto out_shape = in_shape;
  + std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
  +
  + auto resize_layer = ctx->net->addResize(*in);
  + TRTORCH_CHECK(resize_layer, "Unable to create interpolation (resizing) layer from node" << *n);
  +
  + resize_layer->setOutputDimensions(util::toDims(out_shape));
  + resize_layer->setResizeMode(nvinfer1::ResizeMode::kLINEAR);
  + resize_layer->setAlignCorners(align_corners);
  + resize_layer->setName(util::node_info(n).c_str());
  +
  + auto layer_output = ctx->AssociateValueAndTensor(n->outputs()[0], resize_layer->getOutput(0));
  + LOG_DEBUG("Output tensor shape: " << layer_output->getDimensions());
  + } else {
  + TRTORCH_THROW_ERROR("Unable to convert node: " << util::node_info(n) << "\nScale factor parameter for upsample_trilinear3d not supported yet.");
  + }
  +
  + return true;
  + }
  + });
  } // namespace
  } // namespace impl
  