message: Remove is_tensor() since inputs are required to be tensors
diff: @@ -1906,10 +1906,8 @@ tensorflow::Status ConvertExpandDims(OpConverterParams* params) {
  TRT_TensorOrWeights input_tensor = inputs.at(0);
  const nvinfer1::Dims dims = input_tensor.GetTrtDims();
  std::vector<int> input_dims(dims.d, dims.d + dims.nbDims);
  - // Add batch dim back for tensors.
  - if (input_tensor.is_tensor()) {
  + // Add batch dim back.
  input_dims.insert(input_dims.begin(), -1);
  - }
  const int input_rank = input_dims.size();
  // Get axis to expand on.
  TRT_ShapedWeights weights = inputs.at(1).weights();
  @@ -1929,7 +1927,7 @@ tensorflow::Status ConvertExpandDims(OpConverterParams* params) {
  }
  // Convert negative axis to corresponding positive axis.
  if (axis < 0) axis += input_rank + 1;
  - if (input_tensor.is_tensor() && axis == 0) {
  + if (axis == 0) {
  return tensorflow::errors::Unimplemented(
  "Modifying batch dimension is not supported for ExpandDims, at ",
  node_def.name());
  @@ -1939,9 +1937,8 @@ tensorflow::Status ConvertExpandDims(OpConverterParams* params) {
  // ExpandDims: Insert new dim of size 1.
  input_dims.insert(input_dims.begin() + axis, 1);
  // Reshape tensor.
  - const bool ignore_first_dim = input_tensor.is_tensor();
  nvinfer1::Dims new_dims =
  - TensorShapeArrayToTrtDims(input_dims, ignore_first_dim);
  + TensorShapeArrayToTrtDims(input_dims, /*ignore_first_dim=*/true);
  const nvinfer1::ITensor* output_tensor = nullptr;
  TF_RETURN_IF_ERROR(params->converter->PrepareTensorForShape(
  input_tensor, new_dims, &output_tensor));
  @@ -1965,10 +1962,8 @@ tensorflow::Status ConvertSqueeze(OpConverterParams* params) {
  TRT_TensorOrWeights input_tensor = inputs.at(0);
  const nvinfer1::Dims dims = input_tensor.GetTrtDims();
  std::vector<int> input_dims(dims.d, dims.d + dims.nbDims);
  - // Add batch dim back temporarily.
  - if (input_tensor.is_tensor()) {
  + // Add batch dim back.
  input_dims.insert(input_dims.begin(), -1);
  - }
  const int input_rank = input_dims.size();
  // Mark axes to remove by setting them to 0.
  TFAttrs attrs(node_def);
  @@ -1988,7 +1983,7 @@ tensorflow::Status ConvertSqueeze(OpConverterParams* params) {
  // Convert negative axis to corresponding positive axis.
  if (axis < 0) axis += input_rank;
  // Don't squeeze batch dim.
  - if (input_tensor.is_tensor() && axis == 0) {
  + if (axis == 0) {
  return tensorflow::errors::Unimplemented(
  "Cannot squeeze batch dimension, at ", node_def.name());
  }
  @@ -2007,9 +2002,8 @@ tensorflow::Status ConvertSqueeze(OpConverterParams* params) {
  input_dims.erase(std::remove(input_dims.begin(), input_dims.end(), 0),
  input_dims.end());
  // Reshape tensor.
  - const bool ignore_first_dim = input_tensor.is_tensor();
  nvinfer1::Dims new_dims =
  - TensorShapeArrayToTrtDims(input_dims, ignore_first_dim);
  + TensorShapeArrayToTrtDims(input_dims, /*ignore_first_dim=*/true);
  const nvinfer1::ITensor* output_tensor = nullptr;
  TF_RETURN_IF_ERROR(params->converter->PrepareTensorForShape(
  input_tensor, new_dims, &output_tensor));
  