diff options
Diffstat (limited to 'tensorflow/contrib/tensorrt/convert/convert_nodes.cc')
| -rw-r--r-- | tensorflow/contrib/tensorrt/convert/convert_nodes.cc | 14 |
1 files changed, 7 insertions, 7 deletions
diff --git a/tensorflow/contrib/tensorrt/convert/convert_nodes.cc b/tensorflow/contrib/tensorrt/convert/convert_nodes.cc index 4003ba056d..9ee717dd7f 100644 --- a/tensorflow/contrib/tensorrt/convert/convert_nodes.cc +++ b/tensorflow/contrib/tensorrt/convert/convert_nodes.cc @@ -809,9 +809,9 @@ tensorflow::Status BinaryTensorOpTensor( CHECK_EQ_TYPE(tensor_r->getType(), dtype); auto op_pair = ops.find(node_def.op()); if (op_pair == ops.end()) - return tensorflow::errors::Unimplemented( - "binary op: " + node_def.op() + - " not supported at: " + node_def.name()); + return tensorflow::errors::Unimplemented("binary op: " + node_def.op() + + " not supported at: " + + node_def.name()); nvinfer1::IElementWiseLayer* layer = ctx.network()->addElementWise( *const_cast<nvinfer1::ITensor*>(tensor_l), @@ -1471,13 +1471,13 @@ tensorflow::Status ConvertSubGraphToTensorRTNodeDef( << std::to_string(op_info_vec.size()); // TODO(ben,jie): update TRT input format/dimension - nvinfer1::DimsCHW input_dim_pseudo_chw; - for (int i = 0; i < 3; i++) input_dim_pseudo_chw.d[i] = 1; + nvinfer1::DimsCHW input_dim_psuedo_chw; + for (int i = 0; i < 3; i++) input_dim_psuedo_chw.d[i] = 1; for (int i = 1; i < op_info.shape().dim_size(); i++) { VLOG(2) << "dimension: " << i << " , size: " << op_info.shape().dim(i).size(); - input_dim_pseudo_chw.d[i - 1] = op_info.shape().dim(i).size(); + input_dim_psuedo_chw.d[i - 1] = op_info.shape().dim(i).size(); } // TODO(ben,jie): proper way to restore input tensor name? @@ -1486,7 +1486,7 @@ tensorflow::Status ConvertSubGraphToTensorRTNodeDef( input_tensor_name = node_name + ":" + std::to_string(output_idx); nvinfer1::ITensor* input_tensor = converter.network()->addInput( - input_tensor_name.c_str(), dtype, input_dim_pseudo_chw); + input_tensor_name.c_str(), dtype, input_dim_psuedo_chw); if (!input_tensor) return tensorflow::errors::InvalidArgument( |