Search before asking I have searched the YOLOv8 issues and found no similar bug report. YOLOv8 Component Export Bug This is what happens when I export as the onnx format: Now this is what happens when I export as the engine format: The s...
"dropna must be unspecified with future_stack=True as " "the new implementation does not introduce rows of NA " "values. This argument will be removed in a future " "version of cudf." ) else: if dropna is not no_default or self._data.nlevels > 1: warnings.warn( "The previous imple...
"month_day_nano_interval must have exactly 3 elements, had ", json_obj.Size()); } RETURN_NOT_OK(ConvertNumber<Int32Type>(json_obj[0], *this->type_, &value.months)); RETURN_NOT_OK(ConvertNumber<Int32Type>(json_obj[1], *this->type_, &value.days)); RETURN_NOT_OK( ConvertNumber<...
For example if the total number of chunks, or the size of the last chunk is not known at the time the header is created.The following constraints exist on the header entries:last-chunk must be less than or equal to chunk-size. nchunks + max_app_chunks must be less than or equal to...
HasArgument("dtype")) { Expand Down Expand Up @@ -53,13 +55,16 @@ class GivenTensorByteStringToUInt8FillOp final : public FillerOp<Context> { << " given size: " << source_values.size(); auto str = source_values[0]; ReinitializeTensor(&values_, {static_cast<int64_t>(str.size...
add_argument( "--outputs", nargs="+", type=str, help="Output of the model, OUTPUT_NAME:DTYPE, e.g. y:fp32 or y1:fp32 y2:fp32. \ If dtype is not specified, the dtype of the output will be the same as the original model \ if it has dtype, otherwise it will be fp32, ...
torch::Tensor indiceNum, int64_t numActOut, int64_t _inverse, int64_t _subM) { bool subM = _subM != 0; bool inverse = _inverse != 0; auto device = features.device().type(); Expand All @@ -36,13 +38,16 @@ torch::Tensor fusedIndiceConvBatchNorm(torch::Tensor features, torch...