module `onnxrt.ops_cpu._op_onnx_numpy`#

Short summary#

module mlprodict.onnxrt.ops_cpu._op_onnx_numpy

C++ helpers of ONNX operators.

source on GitHub

Documentation#

C++ helpers of ONNX operators.

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.array_feature_extractor_double(arg0: numpy.ndarray[numpy.float64], arg1: numpy.ndarray[numpy.int64]) → numpy.ndarray[numpy.float64]#: C++ implementation of operator ArrayFeatureExtractor for float64. The function only works with contiguous arrays.

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.array_feature_extractor_float(arg0: numpy.ndarray[numpy.float32], arg1: numpy.ndarray[numpy.int64]) → numpy.ndarray[numpy.float32]#: C++ implementation of operator ArrayFeatureExtractor for float32. The function only works with contiguous arrays.

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.array_feature_extractor_int64(arg0: numpy.ndarray[numpy.int64], arg1: numpy.ndarray[numpy.int64]) → numpy.ndarray[numpy.int64]#: C++ implementation of operator ArrayFeatureExtractor for int64. The function only works with contiguous arrays.

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.topk_element_fetch_double(arg0: numpy.ndarray[numpy.float64], arg1: numpy.ndarray[numpy.int64]) → numpy.ndarray[numpy.float64]#: Fetches the top k element knowing their indices on each row (= last dimension for a multi dimension array).

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.topk_element_fetch_float(arg0: numpy.ndarray[numpy.float32], arg1: numpy.ndarray[numpy.int64]) → numpy.ndarray[numpy.float32]#: Fetches the top k element knowing their indices on each row (= last dimension for a multi dimension array).

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.topk_element_fetch_int64(arg0: numpy.ndarray[numpy.int64], arg1: numpy.ndarray[numpy.int64]) → numpy.ndarray[numpy.int64]#: Fetches the top k element knowing their indices on each row (= last dimension for a multi dimension array).

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.topk_element_max_double(arg0: numpy.ndarray[numpy.float64], arg1: int, arg2: bool, arg3: int) → numpy.ndarray[numpy.int64]#: C++ implementation of operator TopK for float32. The function only works with contiguous arrays. The function is parallelized for more than th_para rows. It only does it on the last axis.

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.topk_element_max_float(arg0: numpy.ndarray[numpy.float32], arg1: int, arg2: bool, arg3: int) → numpy.ndarray[numpy.int64]#: C++ implementation of operator TopK for float32. The function only works with contiguous arrays. The function is parallelized for more than th_para rows. It only does it on the last axis.

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.topk_element_max_int64(arg0: numpy.ndarray[numpy.int64], arg1: int, arg2: bool, arg3: int) → numpy.ndarray[numpy.int64]#: C++ implementation of operator TopK for float32. The function only works with contiguous arrays. The function is parallelized for more than th_para rows. It only does it on the last axis.

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.topk_element_min_double(arg0: numpy.ndarray[numpy.float64], arg1: int, arg2: bool, arg3: int) → numpy.ndarray[numpy.int64]#: C++ implementation of operator TopK for float32. The function only works with contiguous arrays. The function is parallelized for more than th_para rows. It only does it on the last axis.

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.topk_element_min_float(arg0: numpy.ndarray[numpy.float32], arg1: int, arg2: bool, arg3: int) → numpy.ndarray[numpy.int64]#: C++ implementation of operator TopK for float32. The function only works with contiguous arrays. The function is parallelized for more than th_para rows. It only does it on the last axis.

mlprodict.onnxrt.ops_cpu._op_onnx_numpy.topk_element_min_int64(arg0: numpy.ndarray[numpy.int64], arg1: int, arg2: bool, arg3: int) → numpy.ndarray[numpy.int64]#: C++ implementation of operator TopK for float32. The function only works with contiguous arrays. The function is parallelized for more than th_para rows. It only does it on the last axis.