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Merge pull request #2427 from divyegala/mnmg-decomp
[REVIEW] Moving MNMG decomp to cuml
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| Original file line number | Diff line number | Diff line change |
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| /* | ||
| * Copyright (c) 2020, NVIDIA CORPORATION. | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
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| #pragma once | ||
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| #include <opg/matrix/data.hpp> | ||
| #include <opg/matrix/part_descriptor.hpp> | ||
| #include "pca.hpp" | ||
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| #include <common/cumlHandle.hpp> | ||
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| namespace ML { | ||
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| enum class mg_solver { COV_EIG_DQ, COV_EIG_JACOBI, QR }; | ||
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| typedef paramsTSVDTemplate<mg_solver> paramsTSVDMG; | ||
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| typedef paramsPCATemplate<mg_solver> paramsPCAMG; | ||
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| namespace PCA { | ||
| namespace opg { | ||
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| /** | ||
| * @brief performs MNMG fit operation for the pca | ||
| * @input param handle: the internal cuml handle object | ||
| * @input param rank_sizes: includes all the partition size information for the rank | ||
| * @input param n_parts: number of partitions | ||
| * @input param input: input data | ||
| * @input param components: principal components of the input data | ||
| * @output param explained_var: explained var | ||
| * @output param explained_var_ratio: the explained var ratio | ||
| * @output param singular_vals: singular values of the data | ||
| * @output param mu: mean of every column in input | ||
| * @output param noise_vars: variance of the noise | ||
| * @input param prms: data structure that includes all the parameters from input size to algorithm | ||
| * @input param verbose | ||
| */ | ||
| void fit(cumlHandle &handle, | ||
| std::vector<MLCommon::Matrix::Data<float> *> &input_data, | ||
| MLCommon::Matrix::PartDescriptor &input_desc, float *components, | ||
| float *explained_var, float *explained_var_ratio, float *singular_vals, | ||
| float *mu, float *noise_vars, paramsPCAMG prms, bool verbose = false); | ||
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| void fit(cumlHandle &handle, | ||
| std::vector<MLCommon::Matrix::Data<double> *> &input_data, | ||
| MLCommon::Matrix::PartDescriptor &input_desc, double *components, | ||
| double *explained_var, double *explained_var_ratio, | ||
| double *singular_vals, double *mu, double *noise_vars, | ||
| paramsPCAMG prms, bool verbose = false); | ||
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| /** | ||
| * @brief performs MNMG fit and transform operation for the pca | ||
| * @input param handle: the internal cuml handle object | ||
| * @input param rank_sizes: includes all the partition size information for the rank | ||
| * @input param n_parts: number of partitions | ||
| * @input param input: input data | ||
| * @output param trans_input: transformed input data | ||
| * @output param components: principal components of the input data | ||
| * @output param explained_var: explained var | ||
| * @output param explained_var_ratio: the explained var ratio | ||
| * @output param singular_vals: singular values of the data | ||
| * @output param mu: mean of every column in input | ||
| * @output param noise_vars: variance of the noise | ||
| * @input param prms: data structure that includes all the parameters from input size to algorithm | ||
| * @input param verbose | ||
| */ | ||
| void fit_transform(cumlHandle &handle, | ||
| MLCommon::Matrix::RankSizePair **rank_sizes, size_t n_parts, | ||
| MLCommon::Matrix::floatData_t **input, | ||
| MLCommon::Matrix::floatData_t **trans_input, | ||
| float *components, float *explained_var, | ||
| float *explained_var_ratio, float *singular_vals, float *mu, | ||
| float *noise_vars, paramsPCAMG prms, bool verbose); | ||
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| void fit_transform(cumlHandle &handle, | ||
| MLCommon::Matrix::RankSizePair **rank_sizes, size_t n_parts, | ||
| MLCommon::Matrix::doubleData_t **input, | ||
| MLCommon::Matrix::doubleData_t **trans_input, | ||
| double *components, double *explained_var, | ||
| double *explained_var_ratio, double *singular_vals, | ||
| double *mu, double *noise_vars, paramsPCAMG prms, | ||
| bool verbose); | ||
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| /** | ||
| * @brief performs MNMG transform operation for the pca | ||
| * @input param handle: the internal cuml handle object | ||
| * @input param rank_sizes: includes all the partition size information for the rank | ||
| * @input param n_parts: number of partitions | ||
| * @input param input: input data | ||
| * @input param components: principal components of the input data | ||
| * @output param trans_input: transformed input data | ||
| * @input param singular_vals: singular values of the data | ||
| * @input param mu: mean of every column in input | ||
| * @input param prms: data structure that includes all the parameters from input size to algorithm | ||
| * @input param verbose | ||
| */ | ||
| void transform(cumlHandle &handle, MLCommon::Matrix::RankSizePair **rank_sizes, | ||
| size_t n_parts, MLCommon::Matrix::Data<float> **input, | ||
| float *components, MLCommon::Matrix::Data<float> **trans_input, | ||
| float *singular_vals, float *mu, paramsPCAMG prms, bool verbose); | ||
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| void transform(cumlHandle &handle, MLCommon::Matrix::RankSizePair **rank_sizes, | ||
| size_t n_parts, MLCommon::Matrix::Data<double> **input, | ||
| double *components, MLCommon::Matrix::Data<double> **trans_input, | ||
| double *singular_vals, double *mu, paramsPCAMG prms, | ||
| bool verbose); | ||
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| /** | ||
| * @brief performs MNMG inverse transform operation for the pca | ||
| * @input param handle: the internal cuml handle object | ||
| * @input param rank_sizes: includes all the partition size information for the rank | ||
| * @input param n_parts: number of partitions | ||
| * @input param trans_input: transformed input data | ||
| * @input param components: principal components of the input data | ||
| * @output param input: input data | ||
| * @input param singular_vals: singular values of the data | ||
| * @input param mu: mean of every column in input | ||
| * @input param prms: data structure that includes all the parameters from input size to algorithm | ||
| * @input param verbose | ||
| */ | ||
| void inverse_transform(cumlHandle &handle, | ||
| MLCommon::Matrix::RankSizePair **rank_sizes, | ||
| size_t n_parts, | ||
| MLCommon::Matrix::Data<float> **trans_input, | ||
| float *components, MLCommon::Matrix::Data<float> **input, | ||
| float *singular_vals, float *mu, paramsPCAMG prms, | ||
| bool verbose); | ||
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| void inverse_transform( | ||
| cumlHandle &handle, MLCommon::Matrix::RankSizePair **rank_sizes, | ||
| size_t n_parts, MLCommon::Matrix::Data<double> **trans_input, | ||
| double *components, MLCommon::Matrix::Data<double> **input, | ||
| double *singular_vals, double *mu, paramsPCAMG prms, bool verbose); | ||
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| }; // end namespace opg | ||
| }; // end namespace PCA | ||
| }; // end namespace ML |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,50 @@ | ||
| /* | ||
| * Copyright (c) 2020, NVIDIA CORPORATION. | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
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| #pragma once | ||
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| #include <common/cumlHandle.hpp> | ||
| #include <opg/matrix/data.hpp> | ||
| #include <opg/matrix/part_descriptor.hpp> | ||
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| namespace ML { | ||
| namespace PCA { | ||
| namespace opg { | ||
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| /** | ||
| * @brief sign flip for PCA and tSVD. This is used to stabilize the sign of column major eigen vectors | ||
| * @input param handle: the internal cuml handle object | ||
| * @input/output param input param input: input matrix that will be used to determine the sign. | ||
| * @input param input_desc: MNMG description of the input | ||
| * @input/output param components: components matrix. | ||
| * @input param n_components: number of columns of components matrix | ||
| * @input param streams: cuda streams | ||
| * @input param n_streams: number of streams | ||
| * @{ | ||
| */ | ||
| void sign_flip(cumlHandle &handle, | ||
| std::vector<MLCommon::Matrix::Data<float> *> &input_data, | ||
| MLCommon::Matrix::PartDescriptor &input_desc, float *components, | ||
| int n_components, cudaStream_t *streams, int n_stream); | ||
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| void sign_flip(cumlHandle &handle, | ||
| std::vector<MLCommon::Matrix::Data<double> *> &input_data, | ||
| MLCommon::Matrix::PartDescriptor &input_desc, double *components, | ||
| int n_components, cudaStream_t *streams, int n_stream); | ||
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| }; // end namespace opg | ||
| }; // end namespace PCA | ||
| }; // end namespace ML |
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