Support numeric, boolean, and string keyword arguments to class methods during CPU dispatching #5223
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Fixes rapidsai#4617 Authors: - Victor Lafargue (https://github.com/viclafargue) Approvers: - Micka (https://github.com/lowener) - Corey J. Nolet (https://github.com/cjnolet) URL: rapidsai#4735
Fix static storage error: ``` /usr/bin/ld: bench/CMakeFiles/sg_benchmark.dir/sg/arima_loglikelihood.cu.o: in function `ML::Bench::Fixture::SetUp(benchmark::State const&)': tmpxft_0000bc8b_00000000-6_arima_loglikelihood.cudafe1.cpp:(.text._ZN2ML5Bench7Fixture5SetUpERKN9benchmark5StateE[_ZN2ML5Bench7Fixture5SetUpERKN9benchmark5StateE]+0x2d): undefined reference to `ML::Bench::Fixture::NumStreams' ``` Authors: - Jiaming Yuan (https://github.com/trivialfis) Approvers: - Victor Lafargue (https://github.com/viclafargue) - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4766
Rapids recently bumped the `xgbooot` to `1.6.0` from `1.5.2` in: rapidsai/integration#487, this PR adapts to those recent changes. Authors: - GALI PREM SAGAR (https://github.com/galipremsagar) - Corey J. Nolet (https://github.com/cjnolet) Approvers: - AJ Schmidt (https://github.com/ajschmidt8) - Dante Gama Dessavre (https://github.com/dantegd) - Corey J. Nolet (https://github.com/cjnolet) URL: rapidsai#4777
This PR updates raft outdated pinnings in dev yml files. Authors: - GALI PREM SAGAR (https://github.com/galipremsagar) Approvers: - Thejaswi. N. S (https://github.com/teju85) - Ray Douglass (https://github.com/raydouglass) - AJ Schmidt (https://github.com/ajschmidt8) - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4778
Changes to be in line with: rapidsai/cudf#11058 Authors: - GALI PREM SAGAR (https://github.com/galipremsagar) Approvers: - AJ Schmidt (https://github.com/ajschmidt8) - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4771
Authors: - Jiaming Yuan (https://github.com/trivialfis) Approvers: - Corey J. Nolet (https://github.com/cjnolet) URL: rapidsai#4782
…#4770) Resolves rapidsai#4442 This PR fixes the issue with using mixed data types in regression errors like `mean_squared_error`, `mean_absolute_error` and `mean_squared_log_error`. Authors: - Shaswat Anand (https://github.com/shaswat-indian) Approvers: - William Hicks (https://github.com/wphicks) URL: rapidsai#4770
…th a ColumnTransformer step (rapidsai#4774) This PR fixes a subtle bug in check_array of cuml.thirdparty_adapters.adapters which is the primary cause for the bug. Fix rapidsai#4368. Authors: - https://github.com/VamsiTallam95 - Ray Douglass (https://github.com/raydouglass) Approvers: - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4774
Authors: - Divye Gala (https://github.com/divyegala) - Ray Douglass (https://github.com/raydouglass) Approvers: - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4789
Pin max version of `cuda-python` to `11.7.0` Authors: - Jordan Jacobelli (https://github.com/Ethyling) Approvers: - AJ Schmidt (https://github.com/ajschmidt8) URL: rapidsai#4793
Pin max version of `cuda-python` to `11.7.0` This is a back port of rapidsai#4793. Authors: - Jordan Jacobelli (https://github.com/Ethyling) Approvers:
## Description This PR cleans up some `#include`s for Thrust. This is meant to help ease the transition to Thrust 1.17 when that is updated in rapids-cmake. ## Context I opened a PR rapidsai/cudf#10489 that updates cuDF to Thrust 1.16. Notably, Thrust reduced the number of internal header inclusions: > [rapidsai#1572](NVIDIA/thrust#1572) Removed several unnecessary header includes. Downstream projects may need to update their includes if they were relying on this behavior. I spoke with @robertmaynard and he recommended making similar changes to clean up includes ("include what we use," in essence) to make sure we have compatibility with future versions of Thrust across all RAPIDS libraries. This changeset also removes dependence on `thrust/detail` headers. Authors: - Bradley Dice (https://github.com/bdice) Approvers: - William Hicks (https://github.com/wphicks) URL: rapidsai#4675
closes rapidsai#4210 Added cosine distance metric for computing epsilon neighborhood in DBSCAN. The cosine distance computed as L2 norm of L2 normalized vectors and the epsilon value is adjusted accordingly. Authors: - Tarang Jain (https://github.com/tarang-jain) Approvers: - Corey J. Nolet (https://github.com/cjnolet) URL: rapidsai#4776
Authors: - Peter Andreas Entschev (https://github.com/pentschev) Approvers: - Ray Douglass (https://github.com/raydouglass) - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4809
Authors: - Micka (https://github.com/lowener) Approvers: - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4805
This PR resolves rapidsai#802 by adding python API for `v_measure_score`. Also came across an [issue](rapidsai#4784) while working on this. Authors: - Shaswat Anand (https://github.com/shaswat-indian) Approvers: - Micka (https://github.com/lowener) - William Hicks (https://github.com/wphicks) URL: rapidsai#4785
Fixes issue rapidsai#2387. For large data sizes, the batch size of the DBSCAN algorithm is small in order to fit the distance matrix in memory. This results in a matrix that has dimensions num_points x batch_size, both for the distance and adjacency matrix. The conversion of the boolean adjacency matrix to CSR format is performed in the 'adjgraph' step. This step was slow when the batch size was small, as described in issue rapidsai#2387. In this commit, the adjgraph step is sped up. This is done in two ways: 1. The adjacency matrix is now stored in row-major batch_size x num_points format --- it was transposed before. This required changes in the vertexdeg step. 2. The csr_row_op kernel has been replaced by the adj_to_csr kernel. This kernel can divide the work over multiple blocks even when the number of rows (batch size) is small. It makes optimal use of memory bandwidth because rows of the matrix are laid out contiguously in memory. Authors: - Allard Hendriksen (https://github.com/ahendriksen) - Corey J. Nolet (https://github.com/cjnolet) Approvers: - Corey J. Nolet (https://github.com/cjnolet) - Tamas Bela Feher (https://github.com/tfeher) URL: rapidsai#4803
This functionality has been moved to RAFT. Authors: - Allard Hendriksen (https://github.com/ahendriksen) Approvers: - Tamas Bela Feher (https://github.com/tfeher) - Corey J. Nolet (https://github.com/cjnolet) URL: rapidsai#4829
…4804) This PR removes the naive versions of the DBSCAN algorithms. They were not used anymore and were largely incorrect, as described in rapidsai#3414. This fixes issue rapidsai#3414. Authors: - Allard Hendriksen (https://github.com/ahendriksen) Approvers: - Corey J. Nolet (https://github.com/cjnolet) URL: rapidsai#4804
[gpuCI] Forward-merge branch-22.08 to branch-22.10 [skip gpuci]
Pass `NVTX` option to raft in a more similar way to the other arguments and make sure `RAFT_NVTX` option in the installed `raft-config.cmake`. Authors: - Artem M. Chirkin (https://github.com/achirkin) Approvers: - Corey J. Nolet (https://github.com/cjnolet) - Robert Maynard (https://github.com/robertmaynard) URL: rapidsai#4825
[gpuCI] Forward-merge branch-22.08 to branch-22.10 [skip gpuci]
The conda recipe was updated to UCX 1.13.0 in rapidsai#4809 , but updating conda environment files was missing there. Authors: - Peter Andreas Entschev (https://github.com/pentschev) Approvers: - Jordan Jacobelli (https://github.com/Ethyling) URL: rapidsai#4813
Allows cuML to be installed with CuPy 11. xref: rapidsai/integration#508 Authors: - https://github.com/jakirkham Approvers: - Sevag H (https://github.com/sevagh) - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4837
Resolves rapidsai#3403 This PR adds support for using `pandas.Series` as an input to `TfidfVectorizer`, `HashingVectorizer` and `CountVectorizer`. Authors: - Shaswat Anand (https://github.com/shaswat-indian) - Ray Douglass (https://github.com/raydouglass) Approvers: - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4811
Authors: - William Hicks (https://github.com/wphicks) Approvers: - Victor Lafargue (https://github.com/viclafargue) - Dante Gama Dessavre (https://github.com/dantegd)
Forward-merge branch-23.02 to branch-23.04
Removed slow modulo operator by minor change in index arithmetic. This gave me following performance improvement for a test case:
| | branch-23.02 |kernel-shap-improvments | Gain |
|-------------------------|------------------|-------------------------|------|
| sampled_rows_kernel | 663 | 193 | 3.4x |
| exact_rows_kernel | 363 | 236 | 1.5x |
All times in microseconds.
Code used for benchmarking:
```python
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor as rf
from cuml.explainer import KernelExplainer
import numpy as np
data, labels = make_classification(n_samples=1000, n_features=20, n_informative=20, random_state=42,
n_redundant=0, n_repeated=0)
X_train, X_test, y_train, y_test = train_test_split(data, labels, train_size=998,
random_state=42) #sklearn train_test_split
y_train = np.ravel(y_train)
y_test = np.ravel(y_test)
model = rf(random_state=42).fit(X_train, y_train)
cu_explainer = KernelExplainer(model=model.predict, data=X_train, is_gpu_model=False, random_state=42, nsamples=100)
cu_shap_values = cu_explainer.shap_values(X_test)
print('cu_shap:', cu_shap_values)
```
Authors:
- Vinay Deshpande (https://github.com/vinaydes)
- Dante Gama Dessavre (https://github.com/dantegd)
Approvers:
- Dante Gama Dessavre (https://github.com/dantegd)
URL: rapidsai#5187
Forward-merge branch-23.02 to branch-23.04
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…re numeric, boolean, and strings (i.e., things that can't be coerced to cuml arrays). Continuation of rapidsai#5223
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Closing in favor of #5236 |
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…ds during CPU dispatching (#5236) This PR: - Updates the CPU dispatching logic to support keyword arguments that are numeric, boolean, and strings (i.e., things that can't be coerced to cuml arrays). It doesn't support passing sequences, as I believe this use case isn't necessary - Makes a minor update to the tests to test this dispatching in principle. We may want to expand the testing of keyword arguments in general, but as this is likely worth a broader discussion/test expansion I thought it might be out of scope for this small PR Closes #5218 This is a replacement for #5223 Authors: - Nick Becker (https://github.com/beckernick) - Dante Gama Dessavre (https://github.com/dantegd) Approvers: - Dante Gama Dessavre (https://github.com/dantegd) URL: #5236
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This PR:
Closes #5218