Merge branch 'master' into impl_histogram

Author: antonwolfy

.github/workflows/build-sphinx.yml

@@ -86,13 +86,13 @@ jobs:
           sudo apt-get install -y nvidia-cuda-toolkit clinfo
 
       - name: Checkout repo
-        uses: actions/checkout@1d96c772d19495a3b5c517cd2bc0cb401ea0529f # v4.1.3
+        uses: actions/checkout@0ad4b8fadaa221de15dcec353f45205ec38ea70b # v4.1.4
         with:
           fetch-depth: 0
 
       # https://github.com/marketplace/actions/setup-miniconda
       - name: Setup miniconda
-        uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
+        uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4
         with:
           auto-update-conda: true
           python-version: ${{ env.python-ver }}
@@ -199,7 +199,7 @@ jobs:
     runs-on: ubuntu-20.04
 
     steps:
-      - uses: actions/checkout@1d96c772d19495a3b5c517cd2bc0cb401ea0529f # v4.1.3
+      - uses: actions/checkout@0ad4b8fadaa221de15dcec353f45205ec38ea70b # v4.1.4
         with:
           fetch-depth: 0
 

.github/workflows/conda-package.yml

@@ -84,12 +84,12 @@ jobs:
           access_token: ${{ github.token }}
 
       - name: Checkout DPNP repo
-        uses: actions/checkout@1d96c772d19495a3b5c517cd2bc0cb401ea0529f # v4.1.3
+        uses: actions/checkout@0ad4b8fadaa221de15dcec353f45205ec38ea70b # v4.1.4
         with:
           fetch-depth: 0
 
       - name: Setup miniconda
-        uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
+        uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4
         with:
           auto-update-conda: true
           python-version: ${{ matrix.python }}
@@ -125,7 +125,7 @@ jobs:
         run: conda build --no-test --python ${{ matrix.python }} --numpy 1.23 ${{ env.CHANNELS }} conda-recipe
 
       - name: Upload artifact
-        uses: actions/upload-artifact@1746f4ab65b179e0ea60a494b83293b640dd5bba # v4.3.2
+        uses: actions/upload-artifact@65462800fd760344b1a7b4382951275a0abb4808 # v4.3.3
         with:
           name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
           path: ${{ env.CONDA_BLD }}${{ env.PACKAGE_NAME }}-*.tar.bz2
@@ -158,7 +158,7 @@ jobs:
 
     steps:
       - name: Download artifact
-        uses: actions/download-artifact@8caf195ad4b1dee92908e23f56eeb0696f1dd42d # v4.1.5
+        uses: actions/download-artifact@65a9edc5881444af0b9093a5e628f2fe47ea3b2e # v4.1.7
         with:
           name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
           path: ${{ env.pkg-path-in-channel }}
@@ -169,7 +169,7 @@ jobs:
           tar -xvf ${{ env.pkg-path-in-channel }}/${{ env.PACKAGE_NAME }}-*.tar.bz2 -C ${{ env.extracted-pkg-path }}
 
       - name: Setup miniconda
-        uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
+        uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4
         with:
           auto-update-conda: true
           python-version: ${{ matrix.python }}
@@ -273,7 +273,7 @@ jobs:
 
     steps:
       - name: Download artifact
-        uses: actions/download-artifact@8caf195ad4b1dee92908e23f56eeb0696f1dd42d # v4.1.5
+        uses: actions/download-artifact@65a9edc5881444af0b9093a5e628f2fe47ea3b2e # v4.1.7
         with:
           name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
           path: ${{ env.pkg-path-in-channel }}
@@ -293,7 +293,7 @@ jobs:
           dir ${{ env.extracted-pkg-path }}
 
       - name: Setup miniconda
-        uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
+        uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4
         with:
           auto-update-conda: true
           python-version: ${{ matrix.python }}
@@ -419,12 +419,12 @@ jobs:
 
     steps:
       - name: Download artifact
-        uses: actions/download-artifact@8caf195ad4b1dee92908e23f56eeb0696f1dd42d # v4.1.5
+        uses: actions/download-artifact@65a9edc5881444af0b9093a5e628f2fe47ea3b2e # v4.1.7
         with:
           name: ${{ env.PACKAGE_NAME }} ${{ runner.os }} Python ${{ matrix.python }}
 
       - name: Setup miniconda
-        uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
+        uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4
         with:
           auto-update-conda: true
           python-version: ${{ matrix.python }}
@@ -447,7 +447,7 @@ jobs:
       run:
         shell: bash -el {0}
     steps:
-      - uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
+      - uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4
         with:
           run-post: false
           channel-priority: "disabled"
@@ -458,7 +458,7 @@ jobs:
         run: conda install anaconda-client
 
       - name: Checkout repo
-        uses: actions/checkout@1d96c772d19495a3b5c517cd2bc0cb401ea0529f # v4.1.3
+        uses: actions/checkout@0ad4b8fadaa221de15dcec353f45205ec38ea70b # v4.1.4
         with:
           repository: IntelPython/devops-tools
           fetch-depth: 0

.github/workflows/generate_coverage.yaml

@@ -32,7 +32,7 @@ jobs:
           access_token: ${{ github.token }}
 
       - name: Checkout repo
-        uses: actions/checkout@1d96c772d19495a3b5c517cd2bc0cb401ea0529f # v4.1.3
+        uses: actions/checkout@0ad4b8fadaa221de15dcec353f45205ec38ea70b # v4.1.4
         with:
           fetch-depth: 0
 
@@ -57,7 +57,7 @@ jobs:
           sudo apt-get install lcov
 
       - name: Setup miniconda
-        uses: conda-incubator/setup-miniconda@030178870c779d9e5e1b4e563269f3aa69b04081 # v3.0.3
+        uses: conda-incubator/setup-miniconda@a4260408e20b96e80095f42ff7f1a15b27dd94ca # v3.0.4
         with:
           auto-update-conda: true
           python-version: ${{ env.python-ver }}

.github/workflows/openssf-scorecard.yml

@@ -33,7 +33,7 @@ jobs:
 
     steps:
       - name: "Checkout code"
-        uses: actions/checkout@1d96c772d19495a3b5c517cd2bc0cb401ea0529f # v4.1.3
+        uses: actions/checkout@0ad4b8fadaa221de15dcec353f45205ec38ea70b # v4.1.4
         with:
           persist-credentials: false
 
@@ -60,14 +60,14 @@ jobs:
       # Upload the results as artifacts (optional). Commenting out will disable uploads of run results in SARIF
       # format to the repository Actions tab.
       - name: "Upload artifact"
-        uses: actions/upload-artifact@1746f4ab65b179e0ea60a494b83293b640dd5bba # v4.3.2
+        uses: actions/upload-artifact@65462800fd760344b1a7b4382951275a0abb4808 # v4.3.3
         with:
           name: SARIF file
           path: results.sarif
           retention-days: 14
 
       # Upload the results to GitHub's code scanning dashboard.
       - name: "Upload to code-scanning"
-        uses: github/codeql-action/upload-sarif@c7f9125735019aa87cfc361530512d50ea439c71 # v3.25.1
+        uses: github/codeql-action/upload-sarif@d39d31e687223d841ef683f52467bd88e9b21c14 # v3.25.3
         with:
           sarif_file: results.sarif

.github/workflows/pre-commit.yml

@@ -26,7 +26,7 @@ jobs:
             pylint
 
       - name: Checkout DPNP repo
-        uses: actions/checkout@1d96c772d19495a3b5c517cd2bc0cb401ea0529f # v4.1.3
+        uses: actions/checkout@0ad4b8fadaa221de15dcec353f45205ec38ea70b # v4.1.4
 
       - name: Set up python
         uses: actions/setup-python@82c7e631bb3cdc910f68e0081d67478d79c6982d # v5.1.0

dpnp/linalg/dpnp_iface_linalg.py

@@ -42,13 +42,15 @@
 import dpnp
 
 from .dpnp_utils_linalg import (
+    check_2d,
     check_stacked_2d,
     check_stacked_square,
     dpnp_cholesky,
     dpnp_cond,
     dpnp_det,
     dpnp_eigh,
     dpnp_inv,
+    dpnp_lstsq,
     dpnp_matrix_power,
     dpnp_matrix_rank,
     dpnp_multi_dot,
@@ -69,6 +71,7 @@
     "eigvals",
     "eigvalsh",
     "inv",
+    "lstsq",
     "matrix_power",
     "matrix_rank",
     "multi_dot",
@@ -594,6 +597,79 @@ def inv(a):
     return dpnp_inv(a)
 
 
+def lstsq(a, b, rcond=None):
+    """
+    Return the least-squares solution to a linear matrix equation.
+
+    For full documentation refer to :obj:`numpy.linalg.lstsq`.
+
+    Parameters
+    ----------
+    a : (M, N) {dpnp.ndarray, usm_ndarray}
+        "Coefficient" matrix.
+    b : {(M,), (M, K)} {dpnp.ndarray, usm_ndarray}
+        Ordinate or "dependent variable" values.
+        If `b` is two-dimensional, the least-squares solution
+        is calculated for each of the `K` columns of `b`.
+    rcond : {int, float, None}, optional
+        Cut-off ratio for small singular values of `a`.
+        For the purposes of rank determination, singular values are treated
+        as zero if they are smaller than `rcond` times the largest singular
+        value of `a`.
+        The default uses the machine precision times ``max(M, N)``.  Passing
+        ``-1`` will use machine precision.
+
+    Returns
+    -------
+    x : {(N,), (N, K)} dpnp.ndarray
+        Least-squares solution. If `b` is two-dimensional,
+        the solutions are in the `K` columns of `x`.
+    residuals : {(1,), (K,), (0,)} dpnp.ndarray
+        Sums of squared residuals: Squared Euclidean 2-norm for each column in
+        ``b - a @ x``.
+        If the rank of `a` is < N or M <= N, this is an empty array.
+        If `b` is 1-dimensional, this is a (1,) shape array.
+        Otherwise the shape is (K,).
+    rank : int
+        Rank of matrix `a`.
+    s : (min(M, N),) dpnp.ndarray
+        Singular values of `a`.
+
+    Examples
+    --------
+    Fit a line, ``y = mx + c``, through some noisy data-points:
+
+    >>> import dpnp as np
+    >>> x = np.array([0, 1, 2, 3])
+    >>> y = np.array([-1, 0.2, 0.9, 2.1])
+
+    By examining the coefficients, we see that the line should have a
+    gradient of roughly 1 and cut the y-axis at, more or less, -1.
+
+    We can rewrite the line equation as ``y = Ap``, where ``A = [[x 1]]``
+    and ``p = [[m], [c]]``.  Now use `lstsq` to solve for `p`:
+
+    >>> A = np.vstack([x, np.ones(len(x))]).T
+    >>> A
+    array([[0., 1.],
+           [1., 1.],
+           [2., 1.],
+           [3., 1.]])
+
+    >>> m, c = np.linalg.lstsq(A, y, rcond=None)[0]
+    >>> m, c
+    (array(1.), array(-0.95)) # may vary
+
+    """
+
+    dpnp.check_supported_arrays_type(a, b)
+    check_2d(a)
+    if rcond is not None and not isinstance(rcond, (int, float)):
+        raise TypeError("rcond must be integer, floating type, or None")
+
+    return dpnp_lstsq(a, b, rcond=rcond)
+
+
 def matrix_power(a, n):
     """
     Raise a square matrix to the (integer) power `n`.