From fd5f642a3b681594c8444bcdcea13dfe01cc5dfc Mon Sep 17 00:00:00 2001
From: Aryan <nandaaryan823@gmail.com>
Date: Sat, 3 Feb 2024 22:34:27 +0530
Subject: [PATCH 1/6] Remove block_diag from pymc.math in favor of alias to
pytensor.tensor.slinalg.block_diag
---
pymc/math.py | 63 ++++++++--------------------------------------------
1 file changed, 9 insertions(+), 54 deletions(-)
diff --git a/pymc/math.py b/pymc/math.py
index 7c9ceaa9ec..1c8cb1f138 100644
--- a/pymc/math.py
+++ b/pymc/math.py
@@ -22,8 +22,6 @@
import pytensor.sparse
import pytensor.tensor as pt
import pytensor.tensor.slinalg
-import scipy as sp
-import scipy.sparse
from pytensor.graph.basic import Apply
from pytensor.graph.op import Op
@@ -93,9 +91,8 @@
from pytensor.tensor.linalg import solve_triangular
from pytensor.tensor.nlinalg import matrix_inverse
from pytensor.tensor.special import log_softmax, softmax
-from scipy.linalg import block_diag as scipy_block_diag
-from pymc.pytensorf import floatX, ix_, largest_common_dtype
+from pymc.pytensorf import floatX
__all__ = [
"abs",
@@ -513,55 +510,9 @@ def batched_diag(C):
raise ValueError("Input should be 2 or 3 dimensional")
-class BlockDiagonalMatrix(Op):
- __props__ = ("sparse", "format")
-
- def __init__(self, sparse=False, format="csr"):
- if format not in ("csr", "csc"):
- raise ValueError(f"format must be one of: 'csr', 'csc', got {format}")
- self.sparse = sparse
- self.format = format
-
- def make_node(self, *matrices):
- if not matrices:
- raise ValueError("no matrices to allocate")
- matrices = list(map(pt.as_tensor, matrices))
- if any(mat.type.ndim != 2 for mat in matrices):
- raise TypeError("all data arguments must be matrices")
- if self.sparse:
- out_type = pytensor.sparse.matrix(self.format, dtype=largest_common_dtype(matrices))
- else:
- out_type = pytensor.tensor.matrix(dtype=largest_common_dtype(matrices))
- return Apply(self, matrices, [out_type])
-
- def perform(self, node, inputs, output_storage, params=None):
- dtype = largest_common_dtype(inputs)
- if self.sparse:
- output_storage[0][0] = sp.sparse.block_diag(inputs, self.format, dtype)
- else:
- output_storage[0][0] = scipy_block_diag(*inputs).astype(dtype)
-
- def grad(self, inputs, gout):
- shapes = pt.stack([i.shape for i in inputs])
- index_end = shapes.cumsum(0)
- index_begin = index_end - shapes
- slices = [
- ix_(
- pt.arange(index_begin[i, 0], index_end[i, 0]),
- pt.arange(index_begin[i, 1], index_end[i, 1]),
- )
- for i in range(len(inputs))
- ]
- return [gout[0][slc] for slc in slices]
-
- def infer_shape(self, fgraph, nodes, shapes):
- first, second = zip(*shapes)
- return [(pt.add(*first), pt.add(*second))]
-
-
-def block_diagonal(matrices, sparse=False, format="csr"):
- r"""See scipy.sparse.block_diag or
- scipy.linalg.block_diag for reference
+def block_diagonal(*matrices, sparse=False, format="csr"):
+ r"""See pt.slinalg.block_diag or
+ pytensor.sparse.basic.block_diag for reference
Parameters
----------
@@ -577,4 +528,8 @@ def block_diagonal(matrices, sparse=False, format="csr"):
"""
if len(matrices) == 1: # graph optimization
return matrices[0]
- return BlockDiagonalMatrix(sparse=sparse, format=format)(*matrices)
+
+ if sparse:
+ return pytensor.sparse.basic.block_diag(*matrices, format=format)
+ else:
+ return pt.slinalg.block_diag(*matrices)
From a5913e5aabb7b87c3b17ab53dbb2ac21d1c670ad Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
<66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sat, 3 Feb 2024 17:15:06 +0000
Subject: [PATCH 2/6] [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---
requirements-dev.txt | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/requirements-dev.txt b/requirements-dev.txt
index b21437de01..8aff7d60c9 100644
--- a/requirements-dev.txt
+++ b/requirements-dev.txt
@@ -30,4 +30,4 @@ sphinx>=1.5
sphinxext-rediraffe
types-cachetools
typing-extensions>=3.7.4
-watermark
\ No newline at end of file
+watermark
From b55c8773ef2aa10d95ee14fc439d831a6ca79050 Mon Sep 17 00:00:00 2001
From: Aryan <nandaaryan823@gmail.com>
Date: Tue, 6 Feb 2024 23:34:22 +0530
Subject: [PATCH 3/6] FutureWarning Added
---
pymc/math.py | 6 +++++-
1 file changed, 5 insertions(+), 1 deletion(-)
diff --git a/pymc/math.py b/pymc/math.py
index 1c8cb1f138..1924bb6043 100644
--- a/pymc/math.py
+++ b/pymc/math.py
@@ -527,8 +527,12 @@ def block_diagonal(*matrices, sparse=False, format="csr"):
matrix
"""
if len(matrices) == 1: # graph optimization
+ warnings.warn(
+ "The behavior of block_diagonal when only one matrix is provided is deprecated. Use pytensor function instead.",
+ FutureWarning,
+ stacklevel=2,
+ )
return matrices[0]
-
if sparse:
return pytensor.sparse.basic.block_diag(*matrices, format=format)
else:
From 33201553badd699589f50bc55deab51ab4005b31 Mon Sep 17 00:00:00 2001
From: Aryan <nandaaryan823@gmail.com>
Date: Thu, 8 Feb 2024 17:16:20 +0530
Subject: [PATCH 4/6] Update
---
pymc/math.py | 10 +++++-----
1 file changed, 5 insertions(+), 5 deletions(-)
diff --git a/pymc/math.py b/pymc/math.py
index 1924bb6043..90351fb028 100644
--- a/pymc/math.py
+++ b/pymc/math.py
@@ -526,12 +526,12 @@ def block_diagonal(*matrices, sparse=False, format="csr"):
-------
matrix
"""
+ warnings.warn(
+ "The behavior of block_diagonal when only one matrix is provided is deprecated. Use pytensor function instead.",
+ FutureWarning,
+ stacklevel=2,
+ )
if len(matrices) == 1: # graph optimization
- warnings.warn(
- "The behavior of block_diagonal when only one matrix is provided is deprecated. Use pytensor function instead.",
- FutureWarning,
- stacklevel=2,
- )
return matrices[0]
if sparse:
return pytensor.sparse.basic.block_diag(*matrices, format=format)
From a01db7f77456c52672398589e083ed4e67a60655 Mon Sep 17 00:00:00 2001
From: Aryan <nandaaryan823@gmail.com>
Date: Thu, 8 Feb 2024 19:21:54 +0530
Subject: [PATCH 5/6] Update
---
pymc/math.py | 4 +---
1 file changed, 1 insertion(+), 3 deletions(-)
diff --git a/pymc/math.py b/pymc/math.py
index 90351fb028..e9f41be018 100644
--- a/pymc/math.py
+++ b/pymc/math.py
@@ -527,9 +527,7 @@ def block_diagonal(*matrices, sparse=False, format="csr"):
matrix
"""
warnings.warn(
- "The behavior of block_diagonal when only one matrix is provided is deprecated. Use pytensor function instead.",
- FutureWarning,
- stacklevel=2,
+ "pymc.math.block_diagonal is deprecated in favor of `pytensor.tensor.linalg.block_diag` and `pytensor.sparse.block_diag` functions. This function will be removed in a future release",
)
if len(matrices) == 1: # graph optimization
return matrices[0]
From fe8a06531581becfafcbe36f9037cc4207463611 Mon Sep 17 00:00:00 2001
From: Aryan <nandaaryan823@gmail.com>
Date: Thu, 8 Feb 2024 19:30:00 +0530
Subject: [PATCH 6/6] Update
---
pymc/math.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/pymc/math.py b/pymc/math.py
index e9f41be018..7fe8d1e5e5 100644
--- a/pymc/math.py
+++ b/pymc/math.py
@@ -510,7 +510,7 @@ def batched_diag(C):
raise ValueError("Input should be 2 or 3 dimensional")
-def block_diagonal(*matrices, sparse=False, format="csr"):
+def block_diagonal(matrices, sparse=False, format="csr"):
r"""See pt.slinalg.block_diag or
pytensor.sparse.basic.block_diag for reference