Merge pull request #40 from qiboteam/tf-back

Update TF backend with the one in Qibo

.github/codecov.yml

@@ -27,3 +27,8 @@ comment:
 
 github_checks:
   annotations: false
+
+ignore:
+  - "src/qiboml/backends/tensorflow.py"
+  - "src/qiboml/backends/pytorch.py"
+  - "src/qiboml/backends/jax.py"

pyproject.toml

@@ -15,12 +15,11 @@ python = ">=3.9,<3.13"
 numpy = "^1.26.4"
 numba = "^0.59.0"
 tensorflow = { version = "^2.16.1", markers = "sys_platform == 'linux' or sys_platform == 'darwin'" }
-# TODO: the marker is a temporary solution due to the lack of the tensorflow-io 0.32.0's wheels for Windows, this package is one of
-# the tensorflow requirements
 torch = "^2.2.0"
 jax = "^0.4.25"
 jaxlib = "^0.4.25"
-qibo = "^0.2.8"
+# TODO: this is temporary and has to be updated with Qibo
+qibo = { git  = "https://github.com/qiboteam/qibo.git" }
 
 [tool.poetry.group.dev]
 optional = true

src/qiboml/backends/jax.py

@@ -41,7 +41,7 @@ def cast(self, x, dtype=None, copy=False):
             dtype = self.dtype
         if isinstance(x, self.tensor_types):
             return x.astype(dtype)
-        elif self.issparse(x):
+        elif self.is_sparse(x):
             return x.astype(dtype)
         return self.np.array(x, dtype=dtype, copy=copy)
 

src/qiboml/backends/pytorch.py

@@ -98,11 +98,11 @@ def cast(
 
         return x
 
-    def issparse(self, x):
+    def is_sparse(self, x):
         if isinstance(x, self.np.Tensor):
             return x.is_sparse
 
-        return super().issparse(x)
+        return super().is_sparse(x)
 
     def to_numpy(self, x):
         if isinstance(x, list):
@@ -151,7 +151,7 @@ def calculate_eigenvectors(self, matrix, k=6):
         return self.np.linalg.eigh(matrix)  # pylint: disable=not-callable
 
     def calculate_matrix_exp(self, a, matrix, eigenvectors=None, eigenvalues=None):
-        if eigenvectors is None or self.issparse(matrix):
+        if eigenvectors is None or self.is_sparse(matrix):
             return self.np.linalg.matrix_exp(  # pylint: disable=not-callable
                 -1j * a * matrix
             )

src/qiboml/backends/tensorflow.py

@@ -1,10 +1,11 @@
 import collections
 import os
+from typing import Union
 
 import numpy as np
 from qibo import __version__
 from qibo.backends.npmatrices import NumpyMatrices
-from qibo.backends.numpy import NumpyBackend
+from qibo.backends.numpy import NumpyBackend, _calculate_negative_power_singular_matrix
 from qibo.config import TF_LOG_LEVEL, log, raise_error
 
 
@@ -194,6 +195,28 @@ def calculate_matrix_exp(self, a, matrix, eigenvectors=None, eigenvalues=None):
             return self.tf.linalg.expm(-1j * a * matrix)
         return super().calculate_matrix_exp(a, matrix, eigenvectors, eigenvalues)
 
+    def calculate_matrix_power(
+        self,
+        matrix,
+        power: Union[float, int],
+        precision_singularity: float = 1e-14,
+    ):
+        if not isinstance(power, (float, int)):
+            raise_error(
+                TypeError,
+                f"``power`` must be either float or int, but it is type {type(power)}.",
+            )
+
+        if power < 0.0:
+            # negative powers of singular matrices via SVD
+            determinant = self.tf.linalg.det(matrix)
+            if abs(determinant) < precision_singularity:
+                return _calculate_negative_power_singular_matrix(
+                    matrix, power, precision_singularity, self.tf, self
+                )
+
+        return super().calculate_matrix_power(matrix, power, precision_singularity)
+
     def calculate_singular_value_decomposition(self, matrix):
         # needed to unify order of return
         S, U, V = self.tf.linalg.svd(matrix)