moving distributed circuit into core

doc/source/qibo.rst

@@ -51,7 +51,7 @@ General circuit models
 .. autoclass:: qibo.core.circuit.DensityMatrixCircuit
     :members:
     :member-order: bysource
-.. autoclass:: qibo.tensorflow.distcircuit.DistributedCircuit
+.. autoclass:: qibo.core.distcircuit.DistributedCircuit
     :members:
     :member-order: bysource
 

examples/reuploading_classifier/qlassifier.py

@@ -116,13 +116,15 @@ def minimize(self, method='BFGS', options=None, compile=True):
             parameters = r[1].result.xbest
 
         elif method == 'sgd':
-            from qibo.tensorflow.gates import TensorflowGate
+            from qibo import K
             circuit = self.circuit(self.training_set[0])
             for gate in circuit.queue:
-                if not isinstance(gate, TensorflowGate):
-                    raise RuntimeError('SGD VQE requires native Tensorflow '
-                                       'gates because gradients are not '
-                                       'supported in the custom kernels.')
+                if K.name not in {"tensorflow_defaulteinsum", "tensorflow_matmuleinsum"}:
+                    from qibo.config import raise_error
+                    raise_error(RuntimeError,
+                                'SGD VQE requires native Tensorflow '
+                                'gates because gradients are not '
+                                'supported in the custom kernels.')
 
             sgd_options = {"nepochs": 5001,
                            "nmessage": 1000,
@@ -132,7 +134,7 @@ def minimize(self, method='BFGS', options=None, compile=True):
                 sgd_options.update(options)
 
             # proceed with the training
-            from qibo.config import K
+            from qibo import K
             vparams = K.Variable(self.params)
             optimizer = getattr(K.optimizers, sgd_options["optimizer"])(
                 learning_rate=sgd_options["learning_rate"])

src/qibo/tensorflow/distcircuit.py → src/qibo/core/distcircuit.py

@@ -8,7 +8,7 @@
 from qibo.abstractions.circuit import AbstractCircuit
 from qibo.config import raise_error, get_threads
 from qibo.core import callbacks, circuit, measurements, states
-from qibo.tensorflow.distutils import DistributedQueues
+from qibo.core.distutils import DistributedQueues
 from typing import Dict, List, Optional, Set, Tuple, Union
 
 

src/qibo/core/states.py

@@ -169,7 +169,7 @@ class DistributedState(VectorState):
     """Data structure that holds the pieces of a state vector.
 
     This is created automatically by
-    :class:`qibo.tensorflow.distcircuit.DistributedCircuit`
+    :class:`qibo.core.distcircuit.DistributedCircuit`
     which uses state pieces instead of the full state vector tensor to allow
     distribution to multiple devices.
     Using the ``DistributedState`` instead of the full state vector as a tensor
@@ -182,7 +182,7 @@ class DistributedState(VectorState):
     """
 
     def __init__(self, circuit):
-        from qibo.tensorflow.distcircuit import DistributedCircuit
+        from qibo.core.distcircuit import DistributedCircuit
         super().__init__(circuit.nqubits)
         self.circuit_cls = DistributedCircuit
         if not isinstance(circuit, self.circuit_cls):

src/qibo/models/circuit.py

@@ -21,7 +21,7 @@ def _constructor(cls, *args, **kwargs):
             kwargs = {}
         else:
             try:
-                from qibo.tensorflow.distcircuit import DistributedCircuit
+                from qibo.core.distcircuit import DistributedCircuit
             except ModuleNotFoundError: # pragma: no cover
                 # CI installs all required libraries by default
                 raise_error(ModuleNotFoundError,

src/qibo/models/evolution.py

@@ -104,7 +104,7 @@ def execute(self, final_time, start_time=0.0, initial_state=None):
 
         Returns:
             Final state vector a ``tf.Tensor`` or a
-            :class:`qibo.tensorflow.distutils.DistributedState` when a
+            :class:`qibo.core.distutils.DistributedState` when a
             distributed execution is used.
         """
         state = self.get_initial_state(initial_state)
@@ -154,7 +154,7 @@ class AdiabaticEvolution(StateEvolution):
         solver (str): Solver to use for integrating Schrodinger's equation.
         callbacks (list): List of callbacks to calculate during evolution.
         accelerators (dict): Dictionary of devices to use for distributed
-            execution. See :class:`qibo.tensorflow.distcircuit.DistributedCircuit`
+            execution. See :class:`qibo.core.distcircuit.DistributedCircuit`
             for more details. This option is available only when the Trotter
             decomposition is used for the time evolution.
         memory_device (str): Name of device where the full state will be saved.

src/qibo/models/variational.py

@@ -115,7 +115,7 @@ class QAOA(object):
             Default solver is 'exp' (:class:`qibo.solvers.Exponential`).
         callbacks (list): List of callbacks to calculate during evolution.
         accelerators (dict): Dictionary of devices to use for distributed
-            execution. See :class:`qibo.tensorflow.distcircuit.DistributedCircuit`
+            execution. See :class:`qibo.core.distcircuit.DistributedCircuit`
             for more details. This option is available only when ``hamiltonian``
             is a :class:`qibo.abstractions.hamiltonians.TrotterHamiltonian`.
         memory_device (str): Name of device where the full state will be saved.

src/qibo/tensorflow/custom_operators/python/ops/qibo_tf_custom_operators.py

@@ -37,7 +37,7 @@ def apply_gate(state, gate, qubits, nqubits, target, omp_num_threads=get_threads
         state (tf.Tensor): State vector of shape ``(2 ** nqubits,)``.
         gate (tf.Tensor): Gate matrix of shape ``(2, 2)``.
         qubits (tf.Tensor): Tensor that contains control and target qubits in
-            sorted order. See :meth:`qibo.tensorflow.cgates.TensorflowGate.qubits_tensor`
+            sorted order. See :meth:`qibo.backends.abstract.TensorflowCustomBackend.cache.qubits_tensor`
             for more details.
         nqubits (int): Total number of qubits in the state vector.
         target (int): Qubit ID that the gate will act on.

src/qibo/tests/test_distributed.py

@@ -3,7 +3,7 @@
 import numpy as np
 import qibo
 from qibo import models, gates
-from qibo.tensorflow import distutils
+from qibo.core import distutils
 from qibo.tests import utils
 
 

src/qibo/tests_new/test_core_states_distributed.py

@@ -22,7 +22,7 @@ def test_distributed_state_init():
 def test_distributed_state_constructors(init_type):
     """Tests `zero_state` and `plus_state` for `DistributedState`."""
     from qibo.models import Circuit
-    from qibo.tensorflow.distutils import DistributedQubits
+    from qibo.core.distutils import DistributedQubits
     c = Circuit(6, {"/GPU:0": 2, "/GPU:1": 2})
     c.queues.qubits = DistributedQubits(range(c.nglobal), c.nqubits) # pylint: disable=E1101
     state = getattr(states.DistributedState, f"{init_type}_state")(c)
@@ -40,7 +40,7 @@ def test_distributed_state_constructors(init_type):
 def test_user_initialization(nqubits):
     import itertools
     from qibo.models import Circuit
-    from qibo.tensorflow.distutils import DistributedQubits
+    from qibo.core.distutils import DistributedQubits
     target_state = (np.random.random(2 ** nqubits) +
                     1j * np.random.random(2 ** nqubits))
     c = Circuit(nqubits, {"/GPU:0": 2, "/GPU:1": 2})
@@ -56,7 +56,7 @@ def test_user_initialization(nqubits):
 
 def test_distributed_state_copy():
     from qibo.models import Circuit
-    from qibo.tensorflow.distutils import DistributedQubits
+    from qibo.core.distutils import DistributedQubits
     c = Circuit(4, {"/GPU:0": 2, "/GPU:1": 2})
     c.queues.qubits = DistributedQubits(range(c.nglobal), c.nqubits) # pylint: disable=E1101
     state = states.DistributedState.zero_state(c)