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Merge v0.3.2-rc into main (#359)
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Co-authored-by: Josh Izaac <josh146@gmail.com>
Co-authored-by: Ali Asadi <ali@xanadu.ai>
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@dime10 @josh146 @maliasadi
3 people authored Nov 9, 2023
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235 changes: 139 additions & 96 deletions doc/changelog.md
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Expand Up @@ -16,6 +16,66 @@ This release contains contributions from (in alphabetical order):

<h3>New features</h3>

* The experimental AutoGraph feature now supports Python `while` loops, allowing native Python loops
to be captured and compiled with Catalyst.
[(#318)](https://github.com/PennyLaneAI/catalyst/pull/318)

```python
dev = qml.device("lightning.qubit", wires=4)

@qjit(autograph=True)
@qml.qnode(dev)
def circuit(n: int, x: float):
i = 0

while i < n:
qml.RX(x, wires=i)
i += 1

return qml.expval(qml.PauliZ(0))
```

```pycon
>>> circuit(4, 0.32)
array(0.94923542)
```

This feature extends the existing AutoGraph support for Python `for` loops and `if` statements
introduced in v0.3. Note that TensorFlow must be installed for AutoGraph support.

For more details, please see the
[AutoGraph guide](https://docs.pennylane.ai/projects/catalyst/en/stable/dev/autograph.html).

* In addition to loops and conditional branches, AutoGraph now supports native Python `and`, `or`
and `not` operators in Boolean expressions.
[(#325)](https://github.com/PennyLaneAI/catalyst/pull/325)

```python
dev = qml.device("lightning.qubit", wires=1)

@qjit(autograph=True)
@qml.qnode(dev)
def circuit(x: float):

if x >= 0 and x < jnp.pi:
qml.RX(x, wires=0)

return qml.probs()
```

```pycon
>>> circuit(0.43)
array([0.95448287, 0.04551713])
>>> circuit(4.54)
array([1., 0.])
```

Note that logical Boolean operators will only be captured by AutoGraph if all
operands are dynamic variables (that is, a value known only at runtime, such
as a measurement result or function argument). For other use
cases, it is recommended to use the `jax.numpy.logical_*` set of functions where
appropriate.

* Debug compiled programs and print dynamic values at runtime with ``debug.print``
[(#279)](https://github.com/PennyLaneAI/catalyst/pull/279)
[(#356)](https://github.com/PennyLaneAI/catalyst/pull/356)
Expand All @@ -42,58 +102,46 @@ This release contains contributions from (in alphabetical order):
```

* Catalyst now officially supports macOS X86_64 devices, with macOS binary wheels
available for both AARCH64 and X86_64 on PyPI.
available for both AARCH64 and X86_64.
[(#347)](https://github.com/PennyLaneAI/catalyst/pull/347)
[(#313)](https://github.com/PennyLaneAI/catalyst/pull/313)

<h3>Improvements</h3>

* Improve the compiler driver diagnostic output even more. Now it dumps the failing IR as well as
prints names of failing passes.
[(#349)](https://github.com/PennyLaneAI/catalyst/pull/349)
* It is now possible to dynamically load third-party Catalyst compatible devices directly
into a pre-installed Catalyst runtime on Linux.
[(#327)](https://github.com/PennyLaneAI/catalyst/pull/327)

* Return values of conditional functions no longer need to be of exactly the same type. Catalyst
would apply type promotion to branch return values if their types don't match.
[(#333)](https://github.com/PennyLaneAI/catalyst/pull/333)
To take advantage of this, third-party devices must implement the `Catalyst::Runtime::QuantumDevice`
interface, in addition to defining the following method:

```python
@qjit
def func(i: int, f: float):
@cond(i < 3)
def cond_fn():
return i
@cond_fn.otherwise
def otherwise():
return f
return cond_fn()
```cpp
extern "C" Catalyst::Runtime::QuantumDevice*
getCustomDevice() { return new CustomDevice(); }
```
```pycon
>>> func(1, 4.0)
array(1.0)
```
This support can also be integrated into existing PennyLane Python devices that inherit from
the `QuantumDevice` class, by defining the `get_c_interface` static method.
* Improve the `CopyGlobalMemRefPass` of our MLIR processing pipeline by adding the support of
dynamically shaped arrays.
[(#348)](https://github.com/PennyLaneAI/catalyst/pull/348)
For more details, see the
[custom devices documentation](https://docs.pennylane.ai/projects/catalyst/en/stable/dev/custom_devices.html).
* Improve the compiler driver diagnostic output. The driver now provides more context for error
messages and includes a verbose trace if verbose mode is enabled.
[(#303)](https://github.com/PennyLaneAI/catalyst/pull/303)
<h3>Improvements</h3>
* Return values of conditional functions no longer need to be of exactly the same type. Catalyst
would apply type promotion to branch return values if their types don't match.
* Return values of conditional functions no longer need to be of exactly the same type.
Type promotion is automatically applied to branch return values if their types don't match.
[(#333)](https://github.com/PennyLaneAI/catalyst/pull/333)
```python
@qjit
def func(i: int, f: float):
@cond(i < 3)
def cond_fn():
return i
@cond_fn.otherwise
def otherwise():
return f
return cond_fn()
```

Expand All @@ -102,71 +150,74 @@ This release contains contributions from (in alphabetical order):
array(1.0)
```

* The AutoGraph feature, still experimental, now supports native Python `while` loops as well.
[(#318)](https://github.com/PennyLaneAI/catalyst/pull/318)
Automatic type promotion across conditional branches also works with AutoGraph:

```python
@qjit(autograph=True)
@qml.qnode(qml.device("lightning.qubit", wires=4))
def circuit(n:int):
i = 0
while i < n:
qml.RX(jnp.pi/2, wires=i)
i += 1
return qml.expval(qml.PauliZ(0))
```
def func(i: int, f: float):

* The AutoGraph feature now also supports native Python `and`, `or` and `not` operators in Boolean
expressions.
[(#325)](https://github.com/PennyLaneAI/catalyst/pull/325)
if i < 3:
i = i
else:
i = f

```python
@qjit(autograph=True)
@qml.qnode(qml.device("lightning.qubit", wires=1))
def circuit(param:float):
if param >= 0 and param < jnp.pi:
qml.RX(param, wires=0)
return qml.probs()
return i
```

<h3>Breaking changes</h3>

* The axis ordering for `catalyst.jacobian` is updated to match `jax.jacobian`. Assume we have parameters of shape
`[a,b]` and results of shape `[c,d]`. The jacobian would get the shape `[c,d,a,b]` instead of `[a,b,c,d]`.
[(#283)](https://github.com/PennyLaneAI/catalyst/pull/283)
```pycon
>>> func(1, 4.0)
array(1.0)
```

<h3>Bug fixes</h3>
* AutoGraph now supports converting functions even when they are invoked through functional wrappers such
as `adjoint`, `ctrl`, `grad`, `jacobian`, etc.
[(#336)](https://github.com/PennyLaneAI/catalyst/pull/336)

* The `requirements.txt` file to build Catalyst from source has been updated with a minimum PIP
version, `>=22.3`. Previous versions of pip are unable to perform editable installs when the
system-wide site-packages are read-only, even when the `--user` flag is provided.
[(#311)](https://github.com/PennyLaneAI/catalyst/pull/311)
For example, the following should now succeed:

* Update the frontend to make it compatible with measurements as PyTrees in PennyLane `0.33.0`.
[(#315)](https://github.com/PennyLaneAI/catalyst/pull/315)
```python
def inner(n):
for i in range(n):
qml.T(i)

* Add support for third party devices.
Third party `QuantumDevice` implementations can now be loaded into the runtime.
[(#327)](https://github.com/PennyLaneAI/catalyst/pull/327)
@qjit(autograph=True)
@qml.qnode(dev)
def f(n: int):
adjoint(inner)(n)
return qml.state()
```

* Add `pennylane.compilers` entry points interface.
* To prepare for Catalyst's frontend being integrated with PennyLane, the appropriate plugin entry point
interface has been added to Catalyst.
[(#331)](https://github.com/PennyLaneAI/catalyst/pull/331)

For any compiler packages seeking to be registered in PennyLane, this PR adds the `entry_points`
metadata under the the group name `pennylane.compilers`, with the following entry points:
For any compiler packages seeking to be registered in PennyLane, the `entry_points`
metadata under the the group name `pennylane.compilers` must be added, with the following entry points:

- `context`: Path to the compilation evaluation context manager. This context manager should have
the method context.is_tracing(), which returns True if called within a program that is being
the method `context.is_tracing()`, which returns True if called within a program that is being
traced or captured.

- `ops`: Path to the compiler operations module. This operations module may contain compiler
specific versions of PennyLane operations. Within a JIT context, PennyLane operations may
dispatch to these.

- `qjit`: Path to the JIT compiler decorator provided by the compiler. This decorator should have
the signature `qjit(fn, *args, **kwargs)`, where fn is the function to be compiled.
the signature `qjit(fn, *args, **kwargs)`, where `fn` is the function to be compiled.

* The compiler driver diagnostic output has been improved, and now includes failing IR as well as
the names of failing passes.
[(#349)](https://github.com/PennyLaneAI/catalyst/pull/349)

* The scatter operation in the Catalyst dialect now uses an SCF for loop to avoid ballooning
the compiled code.
[(#307)](https://github.com/PennyLaneAI/catalyst/pull/307)

* The `CopyGlobalMemRefPass` pass of our MLIR processing pipeline now supports
dynamically shaped arrays.
[(#348)](https://github.com/PennyLaneAI/catalyst/pull/348)

* Include the "Catalyst" utility dialect in our MLIR C-API.
* The Catalyst utility dialect is now included in the Catalyst MLIR C-API.
[(#345)](https://github.com/PennyLaneAI/catalyst/pull/345)

* Fix an issue with the AutoGraph conversion system that would prevent the fallback to Python from
Expand All @@ -186,35 +237,26 @@ This release contains contributions from (in alphabetical order):

<h3>Breaking changes</h3>

* The axis ordering for `catalyst.jacobian` is updated to match `jax.jacobian`. Assume we have
parameters of shape `[a,b]` and results of shape `[c,d]`. The jacobian would get the shape
`[c,d,a,b]` instead of `[a,b,c,d]`.
* The axis ordering for `catalyst.jacobian` is updated to match `jax.jacobian`. Assuming we have
parameters of shape `[a,b]` and results of shape `[c,d]`, the returned Jacobian will now have
shape `[c, d, a, b]` instead of `[a, b, c, d]`.
[(#283)](https://github.com/PennyLaneAI/catalyst/pull/283)

<h3>Bug fixes</h3>

* Enable AutoGraph to convert functions even when they are invoked through functional wrappers such
as `adjoint`, `ctrl`, `grad`, `jacobian`, etc.
[(#336)](https://github.com/PennyLaneAI/catalyst/pull/336)

The following should now succeed:

```python
def inner(n):
for i in range(n):
qml.T(i)
* An upstream change in the PennyLane-Lightning project was addressed to prevent compilation issues
in the `StateVectorLQubitDynamic` class in the runtime.
The issue was introduced in [#499](https://github.com/PennyLaneAI/pennylane-lightning/pull/499).
[(#322)](https://github.com/PennyLaneAI/catalyst/pull/322)

@qjit(autograph=True)
@qml.qnode(dev)
def f(n: int):
adjoint(inner)(n)
return qml.state()
```
* The `requirements.txt` file to build Catalyst from source has been updated with a minimum pip
version, `>=22.3`. Previous versions of pip are unable to perform editable installs when the
system-wide site-packages are read-only, even when the `--user` flag is provided.
[(#311)](https://github.com/PennyLaneAI/catalyst/pull/311)

* Fixes the issue with missing `CFP_t` in `StateVectorLQubitDynamic` when building against the
master branch of PennyLane-Lightning. This issue was introduced in
[PR 499](https://github.com/PennyLaneAI/pennylane-lightning/pull/499).
[(#322)](https://github.com/PennyLaneAI/catalyst/pull/322)
* The frontend has been updated to make it compatible with PennyLane `MeasurementProcess` objects
now being PyTrees in PennyLane version 0.33.
[(#315)](https://github.com/PennyLaneAI/catalyst/pull/315)

<h3>Contributors</h3>

Expand All @@ -223,7 +265,8 @@ This release contains contributions from (in alphabetical order):
Ali Asadi,
David Ittah,
Sergei Mironov,
Romain Moyard.
Romain Moyard,
Erick Ochoa Lopez.

# Release 0.3.1

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