[Frontend] Add support for native Python if statements via AutoGraph #235
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dime10
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The verifier function would always exclude the last return type (typically the quantum register), regardless of wether tracing took place in a QNode or not.
FileCheck tests are updated to check for code snippets in the autograph style, rather than the more direct style originally expected from a custom implementation.
Codecov Report
@@ Coverage Diff @@
## main #235 +/- ##
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+ Coverage 99.26% 99.31% +0.04%
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Files 38 41 +3
Lines 6923 7115 +192
Branches 343 370 +27
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+ Hits 6872 7066 +194
+ Misses 28 27 -1
+ Partials 23 22 -1
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Particular emphasis is placed on ensuring that QJIT/QNode decorators work with autograph in various configurations.
pengmai
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Aug 16, 2023
sergei-mironov
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Aug 17, 2023
.. when the user activates the feature.
Still needs to resolve top-level import issue.
Public API functions for autograph can always be imported, in particular the documentation builder can extract their docstrings without a tensorflow installation.
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sergei-mironov
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Just checking is it possible to remove a change request without explicit approval
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@dime10 please see my comment in the remaining discussion and I'm OK with closing it! The QNode copying problem worries me a little, but more in generic rather than in relation to this particular PR. While checking the sources I found that we already use a similar pattern here. I think I'll ask the PL team what do they think about the copying policies. |
josh146
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Introduces support for Python `for .. in ...:` statement capture as part of the compiled program. Similar to PR #235, AutoGraph is used to convert such statements into the equivalent Catalyst version before tracing occurs. Specifically, the following constructs are supported via AutoGraph: - `for elem in iterable:` - These get converted into a `for_loop(0, len(iterable), 1)` with `elem = iterable[i]` automatically assigned using the iteration index, assuming `iterable` is convertible to a JAX array. If this is not the case, the loop is executed as is in Python. - `for i in range(start, stop, step):` These are converted directly into their equivalent `for_loop(start, stop, step)`. Contrary to the default Python `range`, when AutoGraph is enabled `range` can also accept dynamic tracers as `start`, `stop`, `step` values. If _any_ exception is raised during the tracing of the `for_loop` body, Catalyst will fall back to Python with a warning. - `for i, elem in enemurate(iterable):` - These get converted into `for_loop(0, len(iterable), 1)` with the iteration index assigned to the variable chosen by the user (in this case `i`), and `elem = iterable[i]`. This also assumes that `iterable` is convertible to an array, and that the loop body traces without exception, otherwise the loop is executed in Python. Note that a warning is raised when when a Python fallback is triggered due to a tracing exception. Python fallbacks caused by the iterable not being convertible to array are silent. [sc-41287]
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Adds imperative style if-statement support to Catalyst.
The feature is based on the autograph module from tensorflow. Besides the if-statement transformation itself, this PR contains all necessary changes to integrate autograph into the Catalyst pipeline.
Tensorflow is assumed to be installed for tests (not added to
requirements.txtdue to the large package size!), but is otherwise an optional dependency. The user will receive a warning if they try to use it without Tensorflow being installed.A bug in the
condfunction is also fixed that didn't raise an error for mismatched return types in a classical tracing context.[sc-41286]