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This enables changing the location of a block argument. Follows the
approach for updating type of block arg.
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Identified with llvm-use-ranges.
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(#162591)
`PassManager::enableStatistics` seems currently missing in both C API
and Python bindings. So here we added them in this PR, which includes
the `PassDisplayMode` enum type and the `EnableStatistics` method.
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It closes #155996.
This PR added a method `add(callable, ..)` to
`mlir.passmanager.PassManager` to accept a callable object for defining
passes in the Python side.
This is a simple example of a Python-defined pass.
```python
from mlir.passmanager import PassManager
def demo_pass_1(op):
# do something with op
pass
class DemoPass:
def __init__(self, ...):
pass
def __call__(op):
# do something
pass
demo_pass_2 = DemoPass(..)
pm = PassManager('any', ctx)
pm.add(demo_pass_1)
pm.add(demo_pass_2)
pm.add("registered-passes")
pm.run(..)
```
---------
Co-authored-by: cnb.bsD2OPwAgEA <QejD2DJ2eEahUVy6Zg0aZI+cnb.bsD2OPwAgEA@noreply.cnb.cool>
Co-authored-by: Maksim Levental <maksim.levental@gmail.com>
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https://github.com/llvm/llvm-project/pull/155114 broke op hashing
(because the python objects ceased to be reference equivalent). This PR
fixes by binding `OperationEquivalence::computeHash`.
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Historical context: `PyMlirContext::liveOperations` was an optimization
meant to cut down on the number of Python object allocations and
(partially) a mechanism for updating validity of ops after
transformation. E.g. during walking/transforming the AST. See original
patch [here](https://reviews.llvm.org/D87958).
Inspired by a
[renewed](https://github.com/llvm/llvm-project/pull/139721#issuecomment-3217131918)
interest in https://github.com/llvm/llvm-project/pull/139721 (which has
become a little stale...)
<p align="center">
<img width="504" height="375" alt="image"
src="https://github.com/user-attachments/assets/0daad562-d3d1-4876-8d01-5dba382ab186"
/>
</p>
In the previous go-around
(https://github.com/llvm/llvm-project/pull/92631) there were two issues
which have been resolved
1. ops that were "fetched" under a root op which has been transformed
are no longer reported as invalid. We simply "[formally
forbid](https://github.com/llvm/llvm-project/pull/92631#issuecomment-2119397018)"
this;
2. `Module._CAPICreate(module_capsule)` must now be followed by a
`module._clear_mlir_module()` to prevent double-freeing of the actual
`ModuleOp` object (i.e. calling the dtor on the
`OwningOpRef<ModuleOp>`):
```python
module = ...
module_dup = Module._CAPICreate(module._CAPIPtr)
module._clear_mlir_module()
```
- **the alternative choice** here is to remove the `Module._CAPICreate`
API altogether and replace it with something like `Module._move(module)`
which will do both `Module._CAPICreate` and `module._clear_mlir_module`.
Note, the other approach I explored last year was a [weakref
system](https://github.com/llvm/llvm-project/pull/97340) for
`mlir::Operation` which would effectively hoist this `liveOperations`
thing into MLIR core. Possibly doable but I now believe it's a bad idea.
The other potentially breaking change is `is`, which checks object
equality rather than value equality, will now report `False` because we
are always allocating `new` Python objects (ie that's the whole point of
this change). Users wanting to check equality for `Operation` and
`Module` should use `==`.
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This function isn't exposed in any header and unused in the codebase.
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BuiltinTypes.cpp (NFC)
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The motivation is to avoid having to negate `isDynamic*` checks, avoid
double negations, and allow for `ShapedType::isStaticDim` to be used in
ADT functions without having to wrap it in a lambda performing the
negation.
Also add the new functions to C and Python bindings.
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bind `block.getSuccessor` and `block.getPredecessors`.
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bindings (#131521)
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python bindings (#130109)
In some projects like JAX ir.Context are used with disabled multi-threading to avoid
caching multiple threading pools:
https://github.com/jax-ml/jax/blob/623865fe9538100d877ba9d36f788d0f95a11ed2/jax/_src/interpreters/mlir.py#L606-L611
However, when context has enabled multithreading it also uses locks on
the StorageUniquers and this can be helpful to avoid data races in the
multi-threaded execution (for example with free-threaded cpython,
https://github.com/jax-ml/jax/issues/26272).
With this PR user can enable the multi-threading: 1) enables additional
locking and 2) set a shared threading pool such that cached contexts can
have one global pool.
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(#129351)
This PR extends the python bindings for CallSiteLoc, FileLineColRange,
FusedLoc, NameLoc with field accessors. It also adds the missing
`value.location` accessor.
I also did some "spring cleaning" here (`cast` -> `dyn_cast`) after
running into some of my own illegal casts.
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C/Python APIs (#129607)
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For extremely large models, it may be inefficient to load the model into
memory in Python prior to passing it to the MLIR C APIs for
deserialization. This change adds an API to parse a ModuleOp directly
from a file path.
Re-lands
[4e14b8a](https://github.com/llvm/llvm-project/commit/4e14b8afb44af58ab7073bb8c0b52875599b0ae1).
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Reverts llvm/llvm-project#125736
The gcc7 Bot is broken at the moment.
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For extremely large models, it may be inefficient to load the model into
memory in Python prior to passing it to the MLIR C APIs for
deserialization. This change adds an API to parse a ModuleOp directly
from a file path.
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(#124804)
This reapplies #118947 and adapts to nanobind.
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This reverts commit 9dd762e8b10586e749b0ddf3542e5dccf8392395.
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Model the `IndexType` as `uint64_t` when converting to a python integer.
With the python bindings,
```python
DenseIntElementsAttr(op.attributes["attr"])
```
used to `assert` when `attr` had `index` type like `dense<[1, 2, 3, 4]>
: vector<4xindex>`.
---------
Co-authored-by: Christopher McGirr <christopher.mcgirr@amd.com>
Co-authored-by: Tiago Trevisan Jost <tiago.trevisanjost@amd.com>
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Plumbs through creating file ranges to C and Python.
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Turn free-standing `MemRefType`-related helper functions in
`BuiltinTypes.h` into member functions.
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Remove `type.isFloat4E2M1FN()` etc. Use `isa<Float4E2M1FNType>(type)`
instead.
For details, see:
https://discourse.llvm.org/t/rethink-on-approach-to-low-precision-fp-types/82361/28
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This commit removes convenience methods from `FloatType` to make it
independent of concrete interface implementations.
See discussion here:
https://discourse.llvm.org/t/rethink-on-approach-to-low-precision-fp-types/82361
Note for LLVM integration: Replace `FloatType::getF32(` with
`Float32Type::get(` etc.
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Close https://github.com/llvm/llvm-project/pull/65854
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(#117339)
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Problem originally described in [the forums
here](https://discourse.llvm.org/t/mlir-python-expose-replaceallusesexcept/83068/1).
Using the MLIR Python bindings, the method
[`replaceAllUsesWith`](https://mlir.llvm.org/doxygen/classmlir_1_1Value.html#ac56b0fdb6246bcf7fa1805ba0eb71aa2)
for `Value` is exposed, e.g.,
```python
orig_value.replace_all_uses_with(
new_value
)
```
However, in my use-case I am separating a block into multiple blocks, so
thus want to exclude certain Operations from having their Values
replaced (since I want them to diverge).
Within Value, we have
[`replaceAllUsesExcept`](https://mlir.llvm.org/doxygen/classmlir_1_1Value.html#a9ec8d5c61f8a6aada4062f609372cce4),
where we can pass the Operations which should be skipped.
This is not currently exposed in the Python bindings: this PR fixes
this. Adds `replace_all_uses_except`, which works with individual
Operations, and lists of Operations.
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Eliminating g++ warnings. Mostly declaring "[[maybe_unused]]", adding
return statements where missing and fixing casts.
@rengolin
---------
Co-authored-by: Benjamin Maxwell <macdue@dueutil.tech>
Co-authored-by: Renato Golin <rengolin@systemcall.eu>
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This PR adds `f8E8M0FNU` type to MLIR.
`f8E8M0FNU` type is proposed in [OpenCompute MX
Specification](https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf).
It defines a 8-bit floating point number with bit layout S0E8M0. Unlike
IEEE-754 types, there are no infinity, denormals, zeros or negative
values.
```c
f8E8M0FNU
- Exponent bias: 127
- Maximum stored exponent value: 254 (binary 1111'1110)
- Maximum unbiased exponent value: 254 - 127 = 127
- Minimum stored exponent value: 0 (binary 0000'0000)
- Minimum unbiased exponent value: 0 − 127 = -127
- Doesn't have zero
- Doesn't have infinity
- NaN is encoded as binary 1111'1111
Additional details:
- Zeros cannot be represented
- Negative values cannot be represented
- Mantissa is always 1
```
Related PRs:
- [PR-107127](https://github.com/llvm/llvm-project/pull/107127)
[APFloat] Add APFloat support for E8M0 type
- [PR-105573](https://github.com/llvm/llvm-project/pull/105573) [MLIR]
Add f6E3M2FN type - was used as a template for this PR
- [PR-107999](https://github.com/llvm/llvm-project/pull/107999) [MLIR]
Add f6E2M3FN type
- [PR-108877](https://github.com/llvm/llvm-project/pull/108877) [MLIR]
Add f4E2M1FN type
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This PR adds `f4E2M1FN` type to mlir.
`f4E2M1FN` type is proposed in [OpenCompute MX
Specification](https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf).
It defines a 4-bit floating point number with bit layout S1E2M1. Unlike
IEEE-754 types, there are no infinity or NaN values.
```c
f4E2M1FN
- Exponent bias: 1
- Maximum stored exponent value: 3 (binary 11)
- Maximum unbiased exponent value: 3 - 1 = 2
- Minimum stored exponent value: 1 (binary 01)
- Minimum unbiased exponent value: 1 − 1 = 0
- Has Positive and Negative zero
- Doesn't have infinity
- Doesn't have NaNs
Additional details:
- Zeros (+/-): S.00.0
- Max normal number: S.11.1 = ±2^(2) x (1 + 0.5) = ±6.0
- Min normal number: S.01.0 = ±2^(0) = ±1.0
- Min subnormal number: S.00.1 = ±2^(0) x 0.5 = ±0.5
```
Related PRs:
- [PR-95392](https://github.com/llvm/llvm-project/pull/95392) [APFloat]
Add APFloat support for FP4 data type
- [PR-105573](https://github.com/llvm/llvm-project/pull/105573) [MLIR]
Add f6E3M2FN type - was used as a template for this PR
- [PR-107999](https://github.com/llvm/llvm-project/pull/107999) [MLIR]
Add f6E2M3FN type
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When using the `enable_ir_printing` API from Python, it invokes IR
printing with default args, printing the IR before each pass and
printing IR after pass only if there have been changes. This PR attempts
to align the `enable_ir_printing` API with the documentation
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This PR adds `f6E2M3FN` type to mlir.
`f6E2M3FN` type is proposed in [OpenCompute MX
Specification](https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf).
It defines a 6-bit floating point number with bit layout S1E2M3. Unlike
IEEE-754 types, there are no infinity or NaN values.
```c
f6E2M3FN
- Exponent bias: 1
- Maximum stored exponent value: 3 (binary 11)
- Maximum unbiased exponent value: 3 - 1 = 2
- Minimum stored exponent value: 1 (binary 01)
- Minimum unbiased exponent value: 1 − 1 = 0
- Has Positive and Negative zero
- Doesn't have infinity
- Doesn't have NaNs
Additional details:
- Zeros (+/-): S.00.000
- Max normal number: S.11.111 = ±2^(2) x (1 + 0.875) = ±7.5
- Min normal number: S.01.000 = ±2^(0) = ±1.0
- Max subnormal number: S.00.111 = ±2^(0) x 0.875 = ±0.875
- Min subnormal number: S.00.001 = ±2^(0) x 0.125 = ±0.125
```
Related PRs:
- [PR-94735](https://github.com/llvm/llvm-project/pull/94735) [APFloat]
Add APFloat support for FP6 data types
- [PR-105573](https://github.com/llvm/llvm-project/pull/105573) [MLIR]
Add f6E3M2FN type - was used as a template for this PR
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Support IntegerSet attribute python binding.
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This PR adds `f6E3M2FN` type to mlir.
`f6E3M2FN` type is proposed in [OpenCompute MX
Specification](https://www.opencompute.org/documents/ocp-microscaling-formats-mx-v1-0-spec-final-pdf).
It defines a 6-bit floating point number with bit layout S1E3M2. Unlike
IEEE-754 types, there are no infinity or NaN values.
```c
f6E3M2FN
- Exponent bias: 3
- Maximum stored exponent value: 7 (binary 111)
- Maximum unbiased exponent value: 7 - 3 = 4
- Minimum stored exponent value: 1 (binary 001)
- Minimum unbiased exponent value: 1 − 3 = −2
- Has Positive and Negative zero
- Doesn't have infinity
- Doesn't have NaNs
Additional details:
- Zeros (+/-): S.000.00
- Max normal number: S.111.11 = ±2^(4) x (1 + 0.75) = ±28
- Min normal number: S.001.00 = ±2^(-2) = ±0.25
- Max subnormal number: S.000.11 = ±2^(-2) x 0.75 = ±0.1875
- Min subnormal number: S.000.01 = ±2^(-2) x 0.25 = ±0.0625
```
Related PRs:
- [PR-94735](https://github.com/llvm/llvm-project/pull/94735) [APFloat]
Add APFloat support for FP6 data types
- [PR-97118](https://github.com/llvm/llvm-project/pull/97118) [MLIR] Add
f8E4M3 type - was used as a template for this PR
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This PR adds `f8E3M4` type to mlir.
`f8E3M4` type follows IEEE 754 convention
```c
f8E3M4 (IEEE 754)
- Exponent bias: 3
- Maximum stored exponent value: 6 (binary 110)
- Maximum unbiased exponent value: 6 - 3 = 3
- Minimum stored exponent value: 1 (binary 001)
- Minimum unbiased exponent value: 1 − 3 = −2
- Precision specifies the total number of bits used for the significand (mantissa),
including implicit leading integer bit = 4 + 1 = 5
- Follows IEEE 754 conventions for representation of special values
- Has Positive and Negative zero
- Has Positive and Negative infinity
- Has NaNs
Additional details:
- Max exp (unbiased): 3
- Min exp (unbiased): -2
- Infinities (+/-): S.111.0000
- Zeros (+/-): S.000.0000
- NaNs: S.111.{0,1}⁴ except S.111.0000
- Max normal number: S.110.1111 = +/-2^(6-3) x (1 + 15/16) = +/-2^3 x 31 x 2^(-4) = +/-15.5
- Min normal number: S.001.0000 = +/-2^(1-3) x (1 + 0) = +/-2^(-2)
- Max subnormal number: S.000.1111 = +/-2^(-2) x 15/16 = +/-2^(-2) x 15 x 2^(-4) = +/-15 x 2^(-6)
- Min subnormal number: S.000.0001 = +/-2^(-2) x 1/16 = +/-2^(-2) x 2^(-4) = +/-2^(-6)
```
Related PRs:
- [PR-99698](https://github.com/llvm/llvm-project/pull/99698) [APFloat]
Add support for f8E3M4 IEEE 754 type
- [PR-97118](https://github.com/llvm/llvm-project/pull/97118) [MLIR] Add
f8E4M3 IEEE 754 type
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This PR adds `f8E4M3` type to mlir.
`f8E4M3` type follows IEEE 754 convention
```c
f8E4M3 (IEEE 754)
- Exponent bias: 7
- Maximum stored exponent value: 14 (binary 1110)
- Maximum unbiased exponent value: 14 - 7 = 7
- Minimum stored exponent value: 1 (binary 0001)
- Minimum unbiased exponent value: 1 − 7 = −6
- Precision specifies the total number of bits used for the significand (mantisa),
including implicit leading integer bit = 3 + 1 = 4
- Follows IEEE 754 conventions for representation of special values
- Has Positive and Negative zero
- Has Positive and Negative infinity
- Has NaNs
Additional details:
- Max exp (unbiased): 7
- Min exp (unbiased): -6
- Infinities (+/-): S.1111.000
- Zeros (+/-): S.0000.000
- NaNs: S.1111.{001, 010, 011, 100, 101, 110, 111}
- Max normal number: S.1110.111 = +/-2^(7) x (1 + 0.875) = +/-240
- Min normal number: S.0001.000 = +/-2^(-6)
- Max subnormal number: S.0000.111 = +/-2^(-6) x 0.875 = +/-2^(-9) x 7
- Min subnormal number: S.0000.001 = +/-2^(-6) x 0.125 = +/-2^(-9)
```
Related PRs:
- [PR-97179](https://github.com/llvm/llvm-project/pull/97179) [APFloat]
Add support for f8E4M3 IEEE 754 type
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Expose `elideLargeResourceString` to the c api.
This was done in the same way as `elideLargeElementsAttrs` is exposed.
The docs were grabbed from the `elideLargeResourceString` method and
forwarded here.
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This patch is part of a project to move the Presburger library into
LLVM.
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bindings (#96150)
The MLIR C and Python Bindings expose various methods from
`mlir::OpPrintingFlags` . This PR adds a binding for the `skipRegions`
method, which allows to skip the printing of Regions when printing Ops.
It also exposes this option as parameter in the python `get_asm` and
`print` methods
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(#94305)
The PR implements MLIR Python Bindings for a few simple edit operations
on Block arguments, namely, `add_argument`, `erase_argument`, and
`erase_arguments`.
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This change cleans up call sites. Next step is to mark the member
functions deprecated.
See https://mlir.llvm.org/deprecation and
https://discourse.llvm.org/t/preferred-casting-style-going-forward.
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This commit adds `walk` method to PyOperationBase that uses a python
object as a callback, e.g. `op.walk(callback)`. Currently callback must
return a walk result explicitly.
We(SiFive) have implemented walk method with python in our internal
python tool for a while. However the overhead of python is expensive and
it didn't scale well for large MLIR files. Just replacing walk with this
version reduced the entire execution time of the tool by 30~40% and
there are a few configs that the tool takes several hours to finish so
this commit significantly improves tool performance.
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This PR adds the following to the mlir c api:
- The disctinct mlir builtin attribute.
- LLVM attributes (mostly debug related ones)
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The base class llvm::ThreadPoolInterface will be renamed
llvm::ThreadPool in a subsequent commit.
This is a breaking change: clients who use to create a ThreadPool must
now create a DefaultThreadPool instead.
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(#82094)
This decouples the public API used to enqueue tasks and wait for
completion from the actual implementation, and opens up the possibility
for clients to set their own thread pool implementation for the pool.
https://discourse.llvm.org/t/construct-threadpool-from-vector-of-existing-threads/76883
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This allows to
* check if a given ir.Type is a floating point type via isinstance() or
issubclass()
* get the bitwidth of a floating point type
See motivation and discussion in
https://discourse.llvm.org/t/add-floattype-to-mlir-python-bindings/76959.
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