[NFC][Py Reformat] Reformat python files in mlir subdir

This is an ongoing series of commits that are reformatting our
Python code.

Reformatting is done with `black`.

If you end up having problems

[NFC][Py Reformat] Reformat python files in mlir subdir

This is an ongoing series of commits that are reformatting our
Python code.

Reformatting is done with `black`.

If you end up having problems merging this commit because you
have made changes to a python file, the best way to handle that
is to run git checkout --ours <yourfile> and then reformat it
with black.

If you run into any problems, post to discourse about it and
we will try to help.

RFC Thread below:

https://discourse.llvm.org/t/rfc-document-and-standardize-python-code-style

Differential Revision: https://reviews.llvm.org/D150782

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[mlir][OpDSL] Rename function to make signedness explicit (NFC).

The revision renames the following OpDSL functions:
```
TypeFn.cast -> TypeFn.cast_signed
BinaryFn.min -> BinaryFn.min_signed
BinaryF

[mlir][OpDSL] Rename function to make signedness explicit (NFC).

The revision renames the following OpDSL functions:
```
TypeFn.cast -> TypeFn.cast_signed
BinaryFn.min -> BinaryFn.min_signed
BinaryFn.max -> BinaryFn.max_signed
```
The corresponding enum values on the C++ side are renamed accordingly:
```
#linalg.type_fn<cast> -> #linalg.type_fn<cast_signed>
#linalg.binary_fn<min> -> #linalg.binary_fn<min_signed>
#linalg.binary_fn<max> -> #linalg.binary_fn<max_signed>
```

Depends On D120110

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D120562

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[mlir][OpDSL] Add arithmetic function attributes.

The revision extends OpDSL with unary and binary function attributes. A function attribute, makes the operations used in the body of a structured op

[mlir][OpDSL] Add arithmetic function attributes.

The revision extends OpDSL with unary and binary function attributes. A function attribute, makes the operations used in the body of a structured operation configurable. For example, a pooling operation may take an aggregation function attribute that specifies if the op shall implement a min or a max pooling. The goal of this revision is to define less and more flexible operations.

We may thus for example define an element wise op:
```
linalg.elem(lhs, rhs, outs=[out], op=BinaryFn.mul)
```
If the op argument is not set the default operation is used.

Depends On D120109

Reviewed By: nicolasvasilache, aartbik

Differential Revision: https://reviews.llvm.org/D120110

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[mlir][OpDSL] Add type function attributes.

Previously, OpDSL operation used hardcoded type conversion operations (cast or cast_unsigned). Supporting signed and unsigned casts thus meant implementin

[mlir][OpDSL] Add type function attributes.

Previously, OpDSL operation used hardcoded type conversion operations (cast or cast_unsigned). Supporting signed and unsigned casts thus meant implementing two different operations. Type function attributes allow us to define a single operation that has a cast type function attribute which at operation instantiation time may be set to cast or cast_unsigned. We may for example, defina a matmul operation with a cast argument:

```
@linalg_structured_op
def matmul(A=TensorDef(T1, S.M, S.K), B=TensorDef(T2, S.K, S.N), C=TensorDef(U, S.M, S.N, output=True),
cast=TypeFnAttrDef(default=TypeFn.cast)):
C[D.m, D.n] += cast(U, A[D.m, D.k]) * cast(U, B[D.k, D.n])
```

When instantiating the operation the attribute may be set to the desired cast function:

```
linalg.matmul(lhs, rhs, outs=[out], cast=TypeFn.cast_unsigned)
```

The revsion introduces a enum in the Linalg dialect that maps one-by-one to the type functions defined by OpDSL.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D119718

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[mlir][OpDSL] Add default value to index attributes.

Index attributes had no default value, which means the attribute values had to be set on the operation. This revision adds a default parameter to

[mlir][OpDSL] Add default value to index attributes.

Index attributes had no default value, which means the attribute values had to be set on the operation. This revision adds a default parameter to `IndexAttrDef`. After the change, every index attribute has to define a default value. For example, we may define the following strides attribute:
```

```
When using the operation the default stride is used if the strides attribute is not set. The mechanism is implemented using `DefaultValuedAttr`.

Additionally, the revision uses the naming index attribute instead of attribute more consistently, which is a preparation for follow up revisions that will introduce function attributes.

Depends On D119125

Reviewed By: stellaraccident

Differential Revision: https://reviews.llvm.org/D119126

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[mlir][OpDSL] Add `TypeFn` class.

This revision introduces a the `TypeFn` class that similar to the `PrimFn` class contains an extensible set of type conversion functions. Having the same mechanism

[mlir][OpDSL] Add `TypeFn` class.

This revision introduces a the `TypeFn` class that similar to the `PrimFn` class contains an extensible set of type conversion functions. Having the same mechanism for both type conversion functions and arithmetic functions improves code consistency. Additionally, having an explicit function class and function name is a prerequisite to specify a conversion or arithmetic function via attribute. In a follow up commits, we will introduce function attributes to make OpDSL operations more generic. In particular, the goal is to handle signed and unsigned computation in one operations. Today, there is a linalg.matmul and a linalg.matmul_unsigned.

The commit implements the following changes:
- Introduce the class of type conversion functions `TypeFn`
- Replace the hardwired cast and cast_unsigned ops by the `TypeFn` counterparts
- Adapt the python and C++ code generation paths to support the new cast operations

Example:
```
cast(U, A[D.m, D.k])
```
changes to
```
TypeFn.cast(U, A[D.m, D.k])
```

Depends On D115237

Reviewed By: stellaraccident

Differential Revision: https://reviews.llvm.org/D115239

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[mlir][OpDSL] Rename `AttributeDef` to `IndexAttrDef`.

Renaming `AttributeDef` to `IndexAttrDef` prepares OpDSL to support different kinds of attributes and more closely reflects the purpose of the

[mlir][OpDSL] Rename `AttributeDef` to `IndexAttrDef`.

Renaming `AttributeDef` to `IndexAttrDef` prepares OpDSL to support different kinds of attributes and more closely reflects the purpose of the attribute.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D115237

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[mlir][linalg][python] Explicit shape and dimension order in OpDSL.

Extend the OpDSL syntax with an optional `domain` function to specify an explicit dimension order. The extension is needed to prov

[mlir][linalg][python] Explicit shape and dimension order in OpDSL.

Extend the OpDSL syntax with an optional `domain` function to specify an explicit dimension order. The extension is needed to provide more control over the dimension order instead of deducing it implicitly depending on the formulation of the tensor comprehension. Additionally, the patch also ensures the symbols are ordered according to the operand definitions of the operation.

Differential Revision: https://reviews.llvm.org/D105117

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[mlir][linalg][python] Add attribute support to the YAML codegen.

Extend the yaml code generation to support the index attributes that https://reviews.llvm.org/D104711 added to the OpDSL.

Different

[mlir][linalg][python] Add attribute support to the YAML codegen.

Extend the yaml code generation to support the index attributes that https://reviews.llvm.org/D104711 added to the OpDSL.

Differential Revision: https://reviews.llvm.org/D104712

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[mlir][linalg][python] Add attribute support to the OpDSL.

Extend the OpDSL with index attributes. After tensors and scalars, index attributes are the third operand type. An index attribute represen

[mlir][linalg][python] Add attribute support to the OpDSL.

Extend the OpDSL with index attributes. After tensors and scalars, index attributes are the third operand type. An index attribute represents a compile-time constant that is limited to index expressions. A use cases are the strides and dilations defined by convolution and pooling operations.

The patch only updates the OpDSL. The C++ yaml codegen is updated by a followup patch.

Differential Revision: https://reviews.llvm.org/D104711

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[mlir][linalg][python] Adapt the OpDSL to use scalars.

The patch replaces the existing capture functionality by scalar operands that have been introduced by https://reviews.llvm.org/D104109. Scalar

[mlir][linalg][python] Adapt the OpDSL to use scalars.

The patch replaces the existing capture functionality by scalar operands that have been introduced by https://reviews.llvm.org/D104109. Scalar operands behave as tensor operands except for the fact that they are not indexed. As a result ScalarDefs can be accessed directly as no indexing expression is needed.

The patch only updates the OpDSL. The C++ side is updated by a follow up patch.

Differential Revision: https://reviews.llvm.org/D104220

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[mir][Python][linalg] Support OpDSL extensions in C++.

The patch extends the yaml code generation to support the following new OpDSL constructs:
- captures
- constants
- iteration index accesses
- p

[mir][Python][linalg] Support OpDSL extensions in C++.

The patch extends the yaml code generation to support the following new OpDSL constructs:
- captures
- constants
- iteration index accesses
- predefined types
These changes have been introduced by revision
https://reviews.llvm.org/D101364.

Differential Revision: https://reviews.llvm.org/D102075

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