b164f23c29
Introduce support for accepting ops instead of values when constructing ops. A
single-result op can be used instead of a value, including in lists of values,
and any op can be used instead of a list of values. This is similar to, but
more powerful, than the C++ API that allows for implicitly casting an OpType to
Value if it is statically known to have a single result - the cast in Python is
based on the op dynamically having a single result, and also handles the
multi-result case. This allows to build IR in a more concise way:
op = dialect.produce_multiple_results()
other = dialect.produce_single_result()
dialect.consume_multiple_results(other, op)
instead of having to access the results manually
op = dialect.produce.multiple_results()
other = dialect.produce_single_result()
dialect.consume_multiple_results(other.result, op.operation.results)
The dispatch is implemented directly in Python and is triggered automatically
for autogenerated OpView subclasses. Extension OpView classes should use the
functions provided in ods_common.py if they want to implement this behavior.
An alternative could be to implement the dispatch in the C++ bindings code, but
it would require to forward opaque types through all Python functions down to a
binding call, which makes it hard to inspect them in Python, e.g., to obtain
the types of values.
Reviewed By: gysit
Differential Revision: https://reviews.llvm.org/D111306
84 lines
2.5 KiB
Python
84 lines
2.5 KiB
Python
# RUN: %PYTHON %s | FileCheck %s
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from mlir.ir import *
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from mlir.dialects import scf
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from mlir.dialects import std
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from mlir.dialects import builtin
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def constructAndPrintInModule(f):
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print("\nTEST:", f.__name__)
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with Context(), Location.unknown():
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module = Module.create()
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with InsertionPoint(module.body):
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f()
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print(module)
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return f
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# CHECK-LABEL: TEST: testSimpleLoop
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@constructAndPrintInModule
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def testSimpleLoop():
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index_type = IndexType.get()
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@builtin.FuncOp.from_py_func(index_type, index_type, index_type)
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def simple_loop(lb, ub, step):
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loop = scf.ForOp(lb, ub, step, [lb, lb])
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with InsertionPoint(loop.body):
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scf.YieldOp(loop.inner_iter_args)
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return
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# CHECK: func @simple_loop(%[[ARG0:.*]]: index, %[[ARG1:.*]]: index, %[[ARG2:.*]]: index)
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# CHECK: scf.for %{{.*}} = %[[ARG0]] to %[[ARG1]] step %[[ARG2]]
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# CHECK: iter_args(%[[I1:.*]] = %[[ARG0]], %[[I2:.*]] = %[[ARG0]])
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# CHECK: scf.yield %[[I1]], %[[I2]]
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# CHECK-LABEL: TEST: testInductionVar
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@constructAndPrintInModule
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def testInductionVar():
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index_type = IndexType.get()
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@builtin.FuncOp.from_py_func(index_type, index_type, index_type)
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def induction_var(lb, ub, step):
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loop = scf.ForOp(lb, ub, step, [lb])
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with InsertionPoint(loop.body):
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scf.YieldOp([loop.induction_variable])
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return
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# CHECK: func @induction_var(%[[ARG0:.*]]: index, %[[ARG1:.*]]: index, %[[ARG2:.*]]: index)
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# CHECK: scf.for %[[IV:.*]] = %[[ARG0]] to %[[ARG1]] step %[[ARG2]]
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# CHECK: scf.yield %[[IV]]
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@constructAndPrintInModule
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def testOpsAsArguments():
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index_type = IndexType.get()
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callee = builtin.FuncOp(
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"callee", ([], [index_type, index_type]), visibility="private")
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func = builtin.FuncOp("ops_as_arguments", ([], []))
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with InsertionPoint(func.add_entry_block()):
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lb = std.ConstantOp.create_index(0)
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ub = std.ConstantOp.create_index(42)
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step = std.ConstantOp.create_index(2)
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iter_args = std.CallOp(callee, [])
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loop = scf.ForOp(lb, ub, step, iter_args)
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with InsertionPoint(loop.body):
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scf.YieldOp(loop.inner_iter_args)
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std.ReturnOp([])
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# CHECK-LABEL: TEST: testOpsAsArguments
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# CHECK: func private @callee() -> (index, index)
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# CHECK: func @ops_as_arguments() {
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# CHECK: %[[LB:.*]] = constant 0
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# CHECK: %[[UB:.*]] = constant 42
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# CHECK: %[[STEP:.*]] = constant 2
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# CHECK: %[[ARGS:.*]]:2 = call @callee()
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# CHECK: scf.for %arg0 = %c0 to %c42 step %c2
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# CHECK: iter_args(%{{.*}} = %[[ARGS]]#0, %{{.*}} = %[[ARGS]]#1)
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# CHECK: scf.yield %{{.*}}, %{{.*}}
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# CHECK: return
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