def simple_if_else(cond):
if_op = scf.IfOp(cond, [i32, i32], hasElse=True)
with InsertionPoint(if_op.then_block):
x_true = arith.ConstantOp(i32, 0)
y_true = arith.ConstantOp(i32, 1)
scf.YieldOp([x_true, y_true])
with InsertionPoint(if_op.else_block):
x_false = arith.ConstantOp(i32, 2)
y_false = arith.ConstantOp(i32, 3)
scf.YieldOp([x_false, y_false])
add = arith.AddIOp(if_op.results[0], if_op.results[1])
return
def testConstantOp():
c1 = arith.ConstantOp(IntegerType.get_signless(32), 42)
c2 = arith.ConstantOp(IntegerType.get_signless(64), 100)
c3 = arith.ConstantOp(F32Type.get(), 3.14)
c4 = arith.ConstantOp(F64Type.get(), 1.23)
# CHECK: 42
print(c1.literal_value)
# CHECK: 100
print(c2.literal_value)
# CHECK: 3.140000104904175
print(c3.literal_value)
# CHECK: 1.23
print(c4.literal_value)
def simple_if(cond):
if_op = scf.IfOp(cond)
with InsertionPoint(if_op.then_block):
one = arith.ConstantOp(i32, 1)
add = arith.AddIOp(one, one)
scf.YieldOp([])
return
def testConstantOps():
with Context() as ctx, Location.unknown():
module = Module.create()
with InsertionPoint(module.body):
arith.ConstantOp(value=42.42, result=F32Type.get())
# CHECK: %cst = arith.constant 4.242000e+01 : f32
print(module)
def fill_tensor(out):
zero = arith.ConstantOp(value=FloatAttr.get(f32, 0.),
result=f32).result
# TODO: FillOp.result is None. When len(results) == 1 we expect it to
# be results[0] as per _linalg_ops_gen.py. This seems like an
# orthogonal bug in the generator of _linalg_ops_gen.py.
return linalg.FillOp(output=out, value=zero).results[0]
def testVectorConstantOp():
int_type = IntegerType.get_signless(32)
vec_type = VectorType.get([2, 2], int_type)
c1 = arith.ConstantOp(
vec_type,
DenseElementsAttr.get_splat(vec_type, IntegerAttr.get(int_type, 42)))
try:
print(c1.literal_value)
except ValueError as e:
assert "only integer and float constants have literal values" in str(e)
else:
assert False
def pass_an_op_directly(arg0, arg1): one = arith.ConstantOp(F32Type.get(), 1.0) # CHECK: %[[LHS:.*]] = linalg.fill lhs = linalg.FillOp(arg0, one) # CHECK: %[[RHS:.*]] = linalg.fill rhs = linalg.FillOp(arg1, one) # CHECK: %[[INIT:.*]] = linalg.init_tensor init = linalg.InitTensorOp([4, 8], f32) # CHECK: linalg.matmul # CHECK: ins(%[[LHS]], %[[RHS]] # CHECK: outs(%[[INIT]] return linalg.matmul(lhs, rhs, outs=init)
def fill_buffer(out): zero = arith.ConstantOp(value=FloatAttr.get(f32, 0.), result=f32).result linalg.FillOp(output=out, value=zero)
def fill_tensor(out): zero = arith.ConstantOp(value=FloatAttr.get(f32, 0.), result=f32).result return linalg.FillOp(output=out, value=zero).result
def tensor_static_dim(t):
c0 = arith.ConstantOp(indexType, 0)
c1 = arith.ConstantOp(indexType, 1)
d0 = tensor.DimOp(t, c0)
d1 = tensor.DimOp(t, c1)
return [d0.result, d1.result]
def fill_buffer(out):
zero = arith.ConstantOp(value=FloatAttr.get(f32, 0.),
result=f32).result
linalg.fill(zero, outs=[out])
def fill_tensor(out):
zero = arith.ConstantOp(value=FloatAttr.get(f32, 0.),
result=f32).result
return linalg.fill(zero, outs=[out])
