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test_target_codegen_opencl.py
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202 lines (171 loc) · 7.69 KB
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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import tvm
from tvm import te
import tvm.testing
import re
target = "opencl"
@tvm.testing.requires_gpu
@tvm.testing.requires_opencl
def test_opencl_ternary_expression():
def check_if_then_else(dev, n, dtype):
A = te.placeholder((n,), name="A", dtype=dtype)
true_value = tvm.tir.const(1, dtype=dtype)
false_value = tvm.tir.const(3, dtype=dtype)
max_lhs = tvm.tir.const(2, dtype=dtype)
max_rhs = tvm.tir.if_then_else(A[0] > 0, true_value, false_value)
C = te.compute((n,), lambda i: tvm.te.max(max_lhs, max_rhs), name="C")
s = te.create_schedule(C.op)
s[C].bind(s[C].op.axis[0], te.thread_axis("threadIdx.x"))
fun = tvm.build(s, [A, C], target)
a = tvm.nd.empty((n,), A.dtype, dev)
c = tvm.nd.empty((n,), A.dtype, dev)
# Only need to test compiling here
fun(a, c)
def check_select(dev, n, dtype):
A = te.placeholder((n,), name="A", dtype=dtype)
true_value = tvm.tir.const(1, dtype=dtype)
false_value = tvm.tir.const(3, dtype=dtype)
max_lhs = tvm.tir.const(2, dtype=dtype)
max_rhs = tvm.tir.Select(A[0] > 0, true_value, false_value)
C = te.compute((n,), lambda i: tvm.te.max(max_lhs, max_rhs), name="C")
s = te.create_schedule(C.op)
s[C].bind(s[C].op.axis[0], te.thread_axis("threadIdx.x"))
fun = tvm.build(s, [A, C], target)
a = tvm.nd.empty((n,), A.dtype, dev)
c = tvm.nd.empty((n,), A.dtype, dev)
# Only need to test compiling here
fun(a, c)
dev = tvm.device(target, 0)
check_if_then_else(dev, 1, "int8")
check_if_then_else(dev, 1, "uint8")
check_if_then_else(dev, 1, "int16")
check_if_then_else(dev, 1, "uint16")
check_select(dev, 1, "int8")
check_select(dev, 1, "uint8")
check_select(dev, 1, "int16")
check_select(dev, 1, "uint16")
@tvm.testing.requires_gpu
@tvm.testing.requires_opencl
def test_opencl_inf_nan():
def check_inf_nan(dev, n, value, dtype):
A = te.placeholder((n,), name="A", dtype=dtype)
inf_value = tvm.tir.const(value, dtype=dtype)
C = te.compute((n,), lambda i: inf_value, name="C")
s = te.create_schedule(C.op)
s[C].bind(s[C].op.axis[0], te.thread_axis("threadIdx.x"))
fun = tvm.build(s, [A, C], target)
a = tvm.nd.empty((n,), A.dtype, dev)
c = tvm.nd.empty((n,), A.dtype, dev)
# Only need to test compiling here
fun(a, c)
dev = tvm.device(target, 0)
check_inf_nan(dev, 1, -float("inf"), "float32")
check_inf_nan(dev, 1, -float("inf"), "float64")
check_inf_nan(dev, 1, float("inf"), "float32")
check_inf_nan(dev, 1, float("inf"), "float64")
check_inf_nan(dev, 1, float("nan"), "float32")
check_inf_nan(dev, 1, float("nan"), "float64")
@tvm.testing.requires_gpu
@tvm.testing.requires_opencl
def test_opencl_max():
def check_max(dev, n, dtype):
A = te.placeholder((n,), name="A", dtype=dtype)
max_lhs = A[0] + tvm.tir.const(1, dtype=dtype)
max_rhs = tvm.tir.const(0, dtype=dtype)
C = te.compute((n,), lambda i: tvm.te.max(max_lhs, max_rhs), name="C")
s = te.create_schedule(C.op)
s[C].bind(s[C].op.axis[0], te.thread_axis("threadIdx.x"))
fun = tvm.build(s, [A, C], target)
a = tvm.nd.empty((n,), A.dtype, dev)
c = tvm.nd.empty((n,), A.dtype, dev)
# Only need to test compiling here
fun(a, c)
dev = tvm.device(target, 0)
check_max(dev, 1, "int8")
check_max(dev, 1, "uint8")
check_max(dev, 1, "int16")
check_max(dev, 1, "uint16")
check_max(dev, 1, "float32")
check_max(dev, 1, "float64")
def test_opencl_erf():
def check_erf(dev, n, dtype):
A = te.placeholder((n,), name="A", dtype=dtype)
C = te.compute(A.shape, lambda *i: te.erf(A(*i)), name="C")
s = te.create_schedule(C.op)
s[C].bind(s[C].op.axis[0], te.thread_axis("threadIdx.x"))
fun = tvm.build(s, [A, C], target)
source_str = fun.imported_modules[0].get_source()
matches = re.findall("erf", source_str)
error_matches = re.findall("erff", source_str)
assert len(matches) == 1 and len(error_matches) == 0
dev = tvm.device(target, 0)
check_erf(dev, 1, "float32")
check_erf(dev, 1, "float64")
@tvm.testing.requires_gpu
@tvm.testing.requires_opencl
def test_opencl_type_casting():
def check_type_casting(ctx, n, dtype):
block_size = 4
C = te.compute(
(n,),
lambda i: tvm.tir.Select(
tvm.tir.all(
*[
i // block_size == tvm.tir.const(3, "int32"),
i % block_size == tvm.tir.const(3, "int32"),
]
),
tvm.tir.const(1, dtype),
tvm.tir.const(0, dtype),
),
name="C",
)
s = te.create_schedule(C.op)
(tx, vx) = s[C].split(s[C].op.axis[0], factor=block_size)
s[C].vectorize(vx)
thrx = te.thread_axis("threadIdx.x")
s[C].bind(tx, thrx)
fun = tvm.build(s, [C], target)
c = tvm.nd.empty((n,), dtype, ctx)
assembly = fun.imported_modules[0].get_source()
if dtype == "float32":
false_branch = "((float4)(0.000000e+00f, 0.000000e+00f, 0.000000e+00f, 0.000000e+00f))"
true_branch = "((float4)(1.000000e+00f, 1.000000e+00f, 1.000000e+00f, 1.000000e+00f))"
lcond = "convert_int4(((convert_uint4(((uint4)((((int)get_local_id(0)) == 3), (((int)get_local_id(0)) == 3), (((int)get_local_id(0)) == 3), (((int)get_local_id(0)) == 3)))))"
rcond = "(convert_uint4((((int4)((0)+(1*0), (0)+(1*1), (0)+(1*2), (0)+(1*3))) == ((int4)(3, 3, 3, 3)))))"
cond = "({} && {})".format(lcond, rcond)
select = "select({}, {}, {})".format(false_branch, true_branch, cond)
count = assembly.count(select)
assert count == 1
fun(c)
elif dtype == "float16":
false_branch = "((half4)((half)0.000000e+00f, (half)0.000000e+00f, (half)0.000000e+00f, (half)0.000000e+00f))"
true_branch = "((half4)((half)1.000000e+00f, (half)1.000000e+00f, (half)1.000000e+00f, (half)1.000000e+00f))"
lcond = "convert_short4(((convert_uint4(((uint4)((((int)get_local_id(0)) == 3), (((int)get_local_id(0)) == 3), (((int)get_local_id(0)) == 3), (((int)get_local_id(0)) == 3)))))"
rcond = "(convert_uint4((((int4)((0)+(1*0), (0)+(1*1), (0)+(1*2), (0)+(1*3))) == ((int4)(3, 3, 3, 3)))))))"
cond = "({} && {})".format(lcond, rcond)
select = "select({}, {}, {})".format(false_branch, true_branch, cond)
count = assembly.count(select)
assert count == 1
fun(c)
dev = tvm.device(target, 0)
check_type_casting(dev, 16, "float32")
# fp16 is not yet supported in ci
# check_type_casting(dev, 16, "float16")
if __name__ == "__main__":
tvm.testing.main()