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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 json
import pytest
import tvm
import tvm.testing
from tvm.target import Target
def test_all_targets_device_type_verify():
"""Consistency verification for all targets' device type"""
target_kind_set = set(tvm.target.Target.list_kinds())
target_kind_set.remove("composite")
all_targets = [tvm.target.Target(t) for t in target_kind_set]
for tgt in all_targets:
if tgt.kind.name not in tvm.runtime.Device._DEVICE_NAME_TO_TYPE:
raise KeyError(
f"Cannot find target kind: {tgt.kind.name} in Device._DEVICE_NAME_TO_TYPE"
)
assert (
tgt.get_target_device_type() == tvm.runtime.Device._DEVICE_NAME_TO_TYPE[tgt.kind.name]
)
def test_target_string_parse():
target = tvm.target.Target({"kind": "cuda", "model": "unknown", "libs": ["cublas", "cudnn"]})
assert target.kind.name == "cuda"
assert target.attrs["model"] == "unknown"
assert set(target.keys) == set(["cuda", "gpu"])
assert set(target.attrs["libs"]) == set(["cublas", "cudnn"])
assert (
Target({"kind": "opencl", "device": "intel_graphics"}).attrs.get("device", "")
== "intel_graphics"
)
assert Target({"kind": "opencl", "device": "mali"}).attrs.get("device", "") == "mali"
assert Target({"kind": "llvm", "device": "arm_cpu"}).attrs.get("device", "") == "arm_cpu"
def test_target_string_with_spaces():
target = tvm.target.Target(
{"kind": "vulkan", "device_name": "Name of GPU with spaces", "device_type": "discrete"}
)
assert target.attrs["device_name"] == "Name of GPU with spaces"
assert target.attrs["device_type"] == "discrete"
target = tvm.target.Target(str(target))
assert target.attrs["device_name"] == "Name of GPU with spaces"
assert target.attrs["device_type"] == "discrete"
def test_target_llvm_options():
target = tvm.target.Target(
{"kind": "llvm", "cl-opt": ["-unroll-threshold:uint=100", "-unroll-count:uint=3"]}
)
assert sorted(target.attrs["cl-opt"]) == sorted(
["-unroll-threshold:uint=100", "-unroll-count:uint=3"]
)
def test_target_llvm_jit_options():
target = tvm.target.Target({"kind": "llvm", "jit": "mcjit"})
assert target.attrs["jit"] == "mcjit"
target = tvm.target.Target({"kind": "llvm", "jit": "orcjit"})
assert target.attrs["jit"] == "orcjit"
def test_target_llvm_vector_width():
target = tvm.target.Target({"kind": "llvm", "vector-width": 256})
assert target.attrs["vector-width"] == 256
target = tvm.target.Target({"kind": "llvm", "vector-width": 1024})
assert target.attrs["vector-width"] == 1024
def test_target_config():
"""
Test that constructing a target from a dictionary works.
"""
target_config = {
"kind": "llvm",
"keys": ["arm_cpu", "cpu"],
"device": "arm_cpu",
"libs": ["cblas"],
"mfloat-abi": "hard",
"mattr": ["+neon", "-avx512f"],
}
# Convert config dictionary to json string.
target_config_str = json.dumps(target_config)
# Test both dictionary input and json string.
for config in [target_config, target_config_str]:
target = tvm.target.Target(config)
assert target.kind.name == "llvm"
assert all([key in target.keys for key in ["arm_cpu", "cpu"]])
assert target.attrs.get("device", "") == "arm_cpu"
assert list(target.attrs.get("libs", [])) == ["cblas"]
assert target.attrs["mfloat-abi"] == "hard"
assert all([attr in target.attrs["mattr"] for attr in ["+neon", "-avx512f"]])
def test_config_map():
"""
Confirm that constructing a target with invalid
attributes fails as expected.
"""
target_config = {"kind": "llvm", "libs": {"a": "b", "c": "d"}}
with pytest.raises(ValueError):
tvm.target.Target(target_config)
def test_composite_target():
tgt = tvm.target.Target(
{"kind": "composite", "host": {"kind": "llvm"}, "devices": ["cuda", "opencl"]}
)
assert tgt.kind.name == "composite"
assert tgt.host.kind.name == "llvm"
assert len(tgt.attrs["devices"]) == 2
cuda_device, opencl_device = tgt.attrs["devices"]
assert cuda_device.kind.name == "cuda"
assert opencl_device.kind.name == "opencl"
def test_target_tag_0():
tgt = tvm.target.Target("nvidia/geforce-rtx-2080-ti")
assert tgt.kind.name == "cuda"
assert tgt.attrs["arch"] == "sm_75"
assert tgt.attrs["max_shared_memory_per_block"] == 49152
assert tgt.attrs["max_threads_per_block"] == 1024
assert tgt.attrs["thread_warp_size"] == 32
assert tgt.attrs["registers_per_block"] == 65536
def test_target_tag_1():
tgt = tvm.target.Target("nvidia/jetson-nano")
assert tgt.kind.name == "cuda"
assert tgt.attrs["arch"] == "sm_53"
assert tgt.attrs["max_shared_memory_per_block"] == 49152
assert tgt.attrs["max_threads_per_block"] == 1024
assert tgt.attrs["thread_warp_size"] == 32
assert tgt.attrs["registers_per_block"] == 32768
def test_target_tag_override():
"""Test creating a target from a tag with attribute overrides."""
tgt = tvm.target.Target({"tag": "nvidia/nvidia-a100", "l2_cache_size_bytes": 12345})
assert tgt.kind.name == "cuda"
assert tgt.attrs["arch"] == "sm_80"
# Override should take effect
assert int(tgt.attrs["l2_cache_size_bytes"]) == 12345
# Base tag fields should be preserved
assert tgt.attrs["max_shared_memory_per_block"] == 49152
assert tgt.attrs["thread_warp_size"] == 32
# Tag name should be recorded
assert tgt.tag == "nvidia/nvidia-a100"
def test_list_kinds():
targets = tvm.target.Target.list_kinds()
assert len(targets) != 0
assert "llvm" in targets
assert all(isinstance(target_name, str) for target_name in targets)
def test_target_host_tags():
tgt = tvm.target.Target("nvidia/jetson-nano", "nvidia/geforce-rtx-2080-ti")
assert tgt.kind.name == "cuda"
assert tgt.attrs["arch"] == "sm_53"
assert tgt.attrs["max_shared_memory_per_block"] == 49152
assert tgt.attrs["max_threads_per_block"] == 1024
assert tgt.attrs["thread_warp_size"] == 32
assert tgt.attrs["registers_per_block"] == 32768
assert tgt.host.kind.name == "cuda"
assert tgt.host.attrs["arch"] == "sm_75"
assert tgt.host.attrs["max_shared_memory_per_block"] == 49152
assert tgt.host.attrs["max_threads_per_block"] == 1024
assert tgt.host.attrs["thread_warp_size"] == 32
assert tgt.host.attrs["registers_per_block"] == 65536
def test_target_host_tag_dict():
tgt = tvm.target.Target("nvidia/jetson-nano", {"kind": "llvm"})
assert tgt.kind.name == "cuda"
assert tgt.attrs["arch"] == "sm_53"
assert tgt.attrs["max_shared_memory_per_block"] == 49152
assert tgt.attrs["max_threads_per_block"] == 1024
assert tgt.attrs["thread_warp_size"] == 32
assert tgt.attrs["registers_per_block"] == 32768
assert tgt.host.kind.name == "llvm"
def test_target_host_single_dict():
tgt = tvm.target.Target({"kind": "llvm", "host": "nvidia/jetson-nano"})
assert tgt.kind.name == "llvm"
assert tgt.host.kind.name == "cuda"
assert tgt.host.attrs["arch"] == "sm_53"
assert tgt.host.attrs["max_shared_memory_per_block"] == 49152
assert tgt.host.attrs["max_threads_per_block"] == 1024
assert tgt.host.attrs["thread_warp_size"] == 32
assert tgt.host.attrs["registers_per_block"] == 32768
def test_target_host_single_string():
tgt = tvm.target.Target({"kind": "cuda", "host": {"kind": "llvm"}})
assert tgt.kind.name == "cuda"
assert tgt.host.kind.name == "llvm"
def test_target_host_single_string_with_tag():
tgt = tvm.target.Target({"kind": "cuda", "host": "nvidia/jetson-nano"})
assert tgt.kind.name == "cuda"
assert tgt.host.kind.name == "cuda"
assert tgt.host.attrs["arch"] == "sm_53"
assert tgt.host.attrs["max_shared_memory_per_block"] == 49152
assert tgt.host.attrs["max_threads_per_block"] == 1024
assert tgt.host.attrs["thread_warp_size"] == 32
assert tgt.host.attrs["registers_per_block"] == 32768
def test_target_host_merge_0():
tgt = tvm.target.Target(tvm.target.Target({"kind": "cuda", "host": "nvidia/jetson-nano"}), None)
assert tgt.kind.name == "cuda"
assert tgt.host.kind.name == "cuda"
assert tgt.host.attrs["arch"] == "sm_53"
assert tgt.host.attrs["max_shared_memory_per_block"] == 49152
assert tgt.host.attrs["max_threads_per_block"] == 1024
assert tgt.host.attrs["thread_warp_size"] == 32
assert tgt.host.attrs["registers_per_block"] == 32768
def test_target_host_merge_1():
tgt = tvm.target.Target({"kind": "cuda", "host": {"kind": "llvm"}})
tgt = tvm.target.Target(tgt, tgt.host)
assert tgt.kind.name == "cuda"
assert tgt.host.kind.name == "llvm"
def test_target_host_merge_2():
"""Test picking the same host is ok."""
tgt = tvm.target.Target(
tvm.target.Target({"kind": "cuda", "host": {"kind": "llvm"}}),
tvm.target.Target("llvm"),
)
assert tgt.kind.name == "cuda"
assert tgt.host.kind.name == "llvm"
def test_target_tvm_object():
"""Test creating Target by using TVM Objects"""
String = tvm.runtime.container.String
tgt = tvm.target.Target(target={"kind": "cuda", "host": {"kind": "llvm"}})
assert tgt.kind.name == "cuda"
assert tgt.host.kind.name == "llvm"
tgt = tvm.target.Target(target=String("cuda"), host=String("llvm"))
assert tgt.kind.name == "cuda"
assert tgt.host.kind.name == "llvm"
@pytest.mark.skip(reason="Causing infinite loop because of pytest and handle issue")
def test_target_host_merge_3():
with pytest.raises(ValueError, match=r"target host has to be a string or dictionary."):
tvm.target.Target(tvm.target.Target({"kind": "cuda", "host": {"kind": "llvm"}}), 12.34)
def test_target_with_host():
tgt = tvm.target.Target("cuda")
llvm = tvm.target.Target("llvm")
tgt = tgt.with_host(llvm)
assert tgt.kind.name == "cuda"
assert tgt.host.kind.name == "llvm"
cuda_host = tvm.target.Target("nvidia/jetson-nano")
tgt = tgt.with_host(cuda_host)
assert tgt.host.kind.name == "cuda"
assert tgt.host.attrs["arch"] == "sm_53"
assert tgt.host.attrs["max_shared_memory_per_block"] == 49152
assert tgt.host.attrs["max_threads_per_block"] == 1024
assert tgt.host.attrs["thread_warp_size"] == 32
assert tgt.host.attrs["registers_per_block"] == 32768
def test_target_attr_bool_value():
target0 = Target({"kind": "vulkan", "supports_float16": True})
assert target0.attrs["supports_float16"] == 1
target1 = Target({"kind": "vulkan", "supports_float16": True})
assert target1.attrs["supports_float16"] == 1
target2 = Target({"kind": "vulkan", "supports_float16": False})
assert target2.attrs["supports_float16"] == 0
target3 = Target({"kind": "vulkan", "supports_float16": False})
assert target3.attrs["supports_float16"] == 0
def test_target_attr_l2_cache_size_bytes():
target0 = Target("nvidia/nvidia-a100")
assert int(target0.attrs.get("l2_cache_size_bytes", 0)) == 41943040
target1 = Target("nvidia/geforce-rtx-4090")
assert int(target1.attrs.get("l2_cache_size_bytes", 0)) == 75497472
def test_target_features():
target_no_features = Target("cuda")
assert target_no_features.features
assert not target_no_features.features.is_test
target_with_features = Target("test")
assert target_with_features.features.is_test
assert not target_with_features.features.is_missing
@tvm.testing.requires_cuda
@pytest.mark.parametrize("input_device", ["cuda", tvm.cuda()])
def test_target_from_device_cuda(input_device):
target = Target.from_device(input_device)
dev = tvm.cuda()
assert target.kind.name == "cuda"
assert target.attrs["max_threads_per_block"] == dev.max_threads_per_block
assert int(target.attrs["max_shared_memory_per_block"]) == dev.max_shared_memory_per_block
assert int(target.attrs["thread_warp_size"]) == dev.warp_size
assert str(target.attrs.get("arch", "")) == "sm_" + dev.compute_version.replace(".", "")
@tvm.testing.requires_rocm
@pytest.mark.parametrize("input_device", ["rocm", tvm.rocm()])
def test_target_from_device_rocm(input_device):
target = Target.from_device(input_device)
dev = tvm.rocm()
assert target.kind.name == "rocm"
assert target.attrs["mtriple"] == "amdgcn-and-amdhsa-hcc"
assert target.attrs["max_threads_per_block"] == dev.max_threads_per_block
assert int(target.attrs["max_shared_memory_per_block"]) == dev.max_shared_memory_per_block
assert int(target.attrs["thread_warp_size"]) == dev.warp_size
@tvm.testing.requires_vulkan
@pytest.mark.parametrize("input_device", ["vulkan", tvm.vulkan()])
def test_target_from_device_vulkan(input_device):
target = Target.from_device(input_device)
f_get_target_property = tvm.get_global_func("device_api.vulkan.get_target_property")
dev = tvm.vulkan()
assert target.kind.name == "vulkan"
assert target.attrs["max_threads_per_block"] == dev.max_threads_per_block
assert int(target.attrs["max_shared_memory_per_block"]) == dev.max_shared_memory_per_block
assert int(target.attrs["thread_warp_size"]) == dev.warp_size
assert target.attrs["supports_float16"] == f_get_target_property(dev, "supports_float16")
assert target.attrs["supports_int16"] == f_get_target_property(dev, "supports_int16")
assert target.attrs["supports_int8"] == f_get_target_property(dev, "supports_int8")
assert target.attrs["supports_16bit_buffer"] == f_get_target_property(
dev, "supports_16bit_buffer"
)
@tvm.testing.requires_opencl
@pytest.mark.parametrize("input_device", ["opencl", tvm.opencl()])
def test_target_from_device_opencl(input_device):
target = Target.from_device(input_device)
dev = tvm.opencl()
assert target.kind.name == "opencl"
assert target.attrs["max_threads_per_block"] == dev.max_threads_per_block
assert int(target.attrs["max_shared_memory_per_block"]) == dev.max_shared_memory_per_block
assert int(target.attrs["thread_warp_size"]) == dev.warp_size
def test_module_dict_from_deserialized_targets():
target = Target("llvm")
from tvm.script import tir as T
@T.prim_func
def func():
T.evaluate(0)
func = func.with_attr("Target", target)
target2 = tvm.ir.load_json(tvm.ir.save_json(target))
mod = tvm.IRModule({"main": func})
lib = tvm.compile(mod, target=target2)
lib["func"]()
def test_json_roundtrip():
"""Test that Target(str(target)) roundtrips correctly."""
target = Target({"kind": "llvm", "mcpu": "cortex-a53"})
target2 = Target(str(target))
assert target2.kind.name == "llvm"
assert target2.attrs["mcpu"] == "cortex-a53"
# Test with more complex target
target = Target({"kind": "cuda", "arch": "sm_80", "max_threads_per_block": 1024})
target2 = Target(str(target))
assert target2.kind.name == "cuda"
assert target2.attrs["arch"] == "sm_80"
def test_str_is_json():
"""Test that str() output is valid JSON."""
target = Target({"kind": "llvm", "mcpu": "cortex-a53"})
s = str(target)
parsed = json.loads(s)
assert parsed["kind"] == "llvm"
assert parsed["mcpu"] == "cortex-a53"
def test_cli_string_rejected():
"""Test that CLI string form is rejected."""
with pytest.raises(ValueError):
Target("llvm -mcpu=cortex-a53")
def test_webgpu_target_subgroup_attrs():
"""Test WebGPU target defaults and supports_subgroups canonicalization."""
# Default: thread_warp_size=1, supports_subgroups=False
tgt_default = Target({"kind": "webgpu"})
assert tgt_default.attrs["thread_warp_size"] == 1
assert tgt_default.attrs["supports_subgroups"] == 0
# With supports_subgroups=True: thread_warp_size is set to 32
tgt_subgroups = Target({"kind": "webgpu", "supports_subgroups": True})
assert tgt_subgroups.attrs["thread_warp_size"] == 32
assert tgt_subgroups.attrs["supports_subgroups"] == 1
if __name__ == "__main__":
tvm.testing.main()