def test_basic(dev, target):
mod, params = mlp.get_workload(batch_size=1)
if not profiler_vm.enabled():
return
exe = relay.vm.compile(mod, target, params=params)
vm = profiler_vm.VirtualMachineProfiler(exe, dev)
data = np.random.rand(1, 1, 28, 28).astype("float32")
res = vm.profile(tvm.nd.array(data), func_name="main")
assert "softmax" in str(res)
def test_basic():
mod, params = resnet.get_workload()
if not profiler_vm.enabled():
return
for target, dev in enabled_targets():
exe = relay.vm.compile(mod, target, params=params)
vm = profiler_vm.VirtualMachineProfiler(exe, dev)
data = np.random.rand(1, 3, 224, 224).astype("float32")
res = vm.invoke("main", [data])
print("\n{}".format(vm.get_stat()))
print("\n{}".format(vm.get_stat(False)))
def test_basic():
mod, params = resnet.get_workload()
target = 'llvm'
ctx = tvm.cpu()
if not profiler_vm.enabled():
return
exe = relay.vm.compile(mod, target, params=params)
vm = profiler_vm.VirtualMachineProfiler(exe, ctx)
data = np.random.rand(1, 3, 224, 224).astype('float32')
res = vm.invoke("main", [data])
print("\n{}".format(vm.get_stat()))
print("\n{}".format(vm.get_stat(False)))
rows = []
reader = csv.reader(f, delimiter=",")
# force parsing
in_header = True
for row in reader:
if in_header:
headers = row
in_header = False
rows = [[] for x in headers]
else:
for i in range(len(row)):
rows[i].append(row[i])
return dict(zip(headers, rows))
@pytest.mark.skipif(not profiler_vm.enabled(),
reason="VM Profiler not enabled")
@tvm.testing.parametrize_targets
def test_vm(target, dev):
dtype = "float32"
x = relay.var("x", shape=(relay.Any(), relay.Any()), dtype=dtype)
y = relay.var("y", shape=(relay.Any(), relay.Any()), dtype=dtype)
mod = tvm.IRModule()
mod["main"] = relay.Function([x, y], relay.add(x, y))
exe = relay.vm.compile(mod, target)
vm = profiler_vm.VirtualMachineProfiler(exe, dev)
data = np.random.rand(28, 28).astype("float32")
report = vm.profile(data, data, func_name="main")
assert "fused_add" in str(report)
assert "Total" in str(report)
rows = []
reader = csv.reader(f, delimiter=",")
# force parsing
in_header = True
for row in reader:
if in_header:
headers = row
in_header = False
rows = [[] for x in headers]
else:
for i in range(len(row)):
rows[i].append(row[i])
return dict(zip(headers, rows))
@pytest.mark.skipif(not profiler_vm.enabled(), reason="VM Profiler not enabled")
@tvm.testing.parametrize_targets
def test_vm(target, dev):
mod, params = mlp.get_workload(1)
exe = relay.vm.compile(mod, target, params=params)
vm = profiler_vm.VirtualMachineProfiler(exe, dev)
data = np.random.rand(1, 1, 28, 28).astype("float32")
report = vm.profile(data, func_name="main")
assert "fused_nn_softmax" in str(report)
assert "Total" in str(report)
csv = read_csv(report)
assert "Hash" in csv.keys()
assert all([float(x) > 0 for x in csv["Duration (us)"]])