def test_feed_input_tensor(test_case):
test_case.assertTrue(
oneflow.framework.env_util.HasAllMultiClientEnvVars())
x = flow.Tensor(1, 1, 10, 10)
flow.nn.init.uniform_(x, a=-1.0, b=1.0)
session = session_ctx.GetDefaultSession()
test_case.assertTrue(isinstance(session, MultiClientSession))
session.TryInit()
with oneflow._oneflow_internal.lazy_mode.guard(True):
oneflow._oneflow_internal.JobBuildAndInferCtx_Open(
"cc_test_input_op_expr_job")
job_conf = (oneflow._oneflow_internal.oneflow.core.job.job_conf.
JobConfigProto())
job_conf.set_job_name("cc_test_input_op_expr_job")
job_conf.mutable_predict_conf()
c_api_util.CurJobBuildAndInferCtx_SetJobConf(job_conf)
op_name = "cc_Input_0"
input_conf = (oneflow._oneflow_internal.oneflow.core.operator.
op_conf.FeedInputOpConf())
input_conf.set_in_0("EagerTensorInput")
input_conf.set_out_0("out_0")
input_op = oneflow._oneflow_internal.one.FeedInputOpExpr(
op_name, input_conf, ["in_0"], ["out_0"])
attrs = oneflow._oneflow_internal.MutableCfgAttrMap()
out_tensor = _C.dispatch_feed_input(input_op, x)
test_case.assertEqual(out_tensor.shape, (1, 1, 10, 10))
test_case.assertTrue(out_tensor.is_lazy)
test_case.assertTrue(out_tensor.is_local)
oneflow._oneflow_internal.JobBuildAndInferCtx_Close()
def test_feed_var_tensor(test_case):
test_case.assertTrue(
oneflow.framework.env_util.HasAllMultiClientEnvVars())
x = flow.Tensor(1, 1, 10, 10)
flow.nn.init.uniform_(x, a=-1.0, b=1.0)
session = session_ctx.GetDefaultSession()
test_case.assertTrue(isinstance(session, MultiClientSession))
session.TryInit()
with oneflow._oneflow_internal.lazy_mode.guard(True):
oneflow._oneflow_internal.JobBuildAndInferCtx_Open(
"cc_test_variable_op_expr_job")
job_conf = oneflow.core.job.job_conf_pb2.JobConfigProto()
job_conf.job_name = "cc_test_variable_op_expr_job"
job_conf.predict_conf.SetInParent()
c_api_util.CurJobBuildAndInferCtx_SetJobConf(job_conf)
op_name = "cc_Variable_0"
var_conf = oneflow.core.operator.op_conf_pb2.FeedVariableOpConf()
var_conf.in_0 = "EagerTensorInput"
var_conf.out_0 = "out_0"
var_conf_str = text_format.MessageToString(var_conf)
var_op = oneflow._oneflow_internal.one.FeedVariableOpExpr(
op_name, var_conf_str, ["in_0"], ["out_0"])
out_tensor = _C.dispatch_feed_variable(var_op, x, l2=0)
test_case.assertEqual(out_tensor.shape, (1, 1, 10, 10))
test_case.assertTrue(out_tensor.is_lazy)
test_case.assertTrue(out_tensor.is_local)
oneflow._oneflow_internal.JobBuildAndInferCtx_Close()
def open(self, job_name, signature=None, batch_size=None):
self._check_status(self.SessionStatus.OPEN)
c_api_util.JobBuildAndInferCtx_Open(job_name)
if signature is not None:
self.set_job_signature(job_name, signature)
if isinstance(batch_size, int):
self.set_job_batch_size(job_name, batch_size)
job_conf = self._get_job_conf(job_name)
c_api_util.CurJobBuildAndInferCtx_SetJobConf(job_conf)
# NOTE(chengcheng): placement_util is unavailable.
# tag_and_dev_ids = placement_util.GetDefaultMachineDeviceIds(
# self.config_proto_.resource
# )
scope = scope_util.MakeInitialScope(job_conf, "cpu", ["0:0"], None,
self.is_mirrored_)
with runtime_mode.ModeScope(runtime_mode.GLOBAL_MODE):
with scope_util.ScopeContext(scope):
self.cur_job_name_ = job_name
yield self
self.cur_job_name_ = None
oneflow._oneflow_internal.JobBuildAndInferCtx_Close()
def __enter__(self):
c_api_util.JobBuildAndInferCtx_Open(self._job_conf.job_name())
c_api_util.CurJobBuildAndInferCtx_SetJobConf(self._job_conf)
def _test_user_op_graph(test_case, is_cuda):
test_case.assertTrue(oneflow.framework.env_util.HasAllMultiClientEnvVars())
x0 = flow.tensor(np.random.rand(20, 30), dtype=flow.float32)
weight0 = flow.tensor(np.random.rand(30, 50), dtype=flow.float32)
x1 = flow.tensor(np.random.rand(50, 70), dtype=flow.float32)
if is_cuda:
x0 = x0.to(device=flow.device("cuda"))
weight0 = weight0.to(device=flow.device("cuda"))
x1 = x1.to(device=flow.device("cuda"))
# NOTE(chengcheng): this tiny net is:
# x0 * weight0 -> out0
# relu(out0) -> y0
# y0 * x1 -> out1
# relu(out1) -> y1
session = session_ctx.GetDefaultSession()
test_case.assertTrue(isinstance(session, MultiClientSession))
session.TryInit()
with oneflow._oneflow_internal.lazy_mode.guard(True):
oneflow._oneflow_internal.JobBuildAndInferCtx_Open(
"cc_test_user_op_expr_job_with_cuda" + str(is_cuda))
job_conf = oneflow._oneflow_internal.oneflow.core.job.job_conf.JobConfigProto(
)
job_conf.set_job_name("cc_test_user_op_expr_job_with_cuda" +
str(is_cuda))
job_conf.mutable_predict_conf()
c_api_util.CurJobBuildAndInferCtx_SetJobConf(job_conf)
# input_conf.set_in_0("EagerTensorInput")
# input_conf.set_out_0("out_0")
x0_conf = (oneflow._oneflow_internal.oneflow.core.operator.op_conf.
FeedInputOpConf())
x0_op = oneflow._oneflow_internal.one.FeedInputOpExpr(
"cc_Input_0", x0_conf, ["in_0"], ["out_0"])
x1_conf = (oneflow._oneflow_internal.oneflow.core.operator.op_conf.
FeedInputOpConf())
x1_op = oneflow._oneflow_internal.one.FeedInputOpExpr(
"cc_Input_1", x1_conf, ["in_0"], ["out_0"])
weight0_conf = (oneflow._oneflow_internal.oneflow.core.operator.
op_conf.FeedVariableOpConf())
weight0_op = oneflow._oneflow_internal.one.FeedVariableOpExpr(
"cc_Variable_0", weight0_conf, ["in_0"], ["out_0"])
output_conf = (oneflow._oneflow_internal.oneflow.core.operator.op_conf.
FetchOutputOpConf())
output_op = oneflow._oneflow_internal.one.FetchOutputOpExpr(
"cc_Output_0", output_conf, ["in_0"], ["out_0"])
x0_lazy_tensor = _C.dispatch_feed_input(x0_op, x0)
x1_lazy_tensor = _C.dispatch_feed_input(x1_op, x1)
weight0_lazy_tensor = _C.dispatch_feed_input(weight0_op, weight0)
test_case.assertEqual(x0_lazy_tensor.shape, (20, 30))
test_case.assertTrue(x0_lazy_tensor.is_lazy)
test_case.assertEqual(weight0_lazy_tensor.shape, (30, 50))
test_case.assertTrue(weight0_lazy_tensor.is_lazy)
test_case.assertEqual(x1_lazy_tensor.shape, (50, 70))
test_case.assertTrue(x1_lazy_tensor.is_lazy)
out0 = flow._C.matmul(x0_lazy_tensor, weight0_lazy_tensor)
test_case.assertEqual(out0.shape, (20, 50))
test_case.assertTrue(out0.is_lazy)
y0 = flow._C.relu(out0)
test_case.assertEqual(y0.shape, (20, 50))
test_case.assertTrue(y0.is_lazy)
out1 = flow._C.matmul(y0, x1_lazy_tensor)
test_case.assertEqual(out1.shape, (20, 70))
test_case.assertTrue(out1.is_lazy)
y1 = flow._C.relu(out1)
test_case.assertEqual(y1.shape, (20, 70))
test_case.assertTrue(y1.is_lazy)
eager_output = _C.dispatch_fetch_output(output_op, y1)
test_case.assertEqual(eager_output.shape, (20, 70))
test_case.assertTrue(not eager_output.is_lazy)
if is_cuda:
test_case.assertTrue(x0_lazy_tensor.is_cuda)
test_case.assertTrue(x1_lazy_tensor.is_cuda)
test_case.assertTrue(weight0_lazy_tensor.is_cuda)
test_case.assertTrue(out0.is_cuda)
test_case.assertTrue(y0.is_cuda)
test_case.assertTrue(out1.is_cuda)
test_case.assertTrue(y1.is_cuda)
oneflow._oneflow_internal.JobBuildAndInferCtx_Close()