def testIsVariableInitialized(self):
for use_gpu in [True, False]:
with self.test_session(use_gpu=use_gpu):
v0 = state_ops.variable_op([1, 2], dtypes.float32)
self.assertEqual(False, variables.is_variable_initialized(v0).eval())
state_ops.assign(v0, [[2.0, 3.0]]).eval()
self.assertEqual(True, variables.is_variable_initialized(v0).eval())
def testPrepareSessionWithReadyForLocalInitOp(self):
with ops.Graph().as_default():
v = variables.Variable(1, name="v")
w = variables.Variable(
v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.test_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
self.assertEqual(False, variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=variables.report_uninitialized_variables(
variables.global_variables()),
local_init_op=w.initializer)
sess = sm2.prepare_session("", init_op=v.initializer)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEquals(1, sess.run(v))
self.assertEquals(1, sess.run(w))
def testIsVariableInitialized(self):
for use_gpu in [True, False]:
with self.test_session(use_gpu=use_gpu):
v0 = state_ops.variable_op([1, 2], dtypes.float32)
self.assertEqual(False, variables.is_variable_initialized(v0).eval())
state_ops.assign(v0, [[2.0, 3.0]]).eval()
self.assertEqual(True, variables.is_variable_initialized(v0).eval())
def testWaitForSessionLocalInit(self):
server = server_lib.Server.create_local_server()
with ops.Graph().as_default() as graph:
v = variables.Variable(1, name="v")
w = variables.Variable(v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
sm = session_manager.SessionManager(
graph=graph,
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=variables.
report_uninitialized_variables(variables.global_variables()),
local_init_op=w.initializer)
# Initialize v but not w
s = session_lib.Session(server.target, graph=graph)
s.run(v.initializer)
sess = sm.wait_for_session(server.target, max_wait_secs=3)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEquals(1, sess.run(v))
self.assertEquals(1, sess.run(w))
def testPrepareSessionFails(self):
checkpoint_dir = os.path.join(self.get_temp_dir(), "prepare_session")
checkpoint_dir2 = os.path.join(self.get_temp_dir(), "prepare_session2")
try:
gfile.DeleteRecursively(checkpoint_dir)
gfile.DeleteRecursively(checkpoint_dir2)
except errors.OpError:
pass # Ignore
gfile.MakeDirs(checkpoint_dir)
with ops.Graph().as_default():
v = variables.Variable([1.0, 2.0, 3.0], name="v")
sm = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables())
saver = saver_lib.Saver({"v": v})
sess = sm.prepare_session(
"",
init_op=variables.global_variables_initializer(),
saver=saver,
checkpoint_dir=checkpoint_dir)
self.assertAllClose([1.0, 2.0, 3.0], sess.run(v))
checkpoint_filename = os.path.join(checkpoint_dir,
"prepare_session_checkpoint")
saver.save(sess, checkpoint_filename)
# Create a new Graph and SessionManager and recover.
with ops.Graph().as_default():
# Renames the checkpoint directory.
os.rename(checkpoint_dir, checkpoint_dir2)
gfile.MakeDirs(checkpoint_dir)
v = variables.Variable([6.0, 7.0, 8.0], name="v")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables())
saver = saver_lib.Saver({"v": v})
# This should fail as there's no checkpoint within 2 seconds.
with self.assertRaisesRegexp(
RuntimeError, "no init_op or init_fn or local_init_op was given"):
sess = sm.prepare_session(
"",
init_op=None,
saver=saver,
checkpoint_dir=checkpoint_dir,
wait_for_checkpoint=True,
max_wait_secs=2)
# Rename the checkpoint directory back.
gfile.DeleteRecursively(checkpoint_dir)
os.rename(checkpoint_dir2, checkpoint_dir)
# This should succeed as there's checkpoint.
sess = sm.prepare_session(
"",
init_op=None,
saver=saver,
checkpoint_dir=checkpoint_dir,
wait_for_checkpoint=True,
max_wait_secs=2)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
def testWaitForSessionLocalInit(self):
server = server_lib.Server.create_local_server()
with ops.Graph().as_default() as graph:
v = variables.Variable(1, name="v")
w = variables.Variable(
v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
sm = session_manager.SessionManager(
graph=graph,
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=variables.report_uninitialized_variables(
variables.global_variables()),
local_init_op=w.initializer)
# Initialize v but not w
s = session_lib.Session(server.target, graph=graph)
s.run(v.initializer)
sess = sm.wait_for_session(server.target, max_wait_secs=3)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEquals(1, sess.run(v))
self.assertEquals(1, sess.run(w))
def testRecoverSessionNoChkptStillRunsLocalInitOp(self):
# This test checks for backwards compatibility.
# In particular, we continue to ensure that recover_session will execute
# local_init_op exactly once, regardless of whether the session was
# successfully recovered.
with ops.Graph().as_default():
w = variables.Variable(1,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.cached_session():
self.assertEqual(False,
variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=None,
local_init_op=w.initializer)
# Try to recover session from None
sess, initialized = sm2.recover_session("",
saver=None,
checkpoint_dir=None)
# Succeeds because recover_session still run local_init_op
self.assertFalse(initialized)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEquals(1, sess.run(w))
def testPrepareSessionFails(self):
checkpoint_dir = os.path.join(self.get_temp_dir(), "prepare_session")
checkpoint_dir2 = os.path.join(self.get_temp_dir(), "prepare_session2")
try:
gfile.DeleteRecursively(checkpoint_dir)
gfile.DeleteRecursively(checkpoint_dir2)
except errors.OpError:
pass # Ignore
gfile.MakeDirs(checkpoint_dir)
with ops.Graph().as_default():
v = variables.Variable([1.0, 2.0, 3.0], name="v")
sm = session_manager.SessionManager(
ready_op=variables.assert_variables_initialized())
saver = saver_lib.Saver({"v": v})
sess = sm.prepare_session(
"",
init_op=variables.global_variables_initializer(),
saver=saver,
checkpoint_dir=checkpoint_dir)
self.assertAllClose([1.0, 2.0, 3.0], sess.run(v))
checkpoint_filename = os.path.join(checkpoint_dir,
"prepare_session_checkpoint")
saver.save(sess, checkpoint_filename)
# Create a new Graph and SessionManager and recover.
with ops.Graph().as_default():
# Renames the checkpoint directory.
os.rename(checkpoint_dir, checkpoint_dir2)
gfile.MakeDirs(checkpoint_dir)
v = variables.Variable([6.0, 7.0, 8.0], name="v")
with self.cached_session():
self.assertEqual(False,
variables.is_variable_initialized(v).eval())
session_manager.SessionManager(
ready_op=variables.assert_variables_initialized())
saver = saver_lib.Saver({"v": v})
# This should fail as there's no checkpoint within 2 seconds.
with self.assertRaisesRegexp(
RuntimeError,
"no init_op or init_fn or local_init_op was given"):
sess = sm.prepare_session("",
init_op=None,
saver=saver,
checkpoint_dir=checkpoint_dir,
wait_for_checkpoint=True,
max_wait_secs=2)
# Rename the checkpoint directory back.
gfile.DeleteRecursively(checkpoint_dir)
os.rename(checkpoint_dir2, checkpoint_dir)
# This should succeed as there's checkpoint.
sess = sm.prepare_session("",
init_op=None,
saver=saver,
checkpoint_dir=checkpoint_dir,
wait_for_checkpoint=True,
max_wait_secs=2)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
def testRecoverSessionNoChkptStillRunsLocalInitOp(self):
# This test checks for backwards compatibility.
# In particular, we continue to ensure that recover_session will execute
# local_init_op exactly once, regardless of whether the session was
# successfully recovered.
with ops.Graph().as_default():
w = variables.Variable(
1,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=None,
local_init_op=w.initializer)
# Try to recover session from None
sess, initialized = sm2.recover_session(
"", saver=None, checkpoint_dir=None)
# Succeeds because recover_session still run local_init_op
self.assertFalse(initialized)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEquals(1, sess.run(w))
def testPrepareSessionWithReadyForLocalInitOp(self):
with ops.Graph().as_default():
v = variables.Variable(1, name="v")
w = variables.Variable(v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.test_session():
self.assertEqual(False,
variables.is_variable_initialized(v).eval())
self.assertEqual(False,
variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=variables.
report_uninitialized_variables(variables.global_variables()),
local_init_op=w.initializer)
sess = sm2.prepare_session("", init_op=v.initializer)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEquals(1, sess.run(v))
self.assertEquals(1, sess.run(w))
def testRecoverSessionWithReadyForLocalInitOpFailsToReadyLocal(self):
# We use ready_for_local_init_op=report_uninitialized_variables(),
# which causes recover_session to not run local_init_op, and to return
# initialized=False
# Create a checkpoint.
checkpoint_dir = os.path.join(
self.get_temp_dir(),
"recover_session_ready_for_local_init_fails_to_ready_local")
try:
gfile.DeleteRecursively(checkpoint_dir)
except errors.OpError:
pass # Ignore
gfile.MakeDirs(checkpoint_dir)
with ops.Graph().as_default():
v = variables.VariableV1(1, name="v")
sm = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables())
saver = saver_lib.Saver({"v": v})
sess, initialized = sm.recover_session(
"", saver=saver, checkpoint_dir=checkpoint_dir)
self.assertFalse(initialized)
sess.run(v.initializer)
self.assertEqual(1, sess.run(v))
saver.save(
sess, os.path.join(checkpoint_dir,
"recover_session_checkpoint"))
# Create a new Graph and SessionManager and recover.
with ops.Graph().as_default():
v = variables.VariableV1(2, name="v")
w = variables.VariableV1(
v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.cached_session():
self.assertEqual(False,
variables.is_variable_initialized(v).eval())
self.assertEqual(False,
variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=variables.
report_uninitialized_variables(),
local_init_op=w.initializer)
saver = saver_lib.Saver({"v": v})
sess, initialized = sm2.recover_session(
"", saver=saver, checkpoint_dir=checkpoint_dir)
self.assertFalse(initialized)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEqual(
False,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEqual(1, sess.run(v))
def testRecoverSessionWithReadyForLocalInitOpFailsToReadyLocal(self):
# We use ready_for_local_init_op=tf.report_uninitialized_variables(),
# which causes recover_session to not run local_init_op, and to return
# initialized=False
# Create a checkpoint.
checkpoint_dir = os.path.join(
self.get_temp_dir(),
"recover_session_ready_for_local_init_fails_to_ready_local")
try:
gfile.DeleteRecursively(checkpoint_dir)
except errors.OpError:
pass # Ignore
gfile.MakeDirs(checkpoint_dir)
with ops.Graph().as_default():
v = variables.Variable(1, name="v")
sm = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables())
saver = saver_lib.Saver({"v": v})
sess, initialized = sm.recover_session(
"", saver=saver, checkpoint_dir=checkpoint_dir)
self.assertFalse(initialized)
sess.run(v.initializer)
self.assertEquals(1, sess.run(v))
saver.save(sess,
os.path.join(checkpoint_dir, "recover_session_checkpoint"))
# Create a new Graph and SessionManager and recover.
with ops.Graph().as_default():
v = variables.Variable(2, name="v")
w = variables.Variable(
v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
self.assertEqual(False, variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=variables.report_uninitialized_variables(),
local_init_op=w.initializer)
saver = saver_lib.Saver({"v": v})
sess, initialized = sm2.recover_session(
"", saver=saver, checkpoint_dir=checkpoint_dir)
self.assertFalse(initialized)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEqual(
False,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEquals(1, sess.run(v))
def testPrepareSessionDidNotInitLocalVariableList(self):
with ops.Graph().as_default():
v = variables.VariableV1(1, name="v")
w = variables.VariableV1(
v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
self.assertEqual(False, variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables())
with self.assertRaisesRegex(RuntimeError,
"Init operations did not make model ready"):
sm2.prepare_session("", init_op=[v.initializer])
def testPrepareSessionDidNotInitLocalVariableList(self):
with ops.Graph().as_default():
v = variables.Variable(1, name="v")
w = variables.Variable(
v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
self.assertEqual(False, variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables())
with self.assertRaisesRegexp(RuntimeError,
"Init operations did not make model ready"):
sm2.prepare_session("", init_op=[v.initializer])
def testPrepareSessionWithCyclicInitializer(self):
# Regression test. Previously Variable._build_initializer_expr would enter
# into an infinite recursion when the variable's initial_value involved
# cyclic dependencies.
with ops.Graph().as_default():
i = control_flow_ops.while_loop(lambda i: i < 1, lambda i: i + 1, [0])
v = variables.Variable(array_ops.identity(i), name="v")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
sm = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables())
sess = sm.prepare_session("", init_op=v.initializer)
self.assertEqual(1, sess.run(v))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
def testPrepareSessionWithCyclicInitializer(self):
# Regression test. Previously Variable._build_initializer_expr would enter
# into an infinite recursion when the variable's initial_value involved
# cyclic dependencies.
with ops.Graph().as_default():
i = control_flow_ops.while_loop(lambda i: i < 1, lambda i: i + 1, [0])
v = variables.VariableV1(array_ops.identity(i), name="v")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
sm = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables())
sess = sm.prepare_session("", init_op=v.initializer)
self.assertEqual(1, sess.run(v))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
def testPrepareSessionWithInsufficientReadyForLocalInitCheck(self):
with ops.Graph().as_default():
v = variables.Variable(1, name="v")
w = variables.Variable(
v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.test_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
self.assertEqual(False, variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=None,
local_init_op=w.initializer)
with self.assertRaisesRegexp(errors_impl.FailedPreconditionError,
"Attempting to use uninitialized value v"):
sm2.prepare_session("", init_op=None)
def testPrepareSessionWithInsufficientReadyForLocalInitCheck(self):
with ops.Graph().as_default():
v = variables.Variable(1, name="v")
w = variables.Variable(
v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
self.assertEqual(False, variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=None,
local_init_op=w.initializer)
with self.assertRaisesRegexp(RuntimeError,
"Init operations did not make model ready.*"):
sm2.prepare_session("", init_op=None)
def testPrepareSessionWithInsufficientReadyForLocalInitCheck(self):
with ops.Graph().as_default():
v = variables.VariableV1(1, name="v")
w = variables.VariableV1(
v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
self.assertEqual(False, variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=None,
local_init_op=w.initializer)
with self.assertRaisesRegex(RuntimeError,
"Init operations did not make model ready.*"):
sm2.prepare_session("", init_op=None)
def testRecoverSessionFailsStillRunsLocalInitOp(self):
# Create a checkpoint.
checkpoint_dir = os.path.join(
self.get_temp_dir(),
"recover_session_ready_for_local_init_fails_stil_run")
try:
gfile.DeleteRecursively(checkpoint_dir)
except errors.OpError:
pass # Ignore
gfile.MakeDirs(checkpoint_dir)
# Create a new Graph and SessionManager and recover.
with ops.Graph().as_default():
v = variables.VariableV1(2, name="v")
w = variables.VariableV1(
1,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.cached_session():
self.assertEqual(False,
variables.is_variable_initialized(v).eval())
self.assertEqual(False,
variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=None,
local_init_op=w.initializer)
saver = saver_lib.Saver({"v": v})
sess, initialized = sm2.recover_session(
"",
saver=saver,
checkpoint_dir=checkpoint_dir,
wait_for_checkpoint=False)
self.assertFalse(initialized)
self.assertEqual(
False,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEqual(1, sess.run(w))
def testRecoverSessionFailsStillRunsLocalInitOp(self):
# Create a checkpoint.
checkpoint_dir = os.path.join(
self.get_temp_dir(),
"recover_session_ready_for_local_init_fails_stil_run")
try:
gfile.DeleteRecursively(checkpoint_dir)
except errors.OpError:
pass # Ignore
gfile.MakeDirs(checkpoint_dir)
# Create a new Graph and SessionManager and recover.
with ops.Graph().as_default():
v = variables.Variable(2, name="v")
w = variables.Variable(
1,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
self.assertEqual(False, variables.is_variable_initialized(w).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables(),
ready_for_local_init_op=None,
local_init_op=w.initializer)
saver = saver_lib.Saver({"v": v})
sess, initialized = sm2.recover_session(
"",
saver=saver,
checkpoint_dir=checkpoint_dir,
wait_for_checkpoint=False)
self.assertFalse(initialized)
self.assertEqual(
False,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEquals(1, sess.run(w))
def testRecoverSession(self):
# Create a checkpoint.
checkpoint_dir = os.path.join(self.get_temp_dir(), "recover_session")
try:
gfile.DeleteRecursively(checkpoint_dir)
except errors.OpError:
pass # Ignore
gfile.MakeDirs(checkpoint_dir)
with ops.Graph().as_default():
v = variables.Variable(1, name="v")
sm = session_manager.SessionManager(
ready_op=variables.assert_variables_initialized())
saver = saver_lib.Saver({"v": v})
sess, initialized = sm.recover_session(
"", saver=saver, checkpoint_dir=checkpoint_dir)
self.assertFalse(initialized)
sess.run(v.initializer)
self.assertEquals(1, sess.run(v))
saver.save(
sess, os.path.join(checkpoint_dir,
"recover_session_checkpoint"))
# Create a new Graph and SessionManager and recover.
with ops.Graph().as_default():
v = variables.Variable(2, name="v")
with self.cached_session():
self.assertEqual(False,
variables.is_variable_initialized(v).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.assert_variables_initialized())
saver = saver_lib.Saver({"v": v})
sess, initialized = sm2.recover_session(
"", saver=saver, checkpoint_dir=checkpoint_dir)
self.assertTrue(initialized)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEquals(1, sess.run(v))
def _test_recovered_variable(self,
checkpoint_dir=None,
checkpoint_filename_with_path=None):
# Create a new Graph and SessionManager and recover from a checkpoint.
with ops.Graph().as_default():
v = variables.Variable(2, name="v")
with session_lib.Session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables())
saver = saver_lib.Saver({"v": v})
sess, initialized = sm2.recover_session(
"",
saver=saver,
checkpoint_dir=checkpoint_dir,
checkpoint_filename_with_path=checkpoint_filename_with_path)
self.assertTrue(initialized)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEquals(1, sess.run(v))
def _test_recovered_variable(self,
checkpoint_dir=None,
checkpoint_filename_with_path=None):
# Create a new Graph and SessionManager and recover from a checkpoint.
with ops.Graph().as_default():
v = variables.VariableV1(2, name="v")
with session_lib.Session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.report_uninitialized_variables())
saver = saver_lib.Saver({"v": v})
sess, initialized = sm2.recover_session(
"",
saver=saver,
checkpoint_dir=checkpoint_dir,
checkpoint_filename_with_path=checkpoint_filename_with_path)
self.assertTrue(initialized)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEqual(1, sess.run(v))
def testRecoverSession(self):
# Create a checkpoint.
checkpoint_dir = os.path.join(self.get_temp_dir(), "recover_session")
try:
gfile.DeleteRecursively(checkpoint_dir)
except errors.OpError:
pass # Ignore
gfile.MakeDirs(checkpoint_dir)
with ops.Graph().as_default():
v = variables.Variable(1, name="v")
sm = session_manager.SessionManager(
ready_op=variables.assert_variables_initialized())
saver = saver_lib.Saver({"v": v})
sess, initialized = sm.recover_session(
"", saver=saver, checkpoint_dir=checkpoint_dir)
self.assertFalse(initialized)
sess.run(v.initializer)
self.assertEquals(1, sess.run(v))
saver.save(sess,
os.path.join(checkpoint_dir, "recover_session_checkpoint"))
# Create a new Graph and SessionManager and recover.
with ops.Graph().as_default():
v = variables.Variable(2, name="v")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
sm2 = session_manager.SessionManager(
ready_op=variables.assert_variables_initialized())
saver = saver_lib.Saver({"v": v})
sess, initialized = sm2.recover_session(
"", saver=saver, checkpoint_dir=checkpoint_dir)
self.assertTrue(initialized)
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEquals(1, sess.run(v))
def _wait_for_variable_initialization(session):
"""Utility to wait for variables to be initialized."""
all_variables = K._get_variables(K.get_graph()) # pylint: disable=protected-access
candidate_vars = []
for v in all_variables:
if not getattr(v, '_keras_initialized', False):
candidate_vars.append(v)
if not candidate_vars:
return
while True:
is_initialized = session.run(
[variables.is_variable_initialized(v) for v in candidate_vars])
uninitialized_vars = []
for flag, v in zip(is_initialized, candidate_vars):
if not flag:
uninitialized_vars.append(v)
v._keras_initialized = True # pylint: disable=protected-access
if not uninitialized_vars:
break
def _wait_for_variable_initialization(session):
"""Utility to wait for variables to be initialized."""
all_variables = K._get_variables(K.get_graph()) # pylint: disable=protected-access
candidate_vars = []
for v in all_variables:
if not getattr(v, '_keras_initialized', False):
candidate_vars.append(v)
if not candidate_vars:
return
while True:
is_initialized = session.run(
[variables.is_variable_initialized(v) for v in candidate_vars])
uninitialized_vars = []
for flag, v in zip(is_initialized, candidate_vars):
if not flag:
uninitialized_vars.append(v)
v._keras_initialized = True # pylint: disable=protected-access
if not uninitialized_vars:
break
def get_session(config=None, checkpoint_dir=None, checkpoint_path=None):
global _SESSION
if _SESSION is None:
from tensorlib.training.sessions.core import BasicSessionCreator
session_creator = BasicSessionCreator(
config=config or config_pb2.ConfigProto(allow_soft_placement=True),
checkpoint_dir=checkpoint_dir,
checkpoint_path=checkpoint_path)
_SESSION = session_creator.create_session()
session = _SESSION
else:
if config is not None:
import warnings
warnings.warn("Session has already been created without specific"
" session_config: %s, you should invoke method"
" `get_session` manually in the beginning of your"
" program." % str(config))
session = _SESSION
if checkpoint_dir is None and checkpoint_path is None:
with session.graph.as_default():
all_vars = variables.global_variables()
candidate_vars = []
for var in all_vars:
if not getattr(var, "_initialized", False):
candidate_vars.append(var)
if candidate_vars:
is_initialized = session.run([
variables.is_variable_initialized(v)
for v in candidate_vars
])
uninitialized_vars = []
for flag, v in zip(is_initialized, candidate_vars):
if not flag:
uninitialized_vars.append(v)
v._initialized = True
if uninitialized_vars:
session.run(
variables.variables_initializer(uninitialized_vars))
return session
def testPrepareSessionWithPartialInitOp(self):
with ops.Graph().as_default():
v = variables.Variable(1, name="v")
w = variables.Variable(
v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
x = variables.Variable(
3 * v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="x")
# TODO(b/70206927): Use ResourceVariables once they are handled properly.
v_res = variables.Variable(1, name="v_res")
w_res = variables.Variable(
v_res,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w_res")
x_res = variables.Variable(
3 * v_res,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="x_res")
with self.cached_session():
self.assertEqual(False, variables.is_variable_initialized(v).eval())
self.assertEqual(False, variables.is_variable_initialized(w).eval())
self.assertEqual(False, variables.is_variable_initialized(x).eval())
self.assertEqual(False, variables.is_variable_initialized(v_res).eval())
self.assertEqual(False, variables.is_variable_initialized(w_res).eval())
self.assertEqual(False, variables.is_variable_initialized(x_res).eval())
sm2 = session_manager.SessionManager(local_init_op=[
w.initializer, x.initializer, w_res.initializer, x_res.initializer
])
sess = sm2.prepare_session("", init_op=None)
self.assertEqual(
False,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("x:0")).eval(session=sess))
self.assertEquals(1, sess.run(w))
self.assertEquals(3, sess.run(x))
self.assertEqual(
False,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v_res:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w_res:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("x_res:0")).eval(session=sess))
self.assertEquals(1, sess.run(w_res))
self.assertEquals(3, sess.run(x_res))
def testPrepareSessionWithPartialInitOp(self):
with ops.Graph().as_default():
v = variables.Variable(1, name="v")
w = variables.Variable(v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w")
x = variables.Variable(3 * v,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="x")
# TODO(b/70206927): Use ResourceVariables once they are handled properly.
v_res = variables.Variable(1, name="v_res")
w_res = variables.Variable(
v_res,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="w_res")
x_res = variables.Variable(
3 * v_res,
trainable=False,
collections=[ops.GraphKeys.LOCAL_VARIABLES],
name="x_res")
with self.cached_session():
self.assertEqual(False,
variables.is_variable_initialized(v).eval())
self.assertEqual(False,
variables.is_variable_initialized(w).eval())
self.assertEqual(False,
variables.is_variable_initialized(x).eval())
self.assertEqual(
False,
variables.is_variable_initialized(v_res).eval())
self.assertEqual(
False,
variables.is_variable_initialized(w_res).eval())
self.assertEqual(
False,
variables.is_variable_initialized(x_res).eval())
sm2 = session_manager.SessionManager(local_init_op=[
w.initializer, x.initializer, w_res.initializer,
x_res.initializer
])
sess = sm2.prepare_session("", init_op=None)
self.assertEqual(
False,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w:0")).eval(session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("x:0")).eval(session=sess))
self.assertEquals(1, sess.run(w))
self.assertEquals(3, sess.run(x))
self.assertEqual(
False,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("v_res:0")).eval(
session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("w_res:0")).eval(
session=sess))
self.assertEqual(
True,
variables.is_variable_initialized(
sess.graph.get_tensor_by_name("x_res:0")).eval(
session=sess))
self.assertEquals(1, sess.run(w_res))
self.assertEquals(3, sess.run(x_res))
