def testCheckNumericsV2PositiveInfAndNaN(self):
"""Test that CheckNumericsV2 op shows sign of inf when nan is present."""
with self.session(graph=ops.Graph()):
t1 = constant_op.constant([0.0, 1.0])
t2 = constant_op.constant([0.0, 0.0])
with self.assertRaisesRegex(
errors.InvalidArgumentError,
r"pass through test.*had \+Inf and NaN values"):
self.evaluate(
array_ops.check_numerics_v2(t1 / t2, message="pass through test"))
def testCheckNumericsV2OpNegativeAndPositiveInfAndNaN(self):
"""CheckNumericsV2 op distinguishes - & + infs when nan is present."""
with self.session(graph=ops.Graph()):
t1 = constant_op.constant([-1.0, 1.0, 0.0])
t2 = constant_op.constant([0.0, 0.0, 0.0])
with self.assertRaisesRegex(
errors.InvalidArgumentError,
r"pass through test.*had -Inf, \+Inf, and NaN values"):
self.evaluate(
array_ops.check_numerics_v2(t1 / t2, message="pass through test"))
def testCheckNumericsV2OpNegativeAndPositiveInf(self):
"""Test that CheckNumericsV2 op distinguishes negative and positive infs."""
with self.session(graph=ops.Graph()):
t1 = constant_op.constant([-1.0, 1.0])
t2 = constant_op.constant([0.0, 0.0])
with self.assertRaisesRegex(
errors.InvalidArgumentError,
r"pass through test.*had -Inf and \+Inf values"):
self.evaluate(
array_ops.check_numerics_v2(t1 / t2, message="pass through test"))
def testCheckNumericsV2PositiveInfAndNaN(self):
"""Test that CheckNumericsV2 op shows sign of inf when nan is present."""
with self.session(graph=ops.Graph()):
t1 = constant_op.constant([0.0, 1.0])
t2 = constant_op.constant([0.0, 0.0])
checked = array_ops.check_numerics_v2(t1 / t2,
message="pass through test")
caught = None
try:
self.evaluate(checked)
except errors.InvalidArgumentError as error:
caught = error
self.assertIn("had +Inf and NaN values", caught.message)
self.assertIn("pass through test", caught.message)
def testCheckNumericsV2OpNegativeAndPositiveInfAndNaN(self):
"""CheckNumericsV2 op distinguishes - & + infs when nan is present."""
with self.session(graph=ops.Graph()):
t1 = constant_op.constant([-1.0, 1.0, 0.0])
t2 = constant_op.constant([0.0, 0.0, 0.0])
checked = array_ops.check_numerics_v2(t1 / t2,
message="pass through test")
caught = None
try:
self.evaluate(checked)
except errors.InvalidArgumentError as error:
caught = error
self.assertIn("had -Inf, +Inf, and NaN values", caught.message)
self.assertIn("pass through test", caught.message)
def _CheckNumericsV2Grad(op, grad):
"""Gradient for check_numerics op."""
return array_ops.check_numerics_v2(
grad,
"Not a number (NaN) or infinity (Inf) values detected in gradient. %s"
% op.get_attr("message"))
def callback(self,
op_type,
inputs,
attrs,
outputs,
op_name=None,
graph=None):
"""Eager-function unified callback for checking numerics."""
del attrs, op_name # Unused
op_type_bytes = compat.as_bytes(op_type)
is_v1_graph_mode = not ops.executing_eagerly_outside_functions()
if (op_type_bytes in op_callbacks_common.OP_CALLBACK_SKIP_OPS
or op_type_bytes in SAFE_OPS):
return None
if graph:
# Under graph mode. Insert check_numerics op.
instrumented_outputs = []
if is_v1_graph_mode:
for input_tensor in inputs:
if input_tensor in self._placeholder_to_debug_tensor and outputs:
outputs[0].op._add_control_input( # pylint: disable=protected-access
self._placeholder_to_debug_tensor[input_tensor].op)
for slot, output in enumerate(outputs):
if (output.dtype.is_floating
and (op_type_bytes, slot) not in IGNORE_OP_OUTPUTS):
checked_output = array_ops.check_numerics_v2(
# TF v2 has automatic control dependencies added to stateful async
# ops, which allows us to run check_numerics asynchronously.
# In the above case we use debug_summary to reduce all output
# tensors asynchronously from the op being checked and then
# process the tensor summary with check_numerics.
output if is_v1_graph_mode else _debug_summary(output),
get_check_numerics_error_message(
slot,
len(outputs),
op_type,
output,
inputs,
graph=graph,
traceback=output.op.traceback))
_CHECK_NUMERICS_INPUT_LOOKUP[graph][
checked_output.name] = output
instrumented_outputs.append(
self._get_output_tensor(op_type_bytes, output,
checked_output,
is_v1_graph_mode))
else:
instrumented_outputs.append(output)
return instrumented_outputs
else:
if op_type_bytes == b"CheckNumericsV2":
# TODO(b/140334369): Remove this special casing logic once op_callback.
# automatically prevents infinite recursion in eager mode.
return None
# Under eager mode. Eagerly execute check_numerics op.
for slot, output in enumerate(outputs):
if (output.dtype.is_floating
and (op_type_bytes, slot) not in IGNORE_OP_OUTPUTS):
array_ops.check_numerics_v2(
output,
get_check_numerics_error_message(
slot,
len(outputs),
op_type,
output,
inputs,
stack_height_limit=self._stack_height_limit,
path_length_limit=self._path_length_limit))