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Add some log info within GradientTape #27183

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Add some log info within GradientTape #27183

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15 changes: 15 additions & 0 deletions tensorflow/python/eager/backprop.py
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Original file line number Diff line number Diff line change
Expand Up @@ -812,6 +812,10 @@ def watch(self, tensor):
tensor: a Tensor or list of Tensors.
"""
for t in nest.flatten(tensor):
if not t.dtype.is_floating:
logging.vlog(
logging.WARN, "The dtype of the watched tensor must be "
"floating (e.g. tf.float32), got %r", t.dtype)
if hasattr(t, "handle"):
# There are many variable-like objects, all of them currently have
# `handle` attribute that points to a tensor. If this changes, internals
Expand Down Expand Up @@ -940,13 +944,24 @@ def gradient(self,

flat_targets = []
for t in nest.flatten(target):
if not t.dtype.is_floating:
logging.vlog(
logging.WARN, "The dtype of the target tensor must be "
"floating (e.g. tf.float32) when calling GradientTape.gradient, "
"got %r", t.dtype)
if resource_variable_ops.is_resource_variable(t):
with self:
t = ops.convert_to_tensor(t)
flat_targets.append(t)

flat_sources = nest.flatten(sources)
flat_sources = [_handle_or_self(x) for x in flat_sources]
for t in flat_sources:
if not t.dtype.is_floating:
logging.vlog(
logging.WARN, "The dtype of the source tensor must be "
"floating (e.g. tf.float32) when calling GradientTape.gradient, "
"got %r", t.dtype)

if output_gradients is not None:
output_gradients = [None if x is None else ops.convert_to_tensor(x)
Expand Down