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Add tf.stop_gradient in tf.summary.histogram #5311

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Merged
stephanwlee merged 3 commits into from
Sep 15, 2021
Merged

Add tf.stop_gradient in tf.summary.histogram #5311

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f3aa76b
Update summary_v2.py
allenlavoie Sep 14, 2021
0ea05c2
Add a histogram+xla+higher-order gradient test
allenlavoie Sep 15, 2021
651adce
Make the linters happy
allenlavoie Sep 15, 2021
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18 changes: 18 additions & 0 deletions tensorboard/plugins/histogram/summary_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -235,6 +235,24 @@ def graph_fn():
graph_fn()
writer.close()

def test_no_gradient_error_xla(self):
@tf2.function(jit_compile=True)
def graph_fn():
x = tf.constant(1.0)
with tf2.GradientTape() as tape1:
with tf2.GradientTape() as tape2:
tape1.watch(x)
tape2.watch(x)
summary.histogram(name="loss", step=0, data=x, buckets=10)

# Note that XLA CPU/GPU has no outside compilation support, so summaries
# won't actually run in a jit_compiled function. TPUs do, and follow
# some similar codepaths, so this test stops at graph building to
# exercise those paths without a TPU available.
writer = tf2.summary.create_file_writer(self.get_temp_dir())
with writer.as_default():
graph_fn.get_concrete_function()


if __name__ == "__main__":
tf.test.main()
4 changes: 4 additions & 0 deletions tensorboard/plugins/histogram/summary_v2.py
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Expand Up @@ -105,6 +105,10 @@ def histogram(name, data, step=None, buckets=None, description=None):
ValueError: if a default writer exists, but no step was provided and
`tf.summary.experimental.get_step()` is None.
"""
# Avoid building unused gradient graphs for conds below. This works around
# an error building second-order gradient graphs when XlaDynamicUpdateSlice
# is used, and will generally speed up graph building slightly.
data = tf.stop_gradient(data)
summary_metadata = metadata.create_summary_metadata(
display_name=None, description=description
)
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