TensorFlow checks dilated convolution size at runtime
By OnTheRice · Sources and limitations · Report a correction
A dilated convolution could reach a kernel when its effective filter was larger than the padded input. TensorFlow now rejects that mismatch at runtime.
Source confidenceNot assessed
What’s changing?
The guard computes effective filter size from dilation and compares it with the padded input before execution.
Key points
- A dilated convolution could reach a kernel when its effective filter was larger than the padded input. TensorFlow now rejects that mismatch at runtime.
What could change this view?
- XLA tests were excluded, and the first containing release is unknown.
Bottom line
A dilated convolution could reach a kernel when its effective filter was larger than the padded input. TensorFlow now rejects that mismatch at runtime.
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How likely is this call? · Three frameworks
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Evidence behind this view
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Recorded connection
The guard computes effective filter size from dilation and compares it with the padded input before execution.
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Evidence against this view
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Recorded opposing evidence and risks
XLA tests were excluded, and the first containing release is unknown.
Why the direction changed
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No documented bullish-to-bearish or bearish-to-bullish change is available for this card. We keep the original call and its time unchanged.
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Sources, original wording and price checks
Author-submitted research. The underlying facts and market prices have not been independently verified.
Original research record
Observed change: A dilated convolution could reach a kernel when its effective filter was larger than the padded input. TensorFlow now rejects that mismatch at runtime.
Mechanism: The guard computes effective filter size from dilation and compares it with the padded input before execution.
Uncertainty: XLA tests were excluded, and the first containing release is unknown.
Next check: Verify tagged eager and XLA paths across CPU and GPU.
Published
First published through Sites 07 Oct 2026, 18:40:42 SGT
No explicit investible BULLISH or BEARISH call on this card.
What changed
Recorded public historyA dilated convolution could reach a kernel when its effective filter was larger than the padded input. TensorFlow now rejects that…
This is the first recorded public view. Further public updates will appear here.
- TensorFlow checks dilated convolution size at runtime
A dilated convolution could reach a kernel when its effective filter was larger than the padded input. TensorFlow now rejects that mismatch at runtime.
First published by OTR: 7 Oct, 18:40 SGTPublished by OTR: 7 Oct 2026, 18:40 SGT
Why the view changed
This is the first recorded view. Future source-backed updates will appear here.
Evidence, memory & review 1 linked source
Named assets or actors: TensorFlow, dilated convolution, shape validation
Directional takeaway: N/A · NO ENTRY. This is an operational software signal, not an investible price call.
OTR reasoning: The guard computes effective filter size from dilation and compares it with the padded input before execution.
Counterpoint: XLA tests were excluded, and the first containing release is unknown.
Source-grounded facts (paraphrased)
- Time not supplied: A dilated convolution could reach a kernel when its effective filter was larger than the padded input. TensorFlow now rejects that mismatch at runtime. Source record: source-17-1
Source trail
- Upstream merged commit ↗GitHub upstream projectSource event dated 7 October 2026; exact source-page clock remains on the linked record.
Review status: PASS WITH DISCLOSED LIMITS
No score or probability is presented.