One Fall
One Fall is a 2011 American fantasy drama film directed by Marcus Dean Fuller, and produced by Dean Silvers and Marlen Hecht. Filming took place in New York.
One Fall | |
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Directed by | Marcus Dean Fuller |
Produced by | Dean Silvers Marlen Hecht Richard K. Smucker Marcus Dean Fuller Forrest Silvers Julie S. Fuller |
Written by | Marcus Dean Fuller Richard Greenberg |
Starring | Marcus Dean Fuller Zoe McLellan Seamus Mulcahy James McCaffrey Mark Margolis Dominic Fumusa Phyllis Somerville |
Music by | Ben Toth |
Cinematography | Alice Brooks |
Edited by | Marlen Hecht William Henry |
Release date |
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Country | United States |
Language | English |
Plot
Set in the rustic Midwestern U.S. town of One Fall, the film tells the story of a man, James (Marcus Dean Fuller), who miraculously survived a horrific fall from a spectacular 200-foot-high cliff and was never heard from again. However, three years after vanishing James chooses to return to his hometown of One Fall—but he returns a changed man. For an incomprehensible reason, James has developed supernatural healing abilities. He must decide whether to use his abilities to help the ones he once turned his back on or to continue running from his mysterious past.
Cast
- Marcus Dean Fuller as James Bond/The Janitor
- Zoe McLellan as Julie Gardner
- Seamus Mulcahy as Tab Barrows/Repeller Boy
- James McCaffrey as Werber Bond
- Mark La Mura as Cliff Bond
- Dominic Fumusa as Tom Schmidt
- Mark Margolis as Walter Grigg Sr.
- Phyllis Somerville as Mrs. Barrows
- Tyler Silvers as Kyle
gollark: Instead of recomputing the embeddings every time a new sentence comes in.
gollark: The embeddings for your example sentences are the same each time you run the model, so you can just store them somewhere and run the cosine similarity thing on all of them in bulk.
gollark: Well, it doesn't look like you ever actually move the `roberta-large-mnli` model to your GPU, but I think the Sentence Transformers one is slow because you're using it wrong.
gollark: For the sentence_transformers one, are you precomputing the embeddings for the example sentences *then* just cosine-similaritying them against the new sentence? Because if not that's probably a very large bottleneck.
gollark: sentence_transformers says you should be able to do several thousand sentences a second on a V100, which I'm pretty sure is worse than your GPU. Are you actually running it on the GPU?
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