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src/testdata/Isaac.Newton-Opticks.txt
again, to see if I could make it better than that which I kept. And thus by many Trials I learn'd the way of polishing, till I made those two reflecting Perspectives I spake of above. For this Art of polishing will be better learn'd by repeated Practice than by my Description. Before I ground the Object-Metal on the Pitch, I always ground the Putty on it
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Oct 01 16:16:21 UTC 2018 - 553.9K bytes - Viewed (0) -
RELEASE.md
* `tf.keras`: * `Model.fit` major improvements: * You can now use custom training logic with `Model.fit` by overriding `Model.train_step`. * Easily write state-of-the-art training loops without worrying about all of the features `Model.fit` handles for you (distribution strategies, callbacks, data formats, looping logic, etc) * See the default
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 730.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
Otherwise, Knuth's algorithm is used to acquire samples via multiplying uniform random variables. See Donald E. Knuth (1969). Seminumerical Algorithms. The Art of Computer Programming, Volume 2. Addison Wesley }]; let arguments = (ins Arg<TF_I32OrI64Tensor, [{1-D integer tensor. Shape of independent samples to draw from each
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0)