chore(deps): bump terser from 4.2.1 to 4.8.1

[dependabot[bot]]

Bumps terser from 4.2.1 to 4.8.1.

Changelog

Sourced from terser's changelog.

v4.8.1 (backport)

• Security fix for RegExps that should not be evaluated (regexp DDOS)

v4.8.0

• Support for numeric separators (million = 1_000_000) was added.
• Assigning properties to a class is now assumed to be pure.
• Fixed bug where yield wasn't considered a valid property key in generators.

v4.7.0

• A bug was fixed where an arrow function would have the wrong size
• arguments object is now considered safe to retrieve properties from (useful for length, or 0) even when pure_getters is not set.
• Fixed erroneous const declarations without value (which is invalid) in some corner cases when using collapse_vars.

v4.6.13

• Fixed issue where ES5 object properties were being turned into ES6 object properties due to more lax unicode rules.
• Fixed parsing of BigInt with lowercase e in them.

v4.6.12

• Fixed subtree comparison code, making it see that [1,[2, 3]] is different from [1, 2, [3]]
• Printing of unicode identifiers has been improved

v4.6.11

• Read unused classes' properties and method keys, to figure out if they use other variables.
• Prevent inlining into block scopes when there are name collisions
• Functions are no longer inlined into parameter defaults, because they live in their own special scope.
• When inlining identity functions, take into account the fact they may be used to drop this in function calls.
• Nullish coalescing operator (x ?? y), plus basic optimization for it.
• Template literals in binary expressions such as + have been further optimized

v4.6.10

• Do not use reduce_vars when classes are present

v4.6.9

• Check if block scopes actually exist in blocks

v4.6.8

• Take into account "executed bits" of classes like static properties or computed keys, when checking if a class evaluation might throw or have side effects.

v4.6.7

• Some new performance gains through a AST_Node.size() method which measures a node's source code length without printing it to a string first.

... (truncated)

Commits

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[ht014]

Hello, you can try to train only several epochs, e.g. 4 epoches.

[johnson00111]

I try again train the model with 4 epoches for six time but only get mAP in the following table Bitsnum | 12bits | 24bits | 32bits | 48bits Codes1 | 0.4748 | 0.4735 | 0.4723 | 0.4606 Codes2 | 0.4308 | 0.4366 | 0.4600 | 0.4632 Codes3 | 0.4341 | 0.4686 | 0.4528 | 0.4399 Codes4 | 0.3941 | 0.4360 | 0.4368 | 0.4782 Codes5 | 0.4284 | 0.4142 | 0.4698 | 0.4822 Codes6 | 0.4911 | 0.4701 | 0.4723 | 0.4480

In 12 bits mAP is good enough, but when bits number goes bigger the mAP still the same May I ask which tensorflow and prettytensor version you use?

[ximi2018]

I run this code in 12,24,32,48 bits(epochs51) each of them in six times but only 12 bits can get mAP higher than the mAP shown in the paper(0.401) In 32 bits get 0.4599 but paper say the method can get 0.531 and 48 bit get 0.4487 but paper's mAP is 0.558 Is there some setting need to change or how many epochs is prefect ?

Hello，I have the same problem. Have you finally solved it

[zhjy2016]

I try again train the model with 4 epoches for six time but only get mAP in the following table Bitsnum | 12bits | 24bits | 32bits | 48bits Codes1 | 0.4748 | 0.4735 | 0.4723 | 0.4606 Codes2 | 0.4308 | 0.4366 | 0.4600 | 0.4632 Codes3 | 0.4341 | 0.4686 | 0.4528 | 0.4399 Codes4 | 0.3941 | 0.4360 | 0.4368 | 0.4782 Codes5 | 0.4284 | 0.4142 | 0.4698 | 0.4822 Codes6 | 0.4911 | 0.4701 | 0.4723 | 0.4480 In 12 bits mAP is good enough, but when bits number goes bigger the mAP still the same May I ask which tensorflow and prettytensor version you use?

I have this problem, too, how did you solve the problem finally? Could you please share?