Mateen Ulhaq

Input is `"zpqr`. That is, ``` key " sleep 3000ms key z sleep 10ms key p sleep 10ms key q sleep 10ms key r ``` Actual command executed: ``` "z"p"q"r...

```lua function registers._apply_register(register, keep_open_until_keypress) ... elseif registers._previous_mode == "n" or registers._previous_mode_is_visual() then -- Simulate the keypresses require to perform the next actions vim.schedule(function() local keys = "" -- Go to...

This almost fixes it, but `"zp` becomes `"z` instead of `"zp`: ```diff diff --git a/lua/registers.lua b/lua/registers.lua index feb254d..ef68fc3 100644 --- a/lua/registers.lua +++ b/lua/registers.lua @@ -292,6 +292,9 @@ function registers.show_window(options) --...

This seems to fix `"zp`: ```diff diff --git a/lua/registers.lua b/lua/registers.lua index feb254d..52762b3 100644 --- a/lua/registers.lua +++ b/lua/registers.lua @@ -292,6 +292,12 @@ function registers.show_window(options) -- Reset the interruption check registers._interrupted_by =...

The analysis would need to check if the contents are 1. valid python and 2. any referenced variables are in locals/globals

An additional flag is too complex. However, we could instead always return `y_hat`: ```python class SimpleVAECompressionModel(CompressionModel): def forward (self, x): ... return { "x_hat": x_hat, "likelihoods": y_out["likelihoods"], # For debugging...

Because of the symmetry of the normal distribution, `values = torch.abs(values)` has no effect on the result: ```python upper - lower = _standardized_cumulative( z + 0.5) - _standardized_cumulative( z -...

I'm not sure what you mean about normalizing `y`. Could you clarify? Note that `y` (minus mean) gets quantized to integer values like `[..., -2, 1, 0, 1, 2, ...]`....

Depends on the image contents and image resolution. A single point on the RD curve represents a single model at a particular quality. The point is generated by taking the...

If your model inherits from recent versions of [`CompressionModel`](https://github.com/InterDigitalInc/CompressAI/blob/v1.2.6/compressai/models/base.py#L65-L68), it should simplify things: ```python from compressai.models.base import CompressionModel class AEWithEntropy(CompressionModel): ... def eval_autoencoder(...): model.eval() model.update(force=True, update_quantiles=True) ... # model.compress, model.decompress...