refactor: remove redundant Tensor allocation in GaussianConditional.update()

In GaussianConditional.update(), a temporary Tensor is allocated:

    quantized_cdf = torch.Tensor(len(pmf_length), max_length + 2)
    quantized_cdf = self._pmf_to_cdf(pmf, tail_mass, pmf_length, max_length)

The first line is a dead store: the variable is immediately overwritten by
the result of _pmf_to_cdf(). This removes the unnecessary allocation.

- No functional changes
- Slightly reduces heap traffic and avoids creating an uninitialized Tensor
- Keeps dtype/device fully defined by _pmf_to_cdf()

Author: studyingeugene

compressai/entropy_models/entropy_models.py

@@ -677,7 +677,6 @@ def update(self):
 
         tail_mass = 2 * lower[:, :1]
 
-        quantized_cdf = torch.Tensor(len(pmf_length), max_length + 2)
         quantized_cdf = self._pmf_to_cdf(pmf, tail_mass, pmf_length, max_length)
         self._quantized_cdf = quantized_cdf
         self._offset = -pmf_center