Speed up inference by avoiding unnecessary padding

[lostella]

Issue #, if available: Unnecessary context padding slows down inference. We evaluated the models from HF with this change, and found no concerning issue with accuracy.

Test code for a context of length 200:

import torch
from chronos import ChronosPipeline
import time

pipeline = ChronosPipeline.from_pretrained(
    "amazon/chronos-t5-large",
    device_map="cuda",
    torch_dtype=torch.bfloat16,
)

context = torch.ones((8, 200))
prediction_length = 24
num_runs = 10

t0 = time.time()
for _ in range(num_runs):
    forecast = pipeline.predict(
        context,
        prediction_length,
        num_samples=20,
    )
t1 = time.time()

print(f"total time: {t1 - t0}")

Before the change:

total time: 20.005481481552124

After the change:

total time: 9.82350754737854

Description of changes: Remove padding in case the provided batch is shorter than context_length.

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