updated amazon.chronos version and changed type to float32 that speed…

… up inference

Makefile

@@ -136,7 +136,7 @@ DEFAULT_PORT := 3000
 DARTS_VERSION := 0.27.2
 SKTIME_VERSION := 0.26.1
 STATSFORECAST_VERSION := 1.5.0
-CHRONOS_VERSION := 1.1.0
+CHRONOS_VERSION := 1.2.0
 
 
 .PHONY: base-image-darts

models/amazon-chronos/Dockerfile

@@ -1,4 +1,4 @@
-FROM attilabalint/enfobench-models:base-amazon-chronos-1.1.0
+FROM attilabalint/enfobench-models:base-amazon-chronos-1.2.0
 
 WORKDIR /usr/local/app
 
@@ -9,7 +9,7 @@ COPY ./models /usr/local/app/models
 COPY ./src /usr/local/app/src
 
 ENV ENFOBENCH_MODEL_NAME="chronos-t5-tiny"
-ENV ENFOBENCH_NUM_SAMPLES="20"
+ENV ENFOBENCH_NUM_SAMPLES="1"
 
 EXPOSE 3000
 CMD ["uvicorn", "src.main:app", "--host", "0.0.0.0", "--port", "3000", "--workers", "1"]

models/amazon-chronos/src/main.py

@@ -59,7 +59,7 @@ def forecast(
         pipeline = ChronosPipeline.from_pretrained(
             model_dir,
             device_map=device,
-            torch_dtype=torch.bfloat16,
+            torch_dtype=torch.float32,
         )
 
         # context must be either a 1D tensor, a list of 1D tensors,