[Misc] Update tests and examples for Prithvi/Terratorch models (#34416)
Signed-off-by: Christian Pinto <christian.pinto@ibm.com> Co-authored-by: Cyrus Leung <tlleungac@connect.ust.hk>
This commit is contained in:
Christian Pinto
@@ -28,7 +28,7 @@ def main():
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)
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llm = LLM(
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model="christian-pinto/Prithvi-EO-2.0-300M-TL-VLLM",
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model="ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11",
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skip_tokenizer_init=True,
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trust_remote_code=True,
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enforce_eager=True,
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@@ -391,7 +391,7 @@ if __name__ == "__main__":
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parser.add_argument(
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"--model",
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type=str,
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default="christian-pinto/Prithvi-EO-2.0-300M-TL-VLLM",
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default="ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11",
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help="Path to a checkpoint file to load from.",
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)
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parser.add_argument(
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@@ -14,9 +14,7 @@ import requests
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# - install TerraTorch v1.1 (or later):
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# pip install terratorch>=v1.1
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# - start vllm in serving mode with the below args
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# --model='christian-pinto/Prithvi-EO-2.0-300M-TL-VLLM'
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# --model-impl terratorch
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# --trust-remote-code
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# --model='ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11'
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# --skip-tokenizer-init --enforce-eager
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# --io-processor-plugin terratorch_segmentation
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# --enable-mm-embeds
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@@ -34,7 +32,7 @@ def main():
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"out_data_format": "b64_json",
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},
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"priority": 0,
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"model": "christian-pinto/Prithvi-EO-2.0-300M-TL-VLLM",
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"model": "ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11",
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}
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ret = requests.post(server_endpoint, json=request_payload_url)
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@@ -56,7 +56,14 @@ runai-model-streamer[s3,gcs]==0.15.3
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fastsafetensors>=0.2.2 # 0.2.2 contains important fixes for multi-GPU mem usage
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pydantic>=2.12 # 2.11 leads to error on python 3.13
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decord==0.6.0
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terratorch @ git+https://github.com/IBM/terratorch.git@1.1.rc3 # required for PrithviMAE test
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terratorch >= 1.2.2 # Required for Prithvi tests
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imagehash # Required for Prithvi tests
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segmentation-models-pytorch > 0.4.0 # Required for Prithvi tests
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gpt-oss >= 0.0.7; python_version > '3.11'
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perceptron # required for isaac test
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# Newer versions of datasets require torchcoded, that makes the tests fail in CI because of a missing library.
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# Older versions are in conflict with teerratorch requirements.
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datasets>=3.3.0,<=3.6.0
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@@ -1,7 +1,9 @@
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# This file was autogenerated by uv via the following command:
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# uv pip compile requirements/test.in -o requirements/test.txt --index-strategy unsafe-best-match --torch-backend cu129 --python-platform x86_64-manylinux_2_28 --python-version 3.12
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absl-py==2.1.0
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# via rouge-score
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# via
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# rouge-score
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# tensorboard
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accelerate==1.0.1
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# via
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# lm-eval
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@@ -31,9 +33,7 @@ albumentations==1.4.6
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# -r requirements/test.in
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# terratorch
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alembic==1.16.4
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# via
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# mlflow
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# optuna
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# via optuna
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annotated-doc==0.0.4
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# via fastapi
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annotated-types==0.7.0
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@@ -74,8 +74,6 @@ bitsandbytes==0.46.1
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# lightning
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black==24.10.0
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# via datamodel-code-generator
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blinker==1.9.0
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# via flask
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blobfile==3.0.0
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# via -r requirements/test.in
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bm25s==0.2.13
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@@ -93,9 +91,7 @@ bounded-pool-executor==0.0.3
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buildkite-test-collector==0.1.9
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# via -r requirements/test.in
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cachetools==5.5.2
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# via
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# google-auth
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# mlflow-skinny
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# via google-auth
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certifi==2024.8.30
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# via
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# fiona
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@@ -106,6 +102,7 @@ certifi==2024.8.30
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# pyproj
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# rasterio
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# requests
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# sentry-sdk
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cffi==1.17.1
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# via soundfile
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chardet==5.2.0
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@@ -120,15 +117,14 @@ click==8.1.7
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# click-plugins
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# cligj
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# fiona
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# flask
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# jiwer
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# mlflow-skinny
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# nltk
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# rasterio
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# ray
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# schemathesis
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# typer
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# uvicorn
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# wandb
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click-plugins==1.1.1.2
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# via
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# fiona
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@@ -137,8 +133,6 @@ cligj==0.7.2
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# via
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# fiona
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# rasterio
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cloudpickle==3.1.1
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# via mlflow-skinny
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colorama==0.4.6
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# via
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# perceptron
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@@ -163,16 +157,15 @@ cupy-cuda12x==13.6.0
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# via ray
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cycler==0.12.1
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# via matplotlib
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databricks-sdk==0.59.0
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# via mlflow-skinny
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datamodel-code-generator==0.26.3
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# via -r requirements/test.in
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dataproperty==1.0.1
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# via
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# pytablewriter
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# tabledata
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datasets==3.0.2
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datasets==3.3.0
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# via
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# -r requirements/test.in
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# evaluate
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# lm-eval
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# mteb
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@@ -180,6 +173,8 @@ decorator==5.1.1
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# via librosa
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decord==0.6.0
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# via -r requirements/test.in
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diffusers==0.36.0
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# via terratorch
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dill==0.3.8
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# via
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# datasets
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@@ -191,15 +186,11 @@ distlib==0.3.9
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dnspython==2.7.0
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# via email-validator
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docker==7.1.0
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# via
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# gpt-oss
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# mlflow
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# via gpt-oss
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docopt==0.6.2
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# via num2words
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docstring-parser==0.17.0
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# via jsonargparse
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efficientnet-pytorch==0.7.1
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# via segmentation-models-pytorch
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einops==0.8.1
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# via
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# -r requirements/test.in
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@@ -217,9 +208,7 @@ encodec==0.1.1
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evaluate==0.4.3
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# via lm-eval
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fastapi==0.128.0
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# via
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# gpt-oss
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# mlflow-skinny
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# via gpt-oss
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fastparquet==2024.11.0
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# via genai-perf
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fastrlock==0.8.2
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@@ -230,6 +219,7 @@ filelock==3.16.1
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# via
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# blobfile
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# datasets
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# diffusers
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# huggingface-hub
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# ray
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# torch
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@@ -237,8 +227,6 @@ filelock==3.16.1
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# virtualenv
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fiona==1.10.1
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# via torchgeo
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flask==3.1.1
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# via mlflow
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fonttools==4.55.0
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# via matplotlib
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fqdn==1.5.1
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@@ -249,7 +237,7 @@ frozenlist==1.5.0
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# via
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# aiohttp
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# aiosignal
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fsspec==2024.9.0
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fsspec==2024.12.0
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# via
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# datasets
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# evaluate
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@@ -257,6 +245,7 @@ fsspec==2024.9.0
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# huggingface-hub
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# lightning
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# pytorch-lightning
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# tacoreader
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# torch
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ftfy==6.3.1
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# via open-clip-torch
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@@ -269,7 +258,7 @@ geopandas==1.0.1
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gitdb==4.0.12
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# via gitpython
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gitpython==3.1.44
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# via mlflow-skinny
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# via wandb
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google-api-core==2.24.2
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# via
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# google-cloud-core
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@@ -277,7 +266,6 @@ google-api-core==2.24.2
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# opencensus
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google-auth==2.40.2
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# via
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# databricks-sdk
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# google-api-core
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# google-cloud-core
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# google-cloud-storage
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@@ -296,25 +284,17 @@ googleapis-common-protos==1.70.0
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# via google-api-core
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gpt-oss==0.0.8
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# via -r requirements/test.in
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graphene==3.4.3
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# via mlflow
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graphql-core==3.2.6
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# via
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# graphene
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# graphql-relay
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# hypothesis-graphql
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graphql-relay==3.2.0
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# via graphene
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# via hypothesis-graphql
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greenlet==3.2.3
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# via sqlalchemy
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grpcio==1.78.0
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# via
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# grpcio-tools
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# ray
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# tensorboard
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grpcio-tools==1.78.0
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# via -r requirements/test.in
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gunicorn==23.0.0
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# via mlflow
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h11==0.14.0
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# via
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# httpcore
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@@ -338,12 +318,14 @@ httpcore==1.0.6
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httpx==0.27.2
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# via
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# -r requirements/test.in
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# diffusers
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# perceptron
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# schemathesis
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huggingface-hub==0.36.2
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# via
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# accelerate
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# datasets
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# diffusers
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# evaluate
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# open-clip-torch
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# peft
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@@ -379,11 +361,13 @@ idna==3.10
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# jsonschema
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# requests
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# yarl
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imagehash==4.3.2
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# via -r requirements/test.in
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imageio==2.37.0
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# via scikit-image
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importlib-metadata==8.7.0
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# via
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# mlflow-skinny
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||||
# diffusers
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||||
# opentelemetry-api
|
||||
importlib-resources==6.5.2
|
||||
# via typeshed-client
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@@ -395,14 +379,10 @@ isoduration==20.11.0
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# via jsonschema
|
||||
isort==5.13.2
|
||||
# via datamodel-code-generator
|
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itsdangerous==2.2.0
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# via flask
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jinja2==3.1.6
|
||||
# via
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# datamodel-code-generator
|
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# flask
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# genai-perf
|
||||
# mlflow
|
||||
# torch
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jiwer==3.0.5
|
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# via -r requirements/test.in
|
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@@ -415,12 +395,14 @@ joblib==1.4.2
|
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# librosa
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# nltk
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# scikit-learn
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jsonargparse==4.35.0
|
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jsonargparse==4.46.0
|
||||
# via
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# lightning
|
||||
# terratorch
|
||||
jsonlines==4.0.0
|
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# via lm-eval
|
||||
jsonnet==0.21.0
|
||||
# via jsonargparse
|
||||
jsonpointer==3.0.0
|
||||
# via jsonschema
|
||||
jsonschema==4.23.0
|
||||
@@ -449,13 +431,13 @@ libnacl==2.1.0
|
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# via tensorizer
|
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librosa==0.10.2.post1
|
||||
# via -r requirements/test.in
|
||||
lightly==1.5.20
|
||||
lightly==1.5.22
|
||||
# via
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# terratorch
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# torchgeo
|
||||
lightly-utils==0.0.2
|
||||
# via lightly
|
||||
lightning==2.5.1.post0
|
||||
lightning==2.6.1
|
||||
# via
|
||||
# terratorch
|
||||
# torchgeo
|
||||
@@ -476,12 +458,11 @@ lxml==5.3.0
|
||||
mako==1.3.10
|
||||
# via alembic
|
||||
markdown==3.8.2
|
||||
# via mlflow
|
||||
# via tensorboard
|
||||
markdown-it-py==3.0.0
|
||||
# via rich
|
||||
markupsafe==3.0.1
|
||||
# via
|
||||
# flask
|
||||
# jinja2
|
||||
# mako
|
||||
# werkzeug
|
||||
@@ -489,7 +470,6 @@ matplotlib==3.9.2
|
||||
# via
|
||||
# -r requirements/test.in
|
||||
# lightning
|
||||
# mlflow
|
||||
# pycocotools
|
||||
# torchgeo
|
||||
mbstrdecoder==1.1.3
|
||||
@@ -501,10 +481,6 @@ mdurl==0.1.2
|
||||
# via markdown-it-py
|
||||
mistral-common==1.9.1
|
||||
# via -r requirements/test.in
|
||||
mlflow==2.22.0
|
||||
# via terratorch
|
||||
mlflow-skinny==2.22.0
|
||||
# via mlflow
|
||||
more-itertools==10.5.0
|
||||
# via lm-eval
|
||||
mpmath==1.3.0
|
||||
@@ -523,8 +499,6 @@ multiprocess==0.70.16
|
||||
# via
|
||||
# datasets
|
||||
# evaluate
|
||||
munch==4.0.0
|
||||
# via pretrainedmodels
|
||||
mypy-extensions==1.0.0
|
||||
# via black
|
||||
networkx==3.2.1
|
||||
@@ -553,6 +527,7 @@ numpy==2.2.6
|
||||
# cupy-cuda12x
|
||||
# datasets
|
||||
# decord
|
||||
# diffusers
|
||||
# einx
|
||||
# encodec
|
||||
# evaluate
|
||||
@@ -560,13 +535,13 @@ numpy==2.2.6
|
||||
# genai-perf
|
||||
# geopandas
|
||||
# h5py
|
||||
# imagehash
|
||||
# imageio
|
||||
# librosa
|
||||
# lightly
|
||||
# lightly-utils
|
||||
# matplotlib
|
||||
# mistral-common
|
||||
# mlflow
|
||||
# mteb
|
||||
# numba
|
||||
# numexpr
|
||||
@@ -578,6 +553,7 @@ numpy==2.2.6
|
||||
# perceptron
|
||||
# pycocotools
|
||||
# pyogrio
|
||||
# pywavelets
|
||||
# rasterio
|
||||
# rioxarray
|
||||
# rouge-score
|
||||
@@ -590,8 +566,10 @@ numpy==2.2.6
|
||||
# shapely
|
||||
# soxr
|
||||
# statsmodels
|
||||
# tensorboard
|
||||
# tensorboardx
|
||||
# tensorizer
|
||||
# terratorch
|
||||
# tifffile
|
||||
# torchgeo
|
||||
# torchmetrics
|
||||
@@ -659,7 +637,6 @@ opencv-python-headless==4.13.0.90
|
||||
# mistral-common
|
||||
opentelemetry-api==1.35.0
|
||||
# via
|
||||
# mlflow-skinny
|
||||
# opentelemetry-exporter-prometheus
|
||||
# opentelemetry-sdk
|
||||
# opentelemetry-semantic-conventions
|
||||
@@ -669,7 +646,6 @@ opentelemetry-proto==1.36.0
|
||||
# via ray
|
||||
opentelemetry-sdk==1.35.0
|
||||
# via
|
||||
# mlflow-skinny
|
||||
# opentelemetry-exporter-prometheus
|
||||
# ray
|
||||
opentelemetry-semantic-conventions==0.56b0
|
||||
@@ -687,7 +663,6 @@ packaging==24.2
|
||||
# evaluate
|
||||
# fastparquet
|
||||
# geopandas
|
||||
# gunicorn
|
||||
# huggingface-hub
|
||||
# hydra-core
|
||||
# kornia
|
||||
@@ -695,7 +670,6 @@ packaging==24.2
|
||||
# lightning
|
||||
# lightning-utilities
|
||||
# matplotlib
|
||||
# mlflow-skinny
|
||||
# optuna
|
||||
# peft
|
||||
# plotly
|
||||
@@ -708,10 +682,12 @@ packaging==24.2
|
||||
# rioxarray
|
||||
# scikit-image
|
||||
# statsmodels
|
||||
# tensorboard
|
||||
# tensorboardx
|
||||
# torchmetrics
|
||||
# transformers
|
||||
# typepy
|
||||
# wandb
|
||||
# xarray
|
||||
pandas==2.2.3
|
||||
# via
|
||||
@@ -720,8 +696,8 @@ pandas==2.2.3
|
||||
# fastparquet
|
||||
# genai-perf
|
||||
# geopandas
|
||||
# mlflow
|
||||
# statsmodels
|
||||
# tacoreader
|
||||
# torchgeo
|
||||
# xarray
|
||||
pathspec==0.12.1
|
||||
@@ -740,7 +716,9 @@ perf-analyzer==0.1.0
|
||||
# via genai-perf
|
||||
pillow==10.4.0
|
||||
# via
|
||||
# diffusers
|
||||
# genai-perf
|
||||
# imagehash
|
||||
# imageio
|
||||
# lightly-utils
|
||||
# matplotlib
|
||||
@@ -748,6 +726,7 @@ pillow==10.4.0
|
||||
# perceptron
|
||||
# scikit-image
|
||||
# segmentation-models-pytorch
|
||||
# tensorboard
|
||||
# torchgeo
|
||||
# torchvision
|
||||
platformdirs==4.3.6
|
||||
@@ -755,6 +734,7 @@ platformdirs==4.3.6
|
||||
# black
|
||||
# pooch
|
||||
# virtualenv
|
||||
# wandb
|
||||
plotly==5.24.1
|
||||
# via genai-perf
|
||||
pluggy==1.5.0
|
||||
@@ -769,8 +749,6 @@ portalocker==2.10.1
|
||||
# via sacrebleu
|
||||
pqdm==0.2.0
|
||||
# via -r requirements/test.in
|
||||
pretrainedmodels==0.7.4
|
||||
# via segmentation-models-pytorch
|
||||
prometheus-client==0.22.0
|
||||
# via
|
||||
# opentelemetry-exporter-prometheus
|
||||
@@ -786,12 +764,13 @@ protobuf==6.33.2
|
||||
# google-api-core
|
||||
# googleapis-common-protos
|
||||
# grpcio-tools
|
||||
# mlflow-skinny
|
||||
# opentelemetry-proto
|
||||
# proto-plus
|
||||
# ray
|
||||
# tensorboard
|
||||
# tensorboardx
|
||||
# tensorizer
|
||||
# wandb
|
||||
psutil==6.1.0
|
||||
# via
|
||||
# accelerate
|
||||
@@ -801,11 +780,12 @@ py==1.11.0
|
||||
# via pytest-forked
|
||||
py-spy==0.4.0
|
||||
# via ray
|
||||
pyarrow==18.0.0
|
||||
pyarrow==23.0.0
|
||||
# via
|
||||
# datasets
|
||||
# genai-perf
|
||||
# mlflow
|
||||
# tacoreader
|
||||
# terratorch
|
||||
pyasn1==0.6.1
|
||||
# via
|
||||
# pyasn1-modules
|
||||
@@ -831,11 +811,11 @@ pydantic==2.12.0
|
||||
# gpt-oss
|
||||
# lightly
|
||||
# mistral-common
|
||||
# mlflow-skinny
|
||||
# mteb
|
||||
# openai-harmony
|
||||
# pydantic-extra-types
|
||||
# ray
|
||||
# wandb
|
||||
pydantic-core==2.41.1
|
||||
# via pydantic
|
||||
pydantic-extra-types==2.10.5
|
||||
@@ -873,7 +853,6 @@ pytest==8.3.5
|
||||
# pytest-subtests
|
||||
# pytest-timeout
|
||||
# schemathesis
|
||||
# terratorch
|
||||
pytest-asyncio==0.24.0
|
||||
# via -r requirements/test.in
|
||||
pytest-cov==6.3.0
|
||||
@@ -896,7 +875,6 @@ python-dateutil==2.9.0.post0
|
||||
# via
|
||||
# arrow
|
||||
# botocore
|
||||
# graphene
|
||||
# lightly
|
||||
# matplotlib
|
||||
# pandas
|
||||
@@ -913,6 +891,8 @@ pytz==2024.2
|
||||
# via
|
||||
# pandas
|
||||
# typepy
|
||||
pywavelets==1.9.0
|
||||
# via imagehash
|
||||
pyyaml==6.0.2
|
||||
# via
|
||||
# accelerate
|
||||
@@ -923,7 +903,6 @@ pyyaml==6.0.2
|
||||
# huggingface-hub
|
||||
# jsonargparse
|
||||
# lightning
|
||||
# mlflow-skinny
|
||||
# omegaconf
|
||||
# optuna
|
||||
# peft
|
||||
@@ -934,6 +913,7 @@ pyyaml==6.0.2
|
||||
# timm
|
||||
# transformers
|
||||
# vocos
|
||||
# wandb
|
||||
rapidfuzz==3.12.1
|
||||
# via jiwer
|
||||
rasterio==1.4.3
|
||||
@@ -951,6 +931,7 @@ referencing==0.35.1
|
||||
# jsonschema-specifications
|
||||
regex==2024.9.11
|
||||
# via
|
||||
# diffusers
|
||||
# nltk
|
||||
# open-clip-torch
|
||||
# sacrebleu
|
||||
@@ -959,8 +940,8 @@ regex==2024.9.11
|
||||
requests==2.32.3
|
||||
# via
|
||||
# buildkite-test-collector
|
||||
# databricks-sdk
|
||||
# datasets
|
||||
# diffusers
|
||||
# docker
|
||||
# evaluate
|
||||
# google-api-core
|
||||
@@ -970,15 +951,16 @@ requests==2.32.3
|
||||
# lightly
|
||||
# lm-eval
|
||||
# mistral-common
|
||||
# mlflow-skinny
|
||||
# mteb
|
||||
# pooch
|
||||
# ray
|
||||
# responses
|
||||
# schemathesis
|
||||
# starlette-testclient
|
||||
# tacoreader
|
||||
# tiktoken
|
||||
# transformers
|
||||
# wandb
|
||||
responses==0.25.3
|
||||
# via genai-perf
|
||||
rfc3339-validator==0.1.4
|
||||
@@ -991,6 +973,7 @@ rich==13.9.4
|
||||
# lightning
|
||||
# mteb
|
||||
# perceptron
|
||||
# terratorch
|
||||
# typer
|
||||
rioxarray==0.19.0
|
||||
# via terratorch
|
||||
@@ -1017,47 +1000,55 @@ sacrebleu==2.4.3
|
||||
safetensors==0.4.5
|
||||
# via
|
||||
# accelerate
|
||||
# diffusers
|
||||
# open-clip-torch
|
||||
# peft
|
||||
# segmentation-models-pytorch
|
||||
# timm
|
||||
# transformers
|
||||
schemathesis==3.39.15
|
||||
# via -r requirements/test.in
|
||||
scikit-image==0.25.2
|
||||
# via albumentations
|
||||
# via
|
||||
# albumentations
|
||||
# terratorch
|
||||
scikit-learn==1.5.2
|
||||
# via
|
||||
# albumentations
|
||||
# librosa
|
||||
# lm-eval
|
||||
# mlflow
|
||||
# mteb
|
||||
# sentence-transformers
|
||||
# terratorch
|
||||
scipy==1.13.1
|
||||
# via
|
||||
# albumentations
|
||||
# bm25s
|
||||
# imagehash
|
||||
# librosa
|
||||
# mlflow
|
||||
# mteb
|
||||
# scikit-image
|
||||
# scikit-learn
|
||||
# sentence-transformers
|
||||
# statsmodels
|
||||
# vocos
|
||||
segmentation-models-pytorch==0.4.0
|
||||
segmentation-models-pytorch==0.5.0
|
||||
# via
|
||||
# -r requirements/test.in
|
||||
# terratorch
|
||||
# torchgeo
|
||||
sentence-transformers==5.2.0
|
||||
# via
|
||||
# -r requirements/test.in
|
||||
# mteb
|
||||
sentry-sdk==2.52.0
|
||||
# via wandb
|
||||
setuptools==77.0.3
|
||||
# via
|
||||
# grpcio-tools
|
||||
# lightning-utilities
|
||||
# pytablewriter
|
||||
# tensorboard
|
||||
# torch
|
||||
shapely==2.1.1
|
||||
# via
|
||||
@@ -1075,7 +1066,6 @@ six==1.16.0
|
||||
# python-dateutil
|
||||
# rfc3339-validator
|
||||
# rouge-score
|
||||
# segmentation-models-pytorch
|
||||
smart-open==7.1.0
|
||||
# via ray
|
||||
smmap==5.0.2
|
||||
@@ -1099,12 +1089,9 @@ soxr==0.5.0.post1
|
||||
sqlalchemy==2.0.41
|
||||
# via
|
||||
# alembic
|
||||
# mlflow
|
||||
# optuna
|
||||
sqlitedict==2.1.0
|
||||
# via lm-eval
|
||||
sqlparse==0.5.3
|
||||
# via mlflow-skinny
|
||||
starlette==0.50.0
|
||||
# via
|
||||
# fastapi
|
||||
@@ -1124,6 +1111,8 @@ tabledata==1.3.3
|
||||
# via pytablewriter
|
||||
tabulate==0.9.0
|
||||
# via sacrebleu
|
||||
tacoreader==0.5.6
|
||||
# via terratorch
|
||||
tblib==3.1.0
|
||||
# via -r requirements/test.in
|
||||
tcolorpy==0.1.6
|
||||
@@ -1133,13 +1122,19 @@ tenacity==9.1.2
|
||||
# gpt-oss
|
||||
# lm-eval
|
||||
# plotly
|
||||
tensorboard==2.20.0
|
||||
# via terratorch
|
||||
tensorboard-data-server==0.7.2
|
||||
# via tensorboard
|
||||
tensorboardx==2.6.4
|
||||
# via lightning
|
||||
tensorizer==2.10.1
|
||||
# via -r requirements/test.in
|
||||
termcolor==3.1.0
|
||||
# via gpt-oss
|
||||
terratorch @ git+https://github.com/IBM/terratorch.git@07184fcf91a1324f831ff521dd238d97fe350e3e
|
||||
# via
|
||||
# gpt-oss
|
||||
# terratorch
|
||||
terratorch==1.2.2
|
||||
# via -r requirements/test.in
|
||||
threadpoolctl==3.5.0
|
||||
# via scikit-learn
|
||||
@@ -1172,7 +1167,6 @@ torch==2.10.0+cu129
|
||||
# -r requirements/test.in
|
||||
# accelerate
|
||||
# bitsandbytes
|
||||
# efficientnet-pytorch
|
||||
# encodec
|
||||
# kornia
|
||||
# lightly
|
||||
@@ -1181,7 +1175,6 @@ torch==2.10.0+cu129
|
||||
# mteb
|
||||
# open-clip-torch
|
||||
# peft
|
||||
# pretrainedmodels
|
||||
# pytorch-lightning
|
||||
# runai-model-streamer
|
||||
# segmentation-models-pytorch
|
||||
@@ -1213,12 +1206,11 @@ torchvision==0.25.0+cu129
|
||||
# -r requirements/test.in
|
||||
# lightly
|
||||
# open-clip-torch
|
||||
# pretrainedmodels
|
||||
# segmentation-models-pytorch
|
||||
# terratorch
|
||||
# timm
|
||||
# torchgeo
|
||||
tqdm==4.66.6
|
||||
tqdm==4.67.3
|
||||
# via
|
||||
# datasets
|
||||
# evaluate
|
||||
@@ -1232,10 +1224,11 @@ tqdm==4.66.6
|
||||
# optuna
|
||||
# peft
|
||||
# pqdm
|
||||
# pretrainedmodels
|
||||
# pytorch-lightning
|
||||
# segmentation-models-pytorch
|
||||
# sentence-transformers
|
||||
# tacoreader
|
||||
# terratorch
|
||||
# tqdm-multiprocess
|
||||
# transformers
|
||||
tqdm-multiprocess==0.0.11
|
||||
@@ -1274,14 +1267,12 @@ typing-extensions==4.15.0
|
||||
# alembic
|
||||
# chz
|
||||
# fastapi
|
||||
# graphene
|
||||
# grpcio
|
||||
# huggingface-hub
|
||||
# librosa
|
||||
# lightning
|
||||
# lightning-utilities
|
||||
# mistral-common
|
||||
# mlflow-skinny
|
||||
# mteb
|
||||
# opentelemetry-api
|
||||
# opentelemetry-sdk
|
||||
@@ -1299,6 +1290,7 @@ typing-extensions==4.15.0
|
||||
# typer
|
||||
# typeshed-client
|
||||
# typing-inspection
|
||||
# wandb
|
||||
typing-inspection==0.4.2
|
||||
# via pydantic
|
||||
tzdata==2024.2
|
||||
@@ -1313,25 +1305,26 @@ urllib3==2.2.3
|
||||
# lightly
|
||||
# requests
|
||||
# responses
|
||||
# sentry-sdk
|
||||
# tritonclient
|
||||
uvicorn==0.35.0
|
||||
# via
|
||||
# gpt-oss
|
||||
# mlflow-skinny
|
||||
# via gpt-oss
|
||||
vector-quantize-pytorch==1.21.2
|
||||
# via -r requirements/test.in
|
||||
virtualenv==20.31.2
|
||||
# via ray
|
||||
vocos==0.1.0
|
||||
# via -r requirements/test.in
|
||||
wandb==0.24.2
|
||||
# via terratorch
|
||||
wcwidth==0.2.13
|
||||
# via ftfy
|
||||
webcolors==24.11.1
|
||||
# via jsonschema
|
||||
werkzeug==3.1.3
|
||||
# via
|
||||
# flask
|
||||
# schemathesis
|
||||
# tensorboard
|
||||
word2number==1.1
|
||||
# via lm-eval
|
||||
wrapt==1.17.2
|
||||
|
||||
@@ -40,7 +40,7 @@ def _run_test(
|
||||
vllm_model.llm.encode(prompt, pooling_task="plugin")
|
||||
|
||||
|
||||
MODELS = ["mgazz/Prithvi-EO-2.0-300M-TL-Sen1Floods11"]
|
||||
MODELS = ["ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11"]
|
||||
|
||||
|
||||
@pytest.mark.core_model
|
||||
|
||||
@@ -13,7 +13,7 @@ from tests.utils import create_new_process_for_each_test
|
||||
"model",
|
||||
[
|
||||
"ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11",
|
||||
"mgazz/Prithvi_v2_eo_300_tl_unet_agb",
|
||||
"ibm-nasa-geospatial/Prithvi-EO-2.0-300M-BurnScars",
|
||||
],
|
||||
)
|
||||
def test_inference(
|
||||
|
||||
@@ -44,12 +44,8 @@ datamodule_config: DataModuleConfig = {
|
||||
"no_label_replace": -1,
|
||||
"num_workers": 8,
|
||||
"test_transform": [
|
||||
albumentations.Resize(
|
||||
always_apply=False, height=448, interpolation=1, p=1, width=448
|
||||
),
|
||||
albumentations.pytorch.ToTensorV2(
|
||||
transpose_mask=False, always_apply=True, p=1.0
|
||||
),
|
||||
albumentations.Resize(height=448, interpolation=1, p=1, width=448),
|
||||
albumentations.pytorch.ToTensorV2(transpose_mask=False, p=1.0),
|
||||
],
|
||||
}
|
||||
|
||||
|
||||
@@ -1,18 +1,39 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
||||
import base64
|
||||
import io
|
||||
|
||||
import imagehash
|
||||
import pytest
|
||||
import requests
|
||||
from PIL import Image
|
||||
|
||||
from tests.utils import RemoteOpenAIServer
|
||||
from vllm.config import VllmConfig
|
||||
from vllm.entrypoints.pooling.pooling.protocol import IOProcessorResponse
|
||||
from vllm.plugins.io_processors import get_io_processor
|
||||
|
||||
MODEL_NAME = "ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11"
|
||||
models_config = {
|
||||
"ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11": {
|
||||
"image_url": "https://huggingface.co/christian-pinto/Prithvi-EO-2.0-300M-TL-VLLM/resolve/main/valencia_example_2024-10-26.tiff", # noqa: E501
|
||||
"out_hash": "aa6d92ad25926a5e",
|
||||
"plugin": "prithvi_to_tiff",
|
||||
},
|
||||
"ibm-nasa-geospatial/Prithvi-EO-2.0-300M-BurnScars": {
|
||||
"image_url": "https://huggingface.co/ibm-nasa-geospatial/Prithvi-EO-2.0-300M-BurnScars/resolve/main/examples/subsetted_512x512_HLS.S30.T10SEH.2018190.v1.4_merged.tif", # noqa: E501
|
||||
"out_hash": "c07f4f602da73552",
|
||||
"plugin": "prithvi_to_tiff",
|
||||
},
|
||||
}
|
||||
|
||||
image_url = "https://huggingface.co/christian-pinto/Prithvi-EO-2.0-300M-TL-VLLM/resolve/main/valencia_example_2024-10-26.tiff" # noqa: E501
|
||||
|
||||
def _compute_image_hash(base64_data: str) -> str:
|
||||
# Decode the base64 output and create image from byte stream
|
||||
decoded_image = base64.b64decode(base64_data)
|
||||
image = Image.open(io.BytesIO(decoded_image))
|
||||
|
||||
# Compute perceptual hash of the output image
|
||||
return str(imagehash.phash(image))
|
||||
|
||||
|
||||
def test_loading_missing_plugin():
|
||||
@@ -22,33 +43,39 @@ def test_loading_missing_plugin():
|
||||
|
||||
|
||||
@pytest.fixture(scope="function")
|
||||
def server():
|
||||
def server(model_name, plugin):
|
||||
args = [
|
||||
"--runner",
|
||||
"pooling",
|
||||
"--enforce-eager",
|
||||
"--trust-remote-code",
|
||||
"--skip-tokenizer-init",
|
||||
# Limit the maximum number of parallel requests
|
||||
# to avoid the model going OOM in CI.
|
||||
"--max-num-seqs",
|
||||
"32",
|
||||
"--io-processor-plugin",
|
||||
"prithvi_to_tiff",
|
||||
"--model-impl",
|
||||
"terratorch",
|
||||
plugin,
|
||||
"--enable-mm-embeds",
|
||||
]
|
||||
|
||||
with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
|
||||
with RemoteOpenAIServer(model_name, args) as remote_server:
|
||||
yield remote_server
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize("model_name", [MODEL_NAME])
|
||||
@pytest.mark.parametrize(
|
||||
"model_name, image_url, plugin, expected_hash",
|
||||
[
|
||||
(model_name, config["image_url"], config["plugin"], config["out_hash"])
|
||||
for model_name, config in models_config.items()
|
||||
],
|
||||
)
|
||||
async def test_prithvi_mae_plugin_online(
|
||||
server: RemoteOpenAIServer,
|
||||
model_name: str,
|
||||
image_url: str | dict,
|
||||
plugin: str,
|
||||
expected_hash: str,
|
||||
):
|
||||
request_payload_url = {
|
||||
"data": {
|
||||
@@ -74,16 +101,25 @@ async def test_prithvi_mae_plugin_online(
|
||||
|
||||
# verify the output is formatted as expected for this plugin
|
||||
plugin_data = parsed_response.data
|
||||
|
||||
assert all(plugin_data.get(attr) for attr in ["type", "format", "data"])
|
||||
|
||||
# We just check that the output is a valid base64 string.
|
||||
# Raises an exception and fails the test if the string is corrupted.
|
||||
base64.b64decode(plugin_data["data"])
|
||||
# Compute the output image hash and compare it against the expected hash
|
||||
image_hash = _compute_image_hash(plugin_data["data"])
|
||||
assert image_hash == expected_hash, (
|
||||
f"Image hash mismatch: expected {expected_hash}, got {image_hash}"
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.parametrize("model_name", [MODEL_NAME])
|
||||
def test_prithvi_mae_plugin_offline(vllm_runner, model_name: str):
|
||||
@pytest.mark.parametrize(
|
||||
"model_name, image_url, plugin, expected_hash",
|
||||
[
|
||||
(model_name, config["image_url"], config["plugin"], config["out_hash"])
|
||||
for model_name, config in models_config.items()
|
||||
],
|
||||
)
|
||||
def test_prithvi_mae_plugin_offline(
|
||||
vllm_runner, model_name: str, image_url: str | dict, plugin: str, expected_hash: str
|
||||
):
|
||||
img_prompt = dict(
|
||||
data=image_url,
|
||||
data_format="url",
|
||||
@@ -96,13 +132,12 @@ def test_prithvi_mae_plugin_offline(vllm_runner, model_name: str):
|
||||
runner="pooling",
|
||||
skip_tokenizer_init=True,
|
||||
enable_mm_embeds=True,
|
||||
trust_remote_code=True,
|
||||
enforce_eager=True,
|
||||
# Limit the maximum number of parallel requests
|
||||
# to avoid the model going OOM in CI.
|
||||
max_num_seqs=1,
|
||||
model_impl="terratorch",
|
||||
io_processor_plugin="prithvi_to_tiff",
|
||||
max_num_seqs=32,
|
||||
io_processor_plugin=plugin,
|
||||
default_torch_num_threads=1,
|
||||
) as llm_runner:
|
||||
pooler_output = llm_runner.get_llm().encode(img_prompt, pooling_task="plugin")
|
||||
output = pooler_output[0].outputs
|
||||
@@ -110,6 +145,8 @@ def test_prithvi_mae_plugin_offline(vllm_runner, model_name: str):
|
||||
# verify the output is formatted as expected for this plugin
|
||||
assert all(hasattr(output, attr) for attr in ["type", "format", "data"])
|
||||
|
||||
# We just check that the output is a valid base64 string.
|
||||
# Raises an exception and fails the test if the string is corrupted.
|
||||
base64.b64decode(output.data)
|
||||
# Compute the output image hash and compare it against the expected hash
|
||||
image_hash = _compute_image_hash(output.data)
|
||||
assert image_hash == expected_hash, (
|
||||
f"Image hash mismatch: expected {expected_hash}, got {image_hash}"
|
||||
)
|
||||
|
||||
Reference in New Issue
Block a user