udpate tests + add platform before docker run

Makefile

@@ -9,6 +9,7 @@ CPU_OR_GPU ?= gpu
 endif
 
 BLOCK_INTERNET ?= true
+PLATFORM_ARGS = --platform linux/amd64
 
 TAG := ${CPU_OR_GPU}-latest
 LOCAL_TAG := ${CPU_OR_GPU}-local
@@ -127,7 +128,7 @@ update-lockfile: runtime/pixi.lock
 		--tag pixi-lock:local
 	@echo Running lock container
 	docker run \
-		--platform linux/amd64 \
+		${PLATFORM_ARGS} \
 		--mount type=bind,source="$(shell pwd)"/runtime/pixi.toml,target=/tmp/pixi.toml \
 		--mount type=bind,source="$(shell pwd)"/runtime/pixi.lock,target=/tmp/pixi.lock \
 		--rm \
@@ -136,6 +137,7 @@ update-lockfile: runtime/pixi.lock
 ## Ensures that your locally built image can import all the Python packages successfully when it runs
 test-container: _check_image _echo_image _submission_write_perms
 	docker run \
+		${PLATFORM_ARGS} \
 		${GPU_ARGS} \
 		${NETWORK_ARGS} \
 		${TTY_ARGS} \
@@ -147,6 +149,7 @@ test-container: _check_image _echo_image _submission_write_perms
 ## Open an interactive bash shell within the running container (with network access)
 interact-container: _check_image _echo_image _submission_write_perms
 	docker run \
+		${PLATFORM_ARGS} \
 		${GPU_ARGS} \
 		${NETWORK_ARGS} \
 		--mount type=bind,source=${shell pwd}/data,target=/code_execution/data,readonly \
@@ -188,6 +191,7 @@ ifeq (,$(wildcard ./submission/submission.zip))
 	  If you want to use the benchmark, you can run `make pack-example <benchmark name>` first)
 endif
 	docker run \
+		${PLATFORM_ARGS} \
 		${TTY_ARGS} \
 		${GPU_ARGS} \
 		${NETWORK_ARGS} \

runtime/pixi.toml

@@ -5,6 +5,7 @@ platforms = ["linux-64"]
 
 # conda package dependencies
 [dependencies]
+accelerate = "1.0.1"
 einops = "0.8.0"
 langchain = "0.3.*"
 librosa = ">=0.10.2.post1,<0.11"

runtime/tests/test_packages.py

@@ -4,16 +4,15 @@
 import pytest
 
 packages = [
-    "gensim",
-    "keras",
     "numpy",
     "pandas",
     "scipy",
-    "spacy",
     "sklearn",
-    "tensorflow",
     "torch",
+    "torchaudio",
     "transformers",
+    "whisper",
+    "speechbrain",
 ]
 
 
@@ -41,46 +40,3 @@ def test_allocate_torch():
     assert torch.cuda.is_available()
 
     torch.zeros(1).cuda()
-
-
-@pytest.mark.skipif(not GPU_AVAILABLE, reason="No GPU available")
-def test_allocate_tf():
-    import tensorflow as tf
-
-    assert tf.test.is_built_with_cuda()
-    assert (devices := tf.config.list_logical_devices("GPU"))
-
-    for device in devices:
-        with tf.device(device.name):
-            tf.constant([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
-
-
-@pytest.mark.skipif(not GPU_AVAILABLE, reason="No GPU available")
-def test_allocate_cupy():
-    import cupy as cp
-
-    cp.array([1, 2, 3, 4, 5, 6])
-
-
-def test_spacy():
-    import spacy
-    from spacy.tokens import DocBin
-
-    if GPU_AVAILABLE:
-        spacy.require_gpu()
-
-    nlp = spacy.blank("en")
-    training_data = [
-        ("Tokyo Tower is 333m tall.", [(0, 11, "BUILDING")]),
-    ]
-
-    # the DocBin will store the example documents
-    db = DocBin()
-    for text, annotations in training_data:
-        doc = nlp(text)
-        ents = []
-        for start, end, label in annotations:
-            span = doc.char_span(start, end, label=label)
-            ents.append(span)
-        doc.ents = ents
-        db.add(doc)