huggingface/text-generation-inference
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add tests

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This commit is contained in:
OlivierDehaene 2023-05-15 17:13:33 +02:00
parent 9a9244937b
commit d69e4d2d1e
27 changed files with 1414 additions and 673 deletions
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47
.github/workflows/build.yaml vendored
View File

@ -70,6 +70,8 @@ jobs:
# with sigstore/fulcio when running outside of PRs. # with sigstore/fulcio when running outside of PRs.
id-token: write id-token: write
security-events: write security-events: write
outputs:
image:
steps: steps:
- name: Checkout repository - name: Checkout repository
uses: actions/checkout@v3 uses: actions/checkout@v3
@ -108,7 +110,19 @@ jobs:
username: ${{ secrets.AZURE_DOCKER_USERNAME }} username: ${{ secrets.AZURE_DOCKER_USERNAME }}
password: ${{ secrets.AZURE_DOCKER_PASSWORD }} password: ${{ secrets.AZURE_DOCKER_PASSWORD }}
registry: db4c2190dd824d1f950f5d1555fbadf0.azurecr.io registry: db4c2190dd824d1f950f5d1555fbadf0.azurecr.io
# If pull request
- name: Extract metadata (tags, labels) for Docker - name: Extract metadata (tags, labels) for Docker
if: ${{ github.event_name == 'pull_request' }}
id: meta
uses: docker/metadata-action@v4.3.0
with:
images: |
registry.internal.huggingface.tech/api-inference/community/text-generation-inference
tags: |
type=raw,value=sha-${{ env.GITHUB_SHA_SHORT }}
# If main, release or tag
- name: Extract metadata (tags, labels) for Docker
if: ${{ github.event_name != 'pull_request' }}
id: meta id: meta
uses: docker/metadata-action@v4.3.0 uses: docker/metadata-action@v4.3.0
with: with:
@ -129,7 +143,7 @@ jobs:
with: with:
context: . context: .
file: Dockerfile file: Dockerfile
push: ${{ github.event_name != 'pull_request' }} push: true
platforms: 'linux/amd64' platforms: 'linux/amd64'
build-args: | build-args: |
GIT_SHA=${{ env.GITHUB_SHA }} GIT_SHA=${{ env.GITHUB_SHA }}
@ -172,11 +186,42 @@ jobs:
with: with:
sarif_file: 'trivy-results.sarif' sarif_file: 'trivy-results.sarif'
integration-tests:
needs:
- start-runner
- build-and-push-image # Wait for the docker image to be built
runs-on: ${{ needs.start-runner.outputs.label }} # run the job on the newly created runner
env:
DOCKER_IMAGE: registry.internal.huggingface.tech/api-inference/community/text-generation-inference:sha-${{ env.GITHUB_SHA_SHORT }}
steps:
- uses: actions/checkout@v2
- name: Set up Python
uses: actions/setup-python@v1
with:
python-version: 3.9
- name: Tailscale
uses: tailscale/github-action@7bd8039bf25c23c4ab1b8d6e2cc2da2280601966
with:
authkey: ${{ secrets.TAILSCALE_AUTHKEY }}
- name: Prepare disks
run: |
sudo mkfs -t ext4 /dev/nvme1n1
sudo mkdir /data
sudo mount /dev/nvme1n1 /data
sudo chown -R $USER:$USER /data
- name: Install
run: |
make install-integration-tests
- name: Run tests
run: |
make integration-tests
stop-runner: stop-runner:
name: Stop self-hosted EC2 runner name: Stop self-hosted EC2 runner
needs: needs:
- start-runner - start-runner
- build-and-push-image - build-and-push-image
- integration-tests
runs-on: ubuntu-latest runs-on: ubuntu-latest
env: env:
AWS_REGION: us-east-1 AWS_REGION: us-east-1

11
Makefile
View File

@ -1,6 +1,9 @@
install-server: install-server:
cd server && make install cd server && make install
install-integration-tests:
cd integration-tests && pip install -r requirements.txt
install-router: install-router:
cd router && cargo install --path . cd router && cargo install --path .
@ -18,9 +21,15 @@ server-dev:
router-dev: router-dev:
cd router && cargo run -- --port 8080 cd router && cargo run -- --port 8080
integration-tests: install-router install-launcher rust-tests: install-router install-launcher
cargo test cargo test
integration-tests: install-integration-tests
pytest -s -vv integration-tests
update-integration-tests: install-integration-tests
pytest -s -vv --snapshot-update integration-tests
python-server-tests: python-server-tests:
HF_HUB_ENABLE_HF_TRANSFER=1 pytest server/tests HF_HUB_ENABLE_HF_TRANSFER=1 pytest server/tests

2
README.md
View File

@ -253,5 +253,7 @@ make python-client-tests
# or both server and client tests # or both server and client tests
make python-tests make python-tests
# rust cargo tests # rust cargo tests
make rust-tests
# integration tests
make integration-tests make integration-tests
``` ```

13
integration-tests/conftest.py
View File

@ -13,6 +13,7 @@ from text_generation.types import Response
DOCKER_IMAGE = os.getenv("DOCKER_IMAGE", None) DOCKER_IMAGE = os.getenv("DOCKER_IMAGE", None)
HUGGING_FACE_HUB_TOKEN = os.getenv("HUGGING_FACE_HUB_TOKEN", None) HUGGING_FACE_HUB_TOKEN = os.getenv("HUGGING_FACE_HUB_TOKEN", None)
DOCKER_VOLUME = os.getenv("DOCKER_VOLUME", "/data")
@pytest.fixture(scope="module") @pytest.fixture(scope="module")
@ -26,7 +27,7 @@ def event_loop():
def launcher(event_loop): def launcher(event_loop):
@contextlib.contextmanager @contextlib.contextmanager
def local_launcher( def local_launcher(
model_id: str, num_shard: Optional[int] = None, quantize: bool = False model_id: str, num_shard: Optional[int] = None, quantize: Optional[str] = None
): ):
port = 9999 port = 9999
master_port = 19999 master_port = 19999
@ -66,7 +67,7 @@ def launcher(event_loop):
@contextlib.contextmanager @contextlib.contextmanager
def docker_launcher( def docker_launcher(
model_id: str, num_shard: Optional[int] = None, quantize: bool = False model_id: str, num_shard: Optional[int] = None, quantize: Optional[str] = None
): ):
port = 9999 port = 9999
@ -94,6 +95,10 @@ def launcher(event_loop):
if HUGGING_FACE_HUB_TOKEN is not None: if HUGGING_FACE_HUB_TOKEN is not None:
env["HUGGING_FACE_HUB_TOKEN"] = HUGGING_FACE_HUB_TOKEN env["HUGGING_FACE_HUB_TOKEN"] = HUGGING_FACE_HUB_TOKEN
volumes = []
if DOCKER_VOLUME:
volumes = [f"{DOCKER_VOLUME}:/data"]
container = client.containers.run( container = client.containers.run(
DOCKER_IMAGE, DOCKER_IMAGE,
command=args, command=args,
@ -104,7 +109,7 @@ def launcher(event_loop):
device_requests=[ device_requests=[
docker.types.DeviceRequest(count=gpu_count, capabilities=[["gpu"]]) docker.types.DeviceRequest(count=gpu_count, capabilities=[["gpu"]])
], ],
volumes=["/data:/data"], volumes=volumes,
ports={"80/tcp": port}, ports={"80/tcp": port},
) )
@ -130,6 +135,6 @@ def generate_load():
] ]
results = await asyncio.gather(*futures) results = await asyncio.gather(*futures)
return results return [r.generated_text for r in results]
return generate_load_inner return generate_load_inner

247
integration-tests/models/__snapshots__/test_bloom_560m.ambr
View File

@ -7,88 +7,233 @@
'generated_tokens': 10, 'generated_tokens': 10,
'prefill': list([ 'prefill': list([
dict({ dict({
'id': 10264, 'id': 17934,
'logprob': None, 'logprob': None,
'text': 'Test', 'text': 'Pour',
}), }),
dict({ dict({
'id': 8821, 'id': 49833,
'logprob': -11.3125, 'logprob': -10.5625,
'text': ' request', 'text': ' dég',
}),
]),
'seed': None,
'tokens': list([
dict({
'id': 11,
'logprob': -2.859375,
'special': False,
'text': '(',
}), }),
dict({ dict({
'id': 5, 'id': 21543,
'logprob': -2.34375, 'logprob': -0.14770508,
'special': False, 'text': 'uster',
'text': '"',
}), }),
dict({ dict({
'id': 1587, 'id': 447,
'logprob': -3.25, 'logprob': -1.9287109,
'special': False, 'text': ' un',
'text': 'get',
}), }),
dict({ dict({
'id': 5, 'id': 46341,
'logprob': -1.828125, 'logprob': -15.4609375,
'special': False, 'text': ' ort',
'text': '"', }),
dict({
'id': 35567,
'logprob': -7.5585938,
'text': 'olan',
}), }),
dict({ dict({
'id': 15, 'id': 15,
'logprob': -0.35546875, 'logprob': -1.4003906,
'special': False,
'text': ',', 'text': ',',
}), }),
dict({ dict({
'id': 567, 'id': 1669,
'logprob': -2.4375, 'logprob': -1.5673828,
'special': False, 'text': ' il',
'text': ' "',
}), }),
dict({ dict({
'id': 17, 'id': 11580,
'logprob': -4.40625, 'logprob': -0.94628906,
'special': False, 'text': ' faut',
'text': '.',
}), }),
dict({ dict({
'id': 5, 'id': 3913,
'logprob': -2.46875, 'logprob': -3.703125,
'special': False, 'text': ' tout',
'text': '"',
}), }),
dict({ dict({
'id': 12, 'id': 39261,
'logprob': -1.6015625, 'logprob': -1.5732422,
'text': " d'abord",
}),
]),
'seed': 0,
'tokens': list([
dict({
'id': 578,
'logprob': -1.6591797,
'special': False, 'special': False,
'text': ')', 'text': ' le',
}), }),
dict({ dict({
'id': 30, 'id': 5608,
'logprob': -0.14550781, 'logprob': -2.4492188,
'special': False, 'special': False,
'text': ';', 'text': ' faire',
}),
dict({
'id': 159570,
'logprob': -6.6835938,
'special': False,
'text': ' réch',
}),
dict({
'id': 810,
'logprob': 0.0,
'special': False,
'text': 'au',
}),
dict({
'id': 12736,
'logprob': 0.0,
'special': False,
'text': 'ffer',
}),
dict({
'id': 1742,
'logprob': -2.5175781,
'special': False,
'text': ' au',
}),
dict({
'id': 6105,
'logprob': -2.0078125,
'special': False,
'text': ' bain',
}),
dict({
'id': 88254,
'logprob': -0.12695312,
'special': False,
'text': '-mar',
}),
dict({
'id': 641,
'logprob': 0.0,
'special': False,
'text': 'ie',
}),
dict({
'id': 2940,
'logprob': -3.5175781,
'special': False,
'text': ' avec',
}), }),
]), ]),
}), }),
'generated_text': '("get", ".");', 'generated_text': ' le faire réchauffer au bain-marie avec',
})
# ---
# name: test_bloom_560m_all_params
dict({
'details': dict({
'best_of_sequences': None,
'finish_reason': <FinishReason.Length: 'length'>,
'generated_tokens': 10,
'prefill': list([
dict({
'id': 15,
'logprob': None,
'text': ',',
}),
dict({
'id': 1669,
'logprob': -5.4414062,
'text': ' il',
}),
dict({
'id': 11580,
'logprob': -2.3378906,
'text': ' faut',
}),
dict({
'id': 3913,
'logprob': -4.3554688,
'text': ' tout',
}),
dict({
'id': 39261,
'logprob': -2.9238281,
'text': " d'abord",
}),
]),
'seed': 0,
'tokens': list([
dict({
'id': 408,
'logprob': -1.9267578,
'special': False,
'text': ' que',
}),
dict({
'id': 20288,
'logprob': -2.9257812,
'special': False,
'text': " l'on",
}),
dict({
'id': 22255,
'logprob': -2.8964844,
'special': False,
'text': ' trouve',
}),
dict({
'id': 1622,
'logprob': -1.1083984,
'special': False,
'text': ' une',
}),
dict({
'id': 187079,
'logprob': -7.796875,
'special': False,
'text': ' posture',
}),
dict({
'id': 501,
'logprob': -5.390625,
'special': False,
'text': ' par',
}),
dict({
'id': 8741,
'logprob': -0.34936523,
'special': False,
'text': ' rapport',
}),
dict({
'id': 693,
'logprob': 0.0,
'special': False,
'text': ' à',
}),
dict({
'id': 366,
'logprob': -2.3378906,
'special': False,
'text': ' la',
}),
dict({
'id': 36503,
'logprob': -3.6640625,
'special': False,
'text': ' pratique',
}),
]),
}),
'generated_text': "Pour déguster un ortolan, il faut tout d'abord que l'on trouve une posture par rapport à la pratique",
}) })
# --- # ---
# name: test_bloom_560m_load # name: test_bloom_560m_load
list([ list([
Response(generated_text='("get", ".");', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=10264, text='Test', logprob=None), PrefillToken(id=8821, text=' request', logprob=-11.3125)], tokens=[Token(id=11, text='(', logprob=-2.859375, special=False), Token(id=5, text='"', logprob=-2.421875, special=False), Token(id=1587, text='get', logprob=-3.109375, special=False), Token(id=5, text='"', logprob=-2.046875, special=False), Token(id=15, text=',', logprob=-0.37890625, special=False), Token(id=567, text=' "', logprob=-2.65625, special=False), Token(id=17, text='.', logprob=-4.28125, special=False), Token(id=5, text='"', logprob=-2.1875, special=False), Token(id=12, text=')', logprob=-1.6328125, special=False), Token(id=30, text=';', logprob=-0.16113281, special=False)], best_of_sequences=None)), " le faire cuire dans de l'eau bouillante sal",
Response(generated_text='("get", ".");', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=10264, text='Test', logprob=None), PrefillToken(id=8821, text=' request', logprob=-11.3125)], tokens=[Token(id=11, text='(', logprob=-2.859375, special=False), Token(id=5, text='"', logprob=-2.421875, special=False), Token(id=1587, text='get', logprob=-3.109375, special=False), Token(id=5, text='"', logprob=-2.046875, special=False), Token(id=15, text=',', logprob=-0.37890625, special=False), Token(id=567, text=' "', logprob=-2.65625, special=False), Token(id=17, text='.', logprob=-4.28125, special=False), Token(id=5, text='"', logprob=-2.1875, special=False), Token(id=12, text=')', logprob=-1.6328125, special=False), Token(id=30, text=';', logprob=-0.16113281, special=False)], best_of_sequences=None)), " le faire cuire dans de l'eau bouillante sal",
Response(generated_text='("get", ".");', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=10264, text='Test', logprob=None), PrefillToken(id=8821, text=' request', logprob=-11.3125)], tokens=[Token(id=11, text='(', logprob=-2.859375, special=False), Token(id=5, text='"', logprob=-2.421875, special=False), Token(id=1587, text='get', logprob=-3.109375, special=False), Token(id=5, text='"', logprob=-2.046875, special=False), Token(id=15, text=',', logprob=-0.37890625, special=False), Token(id=567, text=' "', logprob=-2.65625, special=False), Token(id=17, text='.', logprob=-4.28125, special=False), Token(id=5, text='"', logprob=-2.1875, special=False), Token(id=12, text=')', logprob=-1.6328125, special=False), Token(id=30, text=';', logprob=-0.16113281, special=False)], best_of_sequences=None)), " le faire cuire dans de l'eau bouillante sal",
Response(generated_text='("get", ".");', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=10264, text='Test', logprob=None), PrefillToken(id=8821, text=' request', logprob=-11.3125)], tokens=[Token(id=11, text='(', logprob=-2.859375, special=False), Token(id=5, text='"', logprob=-2.421875, special=False), Token(id=1587, text='get', logprob=-3.109375, special=False), Token(id=5, text='"', logprob=-2.046875, special=False), Token(id=15, text=',', logprob=-0.37890625, special=False), Token(id=567, text=' "', logprob=-2.65625, special=False), Token(id=17, text='.', logprob=-4.28125, special=False), Token(id=5, text='"', logprob=-2.1875, special=False), Token(id=12, text=')', logprob=-1.6328125, special=False), Token(id=30, text=';', logprob=-0.16113281, special=False)], best_of_sequences=None)), " le faire cuire dans de l'eau bouillante sal",
]) ])
# --- # ---

147
integration-tests/models/__snapshots__/test_bloom_560m_sharded.ambr
View File

@ -7,88 +7,133 @@
'generated_tokens': 10, 'generated_tokens': 10,
'prefill': list([ 'prefill': list([
dict({ dict({
'id': 10264, 'id': 17934,
'logprob': None, 'logprob': None,
'text': 'Test', 'text': 'Pour',
}), }),
dict({ dict({
'id': 8821, 'id': 49833,
'logprob': -11.375, 'logprob': -10.5390625,
'text': ' request', 'text': ' dég',
}),
]),
'seed': None,
'tokens': list([
dict({
'id': 11,
'logprob': -2.734375,
'special': False,
'text': '(',
}), }),
dict({ dict({
'id': 5, 'id': 21543,
'logprob': -1.9765625, 'logprob': -0.14758301,
'special': False, 'text': 'uster',
'text': '"',
}), }),
dict({ dict({
'id': 1587, 'id': 447,
'logprob': -3.140625, 'logprob': -1.9296875,
'special': False, 'text': ' un',
'text': 'get',
}), }),
dict({ dict({
'id': 5, 'id': 46341,
'logprob': -3.515625, 'logprob': -15.4453125,
'special': False, 'text': ' ort',
'text': '"', }),
dict({
'id': 35567,
'logprob': -7.59375,
'text': 'olan',
}), }),
dict({ dict({
'id': 15, 'id': 15,
'logprob': -0.37304688, 'logprob': -1.3994141,
'special': False,
'text': ',', 'text': ',',
}), }),
dict({ dict({
'id': 567, 'id': 1669,
'logprob': -2.6875, 'logprob': -1.578125,
'special': False, 'text': ' il',
'text': ' "',
}), }),
dict({ dict({
'id': 17, 'id': 11580,
'logprob': -4.65625, 'logprob': -0.9453125,
'special': False, 'text': ' faut',
'text': '.',
}), }),
dict({ dict({
'id': 5, 'id': 3913,
'logprob': -2.28125, 'logprob': -3.7011719,
'special': False, 'text': ' tout',
'text': '"',
}), }),
dict({ dict({
'id': 12, 'id': 39261,
'logprob': -1.6640625, 'logprob': -1.5732422,
'text': " d'abord",
}),
]),
'seed': 0,
'tokens': list([
dict({
'id': 578,
'logprob': -1.6474609,
'special': False, 'special': False,
'text': ')', 'text': ' le',
}), }),
dict({ dict({
'id': 30, 'id': 5608,
'logprob': -0.14355469, 'logprob': -2.5097656,
'special': False, 'special': False,
'text': ';', 'text': ' faire',
}),
dict({
'id': 159570,
'logprob': -6.65625,
'special': False,
'text': ' réch',
}),
dict({
'id': 810,
'logprob': 0.0,
'special': False,
'text': 'au',
}),
dict({
'id': 12736,
'logprob': 0.0,
'special': False,
'text': 'ffer',
}),
dict({
'id': 1742,
'logprob': -2.5859375,
'special': False,
'text': ' au',
}),
dict({
'id': 6105,
'logprob': -2.03125,
'special': False,
'text': ' bain',
}),
dict({
'id': 88254,
'logprob': -0.12695312,
'special': False,
'text': '-mar',
}),
dict({
'id': 641,
'logprob': 0.0,
'special': False,
'text': 'ie',
}),
dict({
'id': 2940,
'logprob': -3.5175781,
'special': False,
'text': ' avec',
}), }),
]), ]),
}), }),
'generated_text': '("get", ".");', 'generated_text': ' le faire réchauffer au bain-marie avec',
}) })
# --- # ---
# name: test_bloom_560m_sharded_load # name: test_bloom_560m_sharded_load
list([ list([
Response(generated_text='("get", ".");', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=10264, text='Test', logprob=None), PrefillToken(id=8821, text=' request', logprob=-11.375)], tokens=[Token(id=11, text='(', logprob=-2.734375, special=False), Token(id=5, text='"', logprob=-2.328125, special=False), Token(id=1587, text='get', logprob=-2.953125, special=False), Token(id=5, text='"', logprob=-3.546875, special=False), Token(id=15, text=',', logprob=-0.359375, special=False), Token(id=567, text=' "', logprob=-2.484375, special=False), Token(id=17, text='.', logprob=-4.0625, special=False), Token(id=5, text='"', logprob=-2.46875, special=False), Token(id=12, text=')', logprob=-1.671875, special=False), Token(id=30, text=';', logprob=-0.18164062, special=False)], best_of_sequences=None)), " le faire cuire dans de l'eau bouillante sal",
Response(generated_text='("get", ".");', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=10264, text='Test', logprob=None), PrefillToken(id=8821, text=' request', logprob=-11.375)], tokens=[Token(id=11, text='(', logprob=-2.734375, special=False), Token(id=5, text='"', logprob=-2.328125, special=False), Token(id=1587, text='get', logprob=-2.953125, special=False), Token(id=5, text='"', logprob=-3.546875, special=False), Token(id=15, text=',', logprob=-0.359375, special=False), Token(id=567, text=' "', logprob=-2.484375, special=False), Token(id=17, text='.', logprob=-4.0625, special=False), Token(id=5, text='"', logprob=-2.46875, special=False), Token(id=12, text=')', logprob=-1.671875, special=False), Token(id=30, text=';', logprob=-0.18164062, special=False)], best_of_sequences=None)), " le faire cuire dans de l'eau bouillante sal",
Response(generated_text='("get", ".");', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=10264, text='Test', logprob=None), PrefillToken(id=8821, text=' request', logprob=-11.375)], tokens=[Token(id=11, text='(', logprob=-2.734375, special=False), Token(id=5, text='"', logprob=-2.328125, special=False), Token(id=1587, text='get', logprob=-2.953125, special=False), Token(id=5, text='"', logprob=-3.546875, special=False), Token(id=15, text=',', logprob=-0.359375, special=False), Token(id=567, text=' "', logprob=-2.484375, special=False), Token(id=17, text='.', logprob=-4.0625, special=False), Token(id=5, text='"', logprob=-2.46875, special=False), Token(id=12, text=')', logprob=-1.671875, special=False), Token(id=30, text=';', logprob=-0.18164062, special=False)], best_of_sequences=None)), " le faire cuire dans de l'eau bouillante sal",
Response(generated_text='("get", ".");', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=10264, text='Test', logprob=None), PrefillToken(id=8821, text=' request', logprob=-11.375)], tokens=[Token(id=11, text='(', logprob=-2.734375, special=False), Token(id=5, text='"', logprob=-2.328125, special=False), Token(id=1587, text='get', logprob=-2.953125, special=False), Token(id=5, text='"', logprob=-3.546875, special=False), Token(id=15, text=',', logprob=-0.359375, special=False), Token(id=567, text=' "', logprob=-2.484375, special=False), Token(id=17, text='.', logprob=-4.0625, special=False), Token(id=5, text='"', logprob=-2.46875, special=False), Token(id=12, text=')', logprob=-1.671875, special=False), Token(id=30, text=';', logprob=-0.18164062, special=False)], best_of_sequences=None)), " le faire cuire dans de l'eau bouillante sal",
]) ])
# --- # ---

195
integration-tests/models/__snapshots__/test_flash_llama.ambr Normal file
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@ -0,0 +1,195 @@
# serializer version: 1
# name: test_flash_llama
dict({
'details': dict({
'best_of_sequences': None,
'finish_reason': <FinishReason.Length: 'length'>,
'generated_tokens': 10,
'prefill': list([
dict({
'id': 1,
'logprob': None,
'text': '<s>',
}),
dict({
'id': 4321,
'logprob': -8.6875,
'text': 'Test',
}),
dict({
'id': 2009,
'logprob': -11.5546875,
'text': 'request',
}),
]),
'seed': None,
'tokens': list([
dict({
'id': 363,
'logprob': -1.5380859,
'special': False,
'text': ' for',
}),
dict({
'id': 847,
'logprob': -2.5917969,
'special': False,
'text': ' /',
}),
dict({
'id': 2754,
'logprob': -2.2773438,
'special': False,
'text': 'api',
}),
dict({
'id': 29914,
'logprob': -0.034362793,
'special': False,
'text': '/',
}),
dict({
'id': 29894,
'logprob': -0.96533203,
'special': False,
'text': 'v',
}),
dict({
'id': 29896,
'logprob': -0.36669922,
'special': False,
'text': '1',
}),
dict({
'id': 29914,
'logprob': -0.013122559,
'special': False,
'text': '/',
}),
dict({
'id': 16418,
'logprob': -3.1503906,
'special': False,
'text': 'projects',
}),
dict({
'id': 29914,
'logprob': -0.43652344,
'special': False,
'text': '/',
}),
dict({
'id': 29896,
'logprob': -1.9404297,
'special': False,
'text': '1',
}),
]),
}),
'generated_text': 'for /api/v1/projects/1',
})
# ---
# name: test_flash_llama_all_params
dict({
'details': dict({
'best_of_sequences': None,
'finish_reason': <FinishReason.Length: 'length'>,
'generated_tokens': 10,
'prefill': list([
dict({
'id': 1,
'logprob': None,
'text': '<s>',
}),
dict({
'id': 4321,
'logprob': -8.6875,
'text': 'Test',
}),
dict({
'id': 2009,
'logprob': -11.5546875,
'text': 'request',
}),
]),
'seed': 0,
'tokens': list([
dict({
'id': 5229,
'logprob': -3.3085938,
'special': False,
'text': ' failed',
}),
dict({
'id': 363,
'logprob': -3.984375,
'special': False,
'text': ' for',
}),
dict({
'id': 5641,
'logprob': -6.53125,
'special': False,
'text': ' IP',
}),
dict({
'id': 16428,
'logprob': -3.1835938,
'special': False,
'text': ' Address',
}),
dict({
'id': 29901,
'logprob': -1.2324219,
'special': False,
'text': ':',
}),
dict({
'id': 525,
'logprob': -2.6855469,
'special': False,
'text': " '",
}),
dict({
'id': 8516,
'logprob': -7.1601562,
'special': False,
'text': 'None',
}),
dict({
'id': 4286,
'logprob': -2.4433594,
'special': False,
'text': "'.",
}),
dict({
'id': 13,
'logprob': -0.06530762,
'special': False,
'text': '''
''',
}),
dict({
'id': 294,
'logprob': -7.953125,
'special': False,
'text': 'as',
}),
]),
}),
'generated_text': '''
Test requestfailed for IP Address: 'None'.
as
''',
})
# ---
# name: test_flash_llama_load
list([
'for /api/v1/projects/1',
'for /api/v1/projects/1',
'for /api/v1/projects/1',
'for /api/v1/projects/1',
])
# ---

174
integration-tests/models/__snapshots__/test_flash_neox.ambr Normal file
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@ -0,0 +1,174 @@
# serializer version: 1
# name: test_flash_neox
dict({
'details': dict({
'best_of_sequences': None,
'finish_reason': <FinishReason.Length: 'length'>,
'generated_tokens': 10,
'prefill': list([
dict({
'id': 50278,
'logprob': None,
'text': '<|prompter|>',
}),
dict({
'id': 1276,
'logprob': -8.03125,
'text': 'What',
}),
dict({
'id': 310,
'logprob': -5.421875,
'text': ' is',
}),
dict({
'id': 247,
'logprob': -2.1601562,
'text': ' a',
}),
dict({
'id': 1167,
'logprob': -5.4609375,
'text': ' mem',
}),
dict({
'id': 70,
'logprob': -0.005657196,
'text': 'e',
}),
dict({
'id': 13,
'logprob': -7.28125,
'text': ',',
}),
dict({
'id': 285,
'logprob': -0.2980957,
'text': ' and',
}),
dict({
'id': 752,
'logprob': -2.1679688,
'text': ' what',
}),
dict({
'id': 434,
'logprob': -5.6210938,
'text': "'s",
}),
dict({
'id': 253,
'logprob': -0.81103516,
'text': ' the',
}),
dict({
'id': 2892,
'logprob': -6.6640625,
'text': ' history',
}),
dict({
'id': 3212,
'logprob': -2.265625,
'text': ' behind',
}),
dict({
'id': 436,
'logprob': -11.5078125,
'text': ' this',
}),
dict({
'id': 3159,
'logprob': -2.1582031,
'text': ' word',
}),
dict({
'id': 32,
'logprob': -0.008720398,
'text': '?',
}),
dict({
'id': 0,
'logprob': -2.4726562,
'text': '<|endoftext|>',
}),
dict({
'id': 50281,
'logprob': -18.265625,
'text': '<|assistant|>',
}),
]),
'seed': None,
'tokens': list([
dict({
'id': 510,
'logprob': -0.63183594,
'special': False,
'text': 'The',
}),
dict({
'id': 3159,
'logprob': -0.5390625,
'special': False,
'text': ' word',
}),
dict({
'id': 346,
'logprob': -0.045684814,
'special': False,
'text': ' "',
}),
dict({
'id': 6441,
'logprob': -0.002090454,
'special': False,
'text': 'mem',
}),
dict({
'id': 70,
'logprob': -1.3589859e-05,
'special': False,
'text': 'e',
}),
dict({
'id': 3,
'logprob': -0.0009455681,
'special': False,
'text': '"',
}),
dict({
'id': 369,
'logprob': -0.088012695,
'special': False,
'text': ' was',
}),
dict({
'id': 806,
'logprob': -0.12585449,
'special': False,
'text': ' first',
}),
dict({
'id': 908,
'logprob': -0.017196655,
'special': False,
'text': ' used',
}),
dict({
'id': 275,
'logprob': -0.49731445,
'special': False,
'text': ' in',
}),
]),
}),
'generated_text': 'The word "meme" was first used in',
})
# ---
# name: test_flash_neox_load
list([
'The word "meme" was first used in',
'The word "meme" was first used in',
'The word "meme" was first used in',
'The word "meme" was first used in',
])
# ---

153
integration-tests/models/__snapshots__/test_flash_santacoder.ambr
View File

@ -7,95 +7,132 @@
'generated_tokens': 10, 'generated_tokens': 10,
'prefill': list([ 'prefill': list([
dict({ dict({
'id': 804, 'id': 563,
'logprob': None, 'logprob': None,
'text': 'Test', 'text': 'def',
}),
dict({
'id': 942,
'logprob': -5.1367188,
'text': ' print',
}),
dict({
'id': 62,
'logprob': -0.24450684,
'text': '_',
}),
dict({
'id': 7196,
'logprob': -6.9609375,
'text': 'hello',
}), }),
]), ]),
'seed': None, 'seed': None,
'tokens': list([ 'tokens': list([
dict({ dict({
'id': 25, 'id': 1241,
'logprob': -2.828125, 'logprob': -0.9863281,
'special': False, 'special': False,
'text': ':', 'text': '():',
}), }),
dict({ dict({
'id': 287, 'id': 258,
'logprob': -1.5703125, 'logprob': -0.21447754,
'special': False,
'text': ' "',
}),
dict({
'id': 385,
'logprob': -0.03955078,
'special': False,
'text': ' +',
}),
dict({
'id': 1028,
'logprob': -1.453125,
'special': False,
'text': ' request',
}),
dict({
'id': 13,
'logprob': -0.796875,
'special': False,
'text': '.',
}),
dict({
'id': 1832,
'logprob': -1.4296875,
'special': False,
'text': 'toString',
}),
dict({
'id': 782,
'logprob': -0.17871094,
'special': False,
'text': '());',
}),
dict({
'id': 259,
'logprob': -1.359375,
'special': False, 'special': False,
'text': ''' 'text': '''
''', ''',
}), }),
dict({ dict({
'id': 294, 'id': 942,
'logprob': -1.6484375, 'logprob': -0.43701172,
'special': False, 'special': False,
'text': ' }', 'text': ' print',
}), }),
dict({ dict({
'id': 437, 'id': 372,
'logprob': -1.0625, 'logprob': -0.5361328,
'special': False,
'text': '("',
}),
dict({
'id': 7371,
'logprob': -0.44555664,
'special': False,
'text': 'Hello',
}),
dict({
'id': 9956,
'logprob': -1.2412109,
'special': False,
'text': ' World',
}),
dict({
'id': 8657,
'logprob': -0.7583008,
'special': False,
'text': '!")',
}),
dict({
'id': 185,
'logprob': -0.76171875,
'special': False, 'special': False,
'text': ''' 'text': '''
''', ''',
}), }),
dict({
'id': 185,
'logprob': -0.20837402,
'special': False,
'text': '''
''',
}),
dict({
'id': 1018,
'logprob': -1.2470703,
'special': False,
'text': 'print',
}),
]), ]),
}), }),
'generated_text': ''' 'generated_text': '''
: " + request.toString()); ():
} print("Hello World!")
print
''', ''',
}) })
# --- # ---
# name: test_flash_santacoder_load # name: test_flash_santacoder_load
list([ list([
Response(generated_text=':\n def __init__(self, name,', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=804, text='Test', logprob=None)], tokens=[Token(id=25, text=':', logprob=-2.828125, special=False), Token(id=258, text='\n ', logprob=-2.828125, special=False), Token(id=458, text=' def', logprob=-0.7421875, special=False), Token(id=945, text=' __', logprob=-0.46679688, special=False), Token(id=955, text='init', logprob=-0.00680542, special=False), Token(id=1218, text='__(', logprob=-0.0049743652, special=False), Token(id=314, text='self', logprob=-0.020629883, special=False), Token(id=11, text=',', logprob=-0.34179688, special=False), Token(id=693, text=' name', logprob=-3.40625, special=False), Token(id=11, text=',', logprob=-0.6875, special=False)], best_of_sequences=None)), '''
Response(generated_text=':\n def __init__(self, name,', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=804, text='Test', logprob=None)], tokens=[Token(id=25, text=':', logprob=-2.828125, special=False), Token(id=258, text='\n ', logprob=-2.828125, special=False), Token(id=458, text=' def', logprob=-0.7421875, special=False), Token(id=945, text=' __', logprob=-0.46679688, special=False), Token(id=955, text='init', logprob=-0.00680542, special=False), Token(id=1218, text='__(', logprob=-0.0049743652, special=False), Token(id=314, text='self', logprob=-0.020629883, special=False), Token(id=11, text=',', logprob=-0.34179688, special=False), Token(id=693, text=' name', logprob=-3.40625, special=False), Token(id=11, text=',', logprob=-0.6875, special=False)], best_of_sequences=None)), ():
Response(generated_text=': " + request.toString());\n }\n\n ', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=804, text='Test', logprob=None)], tokens=[Token(id=25, text=':', logprob=-2.828125, special=False), Token(id=287, text=' "', logprob=-1.5859375, special=False), Token(id=385, text=' +', logprob=-0.037841797, special=False), Token(id=1028, text=' request', logprob=-1.4453125, special=False), Token(id=13, text='.', logprob=-0.79296875, special=False), Token(id=1832, text='toString', logprob=-1.4375, special=False), Token(id=782, text='());', logprob=-0.19335938, special=False), Token(id=259, text='\n ', logprob=-1.359375, special=False), Token(id=294, text=' }', logprob=-1.609375, special=False), Token(id=437, text='\n\n ', logprob=-1.0546875, special=False)], best_of_sequences=None)), print("Hello World!")
Response(generated_text=':\n def __init__(self, name,', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=804, text='Test', logprob=None)], tokens=[Token(id=25, text=':', logprob=-2.828125, special=False), Token(id=258, text='\n ', logprob=-2.828125, special=False), Token(id=458, text=' def', logprob=-0.7421875, special=False), Token(id=945, text=' __', logprob=-0.46679688, special=False), Token(id=955, text='init', logprob=-0.00680542, special=False), Token(id=1218, text='__(', logprob=-0.0049743652, special=False), Token(id=314, text='self', logprob=-0.020629883, special=False), Token(id=11, text=',', logprob=-0.34179688, special=False), Token(id=693, text=' name', logprob=-3.40625, special=False), Token(id=11, text=',', logprob=-0.6875, special=False)], best_of_sequences=None)),
print
''',
'''
():
print("Hello World!")
print
''',
'''
():
print("Hello World!")
print
''',
'''
():
print("Hello World!")
print
''',
]) ])
# --- # ---

240
integration-tests/models/__snapshots__/test_flash_starcoder.ambr
View File

@ -7,83 +7,249 @@
'generated_tokens': 10, 'generated_tokens': 10,
'prefill': list([ 'prefill': list([
dict({ dict({
'id': 1006, 'id': 589,
'logprob': None, 'logprob': None,
'text': 'Test', 'text': 'def',
}),
dict({
'id': 1459,
'logprob': -5.6289062,
'text': ' print',
}),
dict({
'id': 81,
'logprob': -1.6005859,
'text': '_',
}),
dict({
'id': 7656,
'logprob': -5.9921875,
'text': 'hello',
}), }),
]), ]),
'seed': None, 'seed': None,
'tokens': list([ 'tokens': list([
dict({ dict({
'id': 30, 'id': 2262,
'logprob': -2.734375, 'logprob': -0.7705078,
'special': False, 'special': False,
'text': ',', 'text': '():',
}), }),
dict({ dict({
'id': 892, 'id': 284,
'logprob': -2.828125, 'logprob': -0.2590332,
'special': False, 'special': False,
'text': ' String', 'text': '''
''',
}), }),
dict({ dict({
'id': 1984, 'id': 1459,
'logprob': -3.28125, 'logprob': -0.39379883,
'special': False, 'special': False,
'text': ' url', 'text': ' print',
}), }),
dict({ dict({
'id': 30, 'id': 440,
'logprob': -0.796875, 'logprob': -0.61376953,
'special': False, 'special': False,
'text': ',', 'text': '("',
}), }),
dict({ dict({
'id': 892, 'id': 8279,
'logprob': -1.0390625, 'logprob': -0.47338867,
'special': False, 'special': False,
'text': ' String', 'text': 'Hello',
}), }),
dict({ dict({
'id': 1411, 'id': 10896,
'logprob': -2.078125, 'logprob': -1.5068359,
'special': False, 'special': False,
'text': ' method', 'text': ' World',
}), }),
dict({ dict({
'id': 30, 'id': 657,
'logprob': -0.49609375, 'logprob': -0.80810547,
'special': False, 'special': False,
'text': ',', 'text': '")',
}), }),
dict({ dict({
'id': 892, 'id': 203,
'logprob': -1.0546875, 'logprob': -0.7397461,
'special': False, 'special': False,
'text': ' String', 'text': '''
''',
}), }),
dict({ dict({
'id': 3361, 'id': 203,
'logprob': -1.71875, 'logprob': -0.35229492,
'special': False, 'special': False,
'text': ' body', 'text': '''
''',
}), }),
dict({ dict({
'id': 27, 'id': 589,
'logprob': -0.69921875, 'logprob': -1.0371094,
'special': False, 'special': False,
'text': ')', 'text': 'def',
}), }),
]), ]),
}), }),
'generated_text': ', String url, String method, String body)', 'generated_text': '''
():
print("Hello World")
def
''',
})
# ---
# name: test_flash_starcoder_default_params
dict({
'details': dict({
'best_of_sequences': None,
'finish_reason': <FinishReason.EndOfSequenceToken: 'eos_token'>,
'generated_tokens': 12,
'prefill': list([
dict({
'id': 589,
'logprob': None,
'text': 'def',
}),
dict({
'id': 1459,
'logprob': -5.6289062,
'text': ' print',
}),
dict({
'id': 81,
'logprob': -1.6005859,
'text': '_',
}),
dict({
'id': 7656,
'logprob': -5.9921875,
'text': 'hello',
}),
]),
'seed': 0,
'tokens': list([
dict({
'id': 2262,
'logprob': -0.7451172,
'special': False,
'text': '():',
}),
dict({
'id': 284,
'logprob': -0.21325684,
'special': False,
'text': '''
''',
}),
dict({
'id': 5741,
'logprob': -5.734375,
'special': False,
'text': ' logging',
}),
dict({
'id': 32,
'logprob': 0.0,
'special': False,
'text': '.',
}),
dict({
'id': 1338,
'logprob': -0.3232422,
'special': False,
'text': 'info',
}),
dict({
'id': 463,
'logprob': -1.0380859,
'special': False,
'text': "('",
}),
dict({
'id': 8279,
'logprob': -0.8378906,
'special': False,
'text': 'Hello',
}),
dict({
'id': 30,
'logprob': -1.9501953,
'special': False,
'text': ',',
}),
dict({
'id': 10896,
'logprob': -1.3476562,
'special': False,
'text': ' World',
}),
dict({
'id': 683,
'logprob': -1.796875,
'special': False,
'text': "')",
}),
dict({
'id': 203,
'logprob': -0.9873047,
'special': False,
'text': '''
''',
}),
dict({
'id': 0,
'logprob': -0.7495117,
'special': True,
'text': '<|endoftext|>',
}),
]),
}),
'generated_text': '''
():
logging.info('Hello, World')
<|endoftext|>
''',
}) })
# --- # ---
# name: test_flash_starcoder_load # name: test_flash_starcoder_load
list([ list([
Response(generated_text=', String url, String method, String body)', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=1006, text='Test', logprob=None)], tokens=[Token(id=30, text=',', logprob=-2.734375, special=False), Token(id=892, text=' String', logprob=-2.84375, special=False), Token(id=1984, text=' url', logprob=-3.28125, special=False), Token(id=30, text=',', logprob=-0.796875, special=False), Token(id=892, text=' String', logprob=-1.03125, special=False), Token(id=1411, text=' method', logprob=-2.09375, special=False), Token(id=30, text=',', logprob=-0.49804688, special=False), Token(id=892, text=' String', logprob=-1.0546875, special=False), Token(id=3361, text=' body', logprob=-1.7265625, special=False), Token(id=27, text=')', logprob=-0.703125, special=False)], best_of_sequences=None)), '''
Response(generated_text=', GetNext) {\n std::vector<', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=1006, text='Test', logprob=None)], tokens=[Token(id=30, text=',', logprob=-2.734375, special=False), Token(id=1390, text=' Get', logprob=-3.421875, special=False), Token(id=3353, text='Next', logprob=-4.625, special=False), Token(id=27, text=')', logprob=-2.875, special=False), Token(id=301, text=' {', logprob=-0.14453125, special=False), Token(id=334, text='\n ', logprob=-0.17871094, special=False), Token(id=1230, text=' std', logprob=-2.328125, special=False), Token(id=403, text='::', logprob=-0.0007247925, special=False), Token(id=2402, text='vector', logprob=-0.81640625, special=False), Token(id=46, text='<', logprob=-0.0026397705, special=False)], best_of_sequences=None)), ():
Response(generated_text=', GetNext) {\n std::vector<', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=1006, text='Test', logprob=None)], tokens=[Token(id=30, text=',', logprob=-2.734375, special=False), Token(id=1390, text=' Get', logprob=-3.421875, special=False), Token(id=3353, text='Next', logprob=-4.625, special=False), Token(id=27, text=')', logprob=-2.875, special=False), Token(id=301, text=' {', logprob=-0.14453125, special=False), Token(id=334, text='\n ', logprob=-0.17871094, special=False), Token(id=1230, text=' std', logprob=-2.328125, special=False), Token(id=403, text='::', logprob=-0.0007247925, special=False), Token(id=2402, text='vector', logprob=-0.81640625, special=False), Token(id=46, text='<', logprob=-0.0026397705, special=False)], best_of_sequences=None)), print("Hello World")
Response(generated_text=', GetNext) {\n std::vector<', details=Details(finish_reason=<FinishReason.Length: 'length'>, generated_tokens=10, seed=None, prefill=[PrefillToken(id=1006, text='Test', logprob=None)], tokens=[Token(id=30, text=',', logprob=-2.734375, special=False), Token(id=1390, text=' Get', logprob=-3.421875, special=False), Token(id=3353, text='Next', logprob=-4.625, special=False), Token(id=27, text=')', logprob=-2.875, special=False), Token(id=301, text=' {', logprob=-0.14453125, special=False), Token(id=334, text='\n ', logprob=-0.17871094, special=False), Token(id=1230, text=' std', logprob=-2.328125, special=False), Token(id=403, text='::', logprob=-0.0007247925, special=False), Token(id=2402, text='vector', logprob=-0.81640625, special=False), Token(id=46, text='<', logprob=-0.0026397705, special=False)], best_of_sequences=None)),
def
''',
'''
():
print("Hello World")
def
''',
'''
():
print("Hello World")
def
''',
'''
():
print("Hello World")
def
''',
]) ])
# --- # ---

139
integration-tests/models/__snapshots__/test_mt0_base.ambr Normal file
View File

@ -0,0 +1,139 @@
# serializer version: 1
# name: test_mt0_base
dict({
'details': dict({
'best_of_sequences': None,
'finish_reason': <FinishReason.EndOfSequenceToken: 'eos_token'>,
'generated_tokens': 5,
'prefill': list([
dict({
'id': 0,
'logprob': None,
'text': '<pad>',
}),
]),
'seed': 0,
'tokens': list([
dict({
'id': 926,
'logprob': -4.3554688,
'special': False,
'text': 'To',
}),
dict({
'id': 18295,
'logprob': -7.7734375,
'special': False,
'text': ' sell',
}),
dict({
'id': 7868,
'logprob': -3.9257812,
'special': False,
'text': ' things',
}),
dict({
'id': 260,
'logprob': -2.4179688,
'special': False,
'text': '.',
}),
dict({
'id': 1,
'logprob': 0.0,
'special': True,
'text': '</s>',
}),
]),
}),
'generated_text': 'To sell things.',
})
# ---
# name: test_mt0_base_all_params
dict({
'details': dict({
'best_of_sequences': None,
'finish_reason': <FinishReason.Length: 'length'>,
'generated_tokens': 10,
'prefill': list([
dict({
'id': 0,
'logprob': None,
'text': '<pad>',
}),
]),
'seed': 0,
'tokens': list([
dict({
'id': 16017,
'logprob': -1.3505859,
'special': False,
'text': 'blue',
}),
dict({
'id': 20495,
'logprob': -0.50439453,
'special': False,
'text': ' sky',
}),
dict({
'id': 259,
'logprob': -1.2011719,
'special': False,
'text': ' ',
}),
dict({
'id': 15484,
'logprob': -2.8378906,
'special': False,
'text': 'appear',
}),
dict({
'id': 345,
'logprob': -0.87597656,
'special': False,
'text': 'ed',
}),
dict({
'id': 288,
'logprob': -1.8447266,
'special': False,
'text': ' to',
}),
dict({
'id': 35622,
'logprob': -7.1445312,
'special': False,
'text': ' cloud',
}),
dict({
'id': 263,
'logprob': -1.2929688,
'special': False,
'text': 's',
}),
dict({
'id': 14701,
'logprob': -3.0761719,
'special': False,
'text': ' above',
}),
dict({
'id': 751,
'logprob': -4.4375,
'special': False,
'text': ' all',
}),
]),
}),
'generated_text': 'Why is the sky blue?blue sky appeared to clouds above all',
})
# ---
# name: test_mt0_base_load
list([
'Because it is blue',
'Because it is blue',
'Because it is blue',
'Because it is blue',
])
# ---

37
integration-tests/models/test_bloom_560m.py
View File

@ -13,7 +13,35 @@ def bloom_560(launcher):
async def test_bloom_560m(bloom_560, snapshot): async def test_bloom_560m(bloom_560, snapshot):
await health_check(bloom_560, 60) await health_check(bloom_560, 60)
response = await bloom_560.generate("Test request", max_new_tokens=10) response = await bloom_560.generate(
"Pour déguster un ortolan, il faut tout d'abord",
max_new_tokens=10,
top_p=0.9,
seed=0,
)
assert response.details.generated_tokens == 10
assert response == snapshot
@pytest.mark.asyncio
async def test_bloom_560m_all_params(bloom_560, snapshot):
await health_check(bloom_560, 60)
response = await bloom_560.generate(
"Pour déguster un ortolan, il faut tout d'abord",
max_new_tokens=10,
repetition_penalty=1.2,
return_full_text=True,
stop_sequences=["test"],
temperature=0.5,
top_p=0.9,
top_k=10,
truncate=5,
typical_p=0.9,
watermark=True,
seed=0,
)
assert response.details.generated_tokens == 10 assert response.details.generated_tokens == 10
assert response == snapshot assert response == snapshot
@ -23,7 +51,12 @@ async def test_bloom_560m(bloom_560, snapshot):
async def test_bloom_560m_load(bloom_560, generate_load, snapshot): async def test_bloom_560m_load(bloom_560, generate_load, snapshot):
await health_check(bloom_560, 60) await health_check(bloom_560, 60)
responses = await generate_load(bloom_560, "Test request", max_new_tokens=10, n=4) responses = await generate_load(
bloom_560,
"Pour déguster un ortolan, il faut tout d'abord",
max_new_tokens=10,
n=4,
)
assert len(responses) == 4 assert len(responses) == 4

12
integration-tests/models/test_bloom_560m_sharded.py
View File

@ -13,7 +13,12 @@ def bloom_560m_sharded(launcher):
async def test_bloom_560m_sharded(bloom_560m_sharded, snapshot): async def test_bloom_560m_sharded(bloom_560m_sharded, snapshot):
await health_check(bloom_560m_sharded, 60) await health_check(bloom_560m_sharded, 60)
response = await bloom_560m_sharded.generate("Test request", max_new_tokens=10) response = await bloom_560m_sharded.generate(
"Pour déguster un ortolan, il faut tout d'abord",
max_new_tokens=10,
top_p=0.9,
seed=0,
)
assert response.details.generated_tokens == 10 assert response.details.generated_tokens == 10
assert response == snapshot assert response == snapshot
@ -24,7 +29,10 @@ async def test_bloom_560m_sharded_load(bloom_560m_sharded, generate_load, snapsh
await health_check(bloom_560m_sharded, 60) await health_check(bloom_560m_sharded, 60)
responses = await generate_load( responses = await generate_load(
bloom_560m_sharded, "Test request", max_new_tokens=10, n=4 bloom_560m_sharded,
"Pour déguster un ortolan, il faut tout d'abord",
max_new_tokens=10,
n=4,
) )
assert len(responses) == 4 assert len(responses) == 4

53
integration-tests/models/test_flash_llama.py Normal file
View File

@ -0,0 +1,53 @@
import pytest
from utils import health_check
@pytest.fixture(scope="module")
def flash_llama(launcher):
with launcher("huggingface/llama-7b", num_shard=2) as client:
yield client
@pytest.mark.asyncio
async def test_flash_llama(flash_llama, snapshot):
await health_check(flash_llama, 120)
response = await flash_llama.generate("Test request", max_new_tokens=10)
assert response.details.generated_tokens == 10
assert response == snapshot
@pytest.mark.asyncio
async def test_flash_llama_all_params(flash_llama, snapshot):
await health_check(flash_llama, 120)
response = await flash_llama.generate(
"Test request",
max_new_tokens=10,
repetition_penalty=1.2,
return_full_text=True,
stop_sequences=["test"],
temperature=0.5,
top_p=0.9,
top_k=10,
truncate=5,
typical_p=0.9,
watermark=True,
seed=0,
)
assert response.details.generated_tokens == 10
assert response == snapshot
@pytest.mark.asyncio
async def test_flash_llama_load(flash_llama, generate_load, snapshot):
await health_check(flash_llama, 120)
responses = await generate_load(flash_llama, "Test request", max_new_tokens=10, n=4)
assert len(responses) == 4
assert responses == snapshot

38
integration-tests/models/test_flash_neox.py Normal file
View File

@ -0,0 +1,38 @@
import pytest
from utils import health_check
@pytest.fixture(scope="module")
def flash_neox(launcher):
with launcher("OpenAssistant/oasst-sft-1-pythia-12b", num_shard=2) as client:
yield client
@pytest.mark.asyncio
async def test_flash_neox(flash_neox, snapshot):
await health_check(flash_neox, 240)
response = await flash_neox.generate(
"<|prompter|>What is a meme, and what's the history behind this word?<|endoftext|><|assistant|>",
max_new_tokens=10,
)
assert response.details.generated_tokens == 10
assert response == snapshot
@pytest.mark.asyncio
async def test_flash_neox_load(flash_neox, generate_load, snapshot):
await health_check(flash_neox, 240)
responses = await generate_load(
flash_neox,
"<|prompter|>What is a meme, and what's the history behind this word?<|endoftext|><|assistant|>",
max_new_tokens=10,
n=4,
)
assert len(responses) == 4
assert responses == snapshot

4
integration-tests/models/test_flash_santacoder.py
View File

@ -13,7 +13,7 @@ def flash_santacoder(launcher):
async def test_flash_santacoder(flash_santacoder, snapshot): async def test_flash_santacoder(flash_santacoder, snapshot):
await health_check(flash_santacoder, 60) await health_check(flash_santacoder, 60)
response = await flash_santacoder.generate("Test request", max_new_tokens=10) response = await flash_santacoder.generate("def print_hello", max_new_tokens=10)
assert response.details.generated_tokens == 10 assert response.details.generated_tokens == 10
assert response == snapshot assert response == snapshot
@ -24,7 +24,7 @@ async def test_flash_santacoder_load(flash_santacoder, generate_load, snapshot):
await health_check(flash_santacoder, 60) await health_check(flash_santacoder, 60)
responses = await generate_load( responses = await generate_load(
flash_santacoder, "Test request", max_new_tokens=10, n=4 flash_santacoder, "def print_hello", max_new_tokens=10, n=4
) )
assert len(responses) == 4 assert len(responses) == 4

22
integration-tests/models/test_flash_starcoder.py
View File

@ -5,26 +5,38 @@ from utils import health_check
@pytest.fixture(scope="module") @pytest.fixture(scope="module")
def flash_starcoder(launcher): def flash_starcoder(launcher):
with launcher("bigcode/large-model", num_shard=2) as client: with launcher("bigcode/starcoder", num_shard=2) as client:
yield client yield client
@pytest.mark.asyncio @pytest.mark.asyncio
async def test_flash_starcoder(flash_starcoder, snapshot): async def test_flash_starcoder(flash_starcoder, snapshot):
await health_check(flash_starcoder, 60) await health_check(flash_starcoder, 240)
response = await flash_starcoder.generate("Test request", max_new_tokens=10) response = await flash_starcoder.generate("def print_hello", max_new_tokens=10)
assert response.details.generated_tokens == 10 assert response.details.generated_tokens == 10
assert response == snapshot assert response == snapshot
@pytest.mark.asyncio
async def test_flash_starcoder_default_params(flash_starcoder, snapshot):
await health_check(flash_starcoder, 240)
response = await flash_starcoder.generate(
"def print_hello", max_new_tokens=60, temperature=0.2, top_p=0.95, seed=0
)
assert response.details.generated_tokens == 12
assert response == snapshot
@pytest.mark.asyncio @pytest.mark.asyncio
async def test_flash_starcoder_load(flash_starcoder, generate_load, snapshot): async def test_flash_starcoder_load(flash_starcoder, generate_load, snapshot):
await health_check(flash_starcoder, 60) await health_check(flash_starcoder, 240)
responses = await generate_load( responses = await generate_load(
flash_starcoder, "Test request", max_new_tokens=10, n=4 flash_starcoder, "def print_hello", max_new_tokens=10, n=4
) )
assert len(responses) == 4 assert len(responses) == 4

63
integration-tests/models/test_mt0_base.py Normal file
View File

@ -0,0 +1,63 @@
import pytest
from utils import health_check
@pytest.fixture(scope="module")
def mt0_base(launcher):
with launcher("bigscience/mt0-base") as client:
yield client
@pytest.mark.asyncio
async def test_mt0_base(mt0_base, snapshot):
await health_check(mt0_base, 60)
response = await mt0_base.generate(
"Why is the sky blue?",
max_new_tokens=10,
top_p=0.9,
seed=0,
)
assert response.details.generated_tokens == 5
assert response == snapshot
@pytest.mark.asyncio
async def test_mt0_base_all_params(mt0_base, snapshot):
await health_check(mt0_base, 60)
response = await mt0_base.generate(
"Why is the sky blue?",
max_new_tokens=10,
repetition_penalty=1.2,
return_full_text=True,
stop_sequences=["test"],
temperature=0.5,
top_p=0.9,
top_k=10,
truncate=5,
typical_p=0.9,
watermark=True,
seed=0,
)
assert response.details.generated_tokens == 10
assert response == snapshot
@pytest.mark.asyncio
async def test_mt0_base_load(mt0_base, generate_load, snapshot):
await health_check(mt0_base, 60)
responses = await generate_load(
mt0_base,
"Why is the sky blue?",
max_new_tokens=10,
n=4,
)
assert len(responses) == 4
assert responses == snapshot

2
integration-tests/models/utils.py
View File

@ -12,4 +12,4 @@ async def health_check(client: AsyncClient, timeout: int = 60):
return return
except (ClientConnectorError, ClientOSError, ServerDisconnectedError) as e: except (ClientConnectorError, ClientOSError, ServerDisconnectedError) as e:
time.sleep(1) time.sleep(1)
raise e raise RuntimeError("Health check failed")

142
launcher/tests/bloom_560m.json
View File

@ -1,142 +0,0 @@
{
"generated_text": ".get(\"action\");\n if (action == null) {\n throw new RuntimeException",
"details": {
"finish_reason": "length",
"generated_tokens": 20,
"seed": null,
"prefill": [
{
"id": 10264,
"text": "Test",
"logprob": null
},
{
"id": 8821,
"text": " request",
"logprob": -11.894989
}
],
"tokens": [
{
"id": 17,
"text": ".",
"logprob": -1.8267672,
"special": false
},
{
"id": 1587,
"text": "get",
"logprob": -2.4674969,
"special": false
},
{
"id": 11,
"text": "(",
"logprob": -1.906001,
"special": false
},
{
"id": 5,
"text": "\"",
"logprob": -1.2279545,
"special": false
},
{
"id": 4899,
"text": "action",
"logprob": -4.170299,
"special": false
},
{
"id": 5,
"text": "\"",
"logprob": -0.32478866,
"special": false
},
{
"id": 12,
"text": ")",
"logprob": -1.0773665,
"special": false
},
{
"id": 30,
"text": ";",
"logprob": -0.27640742,
"special": false
},
{
"id": 837,
"text": "\n ",
"logprob": -1.6970354,
"special": false
},
{
"id": 1320,
"text": " if",
"logprob": -1.4495516,
"special": false
},
{
"id": 375,
"text": " (",
"logprob": -0.23609057,
"special": false
},
{
"id": 4899,
"text": "action",
"logprob": -1.1916996,
"special": false
},
{
"id": 3535,
"text": " ==",
"logprob": -0.8918753,
"special": false
},
{
"id": 5109,
"text": " null",
"logprob": -0.3933342,
"special": false
},
{
"id": 12,
"text": ")",
"logprob": -0.43212673,
"special": false
},
{
"id": 731,
"text": " {",
"logprob": -0.17702064,
"special": false
},
{
"id": 1260,
"text": "\n ",
"logprob": -0.07027565,
"special": false
},
{
"id": 10519,
"text": " throw",
"logprob": -1.3915029,
"special": false
},
{
"id": 2084,
"text": " new",
"logprob": -0.04201372,
"special": false
},
{
"id": 150858,
"text": " RuntimeException",
"logprob": -1.7329919,
"special": false
}
]
}
}

172
launcher/tests/integration_tests.rs
View File

@ -1,172 +0,0 @@
use float_eq::assert_float_eq;
use serde::Deserialize;
use serde_json::Value;
use std::fs::File;
use std::io::{BufRead, BufReader};
use std::path::PathBuf;
use std::thread;
use std::thread::sleep;
use std::time::Duration;
use subprocess::{Popen, PopenConfig, Redirection};
#[derive(Deserialize)]
pub struct Token {
id: u32,
text: String,
logprob: Option<f32>,
special: bool,
}
#[derive(Deserialize)]
struct Details {
finish_reason: String,
generated_tokens: u32,
tokens: Vec<Token>,
}
#[derive(Deserialize)]
struct GeneratedText {
generated_text: String,
details: Details,
}
fn start_launcher(model_id: String, num_shard: usize, port: usize, master_port: usize) -> Popen {
let argv = vec![
"text-generation-launcher".to_string(),
"--model-id".to_string(),
model_id.clone(),
"--num-shard".to_string(),
num_shard.to_string(),
"--port".to_string(),
port.to_string(),
"--master-port".to_string(),
master_port.to_string(),
"--shard-uds-path".to_string(),
format!("/tmp/test-{}-{}-{}", num_shard, port, master_port),
];
let mut launcher = Popen::create(
&argv,
PopenConfig {
stdout: Redirection::Pipe,
stderr: Redirection::Merge,
..Default::default()
},
)
.expect("Could not start launcher");
// Redirect STDOUT and STDERR to the console
// (STDERR is merged into STDOUT)
let launcher_stdout = launcher.stdout.take().unwrap();
thread::spawn(move || {
let stdout = BufReader::new(launcher_stdout);
for line in stdout.lines() {
println!("{}", line.unwrap());
}
});
for _ in 0..60 {
let health = reqwest::blocking::get(format!("http://localhost:{}/health", port));
if health.is_ok() {
return launcher;
}
sleep(Duration::from_secs(2));
}
launcher.terminate().unwrap();
launcher.wait().unwrap();
panic!("failed to launch {}", model_id)
}
fn test_model(
model_id: String,
num_shard: usize,
port: usize,
master_port: usize,
) -> GeneratedText {
let mut launcher = start_launcher(model_id, num_shard, port, master_port);
let data = r#"
{
"inputs": "Test request",
"parameters": {
"details": true
}
}"#;
let req: Value = serde_json::from_str(data).unwrap();
let client = reqwest::blocking::Client::new();
let res = client
.post(format!("http://localhost:{}/generate", port))
.json(&req)
.send();
launcher.terminate().unwrap();
launcher.wait().unwrap();
let result: GeneratedText = res.unwrap().json().unwrap();
result
}
fn read_json(name: &str) -> GeneratedText {
let mut d = PathBuf::from(env!("CARGO_MANIFEST_DIR"));
d.push("tests/");
d.push(name);
let file = File::open(d).unwrap();
let reader = BufReader::new(file);
let result: GeneratedText = serde_json::from_reader(reader).unwrap();
result
}
fn compare_results(result: GeneratedText, expected: GeneratedText) {
assert_eq!(result.generated_text, expected.generated_text);
assert_eq!(result.details.finish_reason, expected.details.finish_reason);
assert_eq!(
result.details.generated_tokens,
expected.details.generated_tokens
);
for (token, expected_token) in result
.details
.tokens
.into_iter()
.zip(expected.details.tokens.into_iter())
{
assert_eq!(token.id, expected_token.id);
assert_eq!(token.text, expected_token.text);
assert_eq!(token.special, expected_token.special);
if let Some(logprob) = token.logprob {
let expected_logprob = expected_token.logprob.unwrap();
assert_float_eq!(logprob, expected_logprob, abs <= 0.001);
} else {
assert_eq!(token.logprob, expected_token.logprob);
}
}
}
#[test]
fn test_bloom_560m() {
let expected = read_json("bloom_560m.json");
let result = test_model("bigscience/bloom-560m".to_string(), 1, 3000, 29500);
compare_results(result, expected);
}
#[test]
fn test_bloom_560m_distributed() {
let expected = read_json("bloom_560m.json");
let result = test_model("bigscience/bloom-560m".to_string(), 2, 3001, 29501);
compare_results(result, expected);
}
#[test]
fn test_mt0_base() {
let expected = read_json("mt0_base.json");
let result = test_model("bigscience/mt0-base".to_string(), 1, 3002, 29502);
compare_results(result, expected);
}

137
launcher/tests/mt0_base.json
View File

@ -1,137 +0,0 @@
{
"generated_text": "\"\"\"Test the contents of the contents of the contents. \"\"\" test_test",
"details": {
"finish_reason": "length",
"generated_tokens": 20,
"seed": null,
"prefill": [
{
"id": 0,
"text": "<pad>",
"logprob": null
}
],
"tokens": [
{
"id": 259,
"text": "",
"logprob": -1.3656927,
"special": false
},
{
"id": 215100,
"text": "\"\"\"",
"logprob": -2.6551573,
"special": false
},
{
"id": 46138,
"text": "Test",
"logprob": -1.8059857,
"special": false
},
{
"id": 287,
"text": " the",
"logprob": -1.2102449,
"special": false
},
{
"id": 259,
"text": " ",
"logprob": -1.6057279,
"special": false
},
{
"id": 49076,
"text": "contents",
"logprob": -3.6060903,
"special": false
},
{
"id": 304,
"text": " of",
"logprob": -0.5270343,
"special": false
},
{
"id": 287,
"text": " the",
"logprob": -0.62522805,
"special": false
},
{
"id": 259,
"text": " ",
"logprob": -1.4069618,
"special": false
},
{
"id": 49076,
"text": "contents",
"logprob": -2.621994,
"special": false
},
{
"id": 304,
"text": " of",
"logprob": -1.3172221,
"special": false
},
{
"id": 287,
"text": " the",
"logprob": -0.3501925,
"special": false
},
{
"id": 259,
"text": " ",
"logprob": -0.7219573,
"special": false
},
{
"id": 49076,
"text": "contents",
"logprob": -1.0494149,
"special": false
},
{
"id": 260,
"text": ".",
"logprob": -1.0803378,
"special": false
},
{
"id": 259,
"text": " ",
"logprob": -0.32933083,
"special": false
},
{
"id": 215100,
"text": "\"\"\"",
"logprob": -0.11268901,
"special": false
},
{
"id": 2978,
"text": " test",
"logprob": -1.5846587,
"special": false
},
{
"id": 290,
"text": "_",
"logprob": -0.49796978,
"special": false
},
{
"id": 4125,
"text": "test",
"logprob": -2.0026445,
"special": false
}
]
}
}

1
server/text_generation_server/models/custom_modeling/flash_llama_modeling.py
View File

@ -30,7 +30,6 @@ from typing import Optional
# Flash attention imports # Flash attention imports
import flash_attn_cuda import flash_attn_cuda
from flash_attn.layers.rotary import RotaryEmbedding
from text_generation_server.utils.layers import ( from text_generation_server.utils.layers import (
FastLinear, FastLinear,
TensorParallelRowLinear, TensorParallelRowLinear,

7
server/text_generation_server/models/flash_llama.py
View File

@ -28,7 +28,12 @@ tracer = trace.get_tracer(__name__)
class FlashLlama(FlashCausalLM): class FlashLlama(FlashCausalLM):
def __init__(self, model_id: str, revision: Optional[str] = None, quantize=False): def __init__(
self,
model_id: str,
revision: Optional[str] = None,
quantize: Optional[str] = None,
):
if torch.cuda.is_available(): if torch.cuda.is_available():
device = torch.device("cuda") device = torch.device("cuda")
dtype = torch.float16 dtype = torch.float16

12
server/text_generation_server/models/flash_neox.py
View File

@ -23,7 +23,12 @@ tracer = trace.get_tracer(__name__)
class FlashNeoX(FlashCausalLM): class FlashNeoX(FlashCausalLM):
def __init__(self, model_id: str, revision: Optional[str] = None, quantize=False): def __init__(
self,
model_id: str,
revision: Optional[str] = None,
quantize: Optional[str] = None,
):
super(FlashNeoX, self).__init__( super(FlashNeoX, self).__init__(
FlashGPTNeoXForCausalLM, model_id, revision, quantize FlashGPTNeoXForCausalLM, model_id, revision, quantize
) )
@ -31,7 +36,10 @@ class FlashNeoX(FlashCausalLM):
class FlashNeoXSharded(FlashNeoX): class FlashNeoXSharded(FlashNeoX):
def __init__( def __init__(
self, model_id: str, revision: Optional[str] = None, quantize: bool = False self,
model_id: str,
revision: Optional[str] = None,
quantize: Optional[str] = None,
): ):
self.process_group, rank, world_size = initialize_torch_distributed() self.process_group, rank, world_size = initialize_torch_distributed()
if torch.cuda.is_available(): if torch.cuda.is_available():

12
server/text_generation_server/models/flash_santacoder.py
View File

@ -27,7 +27,12 @@ tracer = trace.get_tracer(__name__)
class FlashSantacoder(FlashCausalLM): class FlashSantacoder(FlashCausalLM):
def __init__(self, model_id: str, revision: Optional[str] = None, quantize=False): def __init__(
self,
model_id: str,
revision: Optional[str] = None,
quantize: Optional[str] = None,
):
if torch.cuda.is_available(): if torch.cuda.is_available():
device = torch.device("cuda") device = torch.device("cuda")
dtype = torch.float16 dtype = torch.float16
@ -170,7 +175,10 @@ class FlashSantacoder(FlashCausalLM):
class FlashSantacoderSharded(FlashSantacoder): class FlashSantacoderSharded(FlashSantacoder):
def __init__( def __init__(
self, model_id: str, revision: Optional[str] = None, quantize: bool = False self,
model_id: str,
revision: Optional[str] = None,
quantize: Optional[str] = None,
): ):
self.process_group, rank, world_size = initialize_torch_distributed() self.process_group, rank, world_size = initialize_torch_distributed()
if torch.cuda.is_available(): if torch.cuda.is_available():

5
server/text_generation_server/models/opt.py
View File

@ -48,7 +48,10 @@ class OPT(CausalLM):
class OPTSharded(OPT): class OPTSharded(OPT):
def __init__( def __init__(
self, model_id: str, revision: Optional[str] = None, quantize: bool = False self,
model_id: str,
revision: Optional[str] = None,
quantize: Optional[str] = None,
): ):
self.process_group, rank, world_size = initialize_torch_distributed() self.process_group, rank, world_size = initialize_torch_distributed()
if torch.cuda.is_available(): if torch.cuda.is_available():