index int64 0 0 | repo_id stringclasses 351
values | file_path stringlengths 26 186 | content stringlengths 1 990k |
|---|---|---|---|
0 | hf_public_repos/api-inference-community | hf_public_repos/api-inference-community/tests/test_audio.py | import os
from unittest import TestCase
import numpy as np
from api_inference_community.validation import ffmpeg_convert, normalize_payload_audio
class ValidationTestCase(TestCase):
def read(self, filename: str) -> bytes:
dirname = os.path.dirname(os.path.abspath(__file__))
filename = os.path.joi... |
0 | hf_public_repos/api-inference-community | hf_public_repos/api-inference-community/tests/test_normalizers.py | from unittest import TestCase
import torch
from api_inference_community.normalizers import speaker_diarization_normalize
class NormalizersTestCase(TestCase):
def test_speaker_diarization_dummy(self):
tensor = torch.zeros((10, 2))
outputs = speaker_diarization_normalize(
tensor, 16000,... |
0 | hf_public_repos/api-inference-community | hf_public_repos/api-inference-community/tests/test_nlp.py | import json
from unittest import TestCase
from api_inference_community.validation import normalize_payload_nlp
from parameterized import parameterized
from pydantic import ValidationError
class ValidationTestCase(TestCase):
def test_malformed_input(self):
bpayload = b"\xc3\x28"
with self.assertRa... |
0 | hf_public_repos/api-inference-community | hf_public_repos/api-inference-community/tests/test_image.py | import os
from unittest import TestCase
import PIL
from api_inference_community.validation import normalize_payload_image
class ValidationTestCase(TestCase):
def test_original_imagefile(self):
dirname = os.path.dirname(os.path.abspath(__file__))
filename = os.path.join(dirname, "samples", "plane.... |
0 | hf_public_repos/api-inference-community | hf_public_repos/api-inference-community/tests/test_routes.py | import io
import json
import logging
import os
from base64 import b64encode
from unittest import TestCase
import numpy as np
from api_inference_community.routes import pipeline_route, status_ok
from PIL import Image
from starlette.applications import Starlette
from starlette.routing import Route
from starlette.testcli... |
0 | hf_public_repos/api-inference-community | hf_public_repos/api-inference-community/tests/test_dockers.py | import base64
import json
import os
import subprocess
import time
import unittest
import uuid
from collections import Counter
from typing import Any, Optional
import httpx
class DockerPopen(subprocess.Popen):
def __exit__(self, exc_type, exc_val, traceback):
self.terminate()
self.wait(20)
... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/setfit/Dockerfile | FROM tiangolo/uvicorn-gunicorn:python3.8
LABEL maintainer="Tom Aarsen <tom.aarsen@huggingface.co>"
# Add any system dependency here
# RUN apt-get update -y && apt-get install libXXX -y
COPY ./requirements.txt /app
RUN pip install --no-cache-dir -r requirements.txt
COPY ./prestart.sh /app/
# Most DL models are quite... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/setfit/requirements.txt | starlette==0.27.0
git+https://github.com/huggingface/api-inference-community.git@f06a71e72e92caeebabaeced979eacb3542bf2ca
huggingface_hub==0.20.2
setfit==1.0.3
|
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/setfit/prestart.sh | python app/main.py
|
0 | hf_public_repos/api-inference-community/docker_images/setfit | hf_public_repos/api-inference-community/docker_images/setfit/app/main.py | import functools
import logging
import os
import pathlib
from typing import Dict, Type
from api_inference_community import hub
from api_inference_community.routes import pipeline_route, status_ok
from app.pipelines import Pipeline, TextClassificationPipeline
from huggingface_hub import constants
from starlette.applica... |
0 | hf_public_repos/api-inference-community/docker_images/setfit/app | hf_public_repos/api-inference-community/docker_images/setfit/app/pipelines/base.py | from abc import ABC, abstractmethod
from typing import Any
class Pipeline(ABC):
@abstractmethod
def __init__(self, model_id: str):
raise NotImplementedError("Pipelines should implement an __init__ method")
@abstractmethod
def __call__(self, inputs: Any) -> Any:
raise NotImplementedErr... |
0 | hf_public_repos/api-inference-community/docker_images/setfit/app | hf_public_repos/api-inference-community/docker_images/setfit/app/pipelines/__init__.py | from app.pipelines.base import Pipeline, PipelineException
from app.pipelines.text_classification import TextClassificationPipeline
|
0 | hf_public_repos/api-inference-community/docker_images/setfit/app | hf_public_repos/api-inference-community/docker_images/setfit/app/pipelines/text_classification.py | from typing import Dict, List
from app.pipelines import Pipeline
from setfit import SetFitModel
class TextClassificationPipeline(Pipeline):
def __init__(
self,
model_id: str,
) -> None:
self.model = SetFitModel.from_pretrained(model_id)
def __call__(self, inputs: str) -> List[Dic... |
0 | hf_public_repos/api-inference-community/docker_images/setfit | hf_public_repos/api-inference-community/docker_images/setfit/tests/test_docker_build.py | import os
import subprocess
from unittest import TestCase
class cd:
"""Context manager for changing the current working directory"""
def __init__(self, newPath):
self.newPath = os.path.expanduser(newPath)
def __enter__(self):
self.savedPath = os.getcwd()
os.chdir(self.newPath)
... |
0 | hf_public_repos/api-inference-community/docker_images/setfit | hf_public_repos/api-inference-community/docker_images/setfit/tests/test_api.py | import os
from typing import Dict
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS, get_pipeline
# Must contain at least one example of each implemented pipeline
# Tests do not check the actual values of the model output, so small dummy
# models are recommended for faster tests.
TESTABLE_MODE... |
0 | hf_public_repos/api-inference-community/docker_images/setfit | hf_public_repos/api-inference-community/docker_images/setfit/tests/test_api_text_classification.py | import json
import os
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS
from starlette.testclient import TestClient
from tests.test_api import TESTABLE_MODELS
@skipIf(
"text-classification" not in ALLOWED_TASKS,
"text-classification not implemented",
)
class TextClassificationTestCase(... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/diffusers/Dockerfile | FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu20.04
LABEL maintainer="Nicolas Patry <nicolas@huggingface.co>"
# Add any system dependency here
# RUN apt-get update -y && apt-get install libXXX -y
ENV DEBIAN_FRONTEND=noninteractive
# Install prerequisites
RUN apt-get update && \
apt-get install -y build-essential ... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/diffusers/requirements.txt | starlette==0.27.0
api-inference-community==0.0.36
# to be replaced with diffusers 0.31.0 as soon as released
git+https://github.com/huggingface/diffusers.git@0f079b932d4382ad6675593f9a140b2a74c8cfb4
transformers==4.41.2
accelerate==0.31.0
hf_transfer==0.1.3
pydantic>=2
ftfy==6.1.1
sentencepiece==0.1.97
scipy==1.10.0
to... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/diffusers/prestart.sh | echo "Prestart start at " $(date)
METRICS_ENABLED=${METRICS_ENABLED:-"0"}
if [ "$METRICS_ENABLED" = "1" ];then
echo "Spawning metrics server"
gunicorn -k "uvicorn.workers.UvicornWorker" --bind :${METRICS_PORT:-9400} "app.healthchecks:app" &
pid=$!
echo "Metrics server pid: $pid"
fi
echo "Prestart don... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers | hf_public_repos/api-inference-community/docker_images/diffusers/app/idle.py | import asyncio
import contextlib
import logging
import os
import signal
import time
LOG = logging.getLogger(__name__)
LAST_START = None
LAST_END = None
UNLOAD_IDLE = os.getenv("UNLOAD_IDLE", "").lower() in ("1", "true")
IDLE_TIMEOUT = int(os.getenv("IDLE_TIMEOUT", 15))
async def live_check_loop():
global LAST... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers | hf_public_repos/api-inference-community/docker_images/diffusers/app/healthchecks.py | """
This file allows users to spawn some side service helping with giving a better view on the main ASGI app status.
The issue with the status route of the main application is that it gets unresponsive as soon as all workers get busy.
Thus, you cannot really use the said route as a healthcheck to decide whether your ap... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers | hf_public_repos/api-inference-community/docker_images/diffusers/app/main.py | import asyncio
import functools
import logging
import os
from typing import Dict, Type
from api_inference_community.routes import pipeline_route, status_ok
from app import idle
from app.pipelines import ImageToImagePipeline, Pipeline, TextToImagePipeline
from starlette.applications import Starlette
from starlette.midd... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers | hf_public_repos/api-inference-community/docker_images/diffusers/app/lora.py | import logging
import torch.nn as nn
from app import offline
from safetensors.torch import load_file
logger = logging.getLogger(__name__)
class LoRAPipelineMixin(offline.OfflineBestEffortMixin):
@staticmethod
def _get_lora_weight_name(model_data):
weight_name_candidate = LoRAPipelineMixin._lora_wei... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers | hf_public_repos/api-inference-community/docker_images/diffusers/app/timing.py | import logging
from functools import wraps
from time import time
logger = logging.getLogger(__name__)
def timing(f):
@wraps(f)
def inner(*args, **kwargs):
start = time()
try:
ret = f(*args, **kwargs)
finally:
end = time()
logger.debug("Func: %r too... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers | hf_public_repos/api-inference-community/docker_images/diffusers/app/offline.py | import json
import logging
import os
from huggingface_hub import file_download, hf_api, hf_hub_download, model_info, utils
logger = logging.getLogger(__name__)
class OfflineBestEffortMixin(object):
def _hub_repo_file(self, repo_id, filename, repo_type="model"):
if self.offline_preferred:
tr... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers | hf_public_repos/api-inference-community/docker_images/diffusers/app/validation.py | import re
STR_TO_BOOL = re.compile(r"^\s*true|yes|1\s*$", re.IGNORECASE)
def str_to_bool(s):
return STR_TO_BOOL.match(str(s))
|
0 | hf_public_repos/api-inference-community/docker_images/diffusers/app | hf_public_repos/api-inference-community/docker_images/diffusers/app/pipelines/image_to_image.py | import json
import logging
import os
import torch
from app import idle, offline, timing, validation
from app.pipelines import Pipeline
from diffusers import (
AltDiffusionImg2ImgPipeline,
AltDiffusionPipeline,
AutoPipelineForImage2Image,
ControlNetModel,
DiffusionPipeline,
DPMSolverMultistepSch... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers/app | hf_public_repos/api-inference-community/docker_images/diffusers/app/pipelines/base.py | from abc import ABC, abstractmethod
from typing import Any
class Pipeline(ABC):
@abstractmethod
def __init__(self, model_id: str):
raise NotImplementedError("Pipelines should implement an __init__ method")
@abstractmethod
def __call__(self, inputs: Any) -> Any:
raise NotImplementedErr... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers/app | hf_public_repos/api-inference-community/docker_images/diffusers/app/pipelines/__init__.py | from app.pipelines.base import Pipeline, PipelineException # isort:skip
from app.pipelines.image_to_image import ImageToImagePipeline
from app.pipelines.text_to_image import TextToImagePipeline
|
0 | hf_public_repos/api-inference-community/docker_images/diffusers/app | hf_public_repos/api-inference-community/docker_images/diffusers/app/pipelines/text_to_image.py | import importlib
import json
import logging
import os
from typing import TYPE_CHECKING
import torch
from app import idle, lora, offline, timing, validation
from app.pipelines import Pipeline
from diffusers import (
AutoencoderKL,
AutoPipelineForText2Image,
DiffusionPipeline,
EulerAncestralDiscreteSched... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers | hf_public_repos/api-inference-community/docker_images/diffusers/tests/test_api_text_to_image.py | import os
from io import BytesIO
from unittest import TestCase, skipIf
import PIL
from app.main import ALLOWED_TASKS
from parameterized import parameterized_class
from starlette.testclient import TestClient
from tests.test_api import TESTABLE_MODELS
@skipIf(
"text-to-image" not in ALLOWED_TASKS,
"text-to-ima... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers | hf_public_repos/api-inference-community/docker_images/diffusers/tests/test_api_image_to_image.py | import base64
import os
from io import BytesIO
from unittest import TestCase, skipIf
import PIL
from app.main import ALLOWED_TASKS
from parameterized import parameterized_class
from starlette.testclient import TestClient
from tests.test_api import TESTABLE_MODELS
@skipIf(
"image-to-image" not in ALLOWED_TASKS,
... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers | hf_public_repos/api-inference-community/docker_images/diffusers/tests/test_docker_build.py | import os
import subprocess
from unittest import TestCase
class cd:
"""Context manager for changing the current working directory"""
def __init__(self, newPath):
self.newPath = os.path.expanduser(newPath)
def __enter__(self):
self.savedPath = os.getcwd()
os.chdir(self.newPath)
... |
0 | hf_public_repos/api-inference-community/docker_images/diffusers | hf_public_repos/api-inference-community/docker_images/diffusers/tests/test_api.py | import os
from typing import Dict, List
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS, get_pipeline
# Must contain at least one example of each implemented pipeline
# Tests do not check the actual values of the model output, so small dummy
# models are recommended for faster tests.
TESTABL... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/mindspore/Dockerfile | FROM tiangolo/uvicorn-gunicorn:python3.8
LABEL maintainer="me <me@example.com>"
# Add any system dependency here
RUN apt-get update -y && apt-get install libglib2.0-dev libsm6 libxrender1 libgl1-mesa-glx -y
COPY requirements.txt /app
RUN /usr/local/bin/python -m pip install --upgrade pip && \
pip install --no-cac... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/mindspore/requirements.txt | starlette==0.27.0
api-inference-community==0.0.25
huggingface_hub==0.11.0
tinyms>=0.3.2 |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/mindspore/prestart.sh | python app/main.py
|
0 | hf_public_repos/api-inference-community/docker_images/mindspore | hf_public_repos/api-inference-community/docker_images/mindspore/app/main.py | import functools
import logging
import os
from typing import Dict, Type
from api_inference_community.routes import pipeline_route, status_ok
from app.pipelines import ImageClassificationPipeline, Pipeline
from starlette.applications import Starlette
from starlette.middleware import Middleware
from starlette.middleware... |
0 | hf_public_repos/api-inference-community/docker_images/mindspore/app | hf_public_repos/api-inference-community/docker_images/mindspore/app/pipelines/base.py | from abc import ABC, abstractmethod
from typing import Any, Optional
class Pipeline(ABC):
task: Optional[str] = None
model_id: Optional[str] = None
@abstractmethod
def __init__(self, model_id: str):
raise NotImplementedError("Pipelines should implement an __init__ method")
@abstractmetho... |
0 | hf_public_repos/api-inference-community/docker_images/mindspore/app | hf_public_repos/api-inference-community/docker_images/mindspore/app/pipelines/image_classification.py | import json
import os
from typing import TYPE_CHECKING, Any, Dict, List
import tinyms as ts
from app.pipelines import Pipeline
from huggingface_hub import snapshot_download
from tinyms import Tensor, model, vision
from tinyms.primitives import Softmax
if TYPE_CHECKING:
from PIL import Image
ALLOWED_MODEL = {
... |
0 | hf_public_repos/api-inference-community/docker_images/mindspore/app | hf_public_repos/api-inference-community/docker_images/mindspore/app/pipelines/__init__.py | from app.pipelines.base import Pipeline, PipelineException # isort:skip
from app.pipelines.image_classification import ImageClassificationPipeline
|
0 | hf_public_repos/api-inference-community/docker_images/mindspore | hf_public_repos/api-inference-community/docker_images/mindspore/tests/test_api_image_classification.py | import json
import os
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS
from starlette.testclient import TestClient
from tests.test_api import TESTABLE_MODELS
@skipIf(
"image-classification" not in ALLOWED_TASKS,
"image-classification not implemented",
)
class ImageClassificationTestCa... |
0 | hf_public_repos/api-inference-community/docker_images/mindspore | hf_public_repos/api-inference-community/docker_images/mindspore/tests/test_docker_build.py | import os
import subprocess
from unittest import TestCase
class cd:
"""Context manager for changing the current working directory"""
def __init__(self, newPath):
self.newPath = os.path.expanduser(newPath)
def __enter__(self):
self.savedPath = os.getcwd()
os.chdir(self.newPath)
... |
0 | hf_public_repos/api-inference-community/docker_images/mindspore | hf_public_repos/api-inference-community/docker_images/mindspore/tests/test_api.py | import os
from typing import Dict
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS, get_pipeline
# Must contain at least one example of each implemented pipeline
# Tests do not check the actual values of the model output, so small dummy
# models are recommended for faster tests.
TESTABLE_MODE... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/peft/Dockerfile | FROM tiangolo/uvicorn-gunicorn:python3.8
LABEL maintainer="Nicolas Patry <nicolas@huggingface.co>"
# Add any system dependency here
# RUN apt-get update -y && apt-get install libXXX -y
RUN pip install --no-cache-dir torch==2.0.1
COPY ./requirements.txt /app
RUN pip install --no-cache-dir -r requirements.txt
# Uncomm... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/peft/requirements.txt | starlette==0.27.0
api-inference-community==0.0.31
huggingface_hub==0.18.0
safetensors==0.3.1
peft==0.6.2
transformers==4.35.2
accelerate>=0.21.0
hf_transfer==0.1.3
pydantic==1.8.2
ftfy==6.1.1
sentencepiece==0.1.97
scipy==1.10.0
torch==2.0.1
pydantic<2
#Dummy.
|
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/peft/prestart.sh | echo "Prestart start at " $(date)
python app/main.py
echo "Prestart done at " $(date) |
0 | hf_public_repos/api-inference-community/docker_images/peft | hf_public_repos/api-inference-community/docker_images/peft/app/idle.py | import asyncio
import contextlib
import logging
import os
import signal
import time
LOG = logging.getLogger(__name__)
LAST_START = None
LAST_END = None
UNLOAD_IDLE = os.getenv("UNLOAD_IDLE", "").lower() in ("1", "true")
IDLE_TIMEOUT = int(os.getenv("IDLE_TIMEOUT", 15))
async def live_check_loop():
global LAST... |
0 | hf_public_repos/api-inference-community/docker_images/peft | hf_public_repos/api-inference-community/docker_images/peft/app/main.py | import asyncio
import functools
import logging
import os
from typing import Dict, Type
from api_inference_community.routes import pipeline_route, status_ok
from app import idle
from app.pipelines import Pipeline, TextGenerationPipeline
from starlette.applications import Starlette
from starlette.middleware import Middl... |
0 | hf_public_repos/api-inference-community/docker_images/peft | hf_public_repos/api-inference-community/docker_images/peft/app/timing.py | import logging
from functools import wraps
from time import time
logger = logging.getLogger(__name__)
def timing(f):
@wraps(f)
def inner(*args, **kwargs):
start = time()
try:
ret = f(*args, **kwargs)
finally:
end = time()
logger.debug("Func: %r too... |
0 | hf_public_repos/api-inference-community/docker_images/peft/app | hf_public_repos/api-inference-community/docker_images/peft/app/pipelines/text_generation.py | import logging
import os
import torch
from app import idle, timing
from app.pipelines import Pipeline
from huggingface_hub import model_info
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
logger = logging.getLogger(__name__)
class TextGenerationPipeline(Pipeline):
def _... |
0 | hf_public_repos/api-inference-community/docker_images/peft/app | hf_public_repos/api-inference-community/docker_images/peft/app/pipelines/base.py | from abc import ABC, abstractmethod
from typing import Any
class Pipeline(ABC):
@abstractmethod
def __init__(self, model_id: str):
raise NotImplementedError("Pipelines should implement an __init__ method")
@abstractmethod
def __call__(self, inputs: Any) -> Any:
raise NotImplementedErr... |
0 | hf_public_repos/api-inference-community/docker_images/peft/app | hf_public_repos/api-inference-community/docker_images/peft/app/pipelines/__init__.py | from app.pipelines.base import Pipeline, PipelineException # isort:skip
from app.pipelines.text_generation import TextGenerationPipeline
|
0 | hf_public_repos/api-inference-community/docker_images/peft | hf_public_repos/api-inference-community/docker_images/peft/tests/test_api_text_generation.py | import json
import os
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS
from starlette.testclient import TestClient
from tests.test_api import TESTABLE_MODELS
@skipIf(
"text-generation" not in ALLOWED_TASKS,
"text-generation not implemented",
)
class TextGenerationTestCase(TestCase):
... |
0 | hf_public_repos/api-inference-community/docker_images/peft | hf_public_repos/api-inference-community/docker_images/peft/tests/test_api.py | import os
from typing import Dict
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS, get_pipeline
# Must contain at least one example of each implemented pipeline
# Tests do not check the actual values of the model output, so small dummy
# models are recommended for faster tests.
TESTABLE_MODE... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/pyannote_audio/Dockerfile | FROM tiangolo/uvicorn-gunicorn:python3.8
LABEL maintainer="Hervé Bredin <herve.bredin@irit.fr>"
# Add any system dependency here
# RUN apt-get update -y && apt-get install libXXX -y
RUN apt-get update -y && apt-get install ffmpeg -y
COPY ./requirements.txt /app
RUN pip install --no-cache-dir -r requirements.txt
COPY ... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/pyannote_audio/requirements.txt | starlette==0.27.0
api-inference-community==0.0.25
torch==1.13.1
torchvision==0.12.0
torchaudio==0.11.0
torchtext==0.12.0
speechbrain==0.5.12
pyannote-audio==2.0.1
huggingface_hub==0.8.1
|
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/pyannote_audio/prestart.sh | python app/main.py
|
0 | hf_public_repos/api-inference-community/docker_images/pyannote_audio | hf_public_repos/api-inference-community/docker_images/pyannote_audio/app/main.py | import functools
import logging
import os
from typing import Dict, Type
from api_inference_community.routes import pipeline_route, status_ok
from app.pipelines import AutomaticSpeechRecognitionPipeline, Pipeline
from starlette.applications import Starlette
from starlette.middleware import Middleware
from starlette.mid... |
0 | hf_public_repos/api-inference-community/docker_images/pyannote_audio/app | hf_public_repos/api-inference-community/docker_images/pyannote_audio/app/pipelines/base.py | from abc import ABC, abstractmethod
from typing import Any
class Pipeline(ABC):
@abstractmethod
def __init__(self, model_id: str):
raise NotImplementedError("Pipelines should implement an __init__ method")
@abstractmethod
def __call__(self, inputs: Any) -> Any:
raise NotImplementedErr... |
0 | hf_public_repos/api-inference-community/docker_images/pyannote_audio/app | hf_public_repos/api-inference-community/docker_images/pyannote_audio/app/pipelines/__init__.py | from app.pipelines.base import Pipeline, PipelineException # isort:skip
from app.pipelines.automatic_speech_recognition import (
AutomaticSpeechRecognitionPipeline,
)
|
0 | hf_public_repos/api-inference-community/docker_images/pyannote_audio/app | hf_public_repos/api-inference-community/docker_images/pyannote_audio/app/pipelines/automatic_speech_recognition.py | from typing import Dict
import numpy as np
import torch
from app.pipelines import Pipeline
from pyannote.audio import Pipeline as Pypeline
class AutomaticSpeechRecognitionPipeline(Pipeline):
def __init__(self, model_id: str):
# IMPLEMENT_THIS
# Preload all the elements you are going to need at in... |
0 | hf_public_repos/api-inference-community/docker_images/pyannote_audio | hf_public_repos/api-inference-community/docker_images/pyannote_audio/tests/test_api_automatic_speech_recognition.py | import json
import os
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS
from starlette.testclient import TestClient
from tests.test_api import TESTABLE_MODELS
@skipIf(
"automatic-speech-recognition" not in ALLOWED_TASKS,
"automatic-speech-recognition not implemented",
)
class Automatic... |
0 | hf_public_repos/api-inference-community/docker_images/pyannote_audio | hf_public_repos/api-inference-community/docker_images/pyannote_audio/tests/test_docker_build.py | import os
import subprocess
from unittest import TestCase
class cd:
"""Context manager for changing the current working directory"""
def __init__(self, newPath):
self.newPath = os.path.expanduser(newPath)
def __enter__(self):
self.savedPath = os.getcwd()
os.chdir(self.newPath)
... |
0 | hf_public_repos/api-inference-community/docker_images/pyannote_audio | hf_public_repos/api-inference-community/docker_images/pyannote_audio/tests/test_api.py | import os
from typing import Dict
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS, get_pipeline
# Must contain at least one example of each implemented pipeline
# Tests do not check the actual values of the model output, so small dummy
# models are recommended for faster tests.
TESTABLE_MODE... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/allennlp/Dockerfile | FROM tiangolo/uvicorn-gunicorn:python3.8
LABEL maintainer="me <me@example.com>"
# Add any system dependency here
# RUN apt-get update -y && apt-get install libXXX -y
COPY ./requirements.txt /app
RUN pip install --no-cache-dir -r requirements.txt
RUN pip install spacy && python -m spacy download en_core_web_sm
COPY .... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/allennlp/requirements.txt | starlette==0.27.0
numpy==1.22.0
allennlp>=2.5.0,<3.0.0
# Even though it is not imported, it is actually required.
allennlp_models>=2.5.0,<3.0.0
api-inference-community==0.0.23
huggingface_hub==0.5.1
|
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/allennlp/prestart.sh | python app/main.py
|
0 | hf_public_repos/api-inference-community/docker_images/allennlp | hf_public_repos/api-inference-community/docker_images/allennlp/app/main.py | import functools
import logging
import os
from typing import Dict, Type
from api_inference_community.routes import pipeline_route, status_ok
from app.pipelines import Pipeline, QuestionAnsweringPipeline
from starlette.applications import Starlette
from starlette.middleware import Middleware
from starlette.middleware.g... |
0 | hf_public_repos/api-inference-community/docker_images/allennlp/app | hf_public_repos/api-inference-community/docker_images/allennlp/app/pipelines/base.py | from abc import ABC, abstractmethod
from typing import Any, Optional
class Pipeline(ABC):
task: Optional[str] = None
model_id: Optional[str] = None
@abstractmethod
def __init__(self, model_id: str):
raise NotImplementedError("Pipelines should implement an __init__ method")
@abstractmetho... |
0 | hf_public_repos/api-inference-community/docker_images/allennlp/app | hf_public_repos/api-inference-community/docker_images/allennlp/app/pipelines/question_answering.py | import os
import shutil
from typing import Any, Dict
# Even though it is not imported, it is actually required, it downloads some stuff.
import allennlp_models # noqa: F401
from allennlp.predictors.predictor import Predictor
from app.pipelines import Pipeline
class QuestionAnsweringPipeline(Pipeline):
def __ini... |
0 | hf_public_repos/api-inference-community/docker_images/allennlp/app | hf_public_repos/api-inference-community/docker_images/allennlp/app/pipelines/__init__.py | from app.pipelines.base import Pipeline, PipelineException # isort:skip
from app.pipelines.question_answering import QuestionAnsweringPipeline
|
0 | hf_public_repos/api-inference-community/docker_images/allennlp | hf_public_repos/api-inference-community/docker_images/allennlp/tests/test_docker_build.py | import os
import subprocess
from unittest import TestCase
class cd:
"""Context manager for changing the current working directory"""
def __init__(self, newPath):
self.newPath = os.path.expanduser(newPath)
def __enter__(self):
self.savedPath = os.getcwd()
os.chdir(self.newPath)
... |
0 | hf_public_repos/api-inference-community/docker_images/allennlp | hf_public_repos/api-inference-community/docker_images/allennlp/tests/test_api.py | import os
from typing import Dict
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS, get_pipeline
# Must contain at least one example of each implemented pipeline
# Tests do not check the actual values of the model output, so small dummy
# models are recommended for faster tests.
TESTABLE_MODE... |
0 | hf_public_repos/api-inference-community/docker_images/allennlp | hf_public_repos/api-inference-community/docker_images/allennlp/tests/test_api_question_answering.py | import json
import os
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS
from starlette.testclient import TestClient
from tests.test_api import TESTABLE_MODELS
@skipIf(
"question-answering" not in ALLOWED_TASKS,
"question-answering not implemented",
)
class QuestionAnsweringTestCase(Tes... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/fairseq/Dockerfile | FROM tiangolo/uvicorn-gunicorn:python3.8
LABEL maintainer="me <me@example.com>"
# Add any system dependency here
# RUN apt-get update -y && apt-get install libXXX -y
RUN apt-get update -y && apt-get install ffmpeg espeak-ng -y
RUN pip install --no-cache-dir numpy==1.22 torch==1.11
COPY ./requirements.txt /app
RUN pip... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/fairseq/requirements.txt | api-inference-community==0.0.23
g2p_en==2.1.0
g2pc==0.9.9.3
phonemizer==2.2.1
librosa==0.8.1
hanziconv==0.3.2
sentencepiece==0.1.96
# Dummy comment to trigger automatic deploy.
git+https://github.com/facebookresearch/fairseq.git@d47119871c2ac9a0a0aa2904dd8cfc1929b113d9#egg=fairseq
huggingface_hub==0.5.1
|
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/fairseq/prestart.sh | python app/main.py
|
0 | hf_public_repos/api-inference-community/docker_images/fairseq | hf_public_repos/api-inference-community/docker_images/fairseq/app/main.py | import functools
import logging
import os
from typing import Dict, Type
from api_inference_community.routes import pipeline_route, status_ok
from app.pipelines import Pipeline, SpeechToSpeechPipeline, TextToSpeechPipeline
from starlette.applications import Starlette
from starlette.middleware import Middleware
from sta... |
0 | hf_public_repos/api-inference-community/docker_images/fairseq/app | hf_public_repos/api-inference-community/docker_images/fairseq/app/pipelines/audio_to_audio.py | import json
import os
from pathlib import Path
from typing import List, Tuple
import numpy as np
import torch
from app.pipelines import Pipeline
from app.pipelines.utils import ARG_OVERRIDES_MAP
from fairseq import hub_utils
from fairseq.checkpoint_utils import load_model_ensemble_and_task_from_hf_hub
from fairseq.mod... |
0 | hf_public_repos/api-inference-community/docker_images/fairseq/app | hf_public_repos/api-inference-community/docker_images/fairseq/app/pipelines/text_to_speech.py | import os
from typing import Tuple
import numpy as np
from app.pipelines import Pipeline
from fairseq.checkpoint_utils import load_model_ensemble_and_task_from_hf_hub
from fairseq.models.text_to_speech.hub_interface import TTSHubInterface
class TextToSpeechPipeline(Pipeline):
def __init__(self, model_id: str):
... |
0 | hf_public_repos/api-inference-community/docker_images/fairseq/app | hf_public_repos/api-inference-community/docker_images/fairseq/app/pipelines/base.py | from abc import ABC, abstractmethod
from typing import Any
class Pipeline(ABC):
@abstractmethod
def __init__(self, model_id: str):
raise NotImplementedError("Pipelines should implement an __init__ method")
@abstractmethod
def __call__(self, inputs: Any) -> Any:
raise NotImplementedErr... |
0 | hf_public_repos/api-inference-community/docker_images/fairseq/app | hf_public_repos/api-inference-community/docker_images/fairseq/app/pipelines/utils.py | ARG_OVERRIDES_MAP = {
"facebook/xm_transformer_s2ut_800m-es-en-st-asr-bt_h1_2022": {
"config_yaml": "config.yaml",
"task": "speech_to_text",
}
}
|
0 | hf_public_repos/api-inference-community/docker_images/fairseq/app | hf_public_repos/api-inference-community/docker_images/fairseq/app/pipelines/__init__.py | from app.pipelines.base import Pipeline, PipelineException # isort:skip
from app.pipelines.audio_to_audio import SpeechToSpeechPipeline
from app.pipelines.text_to_speech import TextToSpeechPipeline
|
0 | hf_public_repos/api-inference-community/docker_images/fairseq | hf_public_repos/api-inference-community/docker_images/fairseq/tests/test_api_text_to_speech.py | import os
from unittest import TestCase, skipIf
from api_inference_community.validation import ffmpeg_read
from app.main import ALLOWED_TASKS
from starlette.testclient import TestClient
from tests.test_api import TESTABLE_MODELS
@skipIf(
"text-to-speech" not in ALLOWED_TASKS,
"text-to-speech not implemented"... |
0 | hf_public_repos/api-inference-community/docker_images/fairseq | hf_public_repos/api-inference-community/docker_images/fairseq/tests/test_docker_build.py | import os
import subprocess
from unittest import TestCase
class cd:
"""Context manager for changing the current working directory"""
def __init__(self, newPath):
self.newPath = os.path.expanduser(newPath)
def __enter__(self):
self.savedPath = os.getcwd()
os.chdir(self.newPath)
... |
0 | hf_public_repos/api-inference-community/docker_images/fairseq | hf_public_repos/api-inference-community/docker_images/fairseq/tests/test_api.py | import os
from typing import Dict
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS, get_pipeline
# Must contain at least one example of each implemented pipeline
# Tests do not check the actual values of the model output, so small dummy
# models are recommended for faster tests.
TESTABLE_MODE... |
0 | hf_public_repos/api-inference-community/docker_images/fairseq | hf_public_repos/api-inference-community/docker_images/fairseq/tests/test_api_audio_to_audio.py | import base64
import json
import os
from unittest import TestCase, skipIf
from api_inference_community.validation import ffmpeg_read
from app.main import ALLOWED_TASKS
from starlette.testclient import TestClient
from tests.test_api import TESTABLE_MODELS
@skipIf(
"audio-to-audio" not in ALLOWED_TASKS,
"audio... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/open_clip/Dockerfile | FROM tiangolo/uvicorn-gunicorn:python3.8
LABEL maintainer="me <me@example.com>"
# Add any system dependency here
# RUN apt-get update -y && apt-get install libXXX -y
COPY ./requirements.txt /app
RUN pip install --no-cache-dir -r requirements.txt
COPY ./prestart.sh /app/
# Most DL models are quite large in terms of ... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/open_clip/requirements.txt | starlette==0.27.0
api-inference-community==0.0.32
huggingface_hub>=0.12.1
timm>=0.9.10
transformers>=4.34.0
open_clip_torch>=2.23.0
#dummy.
|
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/open_clip/prestart.sh | python app/main.py
|
0 | hf_public_repos/api-inference-community/docker_images/open_clip | hf_public_repos/api-inference-community/docker_images/open_clip/app/main.py | import functools
import logging
import os
from typing import Dict, Type
from api_inference_community.routes import pipeline_route, status_ok
from app.pipelines import Pipeline, ZeroShotImageClassificationPipeline
from starlette.applications import Starlette
from starlette.middleware import Middleware
from starlette.mi... |
0 | hf_public_repos/api-inference-community/docker_images/open_clip/app | hf_public_repos/api-inference-community/docker_images/open_clip/app/pipelines/zero_shot_image_classification.py | import json
from typing import Any, Dict, List, Optional
import open_clip
import torch
import torch.nn.functional as F
from app.pipelines import Pipeline
from open_clip.pretrained import download_pretrained_from_hf
from PIL import Image
class ZeroShotImageClassificationPipeline(Pipeline):
def __init__(self, mode... |
0 | hf_public_repos/api-inference-community/docker_images/open_clip/app | hf_public_repos/api-inference-community/docker_images/open_clip/app/pipelines/base.py | from abc import ABC, abstractmethod
from typing import Any, Optional
class Pipeline(ABC):
task: Optional[str] = None
model_id: Optional[str] = None
@abstractmethod
def __init__(self, model_id: str):
raise NotImplementedError("Pipelines should implement an __init__ method")
@abstractmetho... |
0 | hf_public_repos/api-inference-community/docker_images/open_clip/app | hf_public_repos/api-inference-community/docker_images/open_clip/app/pipelines/__init__.py | from app.pipelines.base import Pipeline, PipelineException # isort:skip
from app.pipelines.zero_shot_image_classification import (
ZeroShotImageClassificationPipeline,
)
|
0 | hf_public_repos/api-inference-community/docker_images/open_clip | hf_public_repos/api-inference-community/docker_images/open_clip/tests/test_docker_build.py | import os
import subprocess
from unittest import TestCase
class cd:
"""Context manager for changing the current working directory"""
def __init__(self, newPath):
self.newPath = os.path.expanduser(newPath)
def __enter__(self):
self.savedPath = os.getcwd()
os.chdir(self.newPath)
... |
0 | hf_public_repos/api-inference-community/docker_images/open_clip | hf_public_repos/api-inference-community/docker_images/open_clip/tests/test_api.py | import os
from typing import Dict
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS, get_pipeline
# Must contain at least one example of each implemented pipeline
# Tests do not check the actual values of the model output, so small dummy
# models are recommended for faster tests.
TESTABLE_MODE... |
0 | hf_public_repos/api-inference-community/docker_images/open_clip | hf_public_repos/api-inference-community/docker_images/open_clip/tests/test_api_zero_shot_image_classification.py | import json
import os
from base64 import b64encode
from unittest import TestCase, skipIf
from app.main import ALLOWED_TASKS
from parameterized import parameterized_class
from starlette.testclient import TestClient
from tests.test_api import TESTABLE_MODELS
@skipIf(
"zero-shot-image-classification" not in ALLOWED... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/doctr/Dockerfile | FROM tiangolo/uvicorn-gunicorn:python3.8
LABEL maintainer="me <me@example.com>"
# Add any system dependency here
RUN apt-get update -y && apt-get install libgl1-mesa-glx -y
RUN pip install --no-cache-dir -U pip
RUN pip install --no-cache-dir torch==1.11 torchvision==0.12
COPY ./requirements.txt /app
RUN pip install -... |
0 | hf_public_repos/api-inference-community/docker_images | hf_public_repos/api-inference-community/docker_images/doctr/requirements.txt | starlette==0.27.0
api-inference-community==0.0.23
python-doctr[torch]==0.5.1
huggingface_hub==0.5.1
|
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