From a071ac5c70a8208b009b86ec54b57ecf1dd7e409 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Tue, 5 Apr 2022 15:06:45 -0400 Subject: [PATCH 01/36] add megasparse dir --- examples/megasparse/README.md | 66 ++++++++++++++ examples/megasparse/client/app.py | 46 ++++++++++ examples/megasparse/client/pipelineclient.py | 50 +++++++++++ examples/megasparse/client/settings.py | 88 +++++++++++++++++++ examples/megasparse/img/demo_screenshot.png | Bin 0 -> 523495 bytes examples/megasparse/requirements.txt | 2 + examples/megasparse/server/config.yaml | 87 ++++++++++++++++++ 7 files changed, 339 insertions(+) create mode 100644 examples/megasparse/README.md create mode 100644 examples/megasparse/client/app.py create mode 100644 examples/megasparse/client/pipelineclient.py create mode 100644 examples/megasparse/client/settings.py create mode 100644 examples/megasparse/img/demo_screenshot.png create mode 100644 examples/megasparse/requirements.txt create mode 100644 examples/megasparse/server/config.yaml diff --git a/examples/megasparse/README.md b/examples/megasparse/README.md new file mode 100644 index 0000000000..acd4a1bfde --- /dev/null +++ b/examples/megasparse/README.md @@ -0,0 +1,66 @@ +![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) [**NEURAL MAGIC**](https://neuralmagic.com) ![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) + + ███╗ ███╗ ███████╗ ██████╗ █████╗ ███████╗ ██████╗ █████╗ ██████╗ ███████╗ ███████╗ + ████╗ ████║ ██╔════╝ ██╔════╝ ██╔══██╗ ██╔════╝ ██╔══██╗ ██╔══██╗ ██╔══██╗ ██╔════╝ ██╔════╝ + ██╔████╔██║ █████╗ ██║ ███╗ ███████║ ███████╗ ██████╔╝ ███████║ ██████╔╝ ███████╗ █████╗ + ██║╚██╔╝██║ ██╔══╝ ██║ ██║ ██╔══██║ ╚════██║ ██╔═══╝ ██╔══██║ ██╔══██╗ ╚════██║ ██╔══╝ + ██║ ╚═╝ ██║ ███████╗ ╚██████╔╝ ██║ ██║ ███████║ ██║ ██║ ██║ ██║ ██║ ███████║ ███████╗ + ╚═╝ ╚═╝ ╚══════╝ ╚═════╝ ╚═╝ ╚═╝ ╚══════╝ ╚═╝ ╚═╝ ╚═╝ ╚═╝ ╚═╝ ╚══════╝ ╚══════╝ + + *** A Streamlit app for deploying the DeepSparse Server *** +![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) + + +##
`INTRO`
+ + + +
+MegaSparse allows you to quickly serve a streamlit app running with the DeepSparse Server as a backend to run inference on multiple transformer models. The present demo loads 18 Sparse BERT ONNX models fine-tuned for the question answering task. The purpose of this app is for you to familiarize yourself with the high performance inference speeds of sparse models. +
+
+ +[Getting Started with the DeepSparse Server](https://github.com/neuralmagic/deepsparse/tree/main/src/deepsparse/server)🔌 + +
+ + + +
+ +##
`INSTALL`
+ +```bash +git clone https://github.com//megasparse.git +cd megasparse +pip install -r requirements.txt +``` +##
`START SERVER`
+ +Run the DeepSparse Server: +```bash +deepsparse.server --config_file server/config.yaml +``` + +This will download models from the `config.yaml` file and then start the DeepSparse Server on localhost `0.0.0.0` and port `5543`. + +##
`START CLIENT`
+ +Open a new terminal and run Streamlit: + +```bash +streamlit run client/app.py \ + --theme.backgroundColor blue \ + --theme.secondaryBackgroundColor black \ + --theme.textColor white \ + --browser.serverAddress="0.0.0.0" +``` +This will start the Streamlit app in localhost `0.0.0.0` and port `8501`. +Visit `http://0.0.0.0:8501` in your browser to view demo. + +### Support + +- All models able fit on 16GB RAM of a c2-standard-4 VM instance on GCP +- Tested on Ubuntu 20.04.4 LTS +- Python 3.8.10 + diff --git a/examples/megasparse/client/app.py b/examples/megasparse/client/app.py new file mode 100644 index 0000000000..cca06bcf35 --- /dev/null +++ b/examples/megasparse/client/app.py @@ -0,0 +1,46 @@ +# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import streamlit as st +from settings import FeatureHandler as feat +from time import perf_counter + +#Titles +st.markdown(feat.title, unsafe_allow_html=True) +st.markdown(feat.subtitle, unsafe_allow_html=True) + +#Sidebar +st.sidebar.selectbox(feat.tasks_desc, feat.tasks) +model_choice = st.sidebar.radio(feat.variants_desc, feat.variants.keys()) +st.sidebar.markdown(feat.code_banner) +st.sidebar.code(body=feat.code_text, language=feat.language) +st.sidebar.markdown(feat.repo_test) + +#Footer +st.markdown(feat.footer, unsafe_allow_html=True) + +#Inference +for model_name, model in feat.variants.items(): + + if model_choice == model_name: + + context = st.text_area(label=feat.example_context_label, height=150, value=feat.example_context) + question = st.text_area(label=feat.example_question_label, value=feat.example_question) + start = perf_counter() + answer = model(question=question, context=context) + end = perf_counter() + infer_time = end - start + infer_time = round(infer_time, 4) + st.write(feat.answer_label, answer['answer']) + st.write(infer_time, feat.time_label) \ No newline at end of file diff --git a/examples/megasparse/client/pipelineclient.py b/examples/megasparse/client/pipelineclient.py new file mode 100644 index 0000000000..3210c78224 --- /dev/null +++ b/examples/megasparse/client/pipelineclient.py @@ -0,0 +1,50 @@ +# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +""" +Client object for making requests to the example DeepSparse BERT inference server +""" + +import json +from typing import List + +import numpy +import requests + +class MultiPipelineClient: + """ + Client object for making requests to the example DeepSparse BERT inference server + + :param model: model alias of FastAPI route + :param address: IP address of the server, default is 0.0.0.0 + :param port: Port the server is hosted on, default is 5543 + """ + + def __init__(self, model: str, address: str ='0.0.0.0', port: str ='5543'): + + self.model = model + self._url = f'http://{address}:{port}/predict/{self.model}' + + def __call__(self, **kwargs) -> List[numpy.ndarray]: + + """ + :param kwargs: named inputs to the model server pipeline. e.g. for + question-answering - `question="...", context="..." + + :return: json outputs from running the model server pipeline with the given + input(s) + """ + + response = requests.post(self._url, json=kwargs) + return json.loads(response.content) \ No newline at end of file diff --git a/examples/megasparse/client/settings.py b/examples/megasparse/client/settings.py new file mode 100644 index 0000000000..7294040027 --- /dev/null +++ b/examples/megasparse/client/settings.py @@ -0,0 +1,88 @@ +# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +from pipelineclient import MultiPipelineClient + +class FeatureHandler: + + """ + Client object with front-end streamlit content features + + """ + + tasks_desc = "Select task:" + tasks = [ + "Question Answering", + "Name Entity Recognition", + "Text Generation", + "Sentiment Analysis", + "Summarization", + "Translation" + ] + + variants_desc = "Select model:" + variants = { + "Pruned, Quant, Aggressive 95": MultiPipelineClient(model="question_answering/pruned_quant"), + "Pruned, Quant, Moderate": MultiPipelineClient(model="question_answering/quantmod"), + "Pruned, Agressive 98": MultiPipelineClient(model="question_answering/agg98"), + "Pruned, Agressive 94": MultiPipelineClient(model="question_answering/agg94"), + "Pruned, Conservative": MultiPipelineClient(model="question_answering/conserv"), + "Pruned, Quant 6layers, Aggressive 96": MultiPipelineClient(model="question_answering/quant6lagg96"), + "Pruned, Quant 6layers, Aggressive 91": MultiPipelineClient(model="question_answering/quant6lagg91"), + "Pruned, 6layers, Aggressive 98": MultiPipelineClient(model="question_answering/6lagg98"), + "Pruned, 6layers, Aggressive 97": MultiPipelineClient(model="question_answering/6lagg97"), + "Pruned, 6layers, Aggressive 96": MultiPipelineClient(model="question_answering/6lagg96"), + "Pruned, 6layers, Aggressive 94": MultiPipelineClient(model="question_answering/6lagg94"), + "Pruned, Quant 3layers, Aggressive 89": MultiPipelineClient(model="question_answering/quant3lagg89"), + "Pruned, Quant 3layers, Aggressive 84": MultiPipelineClient(model="question_answering/quant3lagg84"), + "Pruned, 3layers, Aggressive 90": MultiPipelineClient(model="question_answering/3lagg90"), + "Pruned, 3layers, Aggressive 89": MultiPipelineClient(model="question_answering/3lagg89"), + "Pruned, 3layers, Aggressive 86": MultiPipelineClient(model="question_answering/3lagg86"), + "Pruned, 3layers, Aggressive 83": MultiPipelineClient(model="question_answering/3lagg83"), + "Base Model, Not Sparsified 😥": MultiPipelineClient(model="question_answering/base") + } + + title = "

✨ Neural Magic ✨

" + subtitle = "

Inference with the DeepSparse Server

" + + code_banner = "Get started with faster inference 👇" + code_text = "pip install deepsparse[server]" + language = "python" + repo_test = "Give the [DeepSparse](https://github.com/neuralmagic/deepsparse) repo a ⭐!" + + example_context_label = "Enter Context" + example_question_label = "Enter Question" + example_context = r"""The DeepSparse Engine is a CPU runtime that delivers GPU-class performance by taking advantage of sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. It is focused on model deployment and scaling machine learning pipelines, fitting seamlessly into your existing deployments as an inference backend.""" + example_question = "What does the DeepSparse Engine take advantage of within neural networks?" + answer_label = "ANSWER: " + time_label = "seconds" + + footer = """ + +
+

Made with ☠️ and Streamlit . +

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file mode 100644 index 0000000000..3a348208ea --- /dev/null +++ b/examples/megasparse/requirements.txt @@ -0,0 +1,2 @@ +deepsparse[server] +streamlit \ No newline at end of file diff --git a/examples/megasparse/server/config.yaml b/examples/megasparse/server/config.yaml new file mode 100644 index 0000000000..c730b9e9a3 --- /dev/null +++ b/examples/megasparse/server/config.yaml @@ -0,0 +1,87 @@ +# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +models: + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant-aggressive_95 + batch_size: 1 + alias: question_answering/pruned_quant + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant-moderate + batch_size: 1 + alias: question_answering/quantmod + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_98 + batch_size: 1 + alias: question_answering/agg98 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_94 + batch_size: 1 + alias: question_answering/agg94 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-conservative + batch_size: 1 + alias: question_answering/conserv + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_96 + batch_size: 1 + alias: question_answering/quant6lagg96 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_91 + batch_size: 1 + alias: question_answering/quant6lagg91 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_98 + batch_size: 1 + alias: question_answering/6lagg98 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_97 + batch_size: 1 + alias: question_answering/6lagg97 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_96 + batch_size: 1 + alias: question_answering/6lagg96 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_94 + batch_size: 1 + alias: question_answering/6lagg94 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_89 + batch_size: 1 + alias: question_answering/quant3lagg89 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_84 + batch_size: 1 + alias: question_answering/quant3lagg84 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_90 + batch_size: 1 + alias: question_answering/3lagg90 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_89 + batch_size: 1 + alias: question_answering/3lagg89 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_86 + batch_size: 1 + alias: question_answering/3lagg86 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_83 + batch_size: 1 + alias: question_answering/3lagg83 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/base-none + batch_size: 1 + alias: question_answering/base \ No newline at end of file From 1d7712aa342b5d0bc01ed9b20e8fc4dd3bb691e2 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Tue, 5 Apr 2022 15:41:11 -0400 Subject: [PATCH 02/36] edited readme to support DS integration --- examples/megasparse/README.md | 29 ++++-- examples/megasparse/client/settings.py | 3 +- examples/megasparse/server/config.yaml | 128 ++++++++++++------------- 3 files changed, 84 insertions(+), 76 deletions(-) diff --git a/examples/megasparse/README.md b/examples/megasparse/README.md index acd4a1bfde..6470797fb1 100644 --- a/examples/megasparse/README.md +++ b/examples/megasparse/README.md @@ -16,37 +16,46 @@

-MegaSparse allows you to quickly serve a streamlit app running with the DeepSparse Server as a backend to run inference on multiple transformer models. The present demo loads 18 Sparse BERT ONNX models fine-tuned for the question answering task. The purpose of this app is for you to familiarize yourself with the high performance inference speeds of sparse models. +MegaSparse allows you to quickly serve a streamlit app running on top of the DeepSparse Server for comparing latency speeds of various transformer models. Currently, the demo can safely load up to 18 Sparse BERT models fine-tuned on the question answering task on only 16GB of RAM. The purpose of this app is for you to familiarize and compare the inference performance of various models trained on different sparse profiles.
+
[Getting Started with the DeepSparse Server](https://github.com/neuralmagic/deepsparse/tree/main/src/deepsparse/server)🔌
- +
##
`INSTALL`
```bash -git clone https://github.com//megasparse.git -cd megasparse +git clone https://github.com/neuralmagic/deepsparse.git +``` + +```bash +cd examples/megasparse +``` + +```bash pip install -r requirements.txt ``` ##
`START SERVER`
-Run the DeepSparse Server: +The `config.yaml` file contains 18 BERT models, although 16 models are commented out so you can safely get started and add more models at your own pace. If you wish to load all 18 models into memory make sure you have 16GB of RAM available, otherwise you will get out of memory errors. + +To download and initialize the models in the `config.yaml` file, run: ```bash deepsparse.server --config_file server/config.yaml ``` -This will download models from the `config.yaml` file and then start the DeepSparse Server on localhost `0.0.0.0` and port `5543`. +The DeepSparse Server should now be running on localhost `0.0.0.0` and port `5543`. ##
`START CLIENT`
-Open a new terminal and run Streamlit: +Open a new terminal and run the following command to start a Streamlit app: ```bash streamlit run client/app.py \ @@ -58,9 +67,9 @@ streamlit run client/app.py \ This will start the Streamlit app in localhost `0.0.0.0` and port `8501`. Visit `http://0.0.0.0:8501` in your browser to view demo. -### Support +### Testing -- All models able fit on 16GB RAM of a c2-standard-4 VM instance on GCP -- Tested on Ubuntu 20.04.4 LTS +- 18 models were able to fit on 16GB RAM of a c2-standard-4 VM instance on GCP +- Ubuntu 20.04.4 LTS - Python 3.8.10 diff --git a/examples/megasparse/client/settings.py b/examples/megasparse/client/settings.py index 7294040027..9936416d23 100644 --- a/examples/megasparse/client/settings.py +++ b/examples/megasparse/client/settings.py @@ -17,8 +17,7 @@ class FeatureHandler: """ - Client object with front-end streamlit content features - + Class with front-end streamlit content features. """ tasks_desc = "Select task:" diff --git a/examples/megasparse/server/config.yaml b/examples/megasparse/server/config.yaml index c730b9e9a3..fe8a31f9dd 100644 --- a/examples/megasparse/server/config.yaml +++ b/examples/megasparse/server/config.yaml @@ -21,67 +21,67 @@ models: model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant-moderate batch_size: 1 alias: question_answering/quantmod - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_98 - batch_size: 1 - alias: question_answering/agg98 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_94 - batch_size: 1 - alias: question_answering/agg94 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-conservative - batch_size: 1 - alias: question_answering/conserv - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_96 - batch_size: 1 - alias: question_answering/quant6lagg96 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_91 - batch_size: 1 - alias: question_answering/quant6lagg91 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_98 - batch_size: 1 - alias: question_answering/6lagg98 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_97 - batch_size: 1 - alias: question_answering/6lagg97 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_96 - batch_size: 1 - alias: question_answering/6lagg96 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_94 - batch_size: 1 - alias: question_answering/6lagg94 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_89 - batch_size: 1 - alias: question_answering/quant3lagg89 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_84 - batch_size: 1 - alias: question_answering/quant3lagg84 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_90 - batch_size: 1 - alias: question_answering/3lagg90 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_89 - batch_size: 1 - alias: question_answering/3lagg89 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_86 - batch_size: 1 - alias: question_answering/3lagg86 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_83 - batch_size: 1 - alias: question_answering/3lagg83 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/base-none - batch_size: 1 - alias: question_answering/base \ No newline at end of file + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_98 + # batch_size: 1 + # alias: question_answering/agg98 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_94 + # batch_size: 1 + # alias: question_answering/agg94 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-conservative + # batch_size: 1 + # alias: question_answering/conserv + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_96 + # batch_size: 1 + # alias: question_answering/quant6lagg96 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_91 + # batch_size: 1 + # alias: question_answering/quant6lagg91 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_98 + # batch_size: 1 + # alias: question_answering/6lagg98 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_97 + # batch_size: 1 + # alias: question_answering/6lagg97 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_96 + # batch_size: 1 + # alias: question_answering/6lagg96 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_94 + # batch_size: 1 + # alias: question_answering/6lagg94 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_89 + # batch_size: 1 + # alias: question_answering/quant3lagg89 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_84 + # batch_size: 1 + # alias: question_answering/quant3lagg84 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_90 + # batch_size: 1 + # alias: question_answering/3lagg90 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_89 + # batch_size: 1 + # alias: question_answering/3lagg89 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_86 + # batch_size: 1 + # alias: question_answering/3lagg86 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_83 + # batch_size: 1 + # alias: question_answering/3lagg83 + # - task: question_answering + # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/base-none + # batch_size: 1 + # alias: question_answering/base \ No newline at end of file From 9db5ca8440680385ad8ea13b13e3088c910443b2 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Tue, 5 Apr 2022 15:43:49 -0400 Subject: [PATCH 03/36] small edit to docstring --- examples/megasparse/client/pipelineclient.py | 4 ---- 1 file changed, 4 deletions(-) diff --git a/examples/megasparse/client/pipelineclient.py b/examples/megasparse/client/pipelineclient.py index 3210c78224..9064e103b7 100644 --- a/examples/megasparse/client/pipelineclient.py +++ b/examples/megasparse/client/pipelineclient.py @@ -12,10 +12,6 @@ # See the License for the specific language governing permissions and # limitations under the License. -""" -Client object for making requests to the example DeepSparse BERT inference server -""" - import json from typing import List From 47bfdbb22f3dac2a41e5f293686a4fe21f4f1152 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Tue, 5 Apr 2022 15:47:47 -0400 Subject: [PATCH 04/36] edited settings.py module so only 2 models are loaded. --- examples/megasparse/client/settings.py | 16 ---------------- 1 file changed, 16 deletions(-) diff --git a/examples/megasparse/client/settings.py b/examples/megasparse/client/settings.py index 9936416d23..2c33b562df 100644 --- a/examples/megasparse/client/settings.py +++ b/examples/megasparse/client/settings.py @@ -34,22 +34,6 @@ class FeatureHandler: variants = { "Pruned, Quant, Aggressive 95": MultiPipelineClient(model="question_answering/pruned_quant"), "Pruned, Quant, Moderate": MultiPipelineClient(model="question_answering/quantmod"), - "Pruned, Agressive 98": MultiPipelineClient(model="question_answering/agg98"), - "Pruned, Agressive 94": MultiPipelineClient(model="question_answering/agg94"), - "Pruned, Conservative": MultiPipelineClient(model="question_answering/conserv"), - "Pruned, Quant 6layers, Aggressive 96": MultiPipelineClient(model="question_answering/quant6lagg96"), - "Pruned, Quant 6layers, Aggressive 91": MultiPipelineClient(model="question_answering/quant6lagg91"), - "Pruned, 6layers, Aggressive 98": MultiPipelineClient(model="question_answering/6lagg98"), - "Pruned, 6layers, Aggressive 97": MultiPipelineClient(model="question_answering/6lagg97"), - "Pruned, 6layers, Aggressive 96": MultiPipelineClient(model="question_answering/6lagg96"), - "Pruned, 6layers, Aggressive 94": MultiPipelineClient(model="question_answering/6lagg94"), - "Pruned, Quant 3layers, Aggressive 89": MultiPipelineClient(model="question_answering/quant3lagg89"), - "Pruned, Quant 3layers, Aggressive 84": MultiPipelineClient(model="question_answering/quant3lagg84"), - "Pruned, 3layers, Aggressive 90": MultiPipelineClient(model="question_answering/3lagg90"), - "Pruned, 3layers, Aggressive 89": MultiPipelineClient(model="question_answering/3lagg89"), - "Pruned, 3layers, Aggressive 86": MultiPipelineClient(model="question_answering/3lagg86"), - "Pruned, 3layers, Aggressive 83": MultiPipelineClient(model="question_answering/3lagg83"), - "Base Model, Not Sparsified 😥": MultiPipelineClient(model="question_answering/base") } title = "

✨ Neural Magic ✨

" From 9eea30357e555014ac73793a9f9fcf8d1d83487e Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Tue, 5 Apr 2022 16:00:33 -0400 Subject: [PATCH 05/36] added more context to the readme about adding more models. --- examples/megasparse/README.md | 11 ++++++----- examples/megasparse/client/settings.py | 7 +------ 2 files changed, 7 insertions(+), 11 deletions(-) diff --git a/examples/megasparse/README.md b/examples/megasparse/README.md index 6470797fb1..d1ba8a5dcf 100644 --- a/examples/megasparse/README.md +++ b/examples/megasparse/README.md @@ -42,11 +42,12 @@ cd examples/megasparse ```bash pip install -r requirements.txt ``` -##
`START SERVER`
+
+The `config.yaml` file lists the models you want the DeepSparse Server to serve. Currently, it contains up to 18 BERT models, although 16 of these models are commented out so you can safely get started on two models, and later on, add more models at your own pace. If you wish to load all 18 models into memory make sure you have 16GB of RAM available, otherwise you will get out of memory errors. Also, as you add additional models to the `config.yaml` file, make sure to all also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. -The `config.yaml` file contains 18 BERT models, although 16 models are commented out so you can safely get started and add more models at your own pace. If you wish to load all 18 models into memory make sure you have 16GB of RAM available, otherwise you will get out of memory errors. +##
`START SERVER`
-To download and initialize the models in the `config.yaml` file, run: +To download and initialize the two sample models in the `config.yaml` file, run: ```bash deepsparse.server --config_file server/config.yaml ``` @@ -55,7 +56,7 @@ The DeepSparse Server should now be running on localhost `0.0.0.0` and port `554 ##
`START CLIENT`
-Open a new terminal and run the following command to start a Streamlit app: +Open a new terminal and run the following command to start the Streamlit app: ```bash streamlit run client/app.py \ @@ -65,7 +66,7 @@ streamlit run client/app.py \ --browser.serverAddress="0.0.0.0" ``` This will start the Streamlit app in localhost `0.0.0.0` and port `8501`. -Visit `http://0.0.0.0:8501` in your browser to view demo. +Visit `http://0.0.0.0:8501` in your browser to view the demo. ### Testing diff --git a/examples/megasparse/client/settings.py b/examples/megasparse/client/settings.py index 2c33b562df..bf9e13d074 100644 --- a/examples/megasparse/client/settings.py +++ b/examples/megasparse/client/settings.py @@ -22,12 +22,7 @@ class FeatureHandler: tasks_desc = "Select task:" tasks = [ - "Question Answering", - "Name Entity Recognition", - "Text Generation", - "Sentiment Analysis", - "Summarization", - "Translation" + "Question Answering", ] variants_desc = "Select model:" From 03bc62e83e5e909ae9d8fc5dafd70738637990ab Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Tue, 5 Apr 2022 16:08:47 -0400 Subject: [PATCH 06/36] fixed image --- examples/megasparse/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/megasparse/README.md b/examples/megasparse/README.md index d1ba8a5dcf..d29c7cf2c5 100644 --- a/examples/megasparse/README.md +++ b/examples/megasparse/README.md @@ -25,7 +25,7 @@ MegaSparse allows you to quickly serve a streamlit app running on top of the Dee
- +![alt text](./img/demo_screenshot.png)
From dc099796c7f61618410a6495823a122b5e1558f5 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Tue, 5 Apr 2022 16:18:27 -0400 Subject: [PATCH 07/36] added different host to streamlit client as default --- examples/megasparse/README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/examples/megasparse/README.md b/examples/megasparse/README.md index d29c7cf2c5..be60c1c78f 100644 --- a/examples/megasparse/README.md +++ b/examples/megasparse/README.md @@ -52,21 +52,21 @@ To download and initialize the two sample models in the `config.yaml` file, run: deepsparse.server --config_file server/config.yaml ``` -The DeepSparse Server should now be running on localhost `0.0.0.0` and port `5543`. +The DeepSparse Server should now be running on host `0.0.0.0` and port `5543`. ##
`START CLIENT`
-Open a new terminal and run the following command to start the Streamlit app: +Open a new terminal (make sure you are in your environment) and run the following command to start the Streamlit app: ```bash streamlit run client/app.py \ --theme.backgroundColor blue \ --theme.secondaryBackgroundColor black \ --theme.textColor white \ - --browser.serverAddress="0.0.0.0" + --browser.serverAddress="localhost" ``` -This will start the Streamlit app in localhost `0.0.0.0` and port `8501`. -Visit `http://0.0.0.0:8501` in your browser to view the demo. +This will start the Streamlit app on host `localhost` and port `8501`. +Visit `http://localhost:8501` in your browser to view the demo. ### Testing From d1ec8566f0304d7198fbe78eb2930ec04e79a9ac Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Tue, 5 Apr 2022 16:27:25 -0400 Subject: [PATCH 08/36] quality check edits --- examples/megasparse/README.md | 18 +++++++++++++- examples/megasparse/client/app.py | 26 ++++++++++++-------- examples/megasparse/client/pipelineclient.py | 9 ++++--- examples/megasparse/client/settings.py | 19 ++++++++++---- 4 files changed, 52 insertions(+), 20 deletions(-) diff --git a/examples/megasparse/README.md b/examples/megasparse/README.md index be60c1c78f..b8eb85c6ae 100644 --- a/examples/megasparse/README.md +++ b/examples/megasparse/README.md @@ -1,3 +1,19 @@ + + ![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) [**NEURAL MAGIC**](https://neuralmagic.com) ![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) ███╗ ███╗ ███████╗ ██████╗ █████╗ ███████╗ ██████╗ █████╗ ██████╗ ███████╗ ███████╗ @@ -16,7 +32,7 @@
-MegaSparse allows you to quickly serve a streamlit app running on top of the DeepSparse Server for comparing latency speeds of various transformer models. Currently, the demo can safely load up to 18 Sparse BERT models fine-tuned on the question answering task on only 16GB of RAM. The purpose of this app is for you to familiarize and compare the inference performance of various models trained on different sparse profiles. +MegaSparse allows you to serve a streamlit app running on top of the DeepSparse Server for comparing latency speeds of various sparse transformer models. Currently, the demo can safely load up to 18 BERT models fine-tuned on the question answering task on only 16GB of RAM. The purpose of this app is for you to familiarize and compare the inference performance of transformers trained on various sparse approaches.

diff --git a/examples/megasparse/client/app.py b/examples/megasparse/client/app.py index cca06bcf35..ccff7be778 100644 --- a/examples/megasparse/client/app.py +++ b/examples/megasparse/client/app.py @@ -12,35 +12,41 @@ # See the License for the specific language governing permissions and # limitations under the License. +from time import perf_counter + import streamlit as st from settings import FeatureHandler as feat -from time import perf_counter -#Titles + +# Titles st.markdown(feat.title, unsafe_allow_html=True) st.markdown(feat.subtitle, unsafe_allow_html=True) -#Sidebar +# Sidebar st.sidebar.selectbox(feat.tasks_desc, feat.tasks) model_choice = st.sidebar.radio(feat.variants_desc, feat.variants.keys()) st.sidebar.markdown(feat.code_banner) st.sidebar.code(body=feat.code_text, language=feat.language) st.sidebar.markdown(feat.repo_test) -#Footer +# Footer st.markdown(feat.footer, unsafe_allow_html=True) -#Inference +# Inference for model_name, model in feat.variants.items(): if model_choice == model_name: - - context = st.text_area(label=feat.example_context_label, height=150, value=feat.example_context) - question = st.text_area(label=feat.example_question_label, value=feat.example_question) + + context = st.text_area( + label=feat.example_context_label, height=150, value=feat.example_context + ) + question = st.text_area( + label=feat.example_question_label, value=feat.example_question + ) start = perf_counter() answer = model(question=question, context=context) end = perf_counter() infer_time = end - start infer_time = round(infer_time, 4) - st.write(feat.answer_label, answer['answer']) - st.write(infer_time, feat.time_label) \ No newline at end of file + st.write(feat.answer_label, answer["answer"]) + st.write(infer_time, feat.time_label) diff --git a/examples/megasparse/client/pipelineclient.py b/examples/megasparse/client/pipelineclient.py index 9064e103b7..dda88347ad 100644 --- a/examples/megasparse/client/pipelineclient.py +++ b/examples/megasparse/client/pipelineclient.py @@ -18,6 +18,7 @@ import numpy import requests + class MultiPipelineClient: """ Client object for making requests to the example DeepSparse BERT inference server @@ -27,11 +28,11 @@ class MultiPipelineClient: :param port: Port the server is hosted on, default is 5543 """ - def __init__(self, model: str, address: str ='0.0.0.0', port: str ='5543'): + def __init__(self, model: str, address: str = "0.0.0.0", port: str = "5543"): self.model = model - self._url = f'http://{address}:{port}/predict/{self.model}' - + self._url = f"http://{address}:{port}/predict/{self.model}" + def __call__(self, **kwargs) -> List[numpy.ndarray]: """ @@ -43,4 +44,4 @@ def __call__(self, **kwargs) -> List[numpy.ndarray]: """ response = requests.post(self._url, json=kwargs) - return json.loads(response.content) \ No newline at end of file + return json.loads(response.content) diff --git a/examples/megasparse/client/settings.py b/examples/megasparse/client/settings.py index bf9e13d074..20f6ee6492 100644 --- a/examples/megasparse/client/settings.py +++ b/examples/megasparse/client/settings.py @@ -14,6 +14,7 @@ from pipelineclient import MultiPipelineClient + class FeatureHandler: """ @@ -27,8 +28,12 @@ class FeatureHandler: variants_desc = "Select model:" variants = { - "Pruned, Quant, Aggressive 95": MultiPipelineClient(model="question_answering/pruned_quant"), - "Pruned, Quant, Moderate": MultiPipelineClient(model="question_answering/quantmod"), + "Pruned, Quant, Aggressive 95": MultiPipelineClient( + model="question_answering/pruned_quant" + ), + "Pruned, Quant, Moderate": MultiPipelineClient( + model="question_answering/quantmod" + ), } title = "

✨ Neural Magic ✨

" @@ -37,12 +42,16 @@ class FeatureHandler: code_banner = "Get started with faster inference 👇" code_text = "pip install deepsparse[server]" language = "python" - repo_test = "Give the [DeepSparse](https://github.com/neuralmagic/deepsparse) repo a ⭐!" + repo_test = ( + "Give the [DeepSparse](https://github.com/neuralmagic/deepsparse) repo a ⭐!" + ) example_context_label = "Enter Context" example_question_label = "Enter Question" example_context = r"""The DeepSparse Engine is a CPU runtime that delivers GPU-class performance by taking advantage of sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. It is focused on model deployment and scaling machine learning pipelines, fitting seamlessly into your existing deployments as an inference backend.""" - example_question = "What does the DeepSparse Engine take advantage of within neural networks?" + example_question = ( + "What does the DeepSparse Engine take advantage of within neural networks?" + ) answer_label = "ANSWER: " time_label = "seconds" @@ -63,4 +72,4 @@ class FeatureHandler: - """ \ No newline at end of file + """ From 5f26aae83b50ed59940437a1dead79915eb00369 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Tue, 5 Apr 2022 16:37:34 -0400 Subject: [PATCH 09/36] quality check commit --- examples/megasparse/README.md | 18 +----------------- examples/megasparse/client/settings.py | 11 ++++++++--- 2 files changed, 9 insertions(+), 20 deletions(-) diff --git a/examples/megasparse/README.md b/examples/megasparse/README.md index b8eb85c6ae..263c90ed41 100644 --- a/examples/megasparse/README.md +++ b/examples/megasparse/README.md @@ -1,19 +1,3 @@ - - ![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) [**NEURAL MAGIC**](https://neuralmagic.com) ![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) ███╗ ███╗ ███████╗ ██████╗ █████╗ ███████╗ ██████╗ █████╗ ██████╗ ███████╗ ███████╗ @@ -59,7 +43,7 @@ cd examples/megasparse pip install -r requirements.txt ```
-The `config.yaml` file lists the models you want the DeepSparse Server to serve. Currently, it contains up to 18 BERT models, although 16 of these models are commented out so you can safely get started on two models, and later on, add more models at your own pace. If you wish to load all 18 models into memory make sure you have 16GB of RAM available, otherwise you will get out of memory errors. Also, as you add additional models to the `config.yaml` file, make sure to all also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. +The `config.yaml` file lists the models you want the DeepSparse Server to serve. Currently, it contains up to 18 BERT models, although 16 of these models are commented out so you can safely get started on two models, and later on, add more models at your own pace. If you wish to load all 18 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. Also, as you add additional models to the `config.yaml` file, make sure to also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. ##
`START SERVER`
diff --git a/examples/megasparse/client/settings.py b/examples/megasparse/client/settings.py index 20f6ee6492..4f7f30f180 100644 --- a/examples/megasparse/client/settings.py +++ b/examples/megasparse/client/settings.py @@ -37,7 +37,7 @@ class FeatureHandler: } title = "

✨ Neural Magic ✨

" - subtitle = "

Inference with the DeepSparse Server

" + subtitle = "

DeepSparse Server

" code_banner = "Get started with faster inference 👇" code_text = "pip install deepsparse[server]" @@ -48,7 +48,12 @@ class FeatureHandler: example_context_label = "Enter Context" example_question_label = "Enter Question" - example_context = r"""The DeepSparse Engine is a CPU runtime that delivers GPU-class performance by taking advantage of sparsity within neural networks to reduce compute required as well as accelerate memory bound workloads. It is focused on model deployment and scaling machine learning pipelines, fitting seamlessly into your existing deployments as an inference backend.""" + example_context = "The DeepSparse Engine is a CPU runtime that delivers \ + GPU-class performance by taking advantage of sparsity within neural \ + networks to reduce compute required as well as accelerate memory bound \ + workloads. It is focused on model deployment and scaling machine \ + learning pipelines, fitting seamlessly into your existing \ + deployments as an inference backend." example_question = ( "What does the DeepSparse Engine take advantage of within neural networks?" ) @@ -70,6 +75,6 @@ class FeatureHandler: }
-

Made with ☠️ and Streamlit . +

Made with ☠️ & Streamlit .

""" From 970e9dd4bec4c01b72c7e45ab82147482503737e Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Tue, 5 Apr 2022 16:53:10 -0400 Subject: [PATCH 10/36] passing copyright quality check --- examples/megasparse/README.md | 15 +++++++++++++++ 1 file changed, 15 insertions(+) diff --git a/examples/megasparse/README.md b/examples/megasparse/README.md index 263c90ed41..b40d5d99c2 100644 --- a/examples/megasparse/README.md +++ b/examples/megasparse/README.md @@ -1,3 +1,18 @@ + ![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) [**NEURAL MAGIC**](https://neuralmagic.com) ![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) ███╗ ███╗ ███████╗ ██████╗ █████╗ ███████╗ ██████╗ █████╗ ██████╗ ███████╗ ███████╗ From a7fe2fb6d9dd9056b1a2b81f1a7131cd013dd2cf Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Tue, 5 Apr 2022 17:05:31 -0400 Subject: [PATCH 11/36] content edits --- examples/megasparse/README.md | 9 ++------- 1 file changed, 2 insertions(+), 7 deletions(-) diff --git a/examples/megasparse/README.md b/examples/megasparse/README.md index b40d5d99c2..fac2450fa9 100644 --- a/examples/megasparse/README.md +++ b/examples/megasparse/README.md @@ -48,17 +48,12 @@ MegaSparse allows you to serve a streamlit app running on top of the DeepSparse ```bash git clone https://github.com/neuralmagic/deepsparse.git -``` - -```bash cd examples/megasparse -``` - -```bash pip install -r requirements.txt ```
-The `config.yaml` file lists the models you want the DeepSparse Server to serve. Currently, it contains up to 18 BERT models, although 16 of these models are commented out so you can safely get started on two models, and later on, add more models at your own pace. If you wish to load all 18 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. Also, as you add additional models to the `config.yaml` file, make sure to also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. + +The `config.yaml` file in the `server` directory lists the models you want the DeepSparse Server to serve. Currently, it contains up to 18 BERT models, although 16 of these models are commented out so you can safely get started on two models, and later on, add more models at your own pace. If you wish to load all 18 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. Also, as you add additional models to the `config.yaml` file, make sure to also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. ##
`START SERVER`
From f0e2e5062115059c4cef7b6c12eaf48ae465cc99 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Fri, 8 Apr 2022 14:01:41 -0400 Subject: [PATCH 12/36] rename dir to sparseserver-ui --- examples/{megasparse => sparseserver-ui}/README.md | 2 +- .../{megasparse => sparseserver-ui}/client/app.py | 0 .../client/pipelineclient.py | 0 .../client/settings.py | 0 .../img/demo_screenshot.png | Bin .../requirements.txt | 0 .../server/config.yaml | 0 7 files changed, 1 insertion(+), 1 deletion(-) rename examples/{megasparse => sparseserver-ui}/README.md (96%) rename examples/{megasparse => sparseserver-ui}/client/app.py (100%) rename examples/{megasparse => sparseserver-ui}/client/pipelineclient.py (100%) rename examples/{megasparse => sparseserver-ui}/client/settings.py (100%) rename examples/{megasparse => sparseserver-ui}/img/demo_screenshot.png (100%) rename examples/{megasparse => sparseserver-ui}/requirements.txt (100%) rename examples/{megasparse => sparseserver-ui}/server/config.yaml (100%) diff --git a/examples/megasparse/README.md b/examples/sparseserver-ui/README.md similarity index 96% rename from examples/megasparse/README.md rename to examples/sparseserver-ui/README.md index fac2450fa9..76915afe65 100644 --- a/examples/megasparse/README.md +++ b/examples/sparseserver-ui/README.md @@ -31,7 +31,7 @@ limitations under the License.
-MegaSparse allows you to serve a streamlit app running on top of the DeepSparse Server for comparing latency speeds of various sparse transformer models. Currently, the demo can safely load up to 18 BERT models fine-tuned on the question answering task on only 16GB of RAM. The purpose of this app is for you to familiarize and compare the inference performance of transformers trained on various sparse approaches. +MegaSparse allows you to serve a streamlit app running on top of the DeepSparse Server for comparing the latency speeds of sparse transformer models. Currently, the demo can safely load up to 18 BERT models fine-tuned on the question answering task on only 16GB of RAM. The purpose of this app is for you to familiarize and compare the inference performance of transformers trained with various sparse approaches.

diff --git a/examples/megasparse/client/app.py b/examples/sparseserver-ui/client/app.py similarity index 100% rename from examples/megasparse/client/app.py rename to examples/sparseserver-ui/client/app.py diff --git a/examples/megasparse/client/pipelineclient.py b/examples/sparseserver-ui/client/pipelineclient.py similarity index 100% rename from examples/megasparse/client/pipelineclient.py rename to examples/sparseserver-ui/client/pipelineclient.py diff --git a/examples/megasparse/client/settings.py b/examples/sparseserver-ui/client/settings.py similarity index 100% rename from examples/megasparse/client/settings.py rename to examples/sparseserver-ui/client/settings.py diff --git a/examples/megasparse/img/demo_screenshot.png b/examples/sparseserver-ui/img/demo_screenshot.png similarity index 100% rename from examples/megasparse/img/demo_screenshot.png rename to examples/sparseserver-ui/img/demo_screenshot.png diff --git a/examples/megasparse/requirements.txt b/examples/sparseserver-ui/requirements.txt similarity index 100% rename from examples/megasparse/requirements.txt rename to examples/sparseserver-ui/requirements.txt diff --git a/examples/megasparse/server/config.yaml b/examples/sparseserver-ui/server/config.yaml similarity index 100% rename from examples/megasparse/server/config.yaml rename to examples/sparseserver-ui/server/config.yaml From 9195b9029d6e1b9e71b40071529f18f3a02c9d46 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Fri, 8 Apr 2022 14:36:24 -0400 Subject: [PATCH 13/36] added new config file for quick start --- examples/sparseserver-ui/README.md | 28 +++--- examples/sparseserver-ui/server/config.yaml | 80 +++-------------- .../sparseserver-ui/server/nuke-config.yaml | 87 +++++++++++++++++++ 3 files changed, 117 insertions(+), 78 deletions(-) create mode 100644 examples/sparseserver-ui/server/nuke-config.yaml diff --git a/examples/sparseserver-ui/README.md b/examples/sparseserver-ui/README.md index 76915afe65..d85d17fec5 100644 --- a/examples/sparseserver-ui/README.md +++ b/examples/sparseserver-ui/README.md @@ -15,12 +15,13 @@ limitations under the License. --> ![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) [**NEURAL MAGIC**](https://neuralmagic.com) ![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) - ███╗ ███╗ ███████╗ ██████╗ █████╗ ███████╗ ██████╗ █████╗ ██████╗ ███████╗ ███████╗ - ████╗ ████║ ██╔════╝ ██╔════╝ ██╔══██╗ ██╔════╝ ██╔══██╗ ██╔══██╗ ██╔══██╗ ██╔════╝ ██╔════╝ - ██╔████╔██║ █████╗ ██║ ███╗ ███████║ ███████╗ ██████╔╝ ███████║ ██████╔╝ ███████╗ █████╗ - ██║╚██╔╝██║ ██╔══╝ ██║ ██║ ██╔══██║ ╚════██║ ██╔═══╝ ██╔══██║ ██╔══██╗ ╚════██║ ██╔══╝ - ██║ ╚═╝ ██║ ███████╗ ╚██████╔╝ ██║ ██║ ███████║ ██║ ██║ ██║ ██║ ██║ ███████║ ███████╗ - ╚═╝ ╚═╝ ╚══════╝ ╚═════╝ ╚═╝ ╚═╝ ╚══════╝ ╚═╝ ╚═╝ ╚═╝ ╚═╝ ╚═╝ ╚══════╝ ╚══════╝ + ███████╗██████╗ █████╗ ██████╗ ███████╗███████╗ ███████╗███████╗██████╗ ██╗ ██╗███████╗██████╗ ██╗ ██╗ ██╗ + ██╔════╝██╔══██╗██╔══██╗██╔══██╗██╔════╝██╔════╝ ██╔════╝██╔════╝██╔══██╗██║ ██║██╔════╝██╔══██╗ ██║ ██║ ██║ + ███████╗██████╔╝███████║██████╔╝███████╗█████╗ ███████╗█████╗ ██████╔╝██║ ██║█████╗ ██████╔╝ ██║ ██║ ██║ + ╚════██║██╔═══╝ ██╔══██║██╔══██╗╚════██║██╔══╝ ╚════██║██╔══╝ ██╔══██╗╚██╗ ██╔╝██╔══╝ ██╔══██╗ ██║ ██║ ██║ + ███████║██║ ██║ ██║██║ ██║███████║███████╗ ███████║███████╗██║ ██║ ╚████╔╝ ███████╗██║ ██║ ██╗ ╚██████╔ ██║ + ╚══════╝╚═╝ ╚═╝ ╚═╝╚═╝ ╚═╝╚══════╝╚══════╝ ╚══════╝╚══════╝╚═╝ ╚═╝ ╚═══╝ ╚══════╝╚═╝ ╚═╝ ╚═╝ ╚═════╝ ╚═╝ + *** A Streamlit app for deploying the DeepSparse Server *** ![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+)![#00F](https://via.placeholder.com/15/00F/000000?text=+) @@ -31,7 +32,7 @@ limitations under the License.
-MegaSparse allows you to serve a streamlit app running on top of the DeepSparse Server for comparing the latency speeds of sparse transformer models. Currently, the demo can safely load up to 18 BERT models fine-tuned on the question answering task on only 16GB of RAM. The purpose of this app is for you to familiarize and compare the inference performance of transformers trained with various sparse approaches. +SparseServer.UI allows you to serve a streamlit app running on top of the DeepSparse Server for comparing the latency speeds of sparse transformer models. Currently, the demo can safely load up to 18 BERT models fine-tuned on the question answering task on only 16GB of RAM. The purpose of this app is for you to familiarize and compare the inference performance of transformers trained with various sparse approaches.

@@ -48,18 +49,25 @@ MegaSparse allows you to serve a streamlit app running on top of the DeepSparse ```bash git clone https://github.com/neuralmagic/deepsparse.git -cd examples/megasparse +cd examples/sparseserver-ui pip install -r requirements.txt ```
-The `config.yaml` file in the `server` directory lists the models you want the DeepSparse Server to serve. Currently, it contains up to 18 BERT models, although 16 of these models are commented out so you can safely get started on two models, and later on, add more models at your own pace. If you wish to load all 18 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. Also, as you add additional models to the `config.yaml` file, make sure to also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. +The `starter-config.yaml` file in the `server` directory has a great started list of four models for DeepSparse Server to serve. + +Currently, it contains up to 18 BERT models, although 16 of these models are commented out so you can safely get started on two models, and later on, add more models at your own pace. + + +If you wish to load all 18 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. Also, as you add additional models to the `config.yaml` file, make sure to also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. + +To add more question answering models please refer to our [updated list](https://sparsezoo.neuralmagic.com/?domain=nlp&sub_domain=question_answering&page=1). ##
`START SERVER`
To download and initialize the two sample models in the `config.yaml` file, run: ```bash -deepsparse.server --config_file server/config.yaml +deepsparse.server --config_file server/starter-config.yaml ``` The DeepSparse Server should now be running on host `0.0.0.0` and port `5543`. diff --git a/examples/sparseserver-ui/server/config.yaml b/examples/sparseserver-ui/server/config.yaml index fe8a31f9dd..5e7052fb73 100644 --- a/examples/sparseserver-ui/server/config.yaml +++ b/examples/sparseserver-ui/server/config.yaml @@ -14,74 +14,18 @@ models: - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant-aggressive_95 + model_path: "zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned80_quant-none-vnni" batch_size: 1 - alias: question_answering/pruned_quant + alias: question_answering/12l_pruned80_quant - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant-moderate + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_96 batch_size: 1 - alias: question_answering/quantmod - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_98 - # batch_size: 1 - # alias: question_answering/agg98 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_94 - # batch_size: 1 - # alias: question_answering/agg94 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-conservative - # batch_size: 1 - # alias: question_answering/conserv - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_96 - # batch_size: 1 - # alias: question_answering/quant6lagg96 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_91 - # batch_size: 1 - # alias: question_answering/quant6lagg91 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_98 - # batch_size: 1 - # alias: question_answering/6lagg98 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_97 - # batch_size: 1 - # alias: question_answering/6lagg97 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_96 - # batch_size: 1 - # alias: question_answering/6lagg96 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_94 - # batch_size: 1 - # alias: question_answering/6lagg94 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_89 - # batch_size: 1 - # alias: question_answering/quant3lagg89 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_84 - # batch_size: 1 - # alias: question_answering/quant3lagg84 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_90 - # batch_size: 1 - # alias: question_answering/3lagg90 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_89 - # batch_size: 1 - # alias: question_answering/3lagg89 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_86 - # batch_size: 1 - # alias: question_answering/3lagg86 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_83 - # batch_size: 1 - # alias: question_answering/3lagg83 - # - task: question_answering - # model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/base-none - # batch_size: 1 - # alias: question_answering/base \ No newline at end of file + alias: question_answering/6lagg96 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_89 + batch_size: 1 + alias: question_answering/3lagg89 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/base-none + batch_size: 1 + alias: question_answering/base \ No newline at end of file diff --git a/examples/sparseserver-ui/server/nuke-config.yaml b/examples/sparseserver-ui/server/nuke-config.yaml new file mode 100644 index 0000000000..c730b9e9a3 --- /dev/null +++ b/examples/sparseserver-ui/server/nuke-config.yaml @@ -0,0 +1,87 @@ +# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +models: + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant-aggressive_95 + batch_size: 1 + alias: question_answering/pruned_quant + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant-moderate + batch_size: 1 + alias: question_answering/quantmod + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_98 + batch_size: 1 + alias: question_answering/agg98 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_94 + batch_size: 1 + alias: question_answering/agg94 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-conservative + batch_size: 1 + alias: question_answering/conserv + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_96 + batch_size: 1 + alias: question_answering/quant6lagg96 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_91 + batch_size: 1 + alias: question_answering/quant6lagg91 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_98 + batch_size: 1 + alias: question_answering/6lagg98 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_97 + batch_size: 1 + alias: question_answering/6lagg97 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_96 + batch_size: 1 + alias: question_answering/6lagg96 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_94 + batch_size: 1 + alias: question_answering/6lagg94 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_89 + batch_size: 1 + alias: question_answering/quant3lagg89 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_84 + batch_size: 1 + alias: question_answering/quant3lagg84 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_90 + batch_size: 1 + alias: question_answering/3lagg90 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_89 + batch_size: 1 + alias: question_answering/3lagg89 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_86 + batch_size: 1 + alias: question_answering/3lagg86 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_83 + batch_size: 1 + alias: question_answering/3lagg83 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/base-none + batch_size: 1 + alias: question_answering/base \ No newline at end of file From 7714dce4dc24440cc39be29dd8d9c1519d453ff3 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Fri, 8 Apr 2022 14:58:43 -0400 Subject: [PATCH 14/36] edited multipipelineclient in settings.py --- examples/sparseserver-ui/README.md | 18 ++++++++---------- examples/sparseserver-ui/client/settings.py | 14 ++++++++++---- .../sparseserver-ui/server/nuke-config.yaml | 10 +++++++++- 3 files changed, 27 insertions(+), 15 deletions(-) diff --git a/examples/sparseserver-ui/README.md b/examples/sparseserver-ui/README.md index d85d17fec5..cdd7459e9e 100644 --- a/examples/sparseserver-ui/README.md +++ b/examples/sparseserver-ui/README.md @@ -45,7 +45,7 @@ SparseServer.UI allows you to serve a streamlit app running on top of the DeepSp
-##
`INSTALL`
+##
`INSTALLATION`
```bash git clone https://github.com/neuralmagic/deepsparse.git @@ -54,20 +54,17 @@ pip install -r requirements.txt ```
-The `starter-config.yaml` file in the `server` directory has a great started list of four models for DeepSparse Server to serve. +The `config.yaml` file in the `server` directory includes a list of four BERT QA models for the DeepSparse Server to get started quickly. If you prefer to add additional models to the `config.yaml` file, make sure to also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. -Currently, it contains up to 18 BERT models, although 16 of these models are commented out so you can safely get started on two models, and later on, add more models at your own pace. +Currently, the SparseZoo contains 20 BERT models, and the `nuke-config.yaml` file contains the full list in case you want to load them all 🤯. If you wish to load all 20 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. - -If you wish to load all 18 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. Also, as you add additional models to the `config.yaml` file, make sure to also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. - -To add more question answering models please refer to our [updated list](https://sparsezoo.neuralmagic.com/?domain=nlp&sub_domain=question_answering&page=1). +For more details on question answering models, please refer to our [updated list](https://sparsezoo.neuralmagic.com/?domain=nlp&sub_domain=question_answering&page=1). ##
`START SERVER`
-To download and initialize the two sample models in the `config.yaml` file, run: +To download and initialize the models in the `config.yaml` file, run: ```bash -deepsparse.server --config_file server/starter-config.yaml +deepsparse.server --config_file server/config.yaml ``` The DeepSparse Server should now be running on host `0.0.0.0` and port `5543`. @@ -83,12 +80,13 @@ streamlit run client/app.py \ --theme.textColor white \ --browser.serverAddress="localhost" ``` + This will start the Streamlit app on host `localhost` and port `8501`. Visit `http://localhost:8501` in your browser to view the demo. ### Testing -- 18 models were able to fit on 16GB RAM of a c2-standard-4 VM instance on GCP +- 20 models were able to fit on 16GB RAM of a c2-standard-4 VM instance on GCP - Ubuntu 20.04.4 LTS - Python 3.8.10 diff --git a/examples/sparseserver-ui/client/settings.py b/examples/sparseserver-ui/client/settings.py index 4f7f30f180..727c002078 100644 --- a/examples/sparseserver-ui/client/settings.py +++ b/examples/sparseserver-ui/client/settings.py @@ -28,11 +28,17 @@ class FeatureHandler: variants_desc = "Select model:" variants = { - "Pruned, Quant, Aggressive 95": MultiPipelineClient( - model="question_answering/pruned_quant" + "80% Pruned, Quantized for VNNI": MultiPipelineClient( + model="question_answering/12l_pruned80_quant" ), - "Pruned, Quant, Moderate": MultiPipelineClient( - model="question_answering/quantmod" + "Pruned, 6layers, Aggressive 96": MultiPipelineClient( + model="question_answering/6lagg96" + ), + "Pruned, 3layers, Aggressive 89": MultiPipelineClient( + model="question_answering/3lagg89" + ), + "Base Model, Not Sparsified 😢": MultiPipelineClient( + model="question_answering/base" ), } diff --git a/examples/sparseserver-ui/server/nuke-config.yaml b/examples/sparseserver-ui/server/nuke-config.yaml index c730b9e9a3..e7179842cf 100644 --- a/examples/sparseserver-ui/server/nuke-config.yaml +++ b/examples/sparseserver-ui/server/nuke-config.yaml @@ -81,7 +81,15 @@ models: model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_83 batch_size: 1 alias: question_answering/3lagg83 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned80_quant-none-vnni + batch_size: 1 + alias: question_answering/12l_pruned80_quant + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned90-none + batch_size: 1 + alias: question_answering/12layer_pruned90 - task: question_answering model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/base-none batch_size: 1 - alias: question_answering/base \ No newline at end of file + alias: question_answering/base From 29ada34080e7c1e394531172bda2f4c0113f510b Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Fri, 8 Apr 2022 15:00:11 -0400 Subject: [PATCH 15/36] changed name of config file --- examples/sparseserver-ui/README.md | 4 +- .../sparseserver-ui/server/nuke-config.yaml | 95 ------------------- 2 files changed, 2 insertions(+), 97 deletions(-) delete mode 100644 examples/sparseserver-ui/server/nuke-config.yaml diff --git a/examples/sparseserver-ui/README.md b/examples/sparseserver-ui/README.md index cdd7459e9e..b6346ddfee 100644 --- a/examples/sparseserver-ui/README.md +++ b/examples/sparseserver-ui/README.md @@ -54,9 +54,9 @@ pip install -r requirements.txt ```
-The `config.yaml` file in the `server` directory includes a list of four BERT QA models for the DeepSparse Server to get started quickly. If you prefer to add additional models to the `config.yaml` file, make sure to also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. +The `config.yaml` file in the `server` directory includes a list of four BERT QA models for the DeepSparse Server to get started. If you prefer to add additional models to the `config.yaml` file, make sure to also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. -Currently, the SparseZoo contains 20 BERT models, and the `nuke-config.yaml` file contains the full list in case you want to load them all 🤯. If you wish to load all 20 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. +Currently, the SparseZoo contains 20 BERT models, and the `big-config.yaml` file contains the full list in case you want to load them all 🤯. If you wish to load all 20 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. For more details on question answering models, please refer to our [updated list](https://sparsezoo.neuralmagic.com/?domain=nlp&sub_domain=question_answering&page=1). diff --git a/examples/sparseserver-ui/server/nuke-config.yaml b/examples/sparseserver-ui/server/nuke-config.yaml deleted file mode 100644 index e7179842cf..0000000000 --- a/examples/sparseserver-ui/server/nuke-config.yaml +++ /dev/null @@ -1,95 +0,0 @@ -# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, -# software distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -models: - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant-aggressive_95 - batch_size: 1 - alias: question_answering/pruned_quant - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant-moderate - batch_size: 1 - alias: question_answering/quantmod - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_98 - batch_size: 1 - alias: question_answering/agg98 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_94 - batch_size: 1 - alias: question_answering/agg94 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-conservative - batch_size: 1 - alias: question_answering/conserv - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_96 - batch_size: 1 - alias: question_answering/quant6lagg96 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_91 - batch_size: 1 - alias: question_answering/quant6lagg91 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_98 - batch_size: 1 - alias: question_answering/6lagg98 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_97 - batch_size: 1 - alias: question_answering/6lagg97 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_96 - batch_size: 1 - alias: question_answering/6lagg96 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_94 - batch_size: 1 - alias: question_answering/6lagg94 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_89 - batch_size: 1 - alias: question_answering/quant3lagg89 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_84 - batch_size: 1 - alias: question_answering/quant3lagg84 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_90 - batch_size: 1 - alias: question_answering/3lagg90 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_89 - batch_size: 1 - alias: question_answering/3lagg89 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_86 - batch_size: 1 - alias: question_answering/3lagg86 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_83 - batch_size: 1 - alias: question_answering/3lagg83 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned80_quant-none-vnni - batch_size: 1 - alias: question_answering/12l_pruned80_quant - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned90-none - batch_size: 1 - alias: question_answering/12layer_pruned90 - - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/base-none - batch_size: 1 - alias: question_answering/base From dee99e5cc9218a3844a3fc7274a65d554be10126 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Fri, 8 Apr 2022 15:00:23 -0400 Subject: [PATCH 16/36] changed name of config file --- .../sparseserver-ui/server/big-config.yaml | 95 +++++++++++++++++++ 1 file changed, 95 insertions(+) create mode 100644 examples/sparseserver-ui/server/big-config.yaml diff --git a/examples/sparseserver-ui/server/big-config.yaml b/examples/sparseserver-ui/server/big-config.yaml new file mode 100644 index 0000000000..e7179842cf --- /dev/null +++ b/examples/sparseserver-ui/server/big-config.yaml @@ -0,0 +1,95 @@ +# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +models: + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant-aggressive_95 + batch_size: 1 + alias: question_answering/pruned_quant + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant-moderate + batch_size: 1 + alias: question_answering/quantmod + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_98 + batch_size: 1 + alias: question_answering/agg98 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-aggressive_94 + batch_size: 1 + alias: question_answering/agg94 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned-conservative + batch_size: 1 + alias: question_answering/conserv + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_96 + batch_size: 1 + alias: question_answering/quant6lagg96 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_91 + batch_size: 1 + alias: question_answering/quant6lagg91 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_98 + batch_size: 1 + alias: question_answering/6lagg98 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_97 + batch_size: 1 + alias: question_answering/6lagg97 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_96 + batch_size: 1 + alias: question_answering/6lagg96 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_94 + batch_size: 1 + alias: question_answering/6lagg94 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_89 + batch_size: 1 + alias: question_answering/quant3lagg89 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_84 + batch_size: 1 + alias: question_answering/quant3lagg84 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_90 + batch_size: 1 + alias: question_answering/3lagg90 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_89 + batch_size: 1 + alias: question_answering/3lagg89 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_86 + batch_size: 1 + alias: question_answering/3lagg86 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_83 + batch_size: 1 + alias: question_answering/3lagg83 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned80_quant-none-vnni + batch_size: 1 + alias: question_answering/12l_pruned80_quant + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned90-none + batch_size: 1 + alias: question_answering/12layer_pruned90 + - task: question_answering + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/base-none + batch_size: 1 + alias: question_answering/base From 9f3fdda40c4f925e88bf65ee8c0ff8ddb7905e15 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Fri, 8 Apr 2022 15:07:12 -0400 Subject: [PATCH 17/36] edited model stubs --- examples/sparseserver-ui/README.md | 2 +- examples/sparseserver-ui/client/settings.py | 8 ++++---- examples/sparseserver-ui/server/config.yaml | 10 +++++----- 3 files changed, 10 insertions(+), 10 deletions(-) diff --git a/examples/sparseserver-ui/README.md b/examples/sparseserver-ui/README.md index b6346ddfee..e0f3fbc3e7 100644 --- a/examples/sparseserver-ui/README.md +++ b/examples/sparseserver-ui/README.md @@ -56,7 +56,7 @@ pip install -r requirements.txt The `config.yaml` file in the `server` directory includes a list of four BERT QA models for the DeepSparse Server to get started. If you prefer to add additional models to the `config.yaml` file, make sure to also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. -Currently, the SparseZoo contains 20 BERT models, and the `big-config.yaml` file contains the full list in case you want to load them all 🤯. If you wish to load all 20 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. +Currently, the SparseZoo contains 20 BERT models, and the `big-config.yaml` file contains the full list in case you want to load them all 🤯. If you wish to load all 20 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. For more details on question answering models, please refer to our [updated list](https://sparsezoo.neuralmagic.com/?domain=nlp&sub_domain=question_answering&page=1). diff --git a/examples/sparseserver-ui/client/settings.py b/examples/sparseserver-ui/client/settings.py index 727c002078..4ca4661acb 100644 --- a/examples/sparseserver-ui/client/settings.py +++ b/examples/sparseserver-ui/client/settings.py @@ -31,11 +31,11 @@ class FeatureHandler: "80% Pruned, Quantized for VNNI": MultiPipelineClient( model="question_answering/12l_pruned80_quant" ), - "Pruned, 6layers, Aggressive 96": MultiPipelineClient( - model="question_answering/6lagg96" + "Pruned, Quant, 6layers, Aggressive 96": MultiPipelineClient( + model="question_answering/quant6lagg96" ), - "Pruned, 3layers, Aggressive 89": MultiPipelineClient( - model="question_answering/3lagg89" + "Pruned, Quant, 3layers, Aggressive 89": MultiPipelineClient( + model="question_answering/quant3lagg89" ), "Base Model, Not Sparsified 😢": MultiPipelineClient( model="question_answering/base" diff --git a/examples/sparseserver-ui/server/config.yaml b/examples/sparseserver-ui/server/config.yaml index 5e7052fb73..a4841afd1b 100644 --- a/examples/sparseserver-ui/server/config.yaml +++ b/examples/sparseserver-ui/server/config.yaml @@ -14,17 +14,17 @@ models: - task: question_answering - model_path: "zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned80_quant-none-vnni" + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned80_quant-none-vnni batch_size: 1 alias: question_answering/12l_pruned80_quant - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_6layers-aggressive_96 + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_6layers-aggressive_96 batch_size: 1 - alias: question_answering/6lagg96 + alias: question_answering/quant6lagg96 - task: question_answering - model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_3layers-aggressive_89 + model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/pruned_quant_3layers-aggressive_89 batch_size: 1 - alias: question_answering/3lagg89 + alias: question_answering/quant3lagg89 - task: question_answering model_path: zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/base-none batch_size: 1 From a1a0a5b07e512925ea4e1250bd2447b5240fa15a Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Fri, 8 Apr 2022 15:11:17 -0400 Subject: [PATCH 18/36] edited readme --- examples/sparseserver-ui/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/sparseserver-ui/README.md b/examples/sparseserver-ui/README.md index e0f3fbc3e7..807fedc8da 100644 --- a/examples/sparseserver-ui/README.md +++ b/examples/sparseserver-ui/README.md @@ -32,7 +32,7 @@ limitations under the License.
-SparseServer.UI allows you to serve a streamlit app running on top of the DeepSparse Server for comparing the latency speeds of sparse transformer models. Currently, the demo can safely load up to 18 BERT models fine-tuned on the question answering task on only 16GB of RAM. The purpose of this app is for you to familiarize and compare the inference performance of transformers trained with various sparse approaches. +SparseServer.UI allows you to serve a streamlit app running on top of the DeepSparse Server for comparing the latency speeds of sparse transformer models. The purpose of this app is for you to familiarize and compare the inference performance of transformers trained with various sparse approaches.

From d53f79220b59c0879a677e79c8d245d3af500295 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Fri, 8 Apr 2022 15:13:42 -0400 Subject: [PATCH 19/36] added dependency pins --- examples/sparseserver-ui/requirements.txt | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/sparseserver-ui/requirements.txt b/examples/sparseserver-ui/requirements.txt index 3a348208ea..c89458a9eb 100644 --- a/examples/sparseserver-ui/requirements.txt +++ b/examples/sparseserver-ui/requirements.txt @@ -1,2 +1,2 @@ -deepsparse[server] -streamlit \ No newline at end of file +deepsparse[server]==0.11.2 +streamlit==1.8.1 \ No newline at end of file From 82864035ff8995b4337a018000c753072e0b53ac Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Fri, 8 Apr 2022 15:46:34 -0400 Subject: [PATCH 20/36] changed server pin --- examples/sparseserver-ui/requirements.txt | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/sparseserver-ui/requirements.txt b/examples/sparseserver-ui/requirements.txt index c89458a9eb..3b75e7e6a2 100644 --- a/examples/sparseserver-ui/requirements.txt +++ b/examples/sparseserver-ui/requirements.txt @@ -1,2 +1,2 @@ -deepsparse[server]==0.11.2 +deepsparse[server]>=0.11 streamlit==1.8.1 \ No newline at end of file From 4de8d88cae72121773abb852b7b94e523ed5a281 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Fri, 8 Apr 2022 16:27:53 -0400 Subject: [PATCH 21/36] edited model choice logic --- examples/sparseserver-ui/client/app.py | 31 ++++++++++----------- examples/sparseserver-ui/client/settings.py | 8 +++--- 2 files changed, 18 insertions(+), 21 deletions(-) diff --git a/examples/sparseserver-ui/client/app.py b/examples/sparseserver-ui/client/app.py index ccff7be778..314c6b34a8 100644 --- a/examples/sparseserver-ui/client/app.py +++ b/examples/sparseserver-ui/client/app.py @@ -33,20 +33,17 @@ st.markdown(feat.footer, unsafe_allow_html=True) # Inference -for model_name, model in feat.variants.items(): - - if model_choice == model_name: - - context = st.text_area( - label=feat.example_context_label, height=150, value=feat.example_context - ) - question = st.text_area( - label=feat.example_question_label, value=feat.example_question - ) - start = perf_counter() - answer = model(question=question, context=context) - end = perf_counter() - infer_time = end - start - infer_time = round(infer_time, 4) - st.write(feat.answer_label, answer["answer"]) - st.write(infer_time, feat.time_label) +model = feat.variants[model_choice] +context = st.text_area( + label=feat.example_context_label, height=150, value=feat.example_context +) +question = st.text_area( + label=feat.example_question_label, value=feat.example_question +) +start = perf_counter() +answer = model(question=question, context=context) +end = perf_counter() +infer_time = end - start +infer_time = round(infer_time, 4) +st.write(feat.answer_label, answer["answer"]) +st.write(infer_time, feat.time_label) diff --git a/examples/sparseserver-ui/client/settings.py b/examples/sparseserver-ui/client/settings.py index 4ca4661acb..a5b2ca4ffa 100644 --- a/examples/sparseserver-ui/client/settings.py +++ b/examples/sparseserver-ui/client/settings.py @@ -28,16 +28,16 @@ class FeatureHandler: variants_desc = "Select model:" variants = { - "80% Pruned, Quantized for VNNI": MultiPipelineClient( + "12-Layer BERT, Sparse Quantized, 99% of Base Accuracy": MultiPipelineClient( model="question_answering/12l_pruned80_quant" ), - "Pruned, Quant, 6layers, Aggressive 96": MultiPipelineClient( + "6-Layer BERT, Sparse Quantized, 96% of Base Accuracy": MultiPipelineClient( model="question_answering/quant6lagg96" ), - "Pruned, Quant, 3layers, Aggressive 89": MultiPipelineClient( + "3-Layer BERT, Sparse Quantized, 89% of Base Accuracy": MultiPipelineClient( model="question_answering/quant3lagg89" ), - "Base Model, Not Sparsified 😢": MultiPipelineClient( + "12-Layer BERT Base, Not Sparsified 😢": MultiPipelineClient( model="question_answering/base" ), } From c9ab2a8e1e13c43f4d09102874a6d3ea1cf7a851 Mon Sep 17 00:00:00 2001 From: Ricky Costa Date: Sat, 9 Apr 2022 18:21:17 -0400 Subject: [PATCH 22/36] altered front-end features --- examples/sparseserver-ui/README.md | 4 +-- examples/sparseserver-ui/client/app.py | 16 ++++----- examples/sparseserver-ui/client/settings.py | 34 +++++++++--------- .../sparseserver-ui/client/squad_samples.py | 14 ++++++++ .../sparseserver-ui/img/demo_screenshot.png | Bin 523495 -> 1485059 bytes examples/sparseserver-ui/server/config.yaml | 3 +- 6 files changed, 41 insertions(+), 30 deletions(-) create mode 100644 examples/sparseserver-ui/client/squad_samples.py diff --git a/examples/sparseserver-ui/README.md b/examples/sparseserver-ui/README.md index 807fedc8da..59c8d4e6fd 100644 --- a/examples/sparseserver-ui/README.md +++ b/examples/sparseserver-ui/README.md @@ -37,7 +37,7 @@ SparseServer.UI allows you to serve a streamlit app running on top of the DeepSp
-[Getting Started with the DeepSparse Server](https://github.com/neuralmagic/deepsparse/tree/main/src/deepsparse/server)🔌 +[Getting Started with the DeepSparse Server](https://github.com/neuralmagic/deepsparse/tree/main/src/deepsparse/server)
@@ -56,7 +56,7 @@ pip install -r requirements.txt The `config.yaml` file in the `server` directory includes a list of four BERT QA models for the DeepSparse Server to get started. If you prefer to add additional models to the `config.yaml` file, make sure to also add a `MultiPipelineClient` object to the `variants` attribute in the `settings.py` module. -Currently, the SparseZoo contains 20 BERT models, and the `big-config.yaml` file contains the full list in case you want to load them all 🤯. If you wish to load all 20 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. +Currently, the SparseZoo contains 20 BERT models, and the `big-config.yaml` file contains the full list in case you want to load them all 🤯. To load all 20 models at once into memory, make sure you have 16GB of RAM available, otherwise you will get out of memory errors. For more details on question answering models, please refer to our [updated list](https://sparsezoo.neuralmagic.com/?domain=nlp&sub_domain=question_answering&page=1). diff --git a/examples/sparseserver-ui/client/app.py b/examples/sparseserver-ui/client/app.py index 314c6b34a8..bf9325fe4a 100644 --- a/examples/sparseserver-ui/client/app.py +++ b/examples/sparseserver-ui/client/app.py @@ -16,7 +16,7 @@ import streamlit as st from settings import FeatureHandler as feat - +from squad_samples import samples # Titles st.markdown(feat.title, unsafe_allow_html=True) @@ -34,16 +34,14 @@ # Inference model = feat.variants[model_choice] -context = st.text_area( - label=feat.example_context_label, height=150, value=feat.example_context -) -question = st.text_area( - label=feat.example_question_label, value=feat.example_question -) +selection = st.selectbox(feat.example_index_label, feat.example_index) +context = st.text_area(label=feat.example_context_label, value=samples[selection]["context"], height=300) +question = st.text_area(label=feat.example_question_label, value=samples[selection]["question"]) start = perf_counter() answer = model(question=question, context=context) end = perf_counter() infer_time = end - start infer_time = round(infer_time, 4) -st.write(feat.answer_label, answer["answer"]) -st.write(infer_time, feat.time_label) +st.markdown(feat.markdown_style, unsafe_allow_html=True) +st.markdown(f'

ANSWER: {answer["answer"]}

', unsafe_allow_html=True) +st.markdown(f'

{infer_time} secs.

', unsafe_allow_html=True) diff --git a/examples/sparseserver-ui/client/settings.py b/examples/sparseserver-ui/client/settings.py index a5b2ca4ffa..b0c035853b 100644 --- a/examples/sparseserver-ui/client/settings.py +++ b/examples/sparseserver-ui/client/settings.py @@ -28,6 +28,9 @@ class FeatureHandler: variants_desc = "Select model:" variants = { + "12-Layer BERT Base, Not Sparsified 😢": MultiPipelineClient( + model="question_answering/base" + ), "12-Layer BERT, Sparse Quantized, 99% of Base Accuracy": MultiPipelineClient( model="question_answering/12l_pruned80_quant" ), @@ -37,35 +40,30 @@ class FeatureHandler: "3-Layer BERT, Sparse Quantized, 89% of Base Accuracy": MultiPipelineClient( model="question_answering/quant3lagg89" ), - "12-Layer BERT Base, Not Sparsified 😢": MultiPipelineClient( - model="question_answering/base" - ), + } title = "

✨ Neural Magic ✨

" - subtitle = "

DeepSparse Server

" + subtitle = "

Inference with the DeepSparse Server

" code_banner = "Get started with faster inference 👇" code_text = "pip install deepsparse[server]" language = "python" repo_test = ( - "Give the [DeepSparse](https://github.com/neuralmagic/deepsparse) repo a ⭐!" + "For code: [DeepSparse repo](https://github.com/neuralmagic/deepsparse)." ) example_context_label = "Enter Context" example_question_label = "Enter Question" - example_context = "The DeepSparse Engine is a CPU runtime that delivers \ - GPU-class performance by taking advantage of sparsity within neural \ - networks to reduce compute required as well as accelerate memory bound \ - workloads. It is focused on model deployment and scaling machine \ - learning pipelines, fitting seamlessly into your existing \ - deployments as an inference backend." - example_question = ( - "What does the DeepSparse Engine take advantage of within neural networks?" - ) - answer_label = "ANSWER: " - time_label = "seconds" - + example_index_label = "Choose an example" + example_index = ["example 1", "example 2", "example 3"] + markdown_style = """ + + """ footer = """

Made with ☠️ and Streamlit .