зеркало из https://github.com/microsoft/SynapseML.git
fix: Some tidying and build fixes (#1984)
* fix: add interpret-ml install * chore: remove precommit and extra requirements.txt * chore: fix test errors * chore: notebook pip install fixes
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fa3734ba2f
Коммит
b23f050599
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@ -1,13 +0,0 @@
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repos:
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- repo: https://github.com/pre-commit/pre-commit-hooks
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rev: v4.3.0
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hooks:
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- id: trailing-whitespace
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- id: end-of-file-fixer
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- id: check-added-large-files
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- repo: https://github.com/psf/black
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rev: 22.3.0
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hooks:
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- id: black
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- id: black-jupyter
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@ -179,7 +179,7 @@ class AnalyzeDocumentSuite extends TransformerFuzzing[AnalyzeDocument] with Form
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"Contoso\nAddress:\n1 Redmond way Suite\n6000 Redmond, WA\n99243\n" +
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"Invoice For: Microsoft\n1020 Enterprise Way",
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"CustomerAddress,CustomerAddressRecipient," +
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"CustomerName,DueDate,InvoiceDate,InvoiceId,Items,VendorAddress,VendorName")
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"CustomerName,DueDate,InvoiceDate,InvoiceId,InvoiceTotal,Items,VendorAddress,VendorName")
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}
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}
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@ -44,3 +44,5 @@ dependencies:
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- huggingface-hub>=0.8.1
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- langchain==0.0.151
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- openai==0.27.5
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- black==22.3.0
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- black[jupyter]==22.3.0
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@ -1,7 +0,0 @@
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#!/usr/bin/env bash
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# If any command fails, exit immediately with that command's exit status
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set -eo pipefail
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echo "Running scalastyle.."
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sbt scalastyle test:scalastyle
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@ -27,6 +27,24 @@
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" - If you are running it on Synapse, you'll need to [create an AML workspace and set up linked Service](https://microsoft.github.io/SynapseML/docs/next/mlflow/installation/). \n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"outputs": [],
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"source": [
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"import subprocess\n",
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"import sys\n",
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"\n",
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"for package in [\"sqlparse\", \"raiwidgets\", \"interpret-community\"]:\n",
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" subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", package])"
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],
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"metadata": {
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"collapsed": false,
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"pycharm": {
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"name": "#%%\n"
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}
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}
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},
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{
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"cell_type": "markdown",
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"metadata": {
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@ -145,27 +163,26 @@
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"experiment_name = f\"/Shared/isolation_forest_experiment-{str(uuid.uuid1())}/\"\n",
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"model_name = f\"isolation-forest-model\"\n",
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"if running_on_synapse():\n",
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" import subprocess\n",
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" import sys\n",
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" from pyspark.sql.functions import udf\n",
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" from synapse.ml.core.platform import materializing_display as display\n",
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"\n",
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" # use regular display when running on interactive notebook\n",
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" # from notebookutils.visualization import display\n",
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"\n",
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" for package in [\"sqlparse\", \"raiwidgets\", \"interpret-community\"]:\n",
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" subprocess.check_call([sys.executable, \"-m\", \"pip\", \"install\", package])"
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" # from notebookutils.visualization import display"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Bootstrap Spark Session\n",
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"spark = SparkSession.builder.getOrCreate()"
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]
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],
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"metadata": {
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"collapsed": false,
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"pycharm": {
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"name": "#%%\n"
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}
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}
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},
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{
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"cell_type": "markdown",
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@ -564,7 +581,7 @@
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"outputs": [],
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"source": [
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"# Define UDF\n",
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"vec2array = udf(lambda vec: vec.toArray().tolist(), ArrayType(FloatType()))"
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"vec2array = F.udf(lambda vec: vec.toArray().tolist(), ArrayType(FloatType()))"
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]
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},
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{
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@ -51,7 +51,6 @@
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"\n",
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"if running_on_synapse():\n",
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" shell = TerminalInteractiveShell.instance()\n",
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" shell.define_macro(\"foo\", \"\"\"a,b=10,20\"\"\")\n",
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" from notebookutils.visualization import display\n",
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"\n",
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"\n",
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@ -65,12 +65,10 @@ jobs:
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scriptLocation: inlineScript
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scriptType: bash
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inlineScript: 'sbt scalastyle test:scalastyle'
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- task: UsePythonVersion@00
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inputs:
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versionSpec: '3.8'
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- script: pip install -r requirements.txt
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displayName: 'Install requirements'
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- template: templates/conda.yml
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- bash: |
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set -e
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source activate synapseml
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black --diff --color . && black --check -q .
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displayName: 'Python Style Check'
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@ -1,7 +0,0 @@
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# Copyright (C) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License. See LICENSE in project root for information.
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# Required to auto-format python code
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black==22.3.0
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black[jupyter]==22.3.0
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pre-commit==2.19.0
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@ -24,7 +24,7 @@ from synapse.ml.train import *
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from numpy import random
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df = spark.createDataFrame(
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[(random.rand(), random.rand()) for _ in range(4096)], ["label", "prediction"]
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[(random.rand(), random.rand()) for _ in range(2048)], ["label", "prediction"]
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)
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cms = (ComputeModelStatistics()
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@ -43,8 +43,8 @@ import com.microsoft.azure.synapse.ml.train._
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import scala.util.Random
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val rand = new Random(1337)
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val df = (Seq.fill(4096)(rand.nextDouble())
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.zip(Seq.fill(4096)(rand.nextDouble()))
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val df = (Seq.fill(2048)(rand.nextDouble())
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.zip(Seq.fill(2048)(rand.nextDouble()))
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.toDF("label", "prediction"))
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val cms = (new ComputeModelStatistics()
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