Use python -m pip instead of the pip executable

.github/workflows/pythonapp.yml

@@ -30,21 +30,21 @@ jobs:
     - name: Lint with flake8
       run: |
         python -m pip install --upgrade pip
-        pip install flake8
+        python -m pip install flake8
         # stop the build if there are Python syntax errors or undefined names
         flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
         # The GitHub editor is 127 chars wide
         flake8 . --count  --max-complexity=10 --max-line-length=127 --statistics
     # PyTorch for Mac has different pip syntax wrt Win and Linux.
     - name: Install pytorch 1.12.0 if mac
       if: ${{  matrix.os == 'macos-11' }}
-      run: pip install torch==1.12.0
+      run: python -m pip install torch==1.12.0
     - name: Install pytorch 1.12.0+cpu if not mac
       if:  ${{  matrix.os != 'macos-11' }}
-      run: pip install torch==1.12.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
+      run: python -m pip install torch==1.12.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
     - name: Install basic dependencies
       run: |
-        pip install -e .[tests] -f https://download.pytorch.org/whl/torch_stable.html
+        python -m pip install -e .[tests] -f https://download.pytorch.org/whl/torch_stable.html
     # Compile (but not push) documentation only for one of the runs (Linux py3.8).
     - name: Generate Documentation
       if: ${{ matrix.python-version == '3.8' && matrix.os == 'ubuntu-18.04' }}
@@ -54,7 +54,7 @@ jobs:
         find ../. -type f -exec sed -i 's/torch.__version__/"1.12.0"/g' {} +
         make sphinx-site -C website/
         # now refresh the code
-        git checkout . && pip install -e .[tests] -f https://download.pytorch.org/whl/torch_stable.html
+        git checkout . && python -m pip install -e .[tests] -f https://download.pytorch.org/whl/torch_stable.html
     - name: Run basic tests without extra
       run: pytest
     - name: Coverage on basic tests without extra
@@ -73,10 +73,10 @@ jobs:
         export LDFLAGS="$LDFLAGS -Wl,-rpath,/usr/local/opt/libomp/lib -L/usr/local/opt/libomp/lib -lomp"
     - name: Install extra dependencies
       run: |
-        pip install .[extra,onnx,sparkml]
-        pip install pandas
-    - name: pip list
-      run: pip list
+        python -m pip install .[extra,onnx,sparkml]
+        python -m pip install pandas
+    - name: python -m pip list
+      run: python -m pip list
     - uses: actions/cache@v1
       # TVM takes forever, we try to cache it.
       if: ${{ matrix.os != 'windows-2019' }}
@@ -129,8 +129,8 @@ jobs:
       working-directory: ../../../tvm/python
       run: |
         python setup.py install
-    - name: pip list
-      run: pip list
+    - name: python -m pip list
+      run: python -m pip list
     # We don't run pytest for Linux py3.8 since we do coverage for that case.
     - name: Test with pytest
       if: ${{ matrix.python-version != '3.8' || matrix.os != 'ubuntu-18.04' }}

CONTRIBUTING.md

@@ -35,7 +35,7 @@ The simplest setup (assuming you have PyTorch already installed) is:
 mkdir hummingbird
 cd hummingbird
 git clone https://github.com/microsoft/hummingbird.git .
-pip install -e .[tests,extra]
+python -m pip install -e .[tests,extra]
 ```
 
 If you do not have pytorch installed, please [install it](https://pytorch.org/get-started/locally/) first.
@@ -51,7 +51,7 @@ For a light-weight, web-based experience, we provide the configuration ([.devcon
 
 ### Tools
 #### Pre-commit
-This project uses [pre-commit](https://pre-commit.com/) hooks. Run  `pip install pre-commit` if you don't already have this in your machine. Afterward, run `pre-commit install` to install pre-commit into your git hooks.
+This project uses [pre-commit](https://pre-commit.com/) hooks. Run  `python -m pip install pre-commit` if you don't already have this in your machine. Afterward, run `pre-commit install` to install pre-commit into your git hooks.
 
 And before you commit, you can run it like this `pre-commit run --all-files` and should see output such as:
 
@@ -84,7 +84,7 @@ flake8 . --count  --max-complexity=10 --max-line-length=127 --statistics
 
 #### Coverage
 
-For coverage, we use [coverage.py](https://coverage.readthedocs.io/en/coverage-5.0.4/) in our Github Actions.  Run  `pip install coverage` if you don't already have this, and any code you commit should generally not significantly impact coverage.
+For coverage, we use [coverage.py](https://coverage.readthedocs.io/en/coverage-5.0.4/) in our Github Actions.  Run  `python -m pip install coverage` if you don't already have this, and any code you commit should generally not significantly impact coverage.
 
 We strive to not let check-ins decrease coverage.  To run all unit tests:
 ```

Dockerfile

@@ -14,7 +14,7 @@ RUN cd /home/hb-dev && git clone https://github.com/microsoft/hummingbird.git
 WORKDIR /home/hb-dev/hummingbird
 
 # Install HB  (Note: you may not need all of these packages and can remove some)
-RUN sudo pip install -e .[docs,tests,extra,onnx]
+RUN sudo python -m pip install -e .[docs,tests,extra,onnx]
 
 # Install precommit hooks
 RUN pre-commit install

README.md

@@ -70,12 +70,12 @@ Hummingbird requires PyTorch >= 1.6.0. Please go [here](https://pytorch.org/) fo
 
 Once PyTorch is installed, you can get Hummingbird from pip with:
 ```
-pip install hummingbird-ml
+python -m pip install hummingbird-ml
 ```
 
 If you require the optional dependencies lightgbm and xgboost, you can use:
 ```
-pip install hummingbird-ml[extra]
+python -m pip install hummingbird-ml[extra]
 ```
 
 

TROUBLESHOOTING.md

@@ -2,7 +2,7 @@
 
 ### Running PyTorch on GPU:
 
-In order to run Hummingbird on PyTorch with GPU, you will need to `pip uninstall torch` and re-install pytorch using the CUDA version of your machine.
+In order to run Hummingbird on PyTorch with GPU, you will need to `python -m pip uninstall torch` and re-install pytorch using the CUDA version of your machine.
 
 ### Installation Issues with External Libraries:
 

hummingbird/ml/_utils.py

@@ -120,7 +120,7 @@ def lightgbm_installed():
 def assert_lightgbm_installed():
     assert (
         lightgbm_installed()
-    ), "To convert LightGBM models you need to install LightGBM (or `pip install hummingbird-ml[extra]`)."
+    ), "To convert LightGBM models you need to install LightGBM (or `python -m pip install hummingbird-ml[extra]`)."
 
 
 def xgboost_installed():
@@ -151,7 +151,7 @@ def xgboost_installed():
 def assert_xgboost_installed():
     assert (
         xgboost_installed()
-    ), "To convert XGBoost models you need to install XGBoost (or `pip install hummingbird-ml[extra]`)."
+    ), "To convert XGBoost models you need to install XGBoost (or `python -m pip install hummingbird-ml[extra]`)."
 
 
 def tvm_installed():

notebooks/LGBM-ONNX-example.ipynb

@@ -1,11 +1,11 @@
 {
  "cells": [
   {
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "### This notebook shows how to convert from LGBM to ONNX"
-   ],
-   "cell_type": "markdown",
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
@@ -14,7 +14,7 @@
    "outputs": [],
    "source": [
     "# Uncomment and run this cell if you need to install Hummingbird and ONNX\n",
-    "#!pip install hummingbird_ml[extra,onnx]"
+    "#!python -m pip install hummingbird_ml[extra,onnx]"
    ]
   },
   {
@@ -42,14 +42,14 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "LGBMClassifier()"
       ]
      },
+     "execution_count": 3,
      "metadata": {},
-     "execution_count": 3
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -64,8 +64,8 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
       "Finished loading model, total used 100 iterations\n"
      ]
@@ -84,8 +84,8 @@
    },
    "outputs": [
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
       "502 ms ± 17.2 ms per loop (mean ± std. dev. of 3 runs, 1 loop each)\n"
      ]
@@ -120,4 +120,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}

notebooks/LGBM-ONNXML-example.ipynb

@@ -1,11 +1,11 @@
 {
  "cells": [
   {
+   "cell_type": "markdown",
+   "metadata": {},
    "source": [
     "### This notebook shows how to convert from LGBM to ONNX and provides an example of the ONNXML converter"
-   ],
-   "cell_type": "markdown",
-   "metadata": {}
+   ]
   },
   {
    "cell_type": "code",
@@ -14,7 +14,7 @@
    "outputs": [],
    "source": [
     "# Uncomment and run this cell if you need to install Hummingbird and ONNX\n",
-    "#!pip install hummingbird_ml[extra,onnx]"
+    "#!python -m pip install hummingbird_ml[extra,onnx]"
    ]
   },
   {
@@ -46,14 +46,14 @@
    "metadata": {},
    "outputs": [
     {
-     "output_type": "execute_result",
      "data": {
       "text/plain": [
        "LGBMClassifier()"
       ]
      },
+     "execution_count": 3,
      "metadata": {},
-     "execution_count": 3
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -93,8 +93,8 @@
    },
    "outputs": [
     {
-     "output_type": "stream",
      "name": "stdout",
+     "output_type": "stream",
      "text": [
       "507 ms ± 16.8 ms per loop (mean ± std. dev. of 3 runs, 1 loop each)\n"
      ]
@@ -129,4 +129,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 2
-}
+}

notebooks/LGBM-example.ipynb

@@ -6,7 +6,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install hummingbird_ml[extra]"
+    "!python -m pip install hummingbird_ml[extra]"
    ]
   },
   {